Tue, 25 Jun 2019

Package pgraph updated to version 1.5 with previous version 0.8 dated 2016-10-13

Title: Build Dependency Graphs using Projection
Description: Implements a general framework for creating dependency graphs using projection as introduced in Fan, Feng and Xia (2019)<arXiv:1501.01617>. Both lasso and sparse additive model projections are implemented. Both Pearson correlation and distance covariance options are available to generate the graph.
Author: Jianqing Fan, Yang Feng and Lucy Xia
Maintainer: Yang Feng <yang.feng@columbia.edu>

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New package PakPMICS2018 with initial version 0.1.0
Package: PakPMICS2018
Type: Package
Title: Multiple Indicator Cluster Survey (MICS) 2017-18 Data for Punjab, Pakistan
Version: 0.1.0
Authors@R: c(person(c("Muhammad", "Yaseen"), email = "myaseen208@gmail.com", role = c("aut", "cre")))
Author: Muhammad Yaseen [aut, cre]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of SDG monitoring, as the survey produces information on 32 global SDG indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using Probability Proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).
Depends: R (>= 3.5.0)
Imports: tibble
License: GPL-2
URL: https://github.com/myaseen208/PakPMICS2018, https://myaseen208.github.io/PakPMICS2018/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat, R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2019-06-20 01:39:43 UTC; myaseen
Repository: CRAN
Date/Publication: 2019-06-25 15:40:06 UTC

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Package GLMMadaptive updated to version 0.6-0 with previous version 0.5-1 dated 2019-01-29

Title: Generalized Linear Mixed Models using Adaptive Gaussian Quadrature
Description: Fits generalized linear mixed models for a single grouping factor under maximum likelihood approximating the integrals over the random effects with an adaptive Gaussian quadrature rule; Jose C. Pinheiro and Douglas M. Bates (1995) <doi:10.1080/10618600.1995.10474663>.
Author: Dimitris Rizopoulos [aut, cre] (<https://orcid.org/0000-0001-9397-0900>)
Maintainer: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>

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Package SimilaR updated to version 1.0.4 with previous version 1.0.3 dated 2019-02-25

Title: R Source Code Similarity Evaluation
Description: An implementation of a novel method to quantify the similarity the code-base of R functions by means of program dependence graphs. Possible use cases include detection of code clones for improving software quality and of plagiarism among students' homework assignments.
Author: Maciej Bartoszuk [aut, cre] (<https://orcid.org/0000-0001-6088-8273>), Marek Gagolewski [aut] (<https://orcid.org/0000-0003-0637-6028>)
Maintainer: Maciej Bartoszuk <bartoszuk@rexamine.com>

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Package matrixTests updated to version 0.1.4 with previous version 0.1.3 dated 2019-06-10

Title: Fast Statistical Hypothesis Tests on Rows and Columns of Matrices
Description: Functions to perform fast statistical hypothesis tests on rows/columns of matrices. The main goals are: 1) speed via vectorization, 2) output that is detailed and easy to use, 3) compatibility with tests implemented in R (like those available in the 'stats' package).
Author: Karolis Koncevičius [aut, cre]
Maintainer: Karolis Koncevičius <karolis.koncevicius@gmail.com>

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Package gsrsb updated to version 1.1.1 with previous version 1.0.3 dated 2017-04-28

Title: Group Sequential Refined Secondary Boundary
Description: A gate-keeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks. Computations related to group sequential primary and secondary boundaries. Refined secondary boundaries are calculated for a gate-keeping test on a primary and a secondary endpoint in a group sequential design with multiple interim looks. The choices include both the standard boundaries and the boundaries using error spending functions. Version 1.0.0 was released on April 12, 2017. See Tamhane et al. (2018), "A gatekeeping procedure to test a primary and a secondary endpoint in a group sequential design with multiple interim looks", Biometrics, 74(1), 40-48.
Author: Jiangtao Gou and Fengqing (Zoe) Zhang
Maintainer: Jiangtao Gou <gouRpackage@gmail.com>

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Package DAMisc updated to version 1.5 with previous version 1.4-3 dated 2016-07-04

Title: Dave Armstrong's Miscellaneous Functions
Description: Miscellaneous set of functions I use in my teaching either at the University of Western Ontario or the Inter-university Consortium for Political and Social Research (ICPSR) Summer Program in Quantitative Methods. Broadly, the functions help with presentation and interpretation of LMs and GLMs, but also implement some new tools like Alternating Least Squares Optimal Scaling for dependent variables, a Bayesian analog to the ALSOS algorithm. There are also tools to help understand interactions in both LMs and binary GLMs.
Author: Dave Armstrong [aut, cre]
Maintainer: Dave Armstrong <dave@quantoid.net>

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Package RcppTOML updated to version 0.1.6 with previous version 0.1.5 dated 2018-10-31

Title: 'Rcpp' Bindings to Parser for Tom's Obvious Markup Language
Description: The configuration format defined by 'TOML' (which expands to "Tom's Obvious Markup Language") specifies an excellent format (described at <https://github.com/toml-lang/toml>) suitable for both human editing as well as the common uses of a machine-readable format. This package uses 'Rcpp' to connect the 'cpptoml' parser written by Chase Geigle (in modern C++11) to R.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package trialr updated to version 0.1.2 with previous version 0.1.1 dated 2019-05-24

Title: Clinical Trial Designs in 'rstan'
Description: A collection of clinical trial designs and methods, implemented in 'rstan' and R, including: the Continual Reassessment Method by O'Quigley et al. (1990) <doi:10.2307/2531628>; EffTox by Thall & Cook (2004) <doi:10.1111/j.0006-341X.2004.00218.x>; and the Augmented Binary method by Wason & Seaman (2013) <doi:10.1002/sim.5867>; and more. We provide functions to aid model-fitting and analysis. The 'rstan' implementations may also serve as a cookbook to anyone looking to extend or embellish these models. We hope that this package encourages the use of Bayesian methods in clinical trials. There is a preponderance of early phase trial designs because this is where Bayesian methods are used most. If there is a method you would like implemented, please get in touch.
Author: Kristian Brock [aut, cre] (<https://orcid.org/0000-0002-3921-0166>), Trustees of Columbia University [cph]
Maintainer: Kristian Brock <kristian.brock@gmail.com>

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New package secsse with initial version 2.0.0
Package: secsse
Type: Package
Title: Several Examined and Concealed States-Dependent Speciation and Extinction
Version: 2.0.0
Date: 2019-06-22
License: GPL-3
Authors@R: c( person("Leonel", "Herrera Alsina", email = "leonelhalsina@gmail.com", role = "cre"), person("Paul", "van Els", email = "paulvanels@gmail.com", role = "aut"), person("Rampal", "Etienne", email = "r.s.etienne@rug.nl", role = "aut"))
Description: Simultaneously infers state-dependent diversification across two or more states of a single or multiple traits while accounting for the role of a possible concealed trait. See Herrera-Alsina et al. 2019 Systematic Biology 68: 317-328 <DOI:10.1093/sysbio/syy057>.
Depends: R (>= 3.5.0)
Imports: utils, DDD (>= 4.0), ape, foreach, doParallel, apTreeshape, phylobase, geiger, deSolve
Suggests: diversitree, phytools, testthat, testit, knitr, rmarkdown
Enhances: doMC
NeedsCompilation: yes
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Packaged: 2019-06-23 15:46:35 UTC; rampa
Author: Leonel Herrera Alsina [cre], Paul van Els [aut], Rampal Etienne [aut]
Maintainer: Leonel Herrera Alsina <leonelhalsina@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-25 11:30:03 UTC

More information about secsse at CRAN
Permanent link

Package RDML updated to version 1.0 with previous version 0.9-9 dated 2017-09-25

Title: Importing Real-Time Thermo Cycler (qPCR) Data from RDML Format Files
Description: Imports real-time thermo cycler (qPCR) data from Real-time PCR Data Markup Language (RDML) and transforms to the appropriate formats of the 'qpcR' and 'chipPCR' packages. Contains a dendrogram visualization for the structure of RDML object and GUI for RDML editing.
Author: Konstantin A. Blagodatskikh [cre, aut], Stefan Roediger [aut], Michal Burdukiewicz [aut] (<https://orcid.org/0000-0001-8926-582X>), Andrej-Nikolai Spiess [aut]
Maintainer: Konstantin A. Blagodatskikh <k.blag@yandex.ru>

Diff between RDML versions 0.9-9 dated 2017-09-25 and 1.0 dated 2019-06-25

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More information about RDML at CRAN
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Package nparcomp updated to version 3.0 with previous version 2.6 dated 2015-03-12

Title: Multiple Comparisons and Simultaneous Confidence Intervals
Description: With this package, it is possible to compute nonparametric simultaneous confidence intervals for relative contrast effects in the unbalanced one way layout. Moreover, it computes simultaneous p-values. The simultaneous confidence intervals can be computed using multivariate normal distribution, multivariate t-distribution with a Satterthwaite Approximation of the degree of freedom or using multivariate range preserving transformations with Logit or Probit as transformation function. 2 sample comparisons can be performed with the same methods described above. There is no assumption on the underlying distribution function, only that the data have to be at least ordinal numbers. See Konietschke et al. (2015) <doi:10.18637/jss.v064.i09> for details.
Author: Frank Konietschke [aut, cre], Kimihiro Noguchi [ctr], Kerstin Rubarth
Maintainer: Kerstin Rubarth <kerstin.rubarth@charite.de>

Diff between nparcomp versions 2.6 dated 2015-03-12 and 3.0 dated 2019-06-25

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Package islasso updated to version 1.1.0 with previous version 1.0.0 dated 2019-04-29

Title: The Induced Smoothed Lasso
Description: An implementation of the induced smoothing (IS) idea to lasso regularization models to allow estimation and inference on the model coefficients (currently hypothesis testing only). Linear, logistic, Poisson and gamma regressions with several link functions are implemented. The algorithm is described in the original paper: Cilluffo, G., Sottile, G., La Grutta, S. and Muggeo, V. (2019) The Induced Smoothed lasso: A practical framework for hypothesis testing in high dimensional regression. <doi:10.1177/0962280219842890>, and discussed in a tutorial: Sottile, G., Cilluffo, G., and Muggeo, V. (2019) The R package islasso: estimation and hypothesis testing in lasso regression. <doi:10.13140/RG.2.2.16360.11521>.
Author: Gianluca Sottile [aut, cre], Giovanna Cilluffo [aut, ctb], Vito MR Muggeo [aut, cre]
Maintainer: Gianluca Sottile <gianluca.sottile@unipa.it>

Diff between islasso versions 1.0.0 dated 2019-04-29 and 1.1.0 dated 2019-06-25

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Package Gifi updated to version 0.3-9 with previous version 0.3-8 dated 2018-10-03

Title: Multivariate Analysis with Optimal Scaling
Description: Implements categorical principal component analysis ('PRINCALS'), multiple correspondence analysis ('HOMALS'), monotone regression analysis ('MORALS'). It replaces the 'homals' package.
Author: Patrick Mair [aut, cre], Jan De Leeuw [aut], Patrick J. F. Groenen [ctb]
Maintainer: Patrick Mair <mair@fas.harvard.edu>

Diff between Gifi versions 0.3-8 dated 2018-10-03 and 0.3-9 dated 2019-06-25

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Package augmentedRCBD (with last version 0.1.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2018-07-10 0.1.0

Permanent link
Package rvg updated to version 0.2.1 with previous version 0.2.0 dated 2019-04-06

Title: R Graphics Devices for Vector Graphics Output
Description: Vector Graphics devices for Microsoft PowerPoint and Excel. Functions extending package 'officer' are provided to embed 'DrawingML' graphics into 'Microsoft PowerPoint' presentations and 'Microsoft Excel' workbooks.
Author: David Gohel [aut, cre], Bob Rudis [ctb] (the javascript code used by function set_attr), Francois Brunetti [ctb] (clipping algorithms)
Maintainer: David Gohel <david.gohel@ardata.fr>

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Package flextable updated to version 0.5.5 with previous version 0.5.4 dated 2019-05-14

Title: Functions for Tabular Reporting
Description: Create pretty tables for 'HTML', 'Microsoft Word' and 'Microsoft PowerPoint' documents. Functions are provided to let users create tables, modify and format their content. It extends package 'officer' that does not contain any feature for customized tabular reporting and can be used within R markdown documents.
Author: David Gohel [aut, cre], Quentin Fazilleau [ctb], Maxim Nazarov [ctb] (rmarkdown for docx output), Titouan Robert [ctb]
Maintainer: David Gohel <david.gohel@ardata.fr>

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Package jsonvalidate updated to version 1.1.0 with previous version 1.0.0 dated 2016-06-13

Title: Validate 'JSON'
Description: Uses the node library 'is-my-json-valid' or 'ajv' to validate 'JSON' against a 'JSON' schema. Drafts 04, 06 and 07 of 'JSON' schema are supported.
Author: Rich FitzJohn [aut, cre], Ian Lyttle [ctb], Kara Woo [ctb], Mathias Buus [cph], Evgeny Poberezkin [cph]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>

Diff between jsonvalidate versions 1.0.0 dated 2016-06-13 and 1.1.0 dated 2019-06-25

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Package rlang updated to version 0.4.0 with previous version 0.3.4 dated 2019-04-07

Title: Functions for Base Types and Core R and 'Tidyverse' Features
Description: A toolbox for working with base types, core R features like the condition system, and core 'Tidyverse' features like tidy evaluation.
Author: Lionel Henry [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>

Diff between rlang versions 0.3.4 dated 2019-04-07 and 0.4.0 dated 2019-06-25

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Package broomExtra updated to version 0.0.4 with previous version 0.0.3 dated 2019-05-20

Title: Enhancements for 'broom' Package Family
Description: Collection of functions to assist 'broom' and 'broom.mixed' package-related data analysis workflows. In particular, the generic functions tidy(), glance(), and augment() choose appropriate S3 methods from these two packages depending on which package exports the needed method. Additionally, 'grouped_' and 'boot_' variants of the generics provides a convenient way to execute functions across a combination of grouping variable(s) in a dataframe or bootstrap them.
Author: Indrajeet Patil [aut, cre, ctb] (<https://orcid.org/0000-0003-1995-6531>)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

Diff between broomExtra versions 0.0.3 dated 2019-05-20 and 0.0.4 dated 2019-06-25

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Permanent link

Package xfun updated to version 0.8 with previous version 0.7 dated 2019-05-14

Title: Miscellaneous Functions by 'Yihui Xie'
Description: Miscellaneous functions commonly used in other packages maintained by 'Yihui Xie'.
Author: Yihui Xie [aut, cre, cph] (<https://orcid.org/0000-0003-0645-5666>), Daijiang Li [ctb], Xianying Tan [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between xfun versions 0.7 dated 2019-05-14 and 0.8 dated 2019-06-25

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More information about xfun at CRAN
Permanent link

Package tinytex updated to version 0.14 with previous version 0.13 dated 2019-05-14

Title: Helper Functions to Install and Maintain 'TeX Live', and Compile 'LaTeX' Documents
Description: Helper functions to install and maintain the 'LaTeX' distribution named 'TinyTeX' (<https://yihui.name/tinytex/>), a lightweight, cross-platform, portable, and easy-to-maintain version of 'TeX Live'. This package also contains helper functions to compile 'LaTeX' documents, and install missing 'LaTeX' packages automatically.
Author: Yihui Xie [aut, cre, cph] (<https://orcid.org/0000-0003-0645-5666>), RStudio, Inc. [cph], Fernando Cagua [ctb], Ethan Heinzen [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between tinytex versions 0.13 dated 2019-05-14 and 0.14 dated 2019-06-25

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More information about tinytex at CRAN
Permanent link

Package qs updated to version 0.17.1 with previous version 0.16.1 dated 2019-05-17

Title: Quick Serialization of R Objects
Description: Provides functions for quickly writing and reading any R object to and from disk.
Author: Travers Ching [aut, cre, cph], Yann Collet [ctb, cph] (Yann Collet is the author of the bundled zstd and lz4 code), Facebook, Inc. [cph] (Facebook is the copyright holder of the bundled zstd code), Reichardt Tino [ctb, cph] (Contributor/copyright holder of zstd bundled code), Skibinski Przemyslaw [ctb, cph] (Contributor/copyright holder of zstd bundled code), Mori Yuta [ctb, cph] (Contributor/copyright holder of zstd bundled code), Romain Francois [ctb, cph] (Derived example/tutorials for Alt-Rep structures), Francesc Alted [ctb, cph] (Shuffling routines derived from Blosc library)
Maintainer: Travers Ching <traversc@gmail.com>

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Package pavo updated to version 2.2.0 with previous version 2.1.0 dated 2019-03-06

Title: Perceptual Analysis, Visualization and Organization of Spectral Colour Data in R
Description: A cohesive framework for parsing, analyzing and organizing colour from spectral data.
Author: Rafael Maia [aut, cre] (<https://orcid.org/0000-0002-7563-9795>), Thomas White [aut] (<https://orcid.org/0000-0002-3976-1734>), Hugo Gruson [aut] (<https://orcid.org/0000-0002-4094-1476>), John Endler [aut], Chad Eliason [aut], Pierre-Paul Bitton [aut] (<https://orcid.org/0000-0001-5984-2331>)
Maintainer: Rafael Maia <rm72@zips.uakron.edu>

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More information about pavo at CRAN
Permanent link

Package commonsMath updated to version 1.2.2 with previous version 1.2 dated 2018-10-26

Title: JAR Files of the Apache Commons Mathematics Library
Description: Java JAR files for the Apache Commons Mathematics Library for use by users and other packages.
Author: David B. Dahl [cre], The Apache Software Foundation [aut, cph]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

Diff between commonsMath versions 1.2 dated 2018-10-26 and 1.2.2 dated 2019-06-25

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Package aws.alexa updated to version 0.1.7 with previous version 0.1.6 dated 2018-03-27

Title: Client for the Amazon Alexa Web Information Services API
Description: Use the Amazon Alexa Web Information Services API to find information about domains, including the kind of content that they carry, how popular are they---rank and traffic history, sites linking to them, among other things. See <https://aws.amazon.com/awis/> for more information.
Author: Gaurav Sood [aut, cre], Thomas Leeper [ctb]
Maintainer: Gaurav Sood <gsood07@gmail.com>

Diff between aws.alexa versions 0.1.6 dated 2018-03-27 and 0.1.7 dated 2019-06-25

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More information about aws.alexa at CRAN
Permanent link

Package RSocrata updated to version 1.7.9-5 with previous version 1.7.8-4 dated 2019-05-15

Title: Download or Upload 'Socrata' Data Sets
Description: Provides easier interaction with 'Socrata' open data portals <http://dev.socrata.com>. Users can provide a 'Socrata' data set resource URL, or a 'Socrata' Open Data API (SoDA) web query, or a 'Socrata' "human-friendly" URL, returns an R data frame. Converts dates to 'POSIX' format and manages throttling by 'Socrata'. Users can upload data to 'Socrata' portals directly from R.
Author: Hugh Devlin, Ph. D., Tom Schenk, Jr., Gene Leynes, Nick Lucius, John Malc, Mark Silverberg, and Peter Schmeideskamp
Maintainer: "Tom Schenk Jr." <developers@cityofchicago.org>

Diff between RSocrata versions 1.7.8-4 dated 2019-05-15 and 1.7.9-5 dated 2019-06-25

 DESCRIPTION               |    8 ++++----
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 README.md                 |    3 +--
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Package abbyyR updated to version 0.5.5 with previous version 0.5.4 dated 2018-05-30

Title: Access to Abbyy Optical Character Recognition (OCR) API
Description: Get text from images of text using Abbyy Cloud Optical Character Recognition (OCR) API. Easily OCR images, barcodes, forms, documents with machine readable zones, e.g. passports. Get the results in a variety of formats including plain text and XML. To learn more about the Abbyy OCR API, see <http://ocrsdk.com/>.
Author: Gaurav Sood [aut, cre]
Maintainer: Gaurav Sood <gsood07@gmail.com>

Diff between abbyyR versions 0.5.4 dated 2018-05-30 and 0.5.5 dated 2019-06-25

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Mon, 24 Jun 2019

Package predictoR updated to version 1.1.0 with previous version 1.0.9 dated 2019-05-10

Title: Predictive Data Analysis System
Description: Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as K-Nearest Neighbors, Decision Trees, ADA Boosting, Extreme Gradient Boosting, Random Forest, Neural Networks, Deep Learning, Support Vector Machines and Bayesian Methods.
Author: Oldemar Rodriguez R. with contributions from Diego Jimenez A. and Andres Navarro D.
Maintainer: Oldemar Rodriguez <oldemar.rodriguez@ucr.ac.cr>

Diff between predictoR versions 1.0.9 dated 2019-05-10 and 1.1.0 dated 2019-06-24

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New package metapost with initial version 1.0-6
Package: metapost
Type: Package
Title: Interface to 'MetaPost'
Version: 1.0-6
Author: Paul Murrell
Maintainer: Paul Murrell <paul@stat.auckland.ac.nz>
Description: Provides an interface to 'MetaPost' (Hobby, 1998) <http://www.tug.org/docs/metapost/mpman.pdf>. There are functions to generate an R description of a 'MetaPost' curve, functions to generate 'MetaPost' code from an R description, functions to process 'MetaPost' code, and functions to read solved 'MetaPost' paths back into R.
Imports: grid, gridBezier
Suggests: grImport
SystemRequirements: mpost
URL: https://github.com/pmur002/metapost, https://stattech.wordpress.fos.auckland.ac.nz/2018/12/03/2018-12-metapost-three-ways/
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-06-24 20:52:29 UTC; pmur002
Repository: CRAN
Date/Publication: 2019-06-24 22:20:03 UTC

More information about metapost at CRAN
Permanent link

Package bamboo updated to version 0.9.24 with previous version 0.9.23 dated 2018-10-19

Title: Protein Secondary Structure Prediction Using the Bamboo Method
Description: Implementation of the Bamboo methods described in Li, Dahl, Vannucci, Joo, and Tsai (2014) <DOI:10.1371/journal.pone.0109832>.
Author: David B. Dahl [aut, cre]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

Diff between bamboo versions 0.9.23 dated 2018-10-19 and 0.9.24 dated 2019-06-24

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Package vegawidget updated to version 0.2.1 with previous version 0.1.0 dated 2019-01-30

Title: 'Htmlwidget' for 'Vega' and 'Vega-Lite'
Description: 'Vega' and 'Vega-Lite' parse text in 'JSON' notation to render chart-specifications into 'HTML'. This package is used to facilitate the rendering. It also provides a means to interact with signals, events, and datasets in a 'Vega' chart using 'JavaScript' or 'Shiny'.
Author: Ian Lyttle [aut, cre] (<https://orcid.org/0000-0001-9962-4849>), Vega/Vega-Lite Developers [aut], Alicia Schep [ctb] (<https://orcid.org/0000-0002-3915-0618>), Stuart Lee [ctb], Kanit Wongsuphasawat [ctb] (Vega/Vega-Lite library), Dominik Moritz [ctb] (Vega/Vega-Lite library), Arvind Satyanarayan [ctb] (Vega/Vega-Lite library), Jeffrey Heer [ctb] (Vega/Vega-Lite library), Mike Bostock [ctb] (D3 library), David Frank [ctb] (node-fetch library)
Maintainer: Ian Lyttle <ian.lyttle@schneider-electric.com>

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Package remotes updated to version 2.1.0 with previous version 2.0.4 dated 2019-04-10

Title: R Package Installation from Remote Repositories, Including 'GitHub'
Description: Download and install R packages stored in 'GitHub', 'BitBucket', or plain 'subversion' or 'git' repositories. This package provides the 'install_*' functions in 'devtools'. Indeed most of the code was copied over from 'devtools'.
Author: Jim Hester [aut, cre], Gábor Csárdi [aut], Hadley Wickham [aut], Winston Chang [aut], RStudio [cph], Martin Morgan [aut], Dan Tenenbaum [aut], Mango Solutions [cph]
Maintainer: Jim Hester <james.hester@rstudio.com>

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Package text2speech updated to version 0.2.5 with previous version 0.2.4 dated 2019-06-14

Title: Text to Speech
Description: Unifies different text to speech engines, such as Google, Microsoft, and Amazon. Text synthesis can be done in any engine with a simple switch of an argument denoting the service requested.
Author: John Muschelli [aut, cre] (<https://orcid.org/0000-0001-6469-1750>)
Maintainer: John Muschelli <muschellij2@gmail.com>

Diff between text2speech versions 0.2.4 dated 2019-06-14 and 0.2.5 dated 2019-06-24

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Package jmuOutlier updated to version 1.5 with previous version 1.4 dated 2018-01-26

Title: Permutation Tests for Nonparametric Statistics
Description: Performs a permutation test on the difference between two location parameters, a permutation correlation test, a permutation F-test, the Siegel-Tukey test, a ratio mean deviance test. Also performs some graphing techniques, such as for confidence intervals, vector addition, and Fourier analysis; and includes functions related to the Laplace (double exponential) and triangular distributions. Performs power calculations for the binomial test.
Author: Steven T. Garren [aut, cre]
Maintainer: Steven T. Garren <GARRENST@JMU.EDU>

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Package fastGraph updated to version 1.3 with previous version 1.1 dated 2016-07-07

Title: Fast Drawing and Shading of Graphs of Statistical Distributions
Description: Provides functionality to produce graphs of probability density functions and cumulative distribution functions with few keystrokes, allows shading under the curve of the probability density function to illustrate concepts such as p-values and critical values, and fits a simple linear regression line on a scatter plot with the equation as the main title.
Author: Steven T. Garren [aut, cre]
Maintainer: Steven T. Garren <garrenst@jmu.edu>

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Package SSDforR updated to version 1.5.6 with previous version 1.5.5 dated 2019-06-17

Title: Functions to Analyze Single System Data
Description: Functions to visually and statistically analyze single system data.
Author: Charles Auerbach [aut, cre], Wendy Zeitlin [aut]
Maintainer: Charles Auerbach <auerbach@yu.edu>

Diff between SSDforR versions 1.5.5 dated 2019-06-17 and 1.5.6 dated 2019-06-24

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New package mcglm with initial version 0.5.0
Package: mcglm
Type: Package
Title: Multivariate Covariance Generalized Linear Models
Version: 0.5.0
Date: 2019-06-25
Author: Wagner Hugo Bonat [aut, cre], Walmes Marques Zeviani [ctb], Fernando de Pol Mayer [ctb]
Maintainer: Wagner Hugo Bonat <wbonat@ufpr.br>
Authors@R: c(person(c("Wagner","Hugo"), "Bonat", role = c("aut", "cre"), email = "wbonat@ufpr.br"), person(c("Walmes","Marques"), "Zeviani", role = "ctb"), person(c("Fernando", "de Pol"), "Mayer", role = "ctb"))
Description: Fitting multivariate covariance generalized linear models (McGLMs) to data. McGLM is a general framework for non-normal multivariate data analysis, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link function combined with a matrix linear predictor involving known matrices. The models take non-normality into account in the conventional way by means of a variance function, and the mean structure is modelled by means of a link function and a linear predictor. The models are fitted using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of different types of response variables and covariance structures, including multivariate extensions of repeated measures, time series, longitudinal, spatial and spatio-temporal structures. The package offers a user-friendly interface for fitting McGLMs similar to the glm() R function. See Bonat (2018) <doi:10.18637/jss.v084.i04>, for more information and examples.
Depends: R (>= 3.2.1)
Suggests: testthat, plyr, lattice, latticeExtra, knitr, rmarkdown, MASS, mvtnorm, tweedie, devtools
Imports: stats, Matrix, assertthat, graphics, Rcpp (>= 0.12.16)
License: GPL-3 | file LICENSE
LazyData: TRUE
URL: https://github.com/wbonat/mcglm
BugReports: https://github.com/wbonat/mcglm/issues
Encoding: UTF-8
VignetteBuilder: knitr
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2019-06-24 18:45:49 UTC; wagner
Repository: CRAN
Date/Publication: 2019-06-24 19:30:03 UTC

More information about mcglm at CRAN
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Package uroot updated to version 2.0-10 with previous version 2.0-9.1 dated 2019-03-24

Title: Unit Root Tests for Seasonal Time Series
Description: Seasonal unit roots and seasonal stability tests. P-values based on response surface regressions are available for both tests. P-values based on bootstrap are available for seasonal unit root tests. A parallel implementation of the bootstrap method requires a CUDA capable GPU with compute capability >= 3.0, otherwise a debugging version fully coded in R is used.
Author: Javier López-de-Lacalle [aut], Georgi N. Boshnakov [cre]
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

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New package spatialfusion with initial version 0.6
Package: spatialfusion
Imports: methods, graphics, stats, utils, rstan, sp, geoR, SDraw, fields
Suggests: INLA, testthat, tmap, R.rsp
Depends: R (>= 3.4.0), Rcpp
Type: Package
VignetteBuilder: R.rsp
Title: Multivariate Analysis of Spatial Data Using a Unifying Spatial Fusion Framework
Version: 0.6
Date: 2019-06-21
Authors@R: c( person("Craig", "Wang", email = "craig.wang@uzh.ch", role = c("aut","cre"),comment = c(ORCID = "0000-0003-1804-2463")), person("Reinhard", "Furrer", email = "reinhard.furrer@math.uzh.ch", role = "ctb",comment = c(ORCID = "0000-0002-6319-2332")))
Maintainer: Craig Wang <craig.wang@uzh.ch>
Description: Multivariate modelling of geostatistical (point), lattice (areal) and point pattern data in a unifying spatial fusion framework. Details are given in Wang and Furrer (2019) <arXiv:1906.00364>. Model inference is done using either 'Stan' <https://mc-stan.org/> or 'INLA' <http://www.r-inla.org>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: TRUE
NeedsCompilation: no
Packaged: 2019-06-21 18:36:19 UTC; crwang
Author: Craig Wang [aut, cre] (<https://orcid.org/0000-0003-1804-2463>), Reinhard Furrer [ctb] (<https://orcid.org/0000-0002-6319-2332>)
Repository: CRAN
Date/Publication: 2019-06-24 18:50:37 UTC

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Package devEMF updated to version 3.6-3 with previous version 3.6-2 dated 2019-01-03

Title: EMF Graphics Output Device
Description: Output graphics to EMF+/EMF.
Author: Philip Johnson
Maintainer: Philip Johnson <plfj@umd.edu>

Diff between devEMF versions 3.6-2 dated 2019-01-03 and 3.6-3 dated 2019-06-24

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Package psda updated to version 1.3.2 with previous version 1.3.1 dated 2019-03-22

Title: Polygonal Symbolic Data Analysis
Description: A toolbox in symbolic data framework as a statistical learning and data mining solution for symbolic polygonal data analysis. This study is a new approach in data analysis and it was proposed by Silva et al. (2019) <doi:10.1016/j.knosys.2018.08.009>. The package presents the estimation of main descriptive statistical measures, e.g, mean, covariance, variance, correlation and coefficient of variation. In addition, a method to obtain polygonal data from classical data is presented. Empirical probability distribution function based on symbolic polygonal histogram and a regression model with its main measures are presented.
Author: Wagner Silva [aut, cre, ths], Renata Souza [aut], Francisco Cysneiros [aut]
Maintainer: Wagner Silva <wjfs@cin.ufpe.br>

Diff between psda versions 1.3.1 dated 2019-03-22 and 1.3.2 dated 2019-06-24

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Package vdiffr updated to version 0.3.1 with previous version 0.3.0 dated 2019-01-02

Title: Visual Regression Testing and Graphical Diffing
Description: An extension to the 'testthat' package that makes it easy to add graphical unit tests. It provides a Shiny application to manage the test cases.
Author: Lionel Henry [cre, aut], RStudio [cph], Carl Sutherland [aut] (jg-imagediff library), Humble Software [cph] (jg-imagediff library), David Hong [aut] (TwoFace library), jQuery Foundation [cph] (jQuery library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/htmlwidgets/lib/jquery-authors.txt), T Jake Luciani [aut] (svglite), Matthieu Decorde [aut] (svglite), Vaudor Lise [aut] (svglite), Tony Plate [ctb] (svglite: Early line dashing code), David Gohel [ctb] (svglite: Line dashing code and raster code), Yixuan Qiu [ctb] (svglite: Improved styles; polypath implementation), Håkon Malmedal [ctb] (svglite: Opacity code)
Maintainer: Lionel Henry <lionel@rstudio.com>

Diff between vdiffr versions 0.3.0 dated 2019-01-02 and 0.3.1 dated 2019-06-24

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Package pivmet updated to version 0.2.0 with previous version 0.1.1 dated 2019-02-26

Title: Pivotal Methods for Bayesian Relabelling and k-Means Clustering
Description: Collection of pivotal algorithms for: relabelling the MCMC chains in order to undo the label switching problem in Bayesian mixture models, as proposed in Egidi, Pappadà, Pauli and Torelli (2018a)<doi:10.1007/s11222-017-9774-2>; initializing the centers of the classical k-means algorithm in order to obtain a better clustering solution. For further details see Egidi, Pappadà, Pauli and Torelli (2018b)<ISBN:9788891910233>.
Author: Leonardo Egidi[aut, cre], Roberta Pappadà[aut], Francesco Pauli[aut], Nicola Torelli[aut]
Maintainer: Leonardo Egidi <legidi@units.it>

Diff between pivmet versions 0.1.1 dated 2019-02-26 and 0.2.0 dated 2019-06-24

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 man/piv_sel.Rd                                                  |   24 
 man/piv_sim.Rd                                                  |   42 
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Package ggstance updated to version 0.3.2 with previous version 0.3.1 dated 2018-07-20

Title: Horizontal 'ggplot2' Components
Description: A 'ggplot2' extension that provides flipped components: horizontal versions of 'Stats' and 'Geoms', and vertical versions of 'Positions'.
Author: Lionel Henry [aut, cre], Hadley Wickham [aut], Winston Chang [aut], RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>

Diff between ggstance versions 0.3.1 dated 2018-07-20 and 0.3.2 dated 2019-06-24

 DESCRIPTION                                                   |   13 
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 R/ggstance.R                                                  |    9 
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Package fhidata updated to version 2019.6.24 with previous version 2019.5.19 dated 2019-05-21

Title: Structural Data for Norway
Description: Provides structural data for Norway. Datasets relating to maps, population in municipalities, vaccination coverage for childhood vaccines, municipality/county matching, and how different municipalities have merged/redistricted over time from 2006 to 2019.
Author: Richard White [aut, cre]
Maintainer: Richard White <w@rwhite.no>

Diff between fhidata versions 2019.5.19 dated 2019-05-21 and 2019.6.24 dated 2019-06-24

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Package bootnet updated to version 1.2.3 with previous version 1.2.2 dated 2019-05-09

Title: Bootstrap Methods for Various Network Estimation Routines
Description: Bootstrap methods to assess accuracy and stability of estimated network structures and centrality indices. Allows for flexible specification of any undirected network estimation procedure in R, and offers default sets for 'qgraph', 'IsingFit', 'IsingSampler', 'glasso', 'huge' and 'parcor' packages.
Author: Sacha Epskamp [aut, cre], Eiko I. Fried [ctb]
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

Diff between bootnet versions 1.2.2 dated 2019-05-09 and 1.2.3 dated 2019-06-24

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Package visvow updated to version 0.5.0 with previous version 0.4.0 dated 2019-01-25

Title: Visible Vowels: Visualization of Vowel Variation
Description: Visualizes vowel variation in f0, F1, F2, F3 and duration.
Author: Wilbert Heeringa, Hans Van de Velde
Maintainer: Wilbert Heeringa <wjheeringa@gmail.com>

Diff between visvow versions 0.4.0 dated 2019-01-25 and 0.5.0 dated 2019-06-24

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New package mcgfa with initial version 2.2.1
Package: mcgfa
Version: 2.2.1
Type: Package
Title: Mixtures of Contaminated Gaussian Factor Analyzers
Authors@R: c(person("Martin", "Blostein", role = c("aut", "cre"), email="martin.blostein@gmail.com"), person("Antonio", "Punzo", role = "aut"), person(c("Paul", "D."), "McNicholas", role = c("aut","ths")))
Description: Clustering and classification using the Mixtures of Contaminated Gaussian Factor Analyzers model. Allows for automatic detection of outliers and noise. Punzo, A, Blostein, M, McNicholas, PD (2017) <arXiv:1408.2128v2>.
Imports: stats, parallel
License: GPL (>= 2)
LazyData: TRUE
NeedsCompilation: yes
Packaged: 2019-06-23 20:13:43 UTC; martin
Author: Martin Blostein [aut, cre], Antonio Punzo [aut], Paul D. McNicholas [aut, ths]
Maintainer: Martin Blostein <martin.blostein@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-24 14:30:03 UTC

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New package GenTag with initial version 1.0
Package: GenTag
Type: Package
Title: Generate Color Tag Sequences
Version: 1.0
Date: 2019-06-21
Author: Carlos Biagolini-Jr.
Maintainer: Carlos Biagolini-Jr.<c.biagolini@gmail.com>
Description: Implement a coherent and flexible protocol for animal color tagging. 'GenTag' provides a simple computational routine with low CPU usage to create color sequences for animal tag. First, a single-color tag sequence is created from an algorithm selected by the user, followed by verification of the combination uniqueness. Three methods to produce color tag sequences are provided. Users can modify the main function core to allow a wide range of applications.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-06-23 15:15:06 UTC; biago
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-06-24 14:20:03 UTC

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Package SqlRender updated to version 1.6.2 with previous version 1.6.0 dated 2019-02-15

Title: Rendering Parameterized SQL and Translation to Dialects
Description: A rendering tool for parameterized SQL that also translates into different SQL dialects. These dialects include 'Microsoft Sql Server', 'Oracle', 'PostgreSql', 'Amazon RedShift', 'Apache Impala', 'IBM Netezza', 'Google BigQuery', 'Microsoft PDW', and 'SQLite'.
Author: Martijn Schuemie [aut, cre], Marc Suchard [aut]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

Diff between SqlRender versions 1.6.0 dated 2019-02-15 and 1.6.2 dated 2019-06-24

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New package sensibo.sky with initial version 1.0.0
Package: sensibo.sky
Title: Access to 'Sensibo Sky' API V2 for Air Conditioners Remote Control
Version: 1.0.0
Authors@R: person("Gabriele", "Baldassarre", role = c("aut", "cre"), email = "gabriele@gabrielebaldassarre.com")
Description: Provides an interface to the 'Sensibo Sky' API which allows to remotely control non-smart air conditioning units. See <https://sensibo.com> for more informations.
URL: https://github.com/theclue/sensibo.sky
BugReports: https://github.com/theclue/sensibo.sky/issues
Depends: R (>= 3.0)
License: MIT + file LICENSE
LazyData: true
NeedsCompilation: no
Imports: httr, jsonlite, glue
Suggests: testthat
RoxygenNote: 6.1.1
Packaged: 2019-06-22 12:54:14 UTC; rstudio
Author: Gabriele Baldassarre [aut, cre]
Maintainer: Gabriele Baldassarre <gabriele@gabrielebaldassarre.com>
Repository: CRAN
Date/Publication: 2019-06-24 13:10:03 UTC

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New package mmetrics with initial version 0.1.0
Package: mmetrics
Type: Package
Title: Easy Computation of Marketing Metrics with Different Analysis Axis
Version: 0.1.0
Authors@R: c( person("Shinichi", "Takayanagi", , "shinichi.takayanagi@gmail.com", role = c("aut", "cre")), person("Nagi", "Teramo", , "teramonagi@gmail.com", role = c("aut")), person("Takahiro", "Yoshinaga", , "t.yoshinaga0106@gmail.com", role = c("aut")) )
Description: Provides a mechanism for easy computation of marketing metrics. By default in this package, metrics for digital marketing (e.g. CTR (Click Through Rate), CVR (Conversion Rate), CPC (Cost Per Click) etc) are calculated but you can define your own metrics easily. In addition to that, you can change an analysis axis to calculate these metrics.
URL: https://github.com/shinichi-takayanagi/mmetrics
BugReports: https://github.com/shinichi-takayanagi/mmetrics/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: magrittr, dplyr, purrr, stringr, rlang
Suggests: covr, devtools, testthat, knitr, rmarkdown
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-23 06:54:12 UTC; stakaya
Author: Shinichi Takayanagi [aut, cre], Nagi Teramo [aut], Takahiro Yoshinaga [aut]
Maintainer: Shinichi Takayanagi <shinichi.takayanagi@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-24 13:30:03 UTC

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Package mev updated to version 1.12 with previous version 1.11 dated 2018-02-22

Title: Multivariate Extreme Value Distributions
Description: Exact simulation from max-stable processes, R-Pareto processes for various parametric models. Threshold selection methods. Multivariate extreme diagnostics. Estimation and likelihoods for univariate extremes.
Author: Leo Belzile [aut, cre] (<https://orcid.org/0000-0002-9135-014X>), Jennifer L. Wadsworth [aut], Paul J. Northrop [aut], Scott D. Grimshaw [aut], Jin Zhang [ctb], Michael A. Stephens [ctb], Art B. Owen [ctb], Raphael Huser [aut]
Maintainer: Leo Belzile <belzilel@gmail.com>

Diff between mev versions 1.11 dated 2018-02-22 and 1.12 dated 2019-06-24

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New package kernelPSI with initial version 1.0.0
Package: kernelPSI
Title: Post-Selection Inference for Nonlinear Variable Selection
Version: 1.0.0
Date: 2019-06-20
Authors@R: c(person("Lotfi", "Slim", email = "lotfi.slim@mines-paristech.fr", role = c("aut", "cre")), person("Clément", "Chatelain", email = "clement.chatelain@sanofi.com", role = "ctb"), person("Chloé-Agathe", "Azencott", email = "chloe-agathe.azencott@mines-paristech.fr", role ="ctb"), person("Jean-Philippe", "Vert", email = "jpvert@google.com", role ="ctb"))
Description: Different post-selection inference strategies for kernel selection, as described in "kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection", Slim et al., Proceedings of Machine Learning Research, 2019, <http://proceedings.mlr.press/v97/slim19a/slim19a.pdf>. The strategies rest upon quadratic kernel association scores to measure the association between a given kernel and an outcome of interest. The inference step tests for the joint effect of the selected kernels on the outcome. A fast constrained sampling algorithm is proposed to derive empirical p-values for the test statistics.
URL: http://proceedings.mlr.press/v97/slim19a.html
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.1), CompQuadForm, tmg, pracma, kernlab, lmtest
Suggests: bindata, knitr, rmarkdown, MASS, testthat
Encoding: UTF-8
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-06-22 21:28:24 UTC; lotfislim
Author: Lotfi Slim [aut, cre], Clément Chatelain [ctb], Chloé-Agathe Azencott [ctb], Jean-Philippe Vert [ctb]
Maintainer: Lotfi Slim <lotfi.slim@mines-paristech.fr>
Repository: CRAN
Date/Publication: 2019-06-24 13:20:03 UTC

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Package forestplot updated to version 1.9 with previous version 1.8 dated 2019-06-01

Title: Advanced Forest Plot Using 'grid' Graphics
Description: A forest plot that allows for multiple confidence intervals per row, custom fonts for each text element, custom confidence intervals, text mixed with expressions, and more. The aim is to extend the use of forest plots beyond meta-analyses. This is a more general version of the original 'rmeta' package's forestplot() function and relies heavily on the 'grid' package.
Author: Max Gordon [aut, cre], Thomas Lumley [aut, ctb]
Maintainer: Max Gordon <max@gforge.se>

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New package SeqNet with initial version 1.0.0
Package: SeqNet
Title: Generate RNA-Seq Data from Gene-Gene Association Networks
Version: 1.0.0
Authors@R: c(person("Tyler", "Grimes", role = c("aut", "cre"), email = "tyler.grimes@ufl.edu"), person("Somnath", "Datta", role = c("aut")))
Author: Tyler Grimes [aut, cre], Somnath Datta [aut]
Maintainer: Tyler Grimes <tyler.grimes@ufl.edu>
Description: Methods to generate random gene-gene association networks and simulate RNA-seq data from them. Includes functions to generate random networks of any size and perturb them to obtain differential networks. Network objects are built from individual, overlapping modules that represent pathways. The resulting network has various topological properties that are characteristic of gene regulatory networks. RNA-seq data can be generated such that the association among gene expression profiles reflect the underlying network. A reference RNA-seq dataset can be provided to model realistic marginal distributions. Plotting functions are available to visualize a network, compare two networks, and compare the expression of two genes across multiple networks.
Depends: R (>= 3.5.0)
Imports: fitdistrplus, ggplot2, grDevices, graphics, igraph, mvtnorm, purrr, RColorBrewer, tibble, Rcpp, rlang, stats, utils
Suggests: knitr, rmarkdown, testthat
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2019-06-21 18:24:30 UTC; Grimes
Repository: CRAN
Date/Publication: 2019-06-24 11:10:03 UTC

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New package hagis with initial version 2.0.0
Package: hagis
Title: Analysis of Plant Pathogen Pathotype Complexities, Distributions and Diversity
Version: 2.0.0
Authors@R: c( person(given = "Austin G.", family = "McCoy", role = c("aut", "ccp"), email = "mccoyaus@msu.edu", comment = c(ORCID = "0000-0003-2483-4184")), person(given = "Zachary", family = "Noel", role = c("aut", "ccp"), email = "noelzach@msu.edu", comment = c(ORCID = "0000-0001-6375-8300")), person(given = "Adam H.", family = "Sparks", role = c("aut", "cre"), email = "adam.sparks@usq.edu.au", comment = c(ORCID = "0000-0002-0061-8359")), person(given = "Martin", family = "Chilvers", role = "aut", email = "chilvers@msu.edu ", comment = c(ORCID = "0000-0001-8832-1666")) )
Description: Analysis of plant pathogen pathotype survey data. Functions provided calculate distribution of susceptibilities, distribution of complexities with statistics, pathotype frequency distribution, as well as diversity indices for pathotypes. This package is meant to be a direct replacement for Herrmann, Löwer, Schachtel's (1999) <doi:10.1046/j.1365-3059.1999.00325.x> Habgood-Gilmour Spreadsheet, 'HaGiS', previously used for pathotype analysis.
Depends: R (>= 3.2.0)
Imports: data.table, ggplot2, graphics, pander, stats, utils, vegan
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: covr, knitr, pkgdown, rmarkdown, testthat, vdiffr
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Language: en-US
URL: https://github.com/openplantpathology/hagis, https://openplantpathology.github.io/hagis/
BugReports: https://github.com/openplantpathology/hagis/issues
X-schema.org-applicationCategory: Tools
X-schema.org-keywords: plant-pathology, pathotype, pathogen-survey, virulence analysis, differential set, assessment scale
X-schema.org-isPartOf: https://openplantpathology.org
NeedsCompilation: no
Packaged: 2019-06-22 03:09:55 UTC; adamsparks
Author: Austin G. McCoy [aut, ccp] (<https://orcid.org/0000-0003-2483-4184>), Zachary Noel [aut, ccp] (<https://orcid.org/0000-0001-6375-8300>), Adam H. Sparks [aut, cre] (<https://orcid.org/0000-0002-0061-8359>), Martin Chilvers [aut] (<https://orcid.org/0000-0001-8832-1666>)
Maintainer: Adam H. Sparks <adam.sparks@usq.edu.au>
Repository: CRAN
Date/Publication: 2019-06-24 11:50:03 UTC

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Package lime updated to version 0.5.0 with previous version 0.4.1 dated 2018-11-21

Title: Local Interpretable Model-Agnostic Explanations
Description: When building complex models, it is often difficult to explain why the model should be trusted. While global measures such as accuracy are useful, they cannot be used for explaining why a model made a specific prediction. 'lime' (a port of the 'lime' 'Python' package) is a method for explaining the outcome of black box models by fitting a local model around the point in question an perturbations of this point. The approach is described in more detail in the article by Ribeiro et al. (2016) <arXiv:1602.04938>.
Author: Thomas Lin Pedersen [cre, aut] (<https://orcid.org/0000-0002-5147-4711>), Michaël Benesty [aut]
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>

Diff between lime versions 0.4.1 dated 2018-11-21 and 0.5.0 dated 2019-06-24

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New package blrm with initial version 1.0-1
Package: blrm
Title: Dose Escalation Design in Phase I Oncology Trial Using Bayesian Logistic Regression Modeling
Version: 1.0-1
Date: 2019-06-16
Author: Furong Sun <furongs@vt.edu>, Zhonggai Li <zli@bostonbiomedical.com>
Depends: R (>= 2.15.1)
Imports: boot, rjags, mvtnorm, openxlsx, reshape2
Description: Plan dose escalation design using adaptive Bayesian logistic regression modeling in Phase I oncology trial.
Maintainer: Furong Sun <furongs@vt.edu>
License: LGPL
NeedsCompilation: no
Packaged: 2019-06-21 18:16:05 UTC; furong
Repository: CRAN
Date/Publication: 2019-06-24 11:00:04 UTC

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Package inlabru updated to version 2.1.12 with previous version 2.1.9 dated 2018-07-24

Title: Spatial Inference using Integrated Nested Laplace Approximation
Description: Facilitates spatial modeling using integrated nested Laplace approximation via the INLA package (<http://www.r-inla.org>). Additionally, implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. See Yuan Yuan, Fabian E. Bachl, Finn Lindgren, David L. Borchers, Janine B. Illian, Stephen T. Buckland, Havard Rue, Tim Gerrodette (2017), <arXiv:1604.06013>.
Author: Fabian E. Bachl [aut, cre] (Fabian Bachl wrote the main code), Finn Lindgren [aut] (<https://orcid.org/0000-0002-5833-2011>, Finn Lindgren wrote code for SPDE posterior plotting, and continued development of the main code), David L. Borchers [ctb] (David Borchers wrote code for Gorilla data import and sampling, multiplot tool), Daniel Simpson [ctb] (Daniel Simpson wrote the basic LGCP sampling method), Lindesay Scott-Howard [ctb] (Lindesay Scott-Howard provied MRSea data import code)
Maintainer: Fabian E. Bachl <bachlfab@gmail.com>

Diff between inlabru versions 2.1.9 dated 2018-07-24 and 2.1.12 dated 2019-06-24

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Package enc updated to version 0.2.1 with previous version 0.2.0 dated 2018-03-03

Title: Portable Tools for 'UTF-8' Character Data
Description: Implements an S3 class for storing 'UTF-8' strings, based on regular character vectors. Also contains routines to portably read and write 'UTF-8' encoded text files, to convert all strings in an object to 'UTF-8', and to create character vectors with various encodings.
Author: Kirill Müller [aut, cre]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

Diff between enc versions 0.2.0 dated 2018-03-03 and 0.2.1 dated 2019-06-24

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Package interim updated to version 0.8.0 with previous version 0.7.0 dated 2017-07-12

Title: Scheduling Interim Analyses in Clinical Trials
Description: Allows the simulation of the recruitment and both the event and treatment phase of a clinical trial. Based on these simulations, the timing of interim analyses can be assessed.
Author: Bastian Becker, Katharina Mueller, Hermann Kulmann
Maintainer: Bastian Becker <bastian.becker@bayer.com>

Diff between interim versions 0.7.0 dated 2017-07-12 and 0.8.0 dated 2019-06-24

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Package huxtable updated to version 4.6.0 with previous version 4.5.0 dated 2019-03-19

Title: Easily Create and Style Tables for LaTeX, HTML and Other Formats
Description: Like 'xtable', creates styled tables. Export to HTML, LaTeX, 'Word', 'Excel', 'PowerPoint' and RTF. Simple, modern interface to manipulate borders, size, position, captions, colours, text styles and number formatting. Table cells can span multiple rows and/or columns. Includes a 'huxreg' function for creation of regression tables, and 'quick_*' one-liners to print data to a new document.
Author: David Hugh-Jones [aut, cre]
Maintainer: David Hugh-Jones <davidhughjones@gmail.com>

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Package ClusVis updated to version 1.2.0 with previous version 1.1.0 dated 2018-04-19

Title: Gaussian-Based Visualization of Gaussian and Non-Gaussian Model-Based Clustering
Description: Gaussian-Based Visualization of Gaussian and Non-Gaussian Model-Based Clustering done on any type of data. Visualization is based on the probabilities of classification.
Author: Christophe Biernacki [aut], Matthieu Marbac [aut, cre], Vincent Vandewalle [aut]
Maintainer: Matthieu Marbac <matthieu.marbac@gmail.com>

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Package IceCast updated to version 2.1.0 with previous version 1.2.0 dated 2017-08-16

Title: Apply Statistical Post-Processing to Improve Sea Ice Predictions
Description: Tools for correcting biases and calibrating sea ice predictions obtained from dynamic ensemble models. Implements and extends Director et al. (2017) <doi:10.1175/JCLI-D-17-0185.1> This package depends on the 'ncdf4' and 'rgeos' R packages. These packages require installing externally from R Unidata's 'NetCDF' library and Geometry Engine - Open Source ('GEOS'). (See the 'rgeos' and 'ncdf4' packages for details.)
Author: Hannah M. Director, Adrian E. Raftery, and Cecilia M. Bitz
Maintainer: Hannah M. Director <direch@uw.edu>

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Package pomp updated to version 2.2 with previous version 2.1 dated 2019-06-03

Title: Statistical Inference for Partially Observed Markov Processes
Description: Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.
Author: Aaron A. King [aut, cre], Edward L. Ionides [aut], Carles Breto [aut], Stephen P. Ellner [ctb], Matthew J. Ferrari [ctb], Bruce E. Kendall [ctb], Michael Lavine [ctb], Dao Nguyen [ctb], Daniel C. Reuman [ctb], Helen Wearing [ctb], Simon N. Wood [ctb], Sebastian Funk [ctb], Steven G. Johnson [ctb], Eamon O'Dea [ctb]
Maintainer: Aaron A. King <kingaa@umich.edu>

Diff between pomp versions 2.1 dated 2019-06-03 and 2.2 dated 2019-06-24

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Package plothelper updated to version 0.1.3 with previous version 0.1.2 dated 2019-06-09

Title: New Plots Based on 'ggplot2' and Functions to Create Regular Shapes
Description: An extension to 'ggplot2' with miscellaneous functions. It contains two groups of functions: Functions in the first group draw 'ggplot2' - based plots: gg_shading_bar() draws barplot with shading colors in each bar. geom_rect_cm(), geom_circle_cm() and geom_ellipse_cm() draw rectangles, circles and ellipses with centimeter as their unit. Thus their sizes do not change when the coordinate system or the aspect ratio changes. annotation_transparent_text() draws labels with transparent texts. annotation_shading_polygon() draws irregular polygons with shading colors. Functions in the second group generate coordinates for regular shapes and make linear transformations.
Author: Jiang Wu [aut, cre] (from Capital Normal University)
Maintainer: Jiang Wu <textidea@sina.com>

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Package pbdSLAP updated to version 0.2-6 with previous version 0.2-5 dated 2019-04-08

Title: Programming with Big Data -- Scalable Linear Algebra Packages
Description: Utilizing scalable linear algebra packages mainly including 'BLACS', 'PBLAS', and 'ScaLAPACK' in double precision via 'pbdMPI' based on 'ScaLAPACK' version 2.0.2.
Author: Wei-Chen Chen [aut, cre], Drew Schmidt [aut], George Ostrouchov [aut], Pragneshkumar Patel [aut], Brian Ripley [ctb] (Solaris & Mac)
Maintainer: Wei-Chen Chen <wccsnow@gmail.com>

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Package IDE updated to version 0.3.0 with previous version 0.2.0 dated 2018-08-07

Title: Integro-Difference Equation Spatio-Temporal Models
Description: The Integro-Difference Equation model is a linear, dynamical model used to model phenomena that evolve in space and in time; see, for example, Cressie and Wikle (2011, ISBN:978-0-471-69274-4) or Dewar et al. (2009) <doi:10.1109/TSP.2008.2005091>. At the heart of the model is the kernel, which dictates how the process evolves from one time point to the next. Both process and parameter reduction are used to facilitate computation, and spatially-varying kernels are allowed. Data used to estimate the parameters are assumed to be readings of the process corrupted by Gaussian measurement error. Parameters are fitted by maximum likelihood, and estimation is carried out using an evolution algorithm.
Author: Andrew Zammit-Mangion [aut, cre]
Maintainer: Andrew Zammit-Mangion <andrewzm@gmail.com>

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Package groupdata2 updated to version 1.1.0 with previous version 1.0.0 dated 2017-10-21

Title: Creating Groups from Data
Description: Subsetting methods for balanced cross-validation, time series windowing, and general grouping and splitting of data.
Author: Ludvig Renbo Olsen [aut, cre]
Maintainer: Ludvig Renbo Olsen <r-pkgs@ludvigolsen.dk>

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Package gggenes updated to version 0.4.0 with previous version 0.3.2 dated 2018-11-07

Title: Draw Gene Arrow Maps in 'ggplot2'
Description: Provides a 'ggplot2' geom and helper functions for drawing gene arrow maps.
Author: David Wilkins [aut, cre], Zachary Kurtz [ctb]
Maintainer: David Wilkins <david@wilkox.org>

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Package colorSpec updated to version 1.0-1 with previous version 0.9-1 dated 2019-05-31

Title: Color Calculations with Emphasis on Spectral Data
Description: Calculate with spectral properties of light sources, materials, cameras, eyes, and scanners. Build complex systems from simpler parts using a spectral product algebra. For light sources, compute CCT, CRI, and SSI. For object colors, compute optimal colors and Logvinenko coordinates. Work with the standard CIE illuminants and color matching functions, and read spectra from text files, including CGATS files. Estimate a spectrum from its response. A user guide and 9 vignettes are included.
Author: Glenn Davis [aut, cre]
Maintainer: Glenn Davis <gdavis@gluonics.com>

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Package QDComparison updated to version 3.0 with previous version 2.0 dated 2018-10-30

Title: Modern Nonparametric Tools for Two-Sample Quantile and Distribution Comparisons
Description: Allows practitioners to determine (i) if two univariate distributions (which can be continuous, discrete, or even mixed) are equal, (ii) how two distributions differ (shape differences, e.g., location, scale, etc.), and (iii) where two distributions differ (at which quantiles), all using nonparametric LP statistics. The primary reference is Jungreis, D. (2019, Technical Report).
Author: David Jungreis, Subhadeep Mukhopadhyay
Maintainer: David Jungreis <dbjungreis@gmail.com>

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Sun, 23 Jun 2019

Package ggfittext updated to version 0.8.0 with previous version 0.7.0 dated 2019-05-29

Title: Fit Text Inside a Box in 'ggplot2'
Description: Provides 'ggplot2' geoms to fit text into a box by growing, shrinking or wrapping the text.
Author: David Wilkins [aut, cre]
Maintainer: David Wilkins <david@wilkox.org>

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Package objectremover updated to version 0.7.0 with previous version 0.6.4 dated 2019-03-06

Title: 'RStudio' Addin for Removing Objects from the Global Environment Based on Patterns and Object Type
Description: An 'RStudio' addin to assist with removing objects from the global environment. Features include removing objects according to name patterns and object type. During the course of an analysis, temporary objects are often created and this tool assists with removing them quickly. This can be useful when memory management within 'R' is important.
Author: Alan Yeung [aut, cre] (<https://orcid.org/0000-0001-5226-3695>)
Maintainer: Alan Yeung <alan_y987@hotmail.com>

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Package guardianapi updated to version 0.1.1 with previous version 0.1.0 dated 2019-02-03

Title: Access 'The Guardian' Newspaper Open Data API
Description: Access to 'The Guardian' newspaper's open API <https://open-platform.theguardian.com/>, containing all articles published in 'The Guardian' from 1999 to the present, including article text, metadata, tags and contributor information. An API key and registration is required.
Author: Evan Odell [aut, cre] (<https://orcid.org/0000-0003-1845-808X>)
Maintainer: Evan Odell <evanodell91@gmail.com>

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Package genepop updated to version 1.1.2 with previous version 1.0.5 dated 2017-08-23

Title: Population Genetic Data Analysis Using Genepop
Description: Makes the Genepop software available in R. This software implements a mixture of traditional population genetic methods and some more focused developments: it computes exact tests for Hardy-Weinberg equilibrium, for population differentiation and for genotypic disequilibrium among pairs of loci; it computes estimates of F-statistics, null allele frequencies, allele size-based statistics for microsatellites, etc.; and it performs analyses of isolation by distance from pairwise comparisons of individuals or population samples.
Author: François Rousset [aut, cre, cph], Jimmy Lopez [ctb], Khalid Belkhir [ctb]
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

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Package officer updated to version 0.3.5 with previous version 0.3.4 dated 2019-04-30

Title: Manipulation of Microsoft Word and PowerPoint Documents
Description: Access and manipulate 'Microsoft Word' and 'Microsoft PowerPoint' documents from R. The package focuses on tabular and graphical reporting from R; it also provides two functions that let users get document content into data objects. A set of functions lets add and remove images, tables and paragraphs of text in new or existing documents. When working with 'PowerPoint' presentations, slides can be added or removed; shapes inside slides can also be added or removed. When working with 'Word' documents, a cursor can be used to help insert or delete content at a specific location in the document. The package does not require any installation of Microsoft products to be able to write Microsoft files.
Author: David Gohel [aut, cre], Frank Hangler [ctb] (function body_replace_all_text), Liz Sander [ctb] (several documentation fixes), Anton Victorson [ctb] (fixes xml structures), Jon Calder [ctb] (update vignettes), John Harrold [ctb] (fuction annotate_base)
Maintainer: David Gohel <david.gohel@ardata.fr>

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Package hR updated to version 0.2.0 with previous version 0.1.9 dated 2019-04-29

Title: Toolkit for Data Analytics in Human Resources
Description: Transform and analyze workforce data in meaningful ways for human resources (HR) analytics. Two functions, 'hierarchyLong' and 'hierarchyWide', convert standard employee and supervisor relationship data into useful formats. A 'workforcePlan' app is available for simple workforce planning.
Author: Dale Kube [aut, cre]
Maintainer: Dale Kube <dkube@uwalumni.com>

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Package pct updated to version 0.2.2 with previous version 0.2.1 dated 2019-05-14

Title: Propensity to Cycle Tool
Description: Functions and example data to teach and increase the reproducibility of the methods and code underlying the Propensity to Cycle Tool (PCT), a research project and web application hosted at <https://www.pct.bike/>. For an academic paper on the methods, see Lovelace et al (2017) <doi:10.5198/jtlu.2016.862>.
Author: Robin Lovelace [aut, cre] (<https://orcid.org/0000-0001-5679-6536>), Layik Hama [aut] (<https://orcid.org/0000-0003-1912-4890>)
Maintainer: Robin Lovelace <rob00x@gmail.com>

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Package PerformanceAnalytics updated to version 1.5.3 with previous version 1.5.2 dated 2018-03-02

Title: Econometric Tools for Performance and Risk Analysis
Description: Collection of econometric functions for performance and risk analysis. In addition to standard risk and performance metrics, this package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.
Author: Brian G. Peterson [cre, aut, cph], Peter Carl [aut, cph], Kris Boudt [ctb, cph], Ross Bennett [ctb], Joshua Ulrich [ctb], Eric Zivot [ctb], Dries Cornilly [ctb], Eric Hung [ctb], Matthieu Lestel [ctb], Kyle Balkissoon [ctb], Diethelm Wuertz [ctb]
Maintainer: Brian G. Peterson <brian@braverock.com>

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Package hmi updated to version 0.9.16 with previous version 0.9.15 dated 2018-12-13

Title: Hierarchical Multiple Imputation
Description: Runs single level and multilevel imputation models. The user just has to pass the data to the main function and, optionally, his analysis model. Basically the package then translates this analysis model into commands to impute the data according to it with functions from 'mice', 'MCMCglmm' or routines build for this package.
Author: Matthias Speidel [aut, cre] (Munich, Germany), Joerg Drechsler [aut] (Institute for Employment Research, Nuremberg, Germany), Shahab Jolani [aut] (Maastricht University, Maastricht, The Netherlands)
Maintainer: Matthias Speidel <matthias.speidel@googlemail.com>

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Package binb updated to version 0.0.4 with previous version 0.0.3 dated 2018-10-12

Title: 'binb' is not 'Beamer'
Description: A collection of 'LaTeX' styles using 'Beamer' customization for pdf-based presentation slides in 'RMarkdown'. At present it contains 'RMarkdown' adaptations of the LaTeX themes 'Metropolis' (formerly 'mtheme') theme by Matthias Vogelgesang and others (now included in 'TeXLive'), the 'IQSS' by Ista Zahn (which is included here), and the 'Monash' theme by Rob J Hyndman. Additional (free) fonts may be needed: 'Metropolis' prefers 'Fira', and 'IQSS' requires 'Libertinus'.
Author: Dirk Eddelbuettel, Ista Zahn and Rob Hyndman
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package txtq updated to version 0.1.3 with previous version 0.1.2 dated 2019-01-06

Title: A Small Message Queue for Parallel Processes
Description: This queue is a data structure that lets parallel processes send and receive messages, and it can help coordinate the work of complicated parallel tasks. Processes can push new messages to the queue, pop old messages, and obtain a log of all the messages ever pushed. File locking preserves the integrity of the data even when multiple processes access the queue simultaneously.
Author: William Michael Landau [aut, cre] (<https://orcid.org/0000-0003-1878-3253>), Ian E. Fellows [ctb], Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>

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Package tabr updated to version 0.3.0 with previous version 0.2.0 dated 2018-05-17

Title: Create Guitar Tablature
Description: Creates guitar tablature from R code by providing functions for describing and organizing musical structures and wrapping around the 'LilyPond' backend (<http://lilypond.org>). 'LilyPond' is open source music engraving software for generating high quality sheet music based on markup language. 'tabr' provides a wrapper around this software and generates files following the 'LilyPond' markup syntax to be subsequently processed by 'LilyPond' into sheet music pdf files. A standalone 'LilyPond' file can be created or the package can make a system call to 'LilyPond' directly to render the guitar tablature output. While 'LilyPond' caters to sheet music in general, 'tabr' is focused on leveraging it specifically for creating quality guitar tablature. 'tabr' offers nominal MIDI file support in addition to its focus on tablature transcription. See the 'tuneR' package for more general use of MIDI files in R. 'tabr' also provides a collection of helper functions for manipulating and transforming strings of musical notes, pitches, chords, keys, scales and modes.
Author: Matthew Leonawicz [aut, cre]
Maintainer: Matthew Leonawicz <matt_leonawicz@esource.com>

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Package spatstat updated to version 1.60-1 with previous version 1.59-0 dated 2019-03-22

Title: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Description: Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images. Contains over 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.
Author: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>, Rolf Turner <r.turner@auckland.ac.nz> and Ege Rubak <rubak@math.aau.dk>, with substantial contributions of code by Kasper Klitgaard Berthelsen; Ottmar Cronie; Tilman Davies; Yongtao Guan; Ute Hahn; Abdollah Jalilian; Marie-Colette van Lieshout; Greg McSwiggan; Tuomas Rajala; Suman Rakshit; Dominic Schuhmacher; Rasmus Waagepetersen; and Hangsheng Wang. Additional contributions by M. Adepeju; C. Anderson; Q.W. Ang; R. Arellano; J. Astrom; M. Austenfeld; S. Azaele; M. Baddeley; C. Beale; M. Bell; R. Bernhardt; T. Bendtsen; A. Bevan; B. Biggerstaff; A. Bilgrau; L. Bischof; C. Biscio; R. Bivand; J.M. Blanco Moreno; F. Bonneu; J. Burgos; S. Byers; Y.M. Chang; J.B. Chen; I. Chernayavsky; Y.C. Chin; B. Christensen; L. Cobo Sanchez; J.-F. Coeurjolly; K. Colyvas; H. Commenges; R. Constantine; R. Corria Ainslie; R. Cotton; M. de la Cruz; P. Dalgaard; M. D'Antuono; S. Das; P.J. Diggle; P. Donnelly; I. Dryden; S. Eglen; A. El-Gabbas; B. Fandohan; O. Flores; E.D. Ford; P. Forbes; S. Frank; J. Franklin; N. Funwi-Gabga; O. Garcia; A. Gault; J. Geldmann; M. Genton; S. Ghalandarayeshi; J. Gilbey; J. Goldstick; P. Grabarnik; C. Graf; U. Hahn; A. Hardegen; M.B. Hansen; M. Hazelton; J. Heikkinen; M. Hering; M. Herrmann; M. Hesselbarth; P. Hewson; H. Heydarian; K. Hingee; K. Hornik; P. Hunziker; J. Hywood; R. Ihaka; C. Icos; A. Jammalamadaka; R. John-Chandran; D. Johnson; M. Khanmohammadi; R. Klaver; P. Kovesi; L. Kozmian-Ledward; M. Kuhn; J. Laake; R.A. Lamb; F. Lavancier; T. Lawrence; T. Lazauskas; J. Lee; G.P. Leser; A. Li; H.T. Li; G. Limitsios; A. Lister; B. Madin; M. Maechler; J. Marcus; K. Marchikanti; R. Mark; J. Mateu; P. McCullagh; U. Mehlig; F. Mestre; S. Meyer; X.C. Mi; L. De Middeleer; R.K. Milne; E. Miranda; J. Moller; I. Moncada; M. Moradi; V. Morera Pujol; E. Mudrak; G.M. Nair; N. Najari; N. Nava; L.S. Nielsen; F. Nunes; J.R. Nyengaard; J. Oehlschlaegel; T. Onkelinx; S. O'Riordan; E. Parilov; J. Picka; N. Picard; T. Pollington; M. Porter; S. Protsiv; A. Raftery; S. Rakshit; B. Ramage; P. Ramon; X. Raynaud; N. Read; M. Reiter; I. Renner; T.O. Richardson; B.D. Ripley; E. Rosenbaum; B. Rowlingson; J. Rudokas; J. Rudge; C. Ryan; F. Safavimanesh; A. Sarkka; C. Schank; K. Schladitz; S. Schutte; B.T. Scott; O. Semboli; F. Semecurbe; V. Shcherbakov; G.C. Shen; P. Shi; H.-J. Ship; T.L. Silva; I.-M. Sintorn; Y. Song; M. Spiess; M. Stevenson; K. Stucki; J. Sulavik; M. Sumner; P. Surovy; B. Taylor; T. Thorarinsdottir; L. Torres; B. Turlach; T. Tvedebrink; K. Ummer; M. Uppala; A. van Burgel; T. Verbeke; M. Vihtakari; A. Villers; F. Vinatier; S. Voss; S. Wagner; H. Wang; H. Wendrock; J. Wild; C. Witthoft; S. Wong; M. Woringer; L. Yates; M.E. Zamboni and A. Zeileis.
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package icr updated to version 0.6.0 with previous version 0.5.9 dated 2019-02-14

Title: Compute Krippendorff's Alpha
Description: Provides functions to compute and plot Krippendorff's inter-coder reliability coefficient alpha and bootstrapped uncertainty estimates (Krippendorff 2004, ISBN:0761915443). The bootstrap routines are set up to make use of parallel threads where supported.
Author: Alexander Staudt [aut, cre], Pierre L'Ecuyer [ctb] (author of the C++ RNG code)
Maintainer: Alexander Staudt <staudtlex@live.de>

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Package AMR updated to version 0.7.1 with previous version 0.7.0 dated 2019-06-03

Title: Antimicrobial Resistance Analysis
Description: Functions to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods.
Author: Matthijs S. Berends [aut, cre] (<https://orcid.org/0000-0001-7620-1800>), Christian F. Luz [aut] (<https://orcid.org/0000-0001-5809-5995>), Erwin E. A. Hassing [ctb], Corinna Glasner [aut, ths] (<https://orcid.org/0000-0003-1241-1328>), Alex W. Friedrich [aut, ths] (<https://orcid.org/0000-0003-4881-038X>), Bhanu N. M. Sinha [aut, ths] (<https://orcid.org/0000-0003-1634-0010>)
Maintainer: Matthijs S. Berends <m.s.berends@umcg.nl>

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Package auk updated to version 0.3.3 with previous version 0.3.2 dated 2019-02-04

Title: eBird Data Extraction and Processing in R
Description: Extract and process bird sightings records from eBird (<http://ebird.org>), an online tool for recording bird observations. Public access to the full eBird database is via the eBird Basic Dataset (EBD; see <http://ebird.org/ebird/data/download> for access), a downloadable text file. This package is an interface to AWK for extracting data from the EBD based on taxonomic, spatial, or temporal filters, to produce a manageable file size that can be imported into R.
Author: Matthew Strimas-Mackey [aut, cre] (<https://orcid.org/0000-0001-8929-7776>), Eliot Miller [aut], Wesley Hochachka [aut], Cornell Lab of Ornithology [cph]
Maintainer: Matthew Strimas-Mackey <mes335@cornell.edu>

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Package strex updated to version 1.1.1 with previous version 1.1.0 dated 2019-06-15

Title: Extra String Manipulation Functions
Description: There are some things that I wish were easier with the 'stringr' or 'stringi' packages. The foremost of these is the extraction of numbers from strings. 'stringr' and 'stringi' make you figure out the regular expression for yourself; 'strex' takes care of this for you. There are many other handy functionalities in 'strex'. Contributions to this package are encouraged: it is intended as a miscellany of string manipulation functions that cannot be found in 'stringi' or 'stringr'.
Author: Rory Nolan [aut, cre] (<https://orcid.org/0000-0002-5239-4043>)
Maintainer: Rory Nolan <rorynoolan@gmail.com>

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Package cricketr updated to version 0.0.20 with previous version 0.0.19 dated 2019-06-08

Title: Analyze Cricketers and Cricket Teams Based on ESPN Cricinfo Statsguru
Description: Tools for analyzing performances of cricketers based on stats in ESPN Cricinfo Statsguru. The toolset can be used for analysis of Tests,ODIs and Twenty20 matches of both batsmen and bowlers. The package can also be used to analyze team performances.
Author: Tinniam V Ganesh
Maintainer: Tinniam V Ganesh <tvganesh.85@gmail.com>

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Package tram updated to version 0.2-6 with previous version 0.2-5 dated 2019-02-27

Title: Transformation Models
Description: Formula-based user-interfaces to specific transformation models implemented in package 'mlt'. Available models include Cox models, some parametric survival models (Weibull, etc.), models for ordered categorical variables, normal and non-normal (Box-Cox type) linear models, and continuous outcome logistic regression (Lohse et al., 2017, <DOI:10.12688/f1000research.12934.1>). The underlying theory is described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package samplesize4surveys updated to version 3.7.5.1 with previous version 3.6.1.0 dated 2018-07-23

Title: Sample Size Calculations for Complex Surveys
Description: Computes the required sample size for estimation of totals, means and proportions under complex sampling designs.
Author: Hugo Andres Gutierrez Rojas
Maintainer: Hugo Andres Gutierrez Rojas <hagutierrezro@gmail.com>

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Package mlt.docreg updated to version 1.0-3 with previous version 1.0-2 dated 2018-08-16

Title: Most Likely Transformations: Documentation and Regression Tests
Description: Additional documentation, a package vignette and regression tests for package mlt.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package missingHE updated to version 1.1.1 with previous version 1.0.1 dated 2019-06-05

Title: Missing Outcome Data in Health Economic Evaluation
Description: Contains a suite of functions for health economic evaluations with missing outcome data. The package can fit different types of statistical models under a fully Bayesian approach using the software 'JAGS' (which should be installed locally and which is loaded in 'missingHE' via the 'R' package 'R2jags'). Three classes of models can be fitted under a variety of missing data assumptions: selection models, pattern mixture models and hurdle models. In addition to model fitting, 'missingHE' provides a set of specialised functions to assess model convergence and summarise the statistical and economic results using different types of measures and graphs. The methods implemented are described in Mason (2018) <doi:10.1002/hec.3793>, Molenberghs (2000) <doi:10.1007/978-1-4419-0300-6_18> and Gabrio (2019) <doi:10.1002/sim.8045>.
Author: Andrea Gabrio [aut, cre]
Maintainer: Andrea Gabrio <ucakgab@ucl.ac.uk>

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Package leafR updated to version 0.2 with previous version 0.1.4 dated 2019-06-11

Title: Calculates the Leaf Area Index (LAD) and Other Related Functions
Description: A set of functions for analyzing the structure of forests based on the leaf area density (LAD) and leaf area index (LAI) measures calculated from Airborne Laser Scanning (ALS), i.e., scanning lidar (Light Detection and Ranging) data. The methodology is discussed and described in Almeida et al. (2019) <doi:10.3390/rs11010092> and Stark et al. (2012) <doi:10.1111/j.1461-0248.2012.01864.x>.
Author: Danilo Roberti Alves de Almeida [aut, cre] (<https://orcid.org/0000-0002-8747-0085>), Scott Christopher Stark [aut] (<https://orcid.org/0000-0002-1579-1648>), Carlos Alberto Silva [aut] (<https://orcid.org/0000-0002-7844-3560>), Caio Hamamura [aut] (<https://orcid.org/0000-0001-6149-5885>)
Maintainer: Danilo Roberti Alves de Almeida <daniloflorestas@gmail.com>

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Package ipc updated to version 0.1.3 with previous version 0.1.2 dated 2019-01-11

Title: Tools for Message Passing Between Processes
Description: Provides tools for passing messages between R processes. Shiny Examples are provided showing how to perform useful tasks such as: updating reactive values from within a future, progress bars for long running async tasks, and interrupting async tasks based on user input.
Author: Ian E. Fellows
Maintainer: Ian E. Fellows <ian@fellstat.com>

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Package hdnom updated to version 6.0.0 with previous version 5.0 dated 2018-05-13

Title: Benchmarking and Visualization Toolkit for Penalized Cox Models
Description: Creates nomogram visualizations for penalized Cox regression models, with the support of reproducible survival model building, validation, calibration, and comparison for high-dimensional data.
Author: Nan Xiao [aut, cre] (<https://orcid.org/0000-0002-0250-5673>), Qing-Song Xu [aut], Miao-Zhu Li [aut], Frank Harrell [ctb]
Maintainer: Nan Xiao <me@nanx.me>

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Package ggpubr updated to version 0.2.1 with previous version 0.2 dated 2018-11-15

Title: 'ggplot2' Based Publication Ready Plots
Description: The 'ggplot2' package is excellent and flexible for elegant data visualization in R. However the default generated plots requires some formatting before we can send them for publication. Furthermore, to customize a 'ggplot', the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills. 'ggpubr' provides some easy-to-use functions for creating and customizing 'ggplot2'- based publication ready plots.
Author: Alboukadel Kassambara [aut, cre]
Maintainer: Alboukadel Kassambara <alboukadel.kassambara@gmail.com>

Diff between ggpubr versions 0.2 dated 2018-11-15 and 0.2.1 dated 2019-06-23

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Package aroma.affymetrix updated to version 3.2.0 with previous version 3.1.1 dated 2018-04-16

Title: Analysis of Large Affymetrix Microarray Data Sets
Description: A cross-platform R framework that facilitates processing of any number of Affymetrix microarray samples regardless of computer system. The only parameter that limits the number of chips that can be processed is the amount of available disk space. The Aroma Framework has successfully been used in studies to process tens of thousands of arrays. This package has actively been used since 2006.
Author: Henrik Bengtsson [aut, cre, cph], James Bullard [ctb], Kasper Hansen [ctb], Pierre Neuvial [ctb], Elizabeth Purdom [ctb], Mark Robinson [ctb], Ken Simpson [ctb]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between aroma.affymetrix versions 3.1.1 dated 2018-04-16 and 3.2.0 dated 2019-06-23

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 R/999.AromaAffymetrix.R                                                             |    2 
 R/999.package.R                                                                     |    8 
 R/AffymetrixCdfFile.R                                                               |    6 
 R/AffymetrixCelFile.R                                                               |    2 
 R/AffymetrixCelSet.R                                                                |    2 
 R/AffymetrixPgfFile.R                                                               |    2 
 R/ChipEffectSet.R                                                                   |    2 
 R/FirmaModel.R                                                                      |    2 
 R/FirmaSet.R                                                                        |    2 
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 R/ResidualSet.R                                                                     |    2 
 R/WeightsSet.R                                                                      |    2 
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 inst/testScripts/system/chipTypes/Test3/11.ArrayExplorer.R                          |   30 
 inst/testScripts/testAll.R                                                          |  208 
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 man/aroma.affymetrix-package.Rd                                                     |    8 
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More information about aroma.affymetrix at CRAN
Permanent link

Sat, 22 Jun 2019

Package xtensor updated to version 0.11.1-0 with previous version 0.11.0-0 dated 2019-04-18

Title: Headers for the 'xtensor' Library
Description: The 'xtensor' C++ library for numerical analysis with multi-dimensional array expressions is provided as a header-only C++14 library. It offers an extensible expression system enabling lazy broadcasting; an API following the idioms of the C++ standard library; and tools to manipulate array expressions and build upon 'xtensor'.
Author: Johan Mabille, Sylvain Corlay and Wolf Vollprecht
Maintainer: Sylvain Corlay <sylvain.corlay@gmail.com>

Diff between xtensor versions 0.11.0-0 dated 2019-04-18 and 0.11.1-0 dated 2019-06-22

 DESCRIPTION                                       |    6 
 MD5                                               |  132 ++++----
 R                                                 |only
 README.md                                         |    3 
 inst/include/xsimd/config/xsimd_config.hpp        |    2 
 inst/include/xsimd/math/xsimd_gamma.hpp           |   46 +--
 inst/include/xsimd/math/xsimd_invtrigo.hpp        |   60 +--
 inst/include/xsimd/math/xsimd_power.hpp           |   10 
 inst/include/xsimd/math/xsimd_rem_pio2.hpp        |    3 
 inst/include/xsimd/math/xsimd_trigo_reduction.hpp |   42 +-
 inst/include/xsimd/stl/algorithms.hpp             |    9 
 inst/include/xsimd/types/xsimd_avx512_double.hpp  |   10 
 inst/include/xsimd/types/xsimd_avx512_float.hpp   |   26 -
 inst/include/xsimd/types/xsimd_avx_double.hpp     |    6 
 inst/include/xsimd/types/xsimd_avx_float.hpp      |   10 
 inst/include/xsimd/types/xsimd_base.hpp           |   18 +
 inst/include/xsimd/types/xsimd_fallback.hpp       |    4 
 inst/include/xsimd/types/xsimd_sse_double.hpp     |    8 
 inst/include/xsimd/types/xsimd_sse_float.hpp      |   14 
 inst/include/xtensor-r/roptional.hpp              |    4 
 inst/include/xtensor-r/xtensor_r_config.hpp       |    2 
 inst/include/xtensor/xaccumulator.hpp             |   14 
 inst/include/xtensor/xassign.hpp                  |   24 -
 inst/include/xtensor/xbuffer_adaptor.hpp          |   17 +
 inst/include/xtensor/xbuilder.hpp                 |   88 +++++
 inst/include/xtensor/xcomplex.hpp                 |   42 +-
 inst/include/xtensor/xcontainer.hpp               |   23 -
 inst/include/xtensor/xdynamic_view.hpp            |   38 --
 inst/include/xtensor/xexception.hpp               |   71 +++-
 inst/include/xtensor/xexpression.hpp              |   16 -
 inst/include/xtensor/xfixed.hpp                   |   25 +
 inst/include/xtensor/xfunction.hpp                |   36 --
 inst/include/xtensor/xfunctor_view.hpp            |   37 +-
 inst/include/xtensor/xgenerator.hpp               |    2 
 inst/include/xtensor/xindex_view.hpp              |    5 
 inst/include/xtensor/xiterator.hpp                |   19 -
 inst/include/xtensor/xjson.hpp                    |    2 
 inst/include/xtensor/xmanipulation.hpp            |   24 -
 inst/include/xtensor/xmath.hpp                    |   22 -
 inst/include/xtensor/xmime.hpp                    |    2 
 inst/include/xtensor/xnorm.hpp                    |   23 +
 inst/include/xtensor/xoffset_view.hpp             |   12 
 inst/include/xtensor/xoperation.hpp               |   68 +++-
 inst/include/xtensor/xoptional.hpp                |   36 +-
 inst/include/xtensor/xoptional_assembly_base.hpp  |    2 
 inst/include/xtensor/xpad.hpp                     |   15 
 inst/include/xtensor/xreducer.hpp                 |   79 ++++-
 inst/include/xtensor/xscalar.hpp                  |   16 -
 inst/include/xtensor/xsemantic.hpp                |    2 
 inst/include/xtensor/xshape.hpp                   |    5 
 inst/include/xtensor/xsort.hpp                    |   11 
 inst/include/xtensor/xstorage.hpp                 |   80 ++++-
 inst/include/xtensor/xstrided_view.hpp            |   85 +----
 inst/include/xtensor/xstrided_view_base.hpp       |  333 +++++++++++-----------
 inst/include/xtensor/xstrides.hpp                 |   18 +
 inst/include/xtensor/xtensor.hpp                  |  258 ++++++++++++++++-
 inst/include/xtensor/xtensor_config.hpp           |   20 -
 inst/include/xtensor/xtensor_forward.hpp          |    3 
 inst/include/xtensor/xtensor_simd.hpp             |   59 +++
 inst/include/xtensor/xutils.hpp                   |   24 +
 inst/include/xtensor/xview.hpp                    |   15 
 inst/include/xtl/xcomplex.hpp                     |    2 
 inst/include/xtl/xmasked_value.hpp                |    4 
 inst/include/xtl/xoptional.hpp                    |   18 -
 inst/include/xtl/xtl_config.hpp                   |    2 
 inst/include/xtl/xtype_traits.hpp                 |   58 +++
 src/RcppExports.cpp                               |only
 tools/vendor                                      |    8 
 68 files changed, 1461 insertions(+), 717 deletions(-)

More information about xtensor at CRAN
Permanent link

Package portalr updated to version 0.2.5 with previous version 0.2.2 dated 2019-02-20

Title: Create Useful Summaries of the Portal Data
Description: Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Project. Portal is a long-term (and ongoing) experimental monitoring site in the Chihuahua desert. The raw data files can be found at <https://github.com/weecology/portaldata>.
Author: Glenda M. Yenni [aut, cre] (<https://orcid.org/0000-0001-6969-1848>), Hao Ye [aut] (<https://orcid.org/0000-0002-8630-1458>), Erica M. Christensen [aut] (<https://orcid.org/0000-0002-5635-2502>), Juniper L. Simonis [aut] (<https://orcid.org/0000-0001-9798-0460>), Ellen K. Bledsoe [aut] (<https://orcid.org/0000-0002-3629-7235>), Renata M. Diaz [aut] (<https://orcid.org/0000-0003-0803-4734>), Shawn D. Taylor [aut] (<https://orcid.org/0000-0002-6178-6903>), Ethan P, White [aut] (<https://orcid.org/0000-0001-6728-7745>), S.K. Morgan Ernest [aut] (<https://orcid.org/0000-0002-6026-8530>)
Maintainer: Glenda M. Yenni <glenda@weecology.org>

Diff between portalr versions 0.2.2 dated 2019-02-20 and 0.2.5 dated 2019-06-22

 portalr-0.2.2/portalr/R/data_processing.R                        |only
 portalr-0.2.2/portalr/man/make_timeseries.Rd                     |only
 portalr-0.2.5/portalr/DESCRIPTION                                |   14 
 portalr-0.2.5/portalr/MD5                                        |  106 ++--
 portalr-0.2.5/portalr/NAMESPACE                                  |   10 
 portalr-0.2.5/portalr/R/NDVI.R                                   |   35 -
 portalr-0.2.5/portalr/R/Weather.R                                |   26 
 portalr-0.2.5/portalr/R/download_data.R                          |  126 ++++
 portalr-0.2.5/portalr/R/get_future_moons.R                       |    3 
 portalr-0.2.5/portalr/R/load_data.R                              |   48 +
 portalr-0.2.5/portalr/R/make_monthly_timeseries.R                |    7 
 portalr-0.2.5/portalr/R/portalr-package.R                        |   17 
 portalr-0.2.5/portalr/R/process_data_utils.R                     |only
 portalr-0.2.5/portalr/R/process_plant_data.R                     |only
 portalr-0.2.5/portalr/R/process_rodent_data.R                    |only
 portalr-0.2.5/portalr/R/season_function.R                        |   88 +--
 portalr-0.2.5/portalr/R/summarize_ants.R                         |  204 +++----
 portalr-0.2.5/portalr/R/summarize_individual_rodents.R           |   34 -
 portalr-0.2.5/portalr/R/summarize_plants.R                       |  261 +---------
 portalr-0.2.5/portalr/R/summarize_rodents.R                      |  218 +-------
 portalr-0.2.5/portalr/R/utils-pipe.R                             |only
 portalr-0.2.5/portalr/R/zzz.R                                    |    9 
 portalr-0.2.5/portalr/README.md                                  |   14 
 portalr-0.2.5/portalr/inst/doc/portal_researcher_examples.R      |    6 
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 portalr-0.2.5/portalr/inst/doc/portal_researcher_examples.html   |  119 ++--
 portalr-0.2.5/portalr/inst/doc/rodent-abundance-demo.R           |    6 
 portalr-0.2.5/portalr/inst/doc/rodent-abundance-demo.Rmd         |    6 
 portalr-0.2.5/portalr/inst/doc/rodent-abundance-demo.html        |   52 +
 portalr-0.2.5/portalr/man/add_seasons.Rd                         |   11 
 portalr-0.2.5/portalr/man/bait_presence_absence.Rd               |   10 
 portalr-0.2.5/portalr/man/check_for_newer_data.Rd                |    7 
 portalr-0.2.5/portalr/man/clean_plant_data.Rd                    |    2 
 portalr-0.2.5/portalr/man/clean_rodent_data.Rd                   |   11 
 portalr-0.2.5/portalr/man/colony_presence_absence.Rd             |   17 
 portalr-0.2.5/portalr/man/download_observations.Rd               |    8 
 portalr-0.2.5/portalr/man/find_incomplete_censuses.Rd            |   12 
 portalr-0.2.5/portalr/man/load_datafile.Rd                       |    8 
 portalr-0.2.5/portalr/man/load_rodent_data.Rd                    |   16 
 portalr-0.2.5/portalr/man/ndvi.Rd                                |    9 
 portalr-0.2.5/portalr/man/pipe.Rd                                |only
 portalr-0.2.5/portalr/man/shrub_cover.Rd                         |   14 
 portalr-0.2.5/portalr/man/summarize_individual_rodents.Rd        |   23 
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 portalr-0.2.5/portalr/man/use_default_data_path.Rd               |only
 portalr-0.2.5/portalr/man/weather.Rd                             |    6 
 portalr-0.2.5/portalr/tests/testthat.R                           |    2 
 portalr-0.2.5/portalr/tests/testthat/test-01-data-retrieval.R    |   36 +
 portalr-0.2.5/portalr/tests/testthat/test-02-data-processing.R   |   15 
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Package biscale updated to version 0.1.2 with previous version 0.1.1 dated 2019-05-19

Title: Tools and Palettes for Bivariate Thematic Mapping
Description: Provides a 'ggplot2' centric approach to bivariate mapping. This is a technique that maps two quantities simultaneously rather than the single value that most thematic maps display. The package provides a suite of tools for calculating breaks using multiple different approaches, a selection of palettes appropriate for bivariate mapping and a scale function for 'ggplot2' calls that adds those palettes to maps. A tool for creating bivariate legends is also included.
Author: Christopher Prener [aut, cre] (<https://orcid.org/0000-0002-4310-9888>), Timo Grossenbacher [aut], Angelo Zehr [aut], Joshua Stevens [ctb]
Maintainer: Christopher Prener <chris.prener@slu.edu>

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Fri, 21 Jun 2019

Package rtika updated to version 1.21 with previous version 1.20 dated 2019-02-27

Title: R Interface to 'Apache Tika'
Description: Extract text or metadata from over a thousand file types, using Apache Tika <https://tika.apache.org/>. Get either plain text or structured XHTML content.
Author: Sasha Goodman [aut, cre], The Apache Software Foundation [aut, cph], Julia Silge [rev] (Reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/191), David Gohel [rev] (Reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/191)
Maintainer: Sasha Goodman <goodmansasha@gmail.com>

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Package mlt updated to version 1.0-5 with previous version 1.0-4 dated 2018-12-03

Title: Most Likely Transformations
Description: Likelihood-based estimation of conditional transformation models via the most likely transformation approach described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package ICRanks updated to version 3.1 with previous version 3.0 dated 2019-06-13

Title: Simultaneous Confidence Intervals for Ranks
Description: Algorithms to construct simultaneous confidence intervals for the ranks of means mu_1,...,mu_n based on an independent Gaussian sample using multiple testing techniques.
Author: Diaa Al Mohamad and Erik W. van Zwet and Jelle J. Goeman
Maintainer: Diaa Al Mohamad <diaa.almohamad@gmail.com>

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Package conflicted updated to version 1.0.4 with previous version 1.0.3 dated 2019-05-01

Title: An Alternative Conflict Resolution Strategy
Description: R's default conflict management system gives the most recently loaded package precedence. This can make it hard to detect conflicts, particularly when they arise because a package update creates ambiguity that did not previously exist. 'conflicted' takes a different approach, making every conflict an error and forcing you to choose which function to use.
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

Diff between conflicted versions 1.0.3 dated 2019-05-01 and 1.0.4 dated 2019-06-21

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Package revdbayes updated to version 1.3.4 with previous version 1.3.3 dated 2019-03-08

Title: Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis
Description: Provides functions for the Bayesian analysis of extreme value models. The 'rust' package <https://cran.r-project.org/package=rust> is used to simulate a random sample from the required posterior distribution. The functionality of 'revdbayes' is similar to the 'evdbayes' package <https://cran.r-project.org/package=evdbayes>, which uses Markov Chain Monte Carlo ('MCMC') methods for posterior simulation. Also provided are functions for making inferences about the extremal index, using the K-gaps model of Suveges and Davison (2010) <doi:10.1214/09-AOAS292>. Also provided are d,p,q,r functions for the Generalised Extreme Value ('GEV') and Generalised Pareto ('GP') distributions that deal appropriately with cases where the shape parameter is very close to zero.
Author: Paul J. Northrop [aut, cre, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

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Package phonics updated to version 1.3.2 with previous version 1.3.0 dated 2019-03-01

Title: Phonetic Spelling Algorithms
Description: Provides a collection of phonetic algorithms including Soundex, Metaphone, NYSIIS, Caverphone, and others.
Author: James Howard [aut, cre], Kyle Haynes [ctb], Amanda Hood [ctb], Os Keyes [ctb]
Maintainer: James Howard <jh@jameshoward.us>

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Package cplexAPI updated to version 1.3.6 with previous version 1.3.3 dated 2017-01-31

Title: R Interface to C API of IBM ILOG CPLEX
Description: This is the R Interface to the C API of IBM ILOG CPLEX. It necessarily depends on IBM ILOG CPLEX (>= 12.1).
Author: Mayo Roettger [cre], Gabriel Gelius-Dietrich [aut], C. Jonathan Fritzemeier [ctb]
Maintainer: Mayo Roettger <mayo.roettger@hhu.de>

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Package SuperExactTest updated to version 1.0.7 with previous version 1.0.6 dated 2019-02-26

Title: Exact Test and Visualization of Multi-Set Intersections
Description: Identification of sets of objects with shared features is a common operation in all disciplines. Analysis of intersections among multiple sets is fundamental for in-depth understanding of their complex relationships. This package implements a theoretical framework for efficient computation of statistical distributions of multi-set intersections based upon combinatorial theory, and provides multiple scalable techniques for visualizing the intersection statistics. The statistical algorithm behind this package was published in Wang et al. (2015) <doi:10.1038/srep16923>.
Author: Minghui Wang, Yongzhong Zhao and Bin Zhang
Maintainer: Minghui Wang <minghui.wang@mssm.edu>

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Package alphahull updated to version 2.2 with previous version 2.1 dated 2016-02-15

Title: Generalization of the Convex Hull of a Sample of Points in the Plane
Description: Computation of the alpha-shape and alpha-convex hull of a given sample of points in the plane. The concepts of alpha-shape and alpha-convex hull generalize the definition of the convex hull of a finite set of points. The programming is based on the duality between the Voronoi diagram and Delaunay triangulation. The package also includes a function that returns the Delaunay mesh of a given sample of points and its dual Voronoi diagram in one single object.
Author: Beatriz Pateiro-Lopez [aut, cre], Alberto Rodriguez-Casal, [aut].
Maintainer: Beatriz Pateiro-Lopez <beatriz.pateiro@usc.es>

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Package subgroup.discovery updated to version 0.2.1 with previous version 0.2.0 dated 2017-08-02

Title: Subgroup Discovery and Bump Hunting
Description: Developed to assist in discovering interesting subgroups in high-dimensional data. The PRIM implementation is based on the 1998 paper "Bump hunting in high-dimensional data" by Jerome H. Friedman and Nicholas I. Fisher. <doi:10.1023/A:1008894516817> PRIM involves finding a set of "rules" which combined imply unusually large (or small) values of some other target variable. Specifically one tries to find a set of sub regions in which the target variable is substantially larger than overall mean. The objective of bump hunting in general is to find regions in the input (attribute/feature) space with relatively high (low) values for the target variable. The regions are described by simple rules of the type if: condition-1 and ... and condition-n then: estimated target value. Given the data (or a subset of the data), the goal is to produce a box B within which the target mean is as large as possible. There are many problems where finding such regions is of considerable practical interest. Often these are problems where a decision maker can in a sense choose or select the values of the input variables so as to optimize the value of the target variable. In bump hunting it is customary to follow a so-called covering strategy. This means that the same box construction (rule induction) algorithm is applied sequentially to subsets of the data.
Author: Jurian Baas [aut, cre, cph], Ad Feelders [ctb]
Maintainer: Jurian Baas <j.baas@uu.nl>

Diff between subgroup.discovery versions 0.2.0 dated 2017-08-02 and 0.2.1 dated 2019-06-21

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New package shinyMolBio with initial version 0.1
Package: shinyMolBio
Type: Package
Title: Molecular Biology Visualization Tools for 'Shiny' Apps
Version: 0.1
Date: 2019-06-20
Authors@R: c( person("Konstantin A.", "Blagodatskikh", email = "k.blag@yandex.ru", role = c("cre", "aut")))
Description: Interactive visualization of 'RDML' files via 'shiny' apps. Package provides (1) PCR plate interface with ability to select individual tubes and (2) amplification/melting plots.
License: MIT + file LICENSE
URL: https://github.com/kablag/shinyMolBio
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Imports: dplyr, purrr, checkmate, RDML, shiny, stringr, whisker, plotly, lazyeval, RColorBrewer
Collate: 'global.R' 'pcrPlate-input.R' 'renderCurves.R' 'runExample.R'
Suggests: knitr, chipPCR
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-21 08:24:08 UTC; kablag
Author: Konstantin A. Blagodatskikh [cre, aut]
Maintainer: Konstantin A. Blagodatskikh <k.blag@yandex.ru>
Repository: CRAN
Date/Publication: 2019-06-21 16:20:03 UTC

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Package praznik updated to version 6.0.0 with previous version 5.0.0 dated 2018-05-08

Title: Collection of Information-Based Feature Selection Filters
Description: A collection of feature selection filters performing greedy optimisation of mutual information-based usefulness criteria, inspired by the overview by Brown, Pocock, Zhao and Lujan (2012) <http://www.jmlr.org/papers/v13/brown12a.html>. Implements, among other, minimum redundancy maximal relevancy ('mRMR') method by Peng, Long and Ding (2005) <doi:10.1109/TPAMI.2005.159>; joint mutual information ('JMI') method by Yang and Moody (1999) <http://papers.nips.cc/paper/1779-data-visualization-and-feature-selection-new-algorithms-for-nongaussian-data>; double input symmetrical relevance ('DISR') method by Meyer and Bontempi (2006) <doi:10.1007/11732242_9> as well as joint mutual information maximisation ('JMIM') method by Bennasar, Hicks and Setchi (2015) <doi:10.1016/j.eswa.2015.07.007>.
Author: Miron B. Kursa [aut, cre] (<https://orcid.org/0000-0001-7672-648X>)
Maintainer: Miron B. Kursa <M.Kursa@icm.edu.pl>

Diff between praznik versions 5.0.0 dated 2018-05-08 and 6.0.0 dated 2019-06-21

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Package plm updated to version 2.0-2 with previous version 2.0-1 dated 2019-05-23

Title: Linear Models for Panel Data
Description: A set of estimators and tests for panel data econometrics, as described in Baltagi (2013) Econometric Analysis of Panel Data, ISBN-13:978-1-118-67232-7, Hsiao (2014) Analysis of Panel Data <doi:10.1017/CBO9781139839327> and Croissant and Millo (2018), Panel Data Econometrics with R, ISBN:978-1-118-94918-4.
Author: Yves Croissant [aut, cre], Giovanni Millo [aut], Kevin Tappe [aut], Ott Toomet [ctb], Christian Kleiber [ctb], Achim Zeileis [ctb], Arne Henningsen [ctb], Liviu Andronic [ctb], Nina Schoenfelder [ctb]
Maintainer: Yves Croissant <yves.croissant@univ-reunion.fr>

Diff between plm versions 2.0-1 dated 2019-05-23 and 2.0-2 dated 2019-06-21

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New package ormPlot with initial version 0.3.2
Package: ormPlot
Type: Package
Title: Advanced Plotting of Ordinal Regression Models
Version: 0.3.2
Authors@R: c(person("Richard", "Meitern", , "richard.meitern@ut.ee", c("aut", "cre")))
Maintainer: Richard Meitern <richard.meitern@ut.ee>
Description: An extension to the Regression Modeling Strategies package that facilitates plotting ordinal regression model predictions together with confidence intervals for each dependent variable level. It also adds a functionality to plot the model summary as a modifiable object.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: ggplot2 (>= 3.1.0), rms (>= 5.1.3), gtable (>= 0.3.0), grid (>= 3.5.0)
Suggests: testthat (>= 2.1.0), vdiffr (>= 0.3.0), knitr (>= 1.22), rmarkdown (>= 1.13), pander (>= 0.6.3)
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-21 13:16:22 UTC; rix133
Author: Richard Meitern [aut, cre]
Repository: CRAN
Date/Publication: 2019-06-21 16:30:08 UTC

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Package DDD updated to version 4.1 with previous version 4.0 dated 2019-04-22

Title: Diversity-Dependent Diversification
Description: Implements maximum likelihood and bootstrap methods based on the diversity-dependent birth-death process to test whether speciation or extinction are diversity-dependent, under various models including various types of key innovations. See Etienne et al. 2012, Proc. Roy. Soc. B 279: 1300-1309, <DOI:10.1098/rspb.2011.1439>, Etienne & Haegeman 2012, Am. Nat. 180: E75-E89, <DOI:10.1086/667574> and Etienne et al. 2016. Meth. Ecol. Evol. 7: 1092-1099, <DOI:10.1111/2041-210X.12565>. Also contains functions to simulate the diversity-dependent process.
Author: Rampal S. Etienne & Bart Haegeman
Maintainer: Rampal S. Etienne <r.s.etienne@rug.nl>

Diff between DDD versions 4.0 dated 2019-04-22 and 4.1 dated 2019-06-21

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New package cppRouting with initial version 1.1
Package: cppRouting
Type: Package
Title: Fast Implementation of Dijkstra Algorithm
Version: 1.1
Date: 2019-06-15
Author: Vincent Larmet
Maintainer: Vincent Larmet <larmet.vincent@gmail.com>
Description: Calculation of distances, shortest paths and isochrones on weighted graphs using several variants of Dijkstra algorithm. Proposed algorithms are unidirectional Dijkstra (Dijkstra, E. W. (1959) <doi:10.1007/BF01386390>), bidirectional Dijkstra (Goldberg, Andrew & Fonseca F. Werneck, Renato (2005) <https://pdfs.semanticscholar.org/0761/18dfbe1d5a220f6ac59b4de4ad07b50283ac.pdf>), A* search (P. E. Hart, N. J. Nilsson et B. Raphael (1968) <doi:10.1109/TSSC.1968.300136>), new bidirectional A* (Pijls & Post (2009) <http://repub.eur.nl/pub/16100/ei2009-10.pdf>).
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.1), parallel
LinkingTo: Rcpp
SystemRequirements: GNU make, C++11
RoxygenNote: 6.1.1
URL: https://github.com/vlarmet/cppRouting
Suggests: knitr, rmarkdown, igraph
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-21 13:53:49 UTC; vlarmet
Repository: CRAN
Date/Publication: 2019-06-21 16:30:12 UTC

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Package nlMS updated to version 1.1 with previous version 1.0 dated 2019-06-19

Title: Non-Linear Model Selection
Description: Package to select best model among several linear and nonlinear models. The main function uses the gnls() function from the 'nlme' package to fit the data to nine regression models, named: "linear", "quadratic", "cubic", "logistic", "exponential", "power", "monod", "haldane", "logit".
Author: Carme Font <carme.font.moragon@gmail.com>
Maintainer: Carme Font <carme.font.moragon@gmail.com>

Diff between nlMS versions 1.0 dated 2019-06-19 and 1.1 dated 2019-06-21

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Package mmmgee updated to version 1.20 with previous version 1.13 dated 2018-10-29

Title: Simultaneous Inference for Multiple Linear Contrasts in GEE Models
Description: Provides global hypothesis tests, multiple testing procedures and simultaneous confidence intervals for multiple linear contrasts of regression coefficients in a single generalized estimating equation (GEE) model or across multiple GEE models. GEE models are fit by a modified version of the 'geeM' package.
Author: Robin Ristl [aut, cre], Lee McDaniel [ctb] (Author of 'geeM' package), Nick Henderson [ctb] (Author of 'geeM' package), Melanie Prague [ctb] (Contributor to 'geeM' package)
Maintainer: Robin Ristl <robin.ristl@meduniwien.ac.at>

Diff between mmmgee versions 1.13 dated 2018-10-29 and 1.20 dated 2019-06-21

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Package CARBayes updated to version 5.1.2 with previous version 5.1.1 dated 2018-12-06

Title: Spatial Generalised Linear Mixed Models for Areal Unit Data
Description: Implements a class of univariate and multivariate spatial generalised linear mixed models for areal unit data, with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation. The response variable can be binomial, Gaussian, multinomial, Poisson or zero-inflated Poisson (ZIP), and spatial autocorrelation is modelled by a set of random effects that are assigned a conditional autoregressive (CAR) prior distribution. A number of different models are available for univariate spatial data, including models with no random effects as well as random effects modelled by different types of CAR prior, including the BYM model (Besag et al. (1991) <doi:10.1007/BF00116466>), the Leroux model (Leroux et al. (2000) <doi:10.1007/978-1-4612-1284-3_4>) and the localised model (Lee et al. (2015) <doi:10.1002/env.2348>). Additionally, a multivariate CAR (MCAR) model for multivariate spatial data is available, as is a two-level hierarchical model for modelling data relating to individuals within areas. Full details are given in the vignette accompanying this package. The initial creation of this package was supported by the Economic and Social Research Council (ESRC) grant RES-000-22-4256, and on-going development has been supported by the Engineering and Physical Science Research Council (EPSRC) grant EP/J017442/1, ESRC grant ES/K006460/1, Innovate UK / Natural Environment Research Council (NERC) grant NE/N007352/1 and the TB Alliance.
Author: Duncan Lee
Maintainer: Duncan Lee <Duncan.Lee@glasgow.ac.uk>

Diff between CARBayes versions 5.1.1 dated 2018-12-06 and 5.1.2 dated 2019-06-21

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Package BEDMatrix updated to version 1.6.1 with previous version 1.5.0 dated 2019-04-25

Title: Extract Genotypes from a PLINK .bed File
Description: A matrix-like data structure that allows for efficient, convenient, and scalable subsetting of binary genotype/phenotype files generated by PLINK (<https://www.cog-genomics.org/plink2>), the whole genome association analysis toolset, without loading the entire file into memory.
Author: Alexander Grueneberg [aut, cre], Gustavo de los Campos [ctb]
Maintainer: Alexander Grueneberg <alexander.grueneberg@googlemail.com>

Diff between BEDMatrix versions 1.5.0 dated 2019-04-25 and 1.6.1 dated 2019-06-21

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Package basefun updated to version 1.0-5 with previous version 1.0-4 dated 2019-02-27

Title: Infrastructure for Computing with Basis Functions
Description: Some very simple infrastructure for basis functions.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between basefun versions 1.0-4 dated 2019-02-27 and 1.0-5 dated 2019-06-21

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New package rmdcev with initial version 0.9.0
Package: rmdcev
Type: Package
Title: Multiple Discrete-Continuous Extreme Value (MDCEV) Model
Version: 0.9.0
Authors@R: c( person(given = "Patrick", family = "Lloyd-Smith", role = c("aut", "cre"), email = "patrick.lloydsmith@usask.ca"), person("Trustees of", "Columbia University", role = "cph"))
Maintainer: Patrick Lloyd-Smith <patrick.lloydsmith@usask.ca>
Description: Estimates different multiple discrete-continuous extreme value (MDCEV) demand model specifications with observed and unobserved individual heterogeneity (Bhat (2008) <doi:10.1016/j.trb.2007.06.002>). Fixed parameter, latent class, and random parameter models can be estimated. These models are estimated using maximum likelihood or Bayesian estimation techniques and are implemented in 'Stan', which is a C++ package for performing full Bayesian inference (see Stan Development Team (2018) <http://mc-stan.org>). The 'rmdcev' package also includes functions for demand simulation (Pinjari and Bhat (2011) <https://repositories.lib.utexas.edu/handle/2152/23880>) and welfare simulation (Lloyd-Smith (2018) <doi:10.1016/j.jocm.2017.12.002>).
License: MIT + file LICENSE
Depends: R (>= 3.4.0), Rcpp (>= 0.12.0), methods
Imports: rstan (>= 2.18.2), rstantools (>= 1.5.1), dplyr (>= 0.7.8), tidyselect, parallel, stringr, purrr, tibble, tidyr, rlang, utils, stats, tmvtnorm
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.4.0), rstan (>= 2.18.2), StanHeaders (>= 2.18.0)
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
SystemRequirements: GNU make C++14
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
Packaged: 2019-06-20 23:21:03 UTC; Pat
Author: Patrick Lloyd-Smith [aut, cre], Trustees of Columbia University [cph]
Repository: CRAN
Date/Publication: 2019-06-21 15:00:03 UTC

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New package pesel with initial version 0.7.2
Package: pesel
Type: Package
Title: Automatic Estimation of Number of Principal Components in PCA
Version: 0.7.2
Date: 2019-06-17
Author: Piotr Sobczyk, Julie Josse, Malgorzata Bogdan
Maintainer: Piotr Sobczyk <pj.sobczyk@gmail.com>
Description: Automatic estimation of number of principal components in PCA with PEnalized SEmi-integrated Likelihood (PESEL). See Piotr Sobczyk, Malgorzata Bogdan, Julie Josse 'Bayesian dimensionality reduction with PCA using penalized semi-integrated likelihood' (2017) <doi:10.1080/10618600.2017.1340302>.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/psobczyk/pesel
BugReports: https://github.com/psobczyk/pesel/issues
Depends: R (>= 3.1.3),
Imports: stats, graphics
LazyData: TRUE
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-20 17:44:21 UTC; piotr
Repository: CRAN
Date/Publication: 2019-06-21 14:40:03 UTC

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Package morse updated to version 3.2.4 with previous version 3.2.2 dated 2019-02-21

Title: Modelling Tools for Reproduction and Survival Data in Ecotoxicology
Description: Tools for ecotoxicologists and regulators dedicated to the mathematical and statistical modelling of toxicity test data. They use advanced and innovative methods for a valuable quantitative environmental risk assessment. See also Delignette-Muller et al. (2017) <doi:10.1021/acs.est.6b05326>. and Baudrot et al. (2018) <doi:10.1021/acs.est.7b05464>.
Author: Virgile Baudrot [aut], Sandrine Charles [aut], Marie Laure Delignette-Muller [aut], Wandrille Duchemin [ctb], Benoit Goussen [ctb], Guillaume Kon-Kam-King [ctb], Christelle Lopes [ctb], Philippe Ruiz [aut], Alexander Singer [ctb], Philippe Veber [aut]
Maintainer: Philippe Veber <philippe.veber@univ-lyon1.fr>

Diff between morse versions 3.2.2 dated 2019-02-21 and 3.2.4 dated 2019-06-21

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Package BIGL updated to version 1.4.1 with previous version 1.3.0 dated 2019-02-28

Title: Biochemically Intuitive Generalized Loewe Model
Description: Response surface methods for drug synergy analysis. Available methods include generalized and classical Loewe formulations as well as Highest Single Agent methodology. Response surfaces can be plotted in an interactive 3-D plot and formal statistical tests for presence of synergistic effects are available. Implemented methods and tests are described in the article "BIGL: Biochemically Intuitive Generalized Loewe null model for prediction of the expected combined effect compatible with partial agonism and antagonism" by Koen Van der Borght, Annelies Tourny, Rytis Bagdziunas, Olivier Thas, Maxim Nazarov, Heather Turner, Bie Verbist & Hugo Ceulemans (2017) <doi:10.1038/s41598-017-18068-5>.
Author: Heather Turner, Annelies Tourny, Olivier Thas, Maxim Nazarov, Rytis Bagdziunas
Maintainer: Maxim Nazarov <maxim.nazarov@openanalytics.eu>

Diff between BIGL versions 1.3.0 dated 2019-02-28 and 1.4.1 dated 2019-06-21

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Package TraMineR updated to version 2.0-12 with previous version 2.0-11.1 dated 2019-03-22

Title: Trajectory Miner: a Toolbox for Exploring and Rendering Sequences
Description: Toolbox for the manipulation, description and rendering of sequences, and more generally the mining of sequence data in the field of social sciences. Although the toolbox is primarily intended for analyzing state or event sequences that describe life courses such as family formation histories or professional careers, its features also apply to many other kinds of categorical sequence data. It accepts many different sequence representations as input and provides tools for converting sequences from one format to another. It offers several functions for describing and rendering sequences, for computing distances between sequences with different metrics (among which optimal matching), original dissimilarity-based analysis tools, and simple functions for extracting the most frequent subsequences and identifying the most discriminating ones among them. A user's guide can be found on the TraMineR web page.
Author: Alexis Gabadinho [aut, cph], Matthias Studer [aut, cph] (<https://orcid.org/0000-0002-6269-1412>), Nicolas Müller [aut], Reto Bürgin [aut], Pierre-Alexandre Fonta [aut], Gilbert Ritschard [aut, cre, cph] (<https://orcid.org/0000-0001-7776-0903>)
Maintainer: Gilbert Ritschard <gilbert.ritschard@unige.ch>

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Package MODIStsp updated to version 1.3.9 with previous version 1.3.8 dated 2019-03-08

Title: A Tool for Automating Download and Preprocessing of MODIS Land Products Data
Description: Allows automating the creation of time series of rasters derived from MODIS Satellite Land Products data. It performs several typical preprocessing steps such as download, mosaicking, reprojection and resize of data acquired on a specified time period. All processing parameters can be set using a user-friendly GUI. Users can select which layers of the original MODIS HDF files they want to process, which additional Quality Indicators should be extracted from aggregated MODIS Quality Assurance layers and, in the case of Surface Reflectance products , which Spectral Indexes should be computed from the original reflectance bands. For each output layer, outputs are saved as single-band raster files corresponding to each available acquisition date. Virtual files allowing access to the entire time series as a single file are also created. Command-line execution exploiting a previously saved processing options file is also possible, allowing to automatically update time series related to a MODIS product whenever a new image is available.
Author: Lorenzo Busetto [aut, cre] (<https://orcid.org/0000-0001-9634-6038>), Luigi Ranghetti [aut] (<https://orcid.org/0000-0001-6207-5188>), Leah Wasser [rev] (Leah Wasser reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/184), Jeff Hanson [rev] (Jeff Hanson reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/184)
Maintainer: Lorenzo Busetto <lbusett@gmail.com>

Diff between MODIStsp versions 1.3.8 dated 2019-03-08 and 1.3.9 dated 2019-06-21

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New package usdarnass with initial version 0.1.0
Package: usdarnass
Type: Package
Title: USDA NASS Quick Stats API
Version: 0.1.0
Description: An alternative for downloading various United States Department of Agriculture (USDA) data from <https://quickstats.nass.usda.gov/> through R. You must sign up for an API token from the mentioned website in order for this package to work.
URL: https://github.com/rdinter/usdarnass
BugReports: https://github.com/rdinter/usdarnass/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: httr, jsonlite, methods, utils, readr
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, tidyverse, dplyr, tidyr
VignetteBuilder: knitr
Authors@R: c(person(given = "Robert", family = "Dinterman", role = c("cre", "aut"), email = "robert.dinterman@gmail.com", comment = c(ORCID = "0000-0002-9055-6082")), person(given = "Jonathan", family = "Eyer", role = "aut", email = "jeyer@usc.edu"))
NeedsCompilation: no
Packaged: 2019-06-20 15:22:05 UTC; robert
Author: Robert Dinterman [cre, aut] (<https://orcid.org/0000-0002-9055-6082>), Jonathan Eyer [aut]
Maintainer: Robert Dinterman <robert.dinterman@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-21 08:50:03 UTC

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Package UCSCXenaTools updated to version 1.2.3 with previous version 1.2.2 dated 2019-06-06

Title: Download and Explore Datasets from UCSC Xena Data Hubs
Description: Download and explore datasets from UCSC Xena data hubs, which are a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others. Databases are normalized so they can be combined, linked, filtered, explored and downloaded.
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>), Martin Morgan [aut]
Maintainer: Shixiang Wang <w_shixiang@163.com>

Diff between UCSCXenaTools versions 1.2.2 dated 2019-06-06 and 1.2.3 dated 2019-06-21

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Package RxODE updated to version 0.9.0-8 with previous version 0.9.0-6 dated 2019-05-30

Title: Facilities for Simulating from ODE-Based Models
Description: Facilities for running simulations from ordinary differential equation (ODE) models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The VODE and LSODA are in the public domain. The information is available in the inst/COPYRIGHTS.
Author: Matthew L. Fidler [aut] (<https://orcid.org/0000-0001-8538-6691>), Melissa Hallow [aut], Wenping Wang [aut, cre], Zufar Mulyukov [ctb], Justin Wilkins [ctb] (<https://orcid.org/0000-0002-7099-9396>), Simon Frost [ctb], Heng Li [ctb], Yu Feng [ctb], Alan Hindmarsh [ctb], Linda Petzold [ctb], Ernst Hairer [ctb], Gerhard Wanner [ctb], J Colinge [ctb], Hadley Wickham [ctb], G Grothendieck [ctb], Robert Gentleman [ctb], Ross Ihaka [ctb], R core team [cph], odepack authors [cph]
Maintainer: Wenping Wang <wwang8198@gmail.com>

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Package plotrix updated to version 3.7-6 with previous version 3.7-5 dated 2019-04-07

Title: Various Plotting Functions
Description: Lots of plots, various labeling, axis and color scaling functions.
Author: Jim Lemon, Ben Bolker, Sander Oom, Eduardo Klein, Barry Rowlingson, Hadley Wickham, Anupam Tyagi, Olivier Eterradossi, Gabor Grothendieck, Michael Toews, John Kane, Rolf Turner, Carl Witthoft, Julian Stander, Thomas Petzoldt, Remko Duursma, Elisa Biancotto, Ofir Levy, Christophe Dutang, Peter Solymos, Robby Engelmann, Michael Hecker, Felix Steinbeck, Hans Borchers, Henrik Singmann, Ted Toal, Derek Ogle, Darshan Baral, Ulrike Groemping, Bill Venables
Maintainer: Jim Lemon <drjimlemon@gmail.com>

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Package parSim updated to version 0.1.1 with previous version 0.1 dated 2017-11-10

Title: Parallel Simulation Studies
Description: Perform flexible simulation studies using one or multiple computer cores. The package is set up to be usable on high-performance clusters in addition to being run locally, see examples on <https://github.com/SachaEpskamp/parSim>.
Author: Sacha Epskamp
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

Diff between parSim versions 0.1 dated 2017-11-10 and 0.1.1 dated 2019-06-21

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New package imgw with initial version 0.1.0
Package: imgw
Title: Polish Meteorological and Hydrological Data
Version: 0.1.0
Authors@R: c(person(given = "Bartosz", family = "Czernecki", role = c("aut", "cre"), email = "nwp@amu.edu.pl", comment = c(ORCID = "0000-0001-6496-1386")), person(given = "Arkadiusz", family = "Głogowski", role = "aut"), person(given = "Jakub", family = "Nowosad", role = "aut", email = "nowosad.jakub@gmail.com", comment = c(ORCID = "0000-0002-1057-3721")), person("IMGW-PIB", role = "ctb", comment = "source of the data"))
Description: Download Polish meteorological and hydrological data from the Institute of Meteorology and Water Management - National Research Institute (<https://dane.imgw.pl/>). This package also allows for adding geographical coordinates for each observation.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.1)
Imports: RCurl, XML
Suggests: testthat
URL: https://imgw.ml
BugReports: https://github.com/bczernecki/imgw/issues
NeedsCompilation: no
Packaged: 2019-06-20 09:48:45 UTC; bartosz
Author: Bartosz Czernecki [aut, cre] (<https://orcid.org/0000-0001-6496-1386>), Arkadiusz Głogowski [aut], Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), IMGW-PIB [ctb] (source of the data)
Maintainer: Bartosz Czernecki <nwp@amu.edu.pl>
Repository: CRAN
Date/Publication: 2019-06-21 08:20:14 UTC

More information about imgw at CRAN
Permanent link

Package h2o updated to version 3.24.0.5 with previous version 3.22.1.1 dated 2019-01-10

Title: R Interface for 'H2O'
Description: R interface for 'H2O', the scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models, Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Cox Proportional Hazards, K-Means, PCA, Word2Vec, as well as a fully automatic machine learning algorithm (AutoML).
Author: Erin LeDell [aut, cre], Navdeep Gill [aut], Spencer Aiello [aut], Anqi Fu [aut], Arno Candel [aut], Cliff Click [aut], Tom Kraljevic [aut], Tomas Nykodym [aut], Patrick Aboyoun [aut], Michal Kurka [aut], Michal Malohlava [aut], Ludi Rehak [ctb], Eric Eckstrand [ctb], Brandon Hill [ctb], Sebastian Vidrio [ctb], Surekha Jadhawani [ctb], Amy Wang [ctb], Raymond Peck [ctb], Wendy Wong [ctb], Jan Gorecki [ctb], Matt Dowle [ctb], Yuan Tang [ctb], Lauren DiPerna [ctb], H2O.ai [cph, fnd]
Maintainer: Erin LeDell <erin@h2o.ai>

Diff between h2o versions 3.22.1.1 dated 2019-01-10 and 3.24.0.5 dated 2019-06-21

 h2o-3.22.1.1/h2o/inst/java                                    |only
 h2o-3.24.0.5/h2o/DESCRIPTION                                  |   22 
 h2o-3.24.0.5/h2o/MD5                                          |  371 +++++----
 h2o-3.24.0.5/h2o/NAMESPACE                                    |   13 
 h2o-3.24.0.5/h2o/R/aggregator.R                               |   15 
 h2o-3.24.0.5/h2o/R/automl.R                                   |  180 ++--
 h2o-3.24.0.5/h2o/R/classes.R                                  |   20 
 h2o-3.24.0.5/h2o/R/communication.R                            |   55 +
 h2o-3.24.0.5/h2o/R/connection.R                               |   22 
 h2o-3.24.0.5/h2o/R/coxph.R                                    |   13 
 h2o-3.24.0.5/h2o/R/deeplearning.R                             |   29 
 h2o-3.24.0.5/h2o/R/deepwater.R                                |   25 
 h2o-3.24.0.5/h2o/R/export.R                                   |   18 
 h2o-3.24.0.5/h2o/R/frame.R                                    |  350 +++++----
 h2o-3.24.0.5/h2o/R/gbm.R                                      |   33 
 h2o-3.24.0.5/h2o/R/generic.R                                  |only
 h2o-3.24.0.5/h2o/R/glm.R                                      |   32 
 h2o-3.24.0.5/h2o/R/glrm.R                                     |   26 
 h2o-3.24.0.5/h2o/R/grid.R                                     |    4 
 h2o-3.24.0.5/h2o/R/import.R                                   |   94 ++
 h2o-3.24.0.5/h2o/R/isolationforest.R                          |   11 
 h2o-3.24.0.5/h2o/R/kmeans.R                                   |   22 
 h2o-3.24.0.5/h2o/R/kvstore.R                                  |   32 
 h2o-3.24.0.5/h2o/R/logging.R                                  |   26 
 h2o-3.24.0.5/h2o/R/models.R                                   |  384 ++++++++--
 h2o-3.24.0.5/h2o/R/naivebayes.R                               |   24 
 h2o-3.24.0.5/h2o/R/parse.R                                    |   22 
 h2o-3.24.0.5/h2o/R/pca.R                                      |   22 
 h2o-3.24.0.5/h2o/R/predict.R                                  |    2 
 h2o-3.24.0.5/h2o/R/randomforest.R                             |   31 
 h2o-3.24.0.5/h2o/R/stackedensemble.R                          |   43 -
 h2o-3.24.0.5/h2o/R/svd.R                                      |   22 
 h2o-3.24.0.5/h2o/R/targetencoder.R                            |only
 h2o-3.24.0.5/h2o/R/w2vutils.R                                 |    4 
 h2o-3.24.0.5/h2o/R/word2vec.R                                 |   18 
 h2o-3.24.0.5/h2o/R/xgboost.R                                  |   25 
 h2o-3.24.0.5/h2o/inst/branch.txt                              |    2 
 h2o-3.24.0.5/h2o/inst/buildnum.txt                            |    2 
 h2o-3.24.0.5/h2o/man/H2OClusteringModel-class.Rd              |    4 
 h2o-3.24.0.5/h2o/man/H2OConnection-class.Rd                   |   10 
 h2o-3.24.0.5/h2o/man/H2OConnectionMutableState.Rd             |    2 
 h2o-3.24.0.5/h2o/man/H2OModel-class.Rd                        |    4 
 h2o-3.24.0.5/h2o/man/aaa.Rd                                   |    2 
 h2o-3.24.0.5/h2o/man/apply.Rd                                 |    2 
 h2o-3.24.0.5/h2o/man/as.character.H2OFrame.Rd                 |    2 
 h2o-3.24.0.5/h2o/man/as.data.frame.H2OFrame.Rd                |    2 
 h2o-3.24.0.5/h2o/man/as.factor.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/as.h2o.Rd                                |    4 
 h2o-3.24.0.5/h2o/man/as.matrix.H2OFrame.Rd                    |    2 
 h2o-3.24.0.5/h2o/man/as.numeric.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/as.vector.H2OFrame.Rd                    |    2 
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 h2o-3.24.0.5/h2o/man/dim.H2OFrame.Rd                          |    2 
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 h2o-3.24.0.5/h2o/man/get_seed.H2OModel.Rd                     |only
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 h2o-3.24.0.5/h2o/man/h2o.abs.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.acos.Rd                              |    2 
 h2o-3.24.0.5/h2o/man/h2o.aggregated_frame.Rd                  |    2 
 h2o-3.24.0.5/h2o/man/h2o.aggregator.Rd                        |    2 
 h2o-3.24.0.5/h2o/man/h2o.aic.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.anomaly.Rd                           |    2 
 h2o-3.24.0.5/h2o/man/h2o.anyFactor.Rd                         |    2 
 h2o-3.24.0.5/h2o/man/h2o.auc.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.automl.Rd                            |   50 -
 h2o-3.24.0.5/h2o/man/h2o.cbind.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.clearLog.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.clusterStatus.Rd                     |    2 
 h2o-3.24.0.5/h2o/man/h2o.columns_by_type.Rd                   |    2 
 h2o-3.24.0.5/h2o/man/h2o.confusionMatrix.Rd                   |    2 
 h2o-3.24.0.5/h2o/man/h2o.cor.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.createFrame.Rd                       |    2 
 h2o-3.24.0.5/h2o/man/h2o.cut.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.dct.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.ddply.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.deepfeatures.Rd                      |    2 
 h2o-3.24.0.5/h2o/man/h2o.deeplearning.Rd                      |    7 
 h2o-3.24.0.5/h2o/man/h2o.deepwater.Rd                         |    5 
 h2o-3.24.0.5/h2o/man/h2o.describe.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.distance.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.downloadAllLogs.Rd                   |    2 
 h2o-3.24.0.5/h2o/man/h2o.downloadCSV.Rd                       |    2 
 h2o-3.24.0.5/h2o/man/h2o.download_mojo.Rd                     |    2 
 h2o-3.24.0.5/h2o/man/h2o.download_pojo.Rd                     |    2 
 h2o-3.24.0.5/h2o/man/h2o.entropy.Rd                           |    2 
 h2o-3.24.0.5/h2o/man/h2o.exportFile.Rd                        |    8 
 h2o-3.24.0.5/h2o/man/h2o.fillna.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.gainsLift.Rd                         |    2 
 h2o-3.24.0.5/h2o/man/h2o.gbm.Rd                               |   14 
 h2o-3.24.0.5/h2o/man/h2o.generic.Rd                           |only
 h2o-3.24.0.5/h2o/man/h2o.genericModel.Rd                      |only
 h2o-3.24.0.5/h2o/man/h2o.getAutoML.Rd                         |    4 
 h2o-3.24.0.5/h2o/man/h2o.getGrid.Rd                           |    2 
 h2o-3.24.0.5/h2o/man/h2o.getModel.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.getTimezone.Rd                       |    4 
 h2o-3.24.0.5/h2o/man/h2o.giniCoef.Rd                          |    8 
 h2o-3.24.0.5/h2o/man/h2o.glm.Rd                               |   21 
 h2o-3.24.0.5/h2o/man/h2o.glrm.Rd                              |    2 
 h2o-3.24.0.5/h2o/man/h2o.grep.Rd                              |    2 
 h2o-3.24.0.5/h2o/man/h2o.grid.Rd                              |    2 
 h2o-3.24.0.5/h2o/man/h2o.gsub.Rd                              |    2 
 h2o-3.24.0.5/h2o/man/h2o.head.Rd                              |    2 
 h2o-3.24.0.5/h2o/man/h2o.ifelse.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.importFile.Rd                        |   11 
 h2o-3.24.0.5/h2o/man/h2o.import_hive_table.Rd                 |only
 h2o-3.24.0.5/h2o/man/h2o.import_mojo.Rd                       |only
 h2o-3.24.0.5/h2o/man/h2o.import_sql_select.Rd                 |    9 
 h2o-3.24.0.5/h2o/man/h2o.import_sql_table.Rd                  |    4 
 h2o-3.24.0.5/h2o/man/h2o.impute.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.init.Rd                              |    4 
 h2o-3.24.0.5/h2o/man/h2o.insertMissingValues.Rd               |    2 
 h2o-3.24.0.5/h2o/man/h2o.interaction.Rd                       |    2 
 h2o-3.24.0.5/h2o/man/h2o.kmeans.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.kurtosis.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.levels.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.listTimezones.Rd                     |    4 
 h2o-3.24.0.5/h2o/man/h2o.list_jobs.Rd                         |only
 h2o-3.24.0.5/h2o/man/h2o.loadModel.Rd                         |    5 
 h2o-3.24.0.5/h2o/man/h2o.ls.Rd                                |    2 
 h2o-3.24.0.5/h2o/man/h2o.lstrip.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.mae.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.make_metrics.Rd                      |    2 
 h2o-3.24.0.5/h2o/man/h2o.match.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.mean.Rd                              |    2 
 h2o-3.24.0.5/h2o/man/h2o.mean_per_class_error.Rd              |    2 
 h2o-3.24.0.5/h2o/man/h2o.mean_residual_deviance.Rd            |    2 
 h2o-3.24.0.5/h2o/man/h2o.median.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.merge.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.metric.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.mse.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.nacnt.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.naiveBayes.Rd                        |    2 
 h2o-3.24.0.5/h2o/man/h2o.nchar.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.parseRaw.Rd                          |    5 
 h2o-3.24.0.5/h2o/man/h2o.parseSetup.Rd                        |    5 
 h2o-3.24.0.5/h2o/man/h2o.partialPlot.Rd                       |    2 
 h2o-3.24.0.5/h2o/man/h2o.performance.Rd                       |    2 
 h2o-3.24.0.5/h2o/man/h2o.pr_auc.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.prcomp.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.predict_json.Rd                      |    2 
 h2o-3.24.0.5/h2o/man/h2o.proj_archetypes.Rd                   |    2 
 h2o-3.24.0.5/h2o/man/h2o.quantile.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.r2.Rd                                |    2 
 h2o-3.24.0.5/h2o/man/h2o.randomForest.Rd                      |   11 
 h2o-3.24.0.5/h2o/man/h2o.rbind.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.reconstruct.Rd                       |    2 
 h2o-3.24.0.5/h2o/man/h2o.relevel.Rd                           |    2 
 h2o-3.24.0.5/h2o/man/h2o.removeAll.Rd                         |    9 
 h2o-3.24.0.5/h2o/man/h2o.rmse.Rd                              |    2 
 h2o-3.24.0.5/h2o/man/h2o.rmsle.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.rstrip.Rd                            |    2 
 h2o-3.24.0.5/h2o/man/h2o.runif.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.scale.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.sd.Rd                                |    2 
 h2o-3.24.0.5/h2o/man/h2o.setLevels.Rd                         |    2 
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 h2o-3.24.0.5/h2o/man/h2o.shutdown.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.skewness.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.splitFrame.Rd                        |    2 
 h2o-3.24.0.5/h2o/man/h2o.stackedEnsemble.Rd                   |   26 
 h2o-3.24.0.5/h2o/man/h2o.startLogging.Rd                      |    2 
 h2o-3.24.0.5/h2o/man/h2o.std_coef_plot.Rd                     |    2 
 h2o-3.24.0.5/h2o/man/h2o.stopLogging.Rd                       |    2 
 h2o-3.24.0.5/h2o/man/h2o.stringdist.Rd                        |    2 
 h2o-3.24.0.5/h2o/man/h2o.strsplit.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.sub.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.substring.Rd                         |    2 
 h2o-3.24.0.5/h2o/man/h2o.sum.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.summary.Rd                           |    2 
 h2o-3.24.0.5/h2o/man/h2o.svd.Rd                               |    2 
 h2o-3.24.0.5/h2o/man/h2o.table.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.tabulate.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.target_encode_apply.Rd               |    2 
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 h2o-3.24.0.5/h2o/man/h2o.toFrame.Rd                           |    2 
 h2o-3.24.0.5/h2o/man/h2o.tokenize.Rd                          |    2 
 h2o-3.24.0.5/h2o/man/h2o.tolower.Rd                           |    2 
 h2o-3.24.0.5/h2o/man/h2o.toupper.Rd                           |    2 
 h2o-3.24.0.5/h2o/man/h2o.transform.Rd                         |    2 
 h2o-3.24.0.5/h2o/man/h2o.trim.Rd                              |    2 
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 h2o-3.24.0.5/h2o/man/h2o.which.Rd                             |    2 
 h2o-3.24.0.5/h2o/man/h2o.xgboost.Rd                           |    5 
 h2o-3.24.0.5/h2o/man/plot.H2OModel.Rd                         |    2 
 h2o-3.24.0.5/h2o/man/plot.H2OTabulate.Rd                      |    2 
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 h2o-3.24.0.5/h2o/man/predict_leaf_node_assignment.H2OModel.Rd |    2 
 h2o-3.24.0.5/h2o/man/staged_predict_proba.H2OModel.Rd         |    2 
 h2o-3.24.0.5/h2o/man/zzz.Rd                                   |    6 
 194 files changed, 1485 insertions(+), 1024 deletions(-)

More information about h2o at CRAN
Permanent link

Package airGR updated to version 1.3.2.23 with previous version 1.2.13.16 dated 2019-04-03

Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
Description: Hydrological modelling tools developed at Irstea-Antony (HYCAR Research Unit, France). The package includes several conceptual rainfall-runoff models (GR4H, GR4J, GR5J, GR6J, GR2M, GR1A), a snow accumulation and melt model (CemaNeige) and the associated functions for their calibration and evaluation. Use help(airGR) for package description and references.
Author: Laurent Coron [aut, trl] (<https://orcid.org/0000-0002-1503-6204>), Olivier Delaigue [aut, cre] (<https://orcid.org/0000-0002-7668-8468>), Guillaume Thirel [aut] (<https://orcid.org/0000-0002-1444-1830>), Charles Perrin [aut, ths] (<https://orcid.org/0000-0001-8552-1881>), Claude Michel [aut, ths], Vazken Andréassian [ctb, ths] (<https://orcid.org/0000-0001-7124-9303>), François Bourgin [ctb] (<https://orcid.org/0000-0002-2820-7260>, 'Parameter estimation' vignettes), Pierre Brigode [ctb] (<https://orcid.org/0000-0001-8257-0741>), Nicolas Le Moine [ctb], Thibaut Mathevet [ctb], Safouane Mouelhi [ctb], Ludovic Oudin [ctb] (<https://orcid.org/0000-0002-3712-0933>), Raji Pushpalatha [ctb], Audrey Valéry [ctb]
Maintainer: Olivier Delaigue <airGR@irstea.fr>

Diff between airGR versions 1.2.13.16 dated 2019-04-03 and 1.3.2.23 dated 2019-06-21

 airGR-1.2.13.16/airGR/man/PEdaily_Oudin.Rd                  |only
 airGR-1.2.13.16/airGR/src/frun_CEMANEIGE.f                  |only
 airGR-1.2.13.16/airGR/src/frun_GR1A.f                       |only
 airGR-1.2.13.16/airGR/src/frun_GR2M.f                       |only
 airGR-1.2.13.16/airGR/src/frun_GR4H.f                       |only
 airGR-1.2.13.16/airGR/src/frun_GR4J.f                       |only
 airGR-1.2.13.16/airGR/src/frun_GR5J.f                       |only
 airGR-1.2.13.16/airGR/src/frun_GR6J.f                       |only
 airGR-1.3.2.23/airGR/DESCRIPTION                            |   12 
 airGR-1.3.2.23/airGR/MD5                                    |  157 -
 airGR-1.3.2.23/airGR/NAMESPACE                              |    3 
 airGR-1.3.2.23/airGR/NEWS                                   |   45 
 airGR-1.3.2.23/airGR/R/Calibration.R                        |   50 
 airGR-1.3.2.23/airGR/R/Calibration_Michel.R                 |    6 
 airGR-1.3.2.23/airGR/R/CreateCalibOptions.R                 |  773 ++---
 airGR-1.3.2.23/airGR/R/CreateIniStates.R                    |    4 
 airGR-1.3.2.23/airGR/R/CreateInputsCrit.R                   |   48 
 airGR-1.3.2.23/airGR/R/CreateInputsModel.R                  |  605 ++--
 airGR-1.3.2.23/airGR/R/CreateRunOptions.R                   |   10 
 airGR-1.3.2.23/airGR/R/DataAltiExtrapolation_Valery.R       | 1102 +++----
 airGR-1.3.2.23/airGR/R/ErrorCrit.R                          |   20 
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Package spaMM updated to version 3.0.0 with previous version 2.7.1 dated 2019-04-14

Title: Mixed-Effect Models, Particularly Spatial Models
Description: Inference based on mixed-effect models, including generalized linear mixed models with spatial correlations and models with non-Gaussian random effects (e.g., Beta). Both classical geostatistical models, and Markov random field models on irregular grids, can be fitted. Variation in residual variance (heteroscedasticity) can itself be represented by a generalized linear mixed model. Various approximations of likelihood or restricted likelihood are implemented, in particular h-likelihood (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) and Laplace approximation.
Author: François Rousset [aut, cre, cph] (<https://orcid.org/0000-0003-4670-0371>), Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut] (<https://orcid.org/0000-0003-0637-2959>), GSL authors [ctb] (src/gsl_bessel.*)
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

Diff between spaMM versions 2.7.1 dated 2019-04-14 and 3.0.0 dated 2019-06-21

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New package SDMtune with initial version 0.1.0
Package: SDMtune
Type: Package
Title: Species Distribution Model Selection
Version: 0.1.0
Date: 2019-06-20
Authors@R: c( person("Sergio", "Vignali", email = "sergio.vignali@iee.unibe.ch", role = c("aut", "cre"), comment = c(ORCID = "00000-0002-3390-5442")), person("Arnaud", "Barras", role = "aut", comment = c(ORCID = "0000-0003-0850-6965")), person("Veronika", "Braunisch", role = "aut", comment = c(ORCID = "00000-0001-7035-4662")), person("Conservation Biology - University of Bern", role = "fnd") )
Description: User-friendly framework that enables the training and the evaluation of species distribution models (SDMs). The package implements functions for data driven variable selection and model tuning and includes numerous utilities to display the results. All the functions used to select variables or to tune model hyperparameters have an interactive real-time chart displayed in the 'RStudio' viewer pane during their execution. At the moment only the maximum entropy method is available using the 'Java' implementation, Phillips et al. (2006) <doi:10.1016/j.ecolmodel.2005.03.026>, through the 'dismo' package and the 'R' implementation through the 'maxnet' package, Phillips et al. (2017) <doi:10.1111/ecog.03049>. 'SDMtune' uses its own script to predict maxent models, resulting in much faster predictions for large datasets compared to native predictions from the use of the 'Java' software. This reduces considerably the computation time when tuning the model using the AICc.
License: GPL-3
URL: https://consbiol-unibern.github.io/SDMtune/
BugReports: https://github.com/ConsBiol-unibern/SDMtune/issues
Depends: R (>= 3.2.0)
Imports: cli (>= 1.1.0), crayon (>= 1.3.4), dismo (>= 1.1-4), ggplot2 (>= 3.2.0), htmltools (>= 0.3.6), jsonlite (>= 1.6), kableExtra (>= 1.1.0), maxnet (>= 0.1.2), methods, progress (>= 1.2.2), raster (>= 2.9-5), rasterVis (>= 0.45), Rcpp (>= 1.0.1), reshape2 (>= 1.4.3), rgdal (>= 1.4-4), rJava (>= 0.9-11), rstudioapi (>= 0.10), scales (>= 1.0.0), stringr (>= 1.4.0), whisker (>= 0.3-2)
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
RoxygenNote: 6.1.1
Suggests: covr, knitr (>= 1.23), maps (>= 3.3.0), pkgdown (>= 1.3.0), rmarkdown (>= 1.13), roxygen2 (>= 6.1.1), snow (>= 0.4-3), testthat (>= 2.1.1), zeallot (>= 0.1.0)
VignetteBuilder: knitr
Collate: 'Maxent_class.R' 'Maxnet_class.R' 'RcppExports.R' 'SDMmodel2MaxEnt.R' 'SWD_class.R' 'SDMmodelCV.R' 'SDMmodel_class.R' 'SDMtune.R' 'SDMtune_class.R' 'aicc.R' 'auc.R' 'chart_utils.R' 'condor.R' 'confMatrix.R' 'corVar.R' 'doJk.R' 'getSubsample.R' 'gridSearch.R' 'maxentTh.R' 'maxentVarImp.R' 'mergeSWD.R' 'modelReport.R' 'optimizeModel.R' 'plotCor.R' 'plotJk.R' 'plotPA.R' 'plotPred.R' 'plotROC.R' 'plotResponse.R' 'plotVarImp.R' 'predict_Maxent.R' 'predict_SDMmodel.R' 'prepareSWD.R' 'randomSearch.R' 'reduceVar.R' 'swd2csv.R' 'thinData.R' 'thresholds.R' 'train.R' 'trainMaxent.R' 'trainMaxnet.R' 'trainValTest.R' 'tss.R' 'utils.R' 'varImp.R' 'varSel.R' 'zzz.R'
NeedsCompilation: yes
Packaged: 2019-06-20 07:08:49 UTC; vignali
Author: Sergio Vignali [aut, cre] (<https://orcid.org/00000-0002-3390-5442>), Arnaud Barras [aut] (<https://orcid.org/0000-0003-0850-6965>), Veronika Braunisch [aut] (<https://orcid.org/00000-0001-7035-4662>), Conservation Biology - University of Bern [fnd]
Maintainer: Sergio Vignali <sergio.vignali@iee.unibe.ch>
Repository: CRAN
Date/Publication: 2019-06-21 08:00:20 UTC

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New package psSubpathway with initial version 0.1.0
Package: psSubpathway
Type: Package
Title: Flexible Identification of Phenotype-Specific Subpathways
Version: 0.1.0
Author: Xudong Han, Junwei Han, Qingfei Kong
Maintainer: Junwei Han <hanjunwei1981@163.com>
Description: A network-based systems biology tool for flexible identification of phenotype-specific subpathways in the cancer gene expression data with multiple categories (such as multiple subtype or developmental stages of cancer). Subtype Set Enrichment Analysis (SubSEA) and Dynamic Changed Subpathway Analysis (DCSA) are developed to flexible identify subtype specific and dynamic changed subpathways respectively. The operation modes include extraction of subpathways from biological pathways, inference of subpathway activities in the context of gene expression data, identification of subtype specific subpathways with SubSEA, identification of dynamic changed subpathways associated with the cancer developmental stage with DCSA, and visualization of the activities of resulting subpathways by using box plots and heat maps. Its capabilities render the tool could find the specific abnormal subpathways in the cancer dataset with multi-phenotype samples.
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: GSVA, igraph,mpmi, pheatmap
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-20 00:31:29 UTC; 12859
Repository: CRAN
Date/Publication: 2019-06-21 07:20:04 UTC

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Package lvnet updated to version 0.3.5 with previous version 0.3.4 dated 2018-11-18

Title: Latent Variable Network Modeling
Description: Estimate, fit and compare Structural Equation Models (SEM) and network models (Gaussian Graphical Models; GGM) using OpenMx. Allows for two possible generalizations to include GGMs in SEM: GGMs can be used between latent variables (latent network modeling; LNM) or between residuals (residual network modeling; RNM). For details, see Epskamp, Rhemtulla and Borsboom (2017) <doi:10.1007/s11336-017-9557-x>.
Author: Sacha Epskamp
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package log4r updated to version 0.3.0 with previous version 0.2 dated 2014-09-29

Title: A Simple Logging System for R, Based on 'log4j'
Description: The log4r package is meant to provide a fast, lightweight, object-oriented approach to logging in R based on the widely-emulated 'log4j' system and etymology.
Author: John Myles White [aut, cph], Kenton White [ctb], Kirill Müller [ctb], Aaron Jacobs [aut, cre]
Maintainer: Aaron Jacobs <atheriel@gmail.com>

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New package frostr with initial version 0.1.0
Package: frostr
Type: Package
Title: R Client to MET Norway's 'Frost' API
Version: 0.1.0
Authors@R: person("Iman", "Ghayoornia", email = "ghayoornia.iman@gmail.com", role = c("aut", "cre"))
Description: An unofficial R client to MET Norway's 'Frost' API <https://frost.met.no/index2.html> to retrieve data as data frames. The 'Frost' API, and the underlying data, is made available by the Norwegian Meteorological Institute (MET Norway). The data and products are distributed under the Norwegian License for Open Data 2.0 (NLOD) <https://data.norge.no/nlod/en/2.0> and Creative Commons 4.0 <https://creativecommons.org/licenses/by/4.0/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: httr, jsonlite, tibble, tidyr
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-06-19 22:45:25 UTC; ImanGhayoornia
Author: Iman Ghayoornia [aut, cre]
Maintainer: Iman Ghayoornia <ghayoornia.iman@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-21 07:10:03 UTC

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Package did updated to version 1.2.2 with previous version 1.2.1 dated 2019-06-14

Title: Treatment Effects with Multiple Periods and Groups
Description: The standard Difference-in-Differences (DID) setup involves two periods and two groups -- a treated group and untreated group. Many applications of DID methods involve more than two periods and have individuals that are treated at different points in time. This package contains tools for computing average treatment effect parameters in Difference in Differences models with more than two periods and with variation in treatment timing using the methods developed in Callaway and Sant'Anna (2018) <https://ssrn.com/abstract=3148250>. The main parameters are group-time average treatment effects which are the average treatment effect for a particular group at a a particular time. These can be aggregated into a fewer number of treatment effect parameters, and the package deals with the cases where there is selective treatment timing, dynamic treatment effects, calendar time effects, or combinations of these. There are also functions for testing the Difference in Differences assumption, and plotting group-time average treatment effects.
Author: Brantly Callaway [aut, cre], Pedro H.C. Sant'Anna [aut]
Maintainer: Brantly Callaway <brantly.callaway@temple.edu>

Diff between did versions 1.2.1 dated 2019-06-14 and 1.2.2 dated 2019-06-21

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Package antitrust updated to version 0.99.11 with previous version 0.99.10 dated 2018-06-10

Title: Tools for Antitrust Practitioners
Description: A collection of tools for antitrust practitioners, including the ability to calibrate different consumer demand systems and simulate the effects of mergers under different competitive regimes.
Author: Charles Taragin and Michael Sandfort
Maintainer: Charles Taragin <ctaragin@ftc.gov>

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Package mefa4 updated to version 0.3-6 with previous version 0.3-5 dated 2018-03-25

Title: Multivariate Data Handling with S4 Classes and Sparse Matrices
Description: An S4 update of the 'mefa' package using sparse matrices for enhanced efficiency. Sparse array-like objects are supported via lists of sparse matrices.
Author: Peter Solymos
Maintainer: Peter Solymos <solymos@ualberta.ca>

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Thu, 20 Jun 2019

Package optionstrat updated to version 1.3.0 with previous version 1.2.0 dated 2019-05-07

Title: Utilizes the Black-Scholes Option Pricing Model to Perform Strategic Option Analysis and Plot Option Strategies
Description: Utilizes the Black-Scholes-Merton option pricing model to calculate key option analytics and graphical analysis of various option strategies. Provides functions to calculate the option premium and option greeks of European-style options.
Author: John T. Buynak [aut, cre]
Maintainer: John T. Buynak <jbuynak94@gmail.com>

Diff between optionstrat versions 1.2.0 dated 2019-05-07 and 1.3.0 dated 2019-06-20

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Package autoimage updated to version 2.0.1 with previous version 2.0 dated 2017-10-24

Title: Multiple Heat Maps for Projected Coordinates
Description: Functions for displaying multiple images with a color scale, i.e., heat maps, possibly with projected coordinates. The package relies on the base graphics system, so graphics are rendered rapidly.
Author: Joshua French
Maintainer: Joshua French <joshua.french@ucdenver.edu>

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Package gemlog updated to version 0.36 with previous version 0.30 dated 2018-07-12

Title: File Conversion for 'Gem Infrasound Logger'
Description: Reads data files from the 'Gem infrasound logger' for analysis and converts to segy format (which is convenient for reading with traditional seismic analysis software). The Gem infrasound logger is a low-cost, lightweight, low-power instrument for recording infrasound in field campaigns; email the maintainer for more information.
Author: Jake Anderson
Maintainer: Jake Anderson <ajakef@gmail.com>

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Package echo.find updated to version 3.0 with previous version 2.0 dated 2018-12-05

Title: Finding Rhythms Using Extended Circadian Harmonic Oscillators (ECHO)
Description: Provides a function (echo_find()) designed to find rhythms from data using extended harmonic oscillators. For more information, see H. De los Santos et al. (2017) <doi:10.1145/3107411.3107420> .
Author: Hannah De los Santos [aut, cre], Emily Collins [aut], Kristin Bennett [aut], Jennifer Hurley [aut]
Maintainer: Hannah De los Santos <delosh@rpi.edu>

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Package rscala updated to version 3.2.13 with previous version 3.2.11 dated 2019-06-08

Title: Bridge Between 'R' and 'Scala' with Callbacks
Description: 'Scala' <http://www.scala-lang.org/> is embedded in 'R' and callbacks from 'Scala' to 'R' are available. Support is provided to write 'R' packages that access 'Scala'. After installation, please run 'rscala::scalaConfig()'.
Author: David B. Dahl [aut, cre]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

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Package mlVAR updated to version 0.4.3 with previous version 0.4.2 dated 2019-01-24

Title: Multi-Level Vector Autoregression
Description: Estimates the multi-level vector autoregression model on time-series data. Three network structures are obtained: temporal networks, contemporaneous networks and between-subjects networks.
Author: Sacha Epskamp, Marie K. Deserno and Laura F. Bringmann
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package skimr updated to version 1.0.7 with previous version 1.0.6 dated 2019-05-27

Title: Compact and Flexible Summaries of Data
Description: A simple to use summary function that can be used with pipes and displays nicely in the console. The default summary statistics may be modified by the user as can the default formatting. Support for data frames and vectors is included, and users can implement their own skim methods for specific object types as described in a vignette. Default summaries include support for inline spark graphs. Instructions for managing these on specific operating systems are given in the "Using skimr" vignette and the README.
Author: Elin Waring [cre], Michael Quinn [aut], Amelia McNamara [aut], Eduardo Arino de la Rubia [aut], Hao Zhu [aut], Julia Lowndes [ctb], Shannon Ellis [aut], Hope McLeod [ctb], Hadley Wickham [ctb], Kirill Müller [ctb], RStudio, Inc. [cph] (Spark functions), Connor Kirkpatrick [ctb], Scott Brenstuhl [ctb], Patrick Schratz [ctb], lbusett [ctb], Mikko Korpela [ctb], Jennifer Thompson [ctb], Harris McGehee [ctb], Patrick Kennedy [ctb], Daniel Possenriede [ctb], Lionel Henry [ctb]
Maintainer: Elin Waring <elin.waring@gmail.com>

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Package rstatix updated to version 0.1.1 with previous version 0.1.0 dated 2019-05-27

Title: Pipe-Friendly Framework for Basic Statistical Tests
Description: Provides a simple and intuitive pipe-friendly framework, coherent with the 'tidyverse' design philosophy, for performing basic statistical tests, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses. The output of each test is automatically transformed into a tidy data frame to facilitate visualization. Additional functions are available for reshaping, reordering, manipulating and visualizing correlation matrix. Functions are also included to facilitate the analysis of factorial experiments, including purely 'within-Ss' designs (repeated measures), purely 'between-Ss' designs, and mixed 'within-and-between-Ss' designs. It's also possible to compute several effect size metrics, including "eta squared" for ANOVA, "Cohen's d" for t-test and "Cramer's V" for the association between categorical variables. The package contains helper functions for identifying univariate and multivariate outliers, assessing normality and homogeneity of variances.
Author: Alboukadel Kassambara [aut, cre]
Maintainer: Alboukadel Kassambara <alboukadel.kassambara@gmail.com>

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Package owdbr updated to version 1.0.1.0 with previous version 1.0.0.35 dated 2019-05-13

Title: Open Welfare Data Brazil
Description: Tools for collecting municipal-level data <http://www.transparencia.gov.br/swagger-ui.html> from several Brazilian governmental social programs.
Author: Joao Pedro Oliveira dos Santos [aut, cre] (<https://orcid.org/0000-0003-1752-265X>)
Maintainer: Joao Pedro Oliveira dos Santos <joaopsantos@pm.me>

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Package CausalKinetiX updated to version 0.2.1 with previous version 0.2 dated 2019-06-10

Title: Learning Stable Structures in Kinetic Systems
Description: Implementation of 'CausalKinetiX', a framework for learning stable structures in kinetic systems. Apart from the main functions CausalKinetiX() and CausalKinetiX.modelranking() it includes functions to generate data from three simulations models, which can be used to benchmark structure learning methods for linear ordinary differential equation models. A detailed description of the underlying methods as well as details on the examples are given in Pfister, Bauer and Peters (2018) <arXiv:1810.11776>.
Author: Niklas Pfister [aut, cre], Stefan Bauer [aut], Jonas Peters [aut]
Maintainer: Niklas Pfister <niklas.pfister@stat.math.ethz.ch>

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Package sequoia updated to version 1.3.3 with previous version 1.3.1 dated 2019-06-14

Title: Pedigree Inference from SNPs
Description: Fast multi-generational pedigree inference from incomplete data on hundreds of SNPs, including parentage assignment and sibship clustering. See Huisman (2017) (DOI:10.1111/1755-0998.12665, citation('sequoia')) for more information.
Author: Jisca Huisman [aut, cre]
Maintainer: Jisca Huisman <jisca.huisman@gmail.com>

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Package poolfstat updated to version 1.1.0 with previous version 1.0.0 dated 2018-09-14

Title: Computing F-Statistics from Pool-Seq Data
Description: Functions for the computation of F-statistics from Pool-Seq data in population genomics studies. The package also includes several utilities to manipulate Pool-Seq data stored in standard format ('vcf' or 'rsync' files generated by the the 'PoPoolation' software) and perform conversion to alternative format (as used in the 'BayPass' and 'SelEstim' software).
Author: Mathieu Gautier, Valentin Hivert and Renaud Vitalis
Maintainer: Mathieu Gautier <mathieu.gautier@inra.fr>

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Package eoffice updated to version 0.1.7 with previous version 0.1.6 dated 2019-06-02

Title: Export or Graph and Tables to 'Microsoft' Office and Import Figures and Tables
Description: Provides wrap functions to export and import graphics and data frames in R to 'microsoft' office. And This package also provide write out figures with lots of different formats. Since people may work on the platform without GUI support, the package also provide function to easily write out figures to lots of different type of formats. Now this package provide function to extract colors from all types of figures and pdf files.
Author: Kai Guo
Maintainer: Kai Guo <guokai8@gmail.com>

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Package ellipsis updated to version 0.2.0 with previous version 0.1.0 dated 2019-02-19

Title: Tools for Working with ...
Description: The ellipsis is a powerful tool for extending functions. Unfortunately this power comes at a cost: misspelled arguments will be silently ignored. The ellipsis package provides a collection of functions to catch problems and alert the user.
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package DynNom updated to version 5.0.1 with previous version 5.0 dated 2019-06-19

Title: Visualising Statistical Models using Dynamic Nomograms
Description: Demonstrate the results of a statistical model object as a dynamic nomogram in an RStudio panel or web browser. The package provides two generics functions: DynNom, which display statistical model objects as a dynamic nomogram; DNbuilder, which builds required scripts to publish a dynamic nomogram on a web server such as the <https://www.shinyapps.io/>. Current version of 'DynNom' supports stats::lm, stats::glm, survival::coxph, rms::ols, rms::Glm, rms::lrm, rms::cph, mgcv::gam and gam::gam model objects.
Author: Amirhossein Jalali, Davood Roshan, Alberto Alvarez-Iglesias, John Newell
Maintainer: Amirhossein Jalali <amir.jalali@ucd.ie>

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Package ace2fastq updated to version 0.6.0 with previous version 0.5.1 dated 2019-06-04

Title: ACE File to FASTQ Converter
Description: The ACE file format is used in genomics to store contigs from sequencing machines. This tools converts it into FASTQ format. Both formats contain the sequence characters and their corresponding quality information. Unlike the FASTQ file, the ace file stores the quality values numerically. The conversion algorithm uses the standard Sanger formula. The package facilitates insertion into pipelines, and content inspection.
Author: Reinhard Simon [aut, cre] (<https://orcid.org/0000-0002-4608-9077>)
Maintainer: Reinhard Simon <rsimon64@gmail.com>

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Package PReMiuM updated to version 3.2.2 with previous version 3.2.1 dated 2018-09-26

Title: Dirichlet Process Bayesian Clustering, Profile Regression
Description: Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership. The package allows Bernoulli, Binomial, Poisson, Normal, survival and categorical response, as well as Normal and discrete covariates. It also allows for fixed effects in the response model, where a spatial CAR (conditional autoregressive) term can be also included. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection. The main reference for the package is Liverani, Hastie, Azizi, Papathomas and Richardson (2015) <doi:10.18637/jss.v064.i07>.
Author: David I. Hastie, Silvia Liverani <liveranis@gmail.com> and Sylvia Richardson with contributions from Aurore J. Lavigne, Lucy Leigh, Lamiae Azizi, Xi Liu, Ruizhu Huang, Austin Gratton, Wei Jing
Maintainer: Silvia Liverani <liveranis@gmail.com>

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Package interflex updated to version 1.0.8 with previous version 1.0.4 dated 2018-04-20

Title: Multiplicative Interaction Models Diagnostics and Visualization
Description: Performs diagnostic tests of multiplicative interaction models and plots non-linear marginal effects of a treatment on an outcome across different values of a moderator.
Author: Jens Hainmueller, Jonathan Mummolo and Yiqing Xu
Maintainer: Yiqing Xu <yiqingxu@stanford.edu>

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Package bayestestR updated to version 0.2.2 with previous version 0.2.0 dated 2019-05-29

Title: Understand and Describe Bayesian Models and Posterior Distributions
Description: Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors).
Author: Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Michael D. Wilson [aut] (<https://orcid.org/0000-0003-4143-7308>)
Maintainer: Dominique Makowski <dom.makowski@gmail.com>

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Package ARPobservation updated to version 1.2.0 with previous version 1.1 dated 2015-02-11

Title: Tools for Simulating Direct Behavioral Observation Recording Procedures Based on Alternating Renewal Processes
Description: Tools for simulating data generated by direct observation recording. Behavior streams are simulated based on an alternating renewal process, given specified distributions of event durations and interim times. Different procedures for recording data can then be applied to the simulated behavior streams. Functions are provided for the following recording methods: continuous duration recording, event counting, momentary time sampling, partial interval recording, whole interval recording, and augmented interval recording.
Author: James E. Pustejovsky, with contributions from Daniel M. Swan
Maintainer: James E. Pustejovsky <jepusto@gmail.com>

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Permanent link

Package variables updated to version 1.0-2 with previous version 1.0-1 dated 2018-09-17

Title: Variable Descriptions
Description: Abstract descriptions of (yet) unobserved variables.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between variables versions 1.0-1 dated 2018-09-17 and 1.0-2 dated 2019-06-20

 DESCRIPTION   |    9 +++++----
 MD5           |    6 +++---
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 inst/NEWS.Rd  |    7 +++++++
 4 files changed, 23 insertions(+), 7 deletions(-)

More information about variables at CRAN
Permanent link

Package distreg.vis updated to version 1.5.0 with previous version 1.1.0 dated 2019-02-21

Title: Framework for the Visualization of Distributional Regression Models
Description: Functions for visualizing distributional regression models fitted using the 'gamlss' or 'bamlss' R package. The core of the package consists of a 'shiny' application, where the model results can be interactively explored and visualized.
Author: Stanislaus Stadlmann [cre, aut] (<https://orcid.org/0000-0001-6542-6342>)
Maintainer: Stanislaus Stadlmann <stadlmann@uni-goettingen.de>

Diff between distreg.vis versions 1.1.0 dated 2019-02-21 and 1.5.0 dated 2019-06-20

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More information about distreg.vis at CRAN
Permanent link

New package TSE with initial version 0.1.0
Package: TSE
Type: Package
Title: Total Survey Error
Version: 0.1.0
Authors@R: c(person("Joshua", "Miller", role = c("aut", "cre"), email = "joshlmiller@msn.com"))
Maintainer: Joshua Miller <joshlmiller@msn.com>
Description: Calculates total survey error (TSE) for one or more surveys, using common scale-dependent and/or scale-independent metrics. On TSE, see: Weisberg, Herbert (2005, ISBN:0-226-89128-3); Biemer, Paul (2010) <doi:10.1093/poq/nfq058>.
Note: Package TSE works directly from the data set – no hand calculations required. Just upload a properly structured data set (see TESTNUMB and its documentation), properly input column names (see examples in the functions documentation), and run your functions.
Imports: stats
Depends: R (>= 3.5)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2019-06-19 12:21:48 UTC; JOSHUA
Author: Joshua Miller [aut, cre]
Repository: CRAN
Date/Publication: 2019-06-20 09:10:03 UTC

More information about TSE at CRAN
Permanent link

Package sirt updated to version 3.5-53 with previous version 3.4-64 dated 2019-05-03

Title: Supplementary Item Response Theory Models
Description: Supplementary functions for item response models aiming to complement existing R packages. The functionality includes among others multidimensional compensatory and noncompensatory IRT models (Reckase, 2009, <doi:10.1007/978-0-387-89976-3>), MCMC for hierarchical IRT models and testlet models (Fox, 2010, <doi:10.1007/978-1-4419-0742-4>), NOHARM (McDonald, 1982, <doi:10.1177/014662168200600402>), Rasch copula model (Braeken, 2011, <doi:10.1007/s11336-010-9190-4>; Schroeders, Robitzsch & Schipolowski, 2014, <doi:10.1111/jedm.12054>), faceted and hierarchical rater models (DeCarlo, Kim & Johnson, 2011, <doi:10.1111/j.1745-3984.2011.00143.x>), ordinal IRT model (ISOP; Scheiblechner, 1995, <doi:10.1007/BF02301417>), DETECT statistic (Stout, Habing, Douglas & Kim, 1996, <doi:10.1177/014662169602000403>), local structural equation modeling (LSEM; Hildebrandt, Luedtke, Robitzsch, Sommer & Wilhelm, 2016, <doi:10.1080/00273171.2016.1142856>).
Author: Alexander Robitzsch [aut,cre] (<https://orcid.org/0000-0002-8226-3132>)
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

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More information about sirt at CRAN
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Package esquisse updated to version 0.2.0 with previous version 0.1.7 dated 2018-11-14

Title: Explore and Visualize Your Data Interactively
Description: A 'shiny' gadget to create 'ggplot2' charts interactively with drag-and-drop to map your variables. You can quickly visualize your data accordingly to their type, export to 'PNG' or 'PowerPoint', and retrieve the code to reproduce the chart.
Author: Fanny Meyer [aut], Victor Perrier [aut, cre], Ian Carroll [ctb] (Facets support)
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>

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Wed, 19 Jun 2019

Package taxotools updated to version 0.0.30 with previous version 0.0.29 dated 2019-05-13

Title: Tools to Handle Taxonomic Lists
Description: Some tools to work with taxonomic name lists.
Author: Vijay Barve [aut, cre] (<https://orcid.org/0000-0002-4852-2567>)
Maintainer: Vijay Barve <vijay.barve@gmail.com>

Diff between taxotools versions 0.0.29 dated 2019-05-13 and 0.0.30 dated 2019-06-19

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More information about taxotools at CRAN
Permanent link

New package SemNetDictionaries with initial version 0.1.2
Package: SemNetDictionaries
Title: Dictionaries for the 'SemNetCleaner' Package
Version: 0.1.2
Date: 2019-06-19
Author: Alexander P. Christensen
Maintainer: Alexander P. Christensen <alexpaulchristensen@gmail.com>
Description: Implements dictionaries that can be used in the 'SemNetCleaner' package. Also includes several functions aimed at facilitating the text cleaning analysis in the 'SemNetCleaner' package. This package is designed to integrate and update word lists and dictionaries based on each user's individual needs by allowing users to store and save their own dictionaries. Dictionaries can be added to the 'SemNetDictionaries' package by submitting user-defined dictionaries to <https://github.com/AlexChristensen/SemNetDictionaries>.
Depends: R (>= 3.5.0)
License: GPL (>= 3.0)
URL: https://github.com/AlexChristensen/SemNetDictionaries
BugReports: https://github.com/AlexChristensen/SemNetDictionaries/issues
NeedsCompilation: no
Encoding: UTF-8
LazyData: true
Imports: tcltk
RoxygenNote: 6.1.1
Packaged: 2019-06-19 17:24:31 UTC; APCHRIST
Repository: CRAN
Date/Publication: 2019-06-19 22:15:19 UTC

More information about SemNetDictionaries at CRAN
Permanent link

New package lobstr with initial version 1.1.0
Package: lobstr
Title: Visualize R Data Structures with Trees
Version: 1.1.0
Authors@R: c( person("Hadley", "Wickham", , "hadley@rstudio.com", role = c("aut", "cre")), person("RStudio", role = "cph") )
Description: A set of tools for inspecting and understanding R data structures inspired by str(). Includes ast() for visualizing abstract syntax trees, ref() for showing shared references, cst() for showing call stack trees, and obj_size() for computing object sizes.
License: GPL-3
URL: https://github.com/r-lib/lobstr
BugReports: https://github.com/r-lib/lobstr/issues
Depends: R (>= 3.2)
Imports: crayon, Rcpp, rlang (>= 0.3.0)
Suggests: covr, pillar, pkgdown, testthat
LinkingTo: Rcpp
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-06-19 20:40:32 UTC; hadley
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>
Repository: CRAN
Date/Publication: 2019-06-19 22:00:23 UTC

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Package fgeo updated to version 1.1.4 with previous version 1.1.3 dated 2019-05-24

Title: Analyze Forest Diversity and Dynamics
Description: To help you access, transform, analyze, and visualize ForestGEO data, we developed a collection of R packages (<https://forestgeo.github.io/fgeo/>). This package, in particular, helps you to install and load the entire package-collection with a single R command, and provides convenient ways to find relevant documentation. Most commonly, you should not worry about the individual packages that make up the package-collection as you can access all features via this package. To learn more about ForestGEO visit <http://www.forestgeo.si.edu/>.
Author: Mauro Lepore [aut, ctr, cre] (<https://orcid.org/0000-0002-1986-7988>), Gabriel Arellano [aut, rev], Richard Condit [aut], Stuart Davies [aut, rev], Matteo Detto [aut], Erika Gonzalez-Akre [aut, rev] (<https://orcid.org/0000-0001-8305-6672>), Pamela Hall [aut], Kyle Harms [aut], Valentine Herrmann [aut, rev] (<https://orcid.org/0000-0002-4519-481X>), Aaron Hogan [rev] (<https://orcid.org/0000-0001-9806-3074>), Bier Kraichak [rev], David Kenfack [aut, rev], Lauren Krizel [rev], Suzanne Lao [aut, rev], Sean McMahon [aut, rev], Haley Overstreet [rev], Sabrina Russo [aut, rev], Cara Scalpone [rev] (<https://orcid.org/0000-0001-8448-2147>), Kristina Anderson-Teixeira [aut, rev], Graham Zemunik [aut, rev], Daniel Zuleta [aut, rev], CTFS-ForestGEO [cph, fnd]
Maintainer: Mauro Lepore <maurolepore@gmail.com>

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Package DynNom updated to version 5.0 with previous version 4.1.1 dated 2017-04-19

Title: Visualising Statistical Models using Dynamic Nomograms
Description: Demonstrate the results of a statistical model object as a dynamic nomogram in an RStudio panel or web browser. The package provides two generics functions: DynNom, which display statistical model objects as a dynamic nomogram; DNbuilder, which builds required scripts to publish a dynamic nomogram on a web server such as the <https://www.shinyapps.io/>. Current version of 'DynNom' supports stats::lm, stats::glm, survival::coxph, rms::ols, rms::Glm, rms::lrm, rms::cph, mgcv::gam and gam::gam model objects.
Author: Amirhossein Jalali, Davood Roshan, Alberto Alvarez-Iglesias, John Newell
Maintainer: Amirhossein Jalali <amir.jalali@ucd.ie>

Diff between DynNom versions 4.1.1 dated 2017-04-19 and 5.0 dated 2019-06-19

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Package civis updated to version 2.0.0 with previous version 1.6.1 dated 2019-02-12

Title: R Client for the 'Civis data science API'
Description: A convenient interface for making requests directly to the 'Civis data science API' <https://www.civisanalytics.com/platform/>.
Author: Patrick Miller [cre, aut], Keith Ingersoll [aut], Bill Lattner [ctb], Anh Le [ctb], Michelangelo D'Agostino [ctb], Sam Weiss [ctb], Stephen Hoover [ctb], Danning Chen [ctb], Elizabeth Sander [ctb], Madison Hobbs [ctb], Anna Bladey [ctb]
Maintainer: Patrick Miller <pmiller@civisanalytics.com>

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 civis-2.0.0/civis/man/await.Rd                                                 |    7 
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 civis-2.0.0/civis/man/civis_ml_gradient_boosting_classifier.Rd                 |    2 
 civis-2.0.0/civis/man/civis_ml_random_forest_classifier.Rd                     |    2 
 civis-2.0.0/civis/man/civis_ml_sparse_logistic.Rd                              |    2 
 civis-2.0.0/civis/man/civis_script.Rd                                          |only
 civis-2.0.0/civis/man/clusters_get_kubernetes.Rd                               |    1 
 civis-2.0.0/civis/man/clusters_get_kubernetes_partitions.Rd                    |    7 
 civis-2.0.0/civis/man/clusters_list_kubernetes.Rd                              |    1 
 civis-2.0.0/civis/man/clusters_list_kubernetes_deployment_stats.Rd             |only
 civis-2.0.0/civis/man/clusters_list_kubernetes_deployments.Rd                  |only
 civis-2.0.0/civis/man/clusters_list_kubernetes_partitions.Rd                   |    7 
 civis-2.0.0/civis/man/clusters_patch_kubernetes_partitions.Rd                  |    9 
 civis-2.0.0/civis/man/clusters_post_kubernetes_partitions.Rd                   |    9 
 civis-2.0.0/civis/man/credentials_delete_shares_groups.Rd                      |    4 
 civis-2.0.0/civis/man/credentials_delete_shares_users.Rd                       |    4 
 civis-2.0.0/civis/man/credentials_list.Rd                                      |    6 
 civis-2.0.0/civis/man/credentials_list_shares.Rd                               |    2 
 civis-2.0.0/civis/man/credentials_post_authenticate.Rd                         |    2 
 civis-2.0.0/civis/man/credentials_put_shares_groups.Rd                         |    6 
 civis-2.0.0/civis/man/credentials_put_shares_users.Rd                          |    6 
 civis-2.0.0/civis/man/databases_get.Rd                                         |only
 civis-2.0.0/civis/man/databases_list.Rd                                        |    1 
 civis-2.0.0/civis/man/databases_post_schemas_scan.Rd                           |only
 civis-2.0.0/civis/man/download_civis.Rd                                        |    2 
 civis-2.0.0/civis/man/enhancements_delete_cass_ncoa_projects.Rd                |    4 
 civis-2.0.0/civis/man/enhancements_delete_cass_ncoa_shares_groups.Rd           |    4 
 civis-2.0.0/civis/man/enhancements_delete_cass_ncoa_shares_users.Rd            |    4 
 civis-2.0.0/civis/man/enhancements_delete_geocode_projects.Rd                  |only
 civis-2.0.0/civis/man/enhancements_delete_geocode_runs.Rd                      |only
 civis-2.0.0/civis/man/enhancements_delete_geocode_shares_groups.Rd             |only
 civis-2.0.0/civis/man/enhancements_delete_geocode_shares_users.Rd              |only
 civis-2.0.0/civis/man/enhancements_get_cass_ncoa.Rd                            |    2 
 civis-2.0.0/civis/man/enhancements_get_civis_data_match.Rd                     |    6 
 civis-2.0.0/civis/man/enhancements_get_data_unification.Rd                     |    9 
 civis-2.0.0/civis/man/enhancements_get_geocode.Rd                              |only
 civis-2.0.0/civis/man/enhancements_get_geocode_runs.Rd                         |only
 civis-2.0.0/civis/man/enhancements_get_table_deduplication.Rd                  |    4 
 civis-2.0.0/civis/man/enhancements_list_cass_ncoa_projects.Rd                  |    4 
 civis-2.0.0/civis/man/enhancements_list_cass_ncoa_shares.Rd                    |    2 
 civis-2.0.0/civis/man/enhancements_list_geocode_projects.Rd                    |only
 civis-2.0.0/civis/man/enhancements_list_geocode_runs.Rd                        |only
 civis-2.0.0/civis/man/enhancements_list_geocode_runs_logs.Rd                   |only
 civis-2.0.0/civis/man/enhancements_list_geocode_runs_outputs.Rd                |only
 civis-2.0.0/civis/man/enhancements_list_geocode_shares.Rd                      |only
 civis-2.0.0/civis/man/enhancements_patch_cass_ncoa.Rd                          |    4 
 civis-2.0.0/civis/man/enhancements_patch_civis_data_match.Rd                   |   19 
 civis-2.0.0/civis/man/enhancements_patch_data_unification.Rd                   |   26 
 civis-2.0.0/civis/man/enhancements_patch_geocode.Rd                            |only
 civis-2.0.0/civis/man/enhancements_patch_table_deduplication.Rd                |   13 
 civis-2.0.0/civis/man/enhancements_post_cass_ncoa.Rd                           |    4 
 civis-2.0.0/civis/man/enhancements_post_civis_data_match.Rd                    |   19 
 civis-2.0.0/civis/man/enhancements_post_data_unification.Rd                    |   26 
 civis-2.0.0/civis/man/enhancements_post_geocode.Rd                             |only
 civis-2.0.0/civis/man/enhancements_post_geocode_cancel.Rd                      |only
 civis-2.0.0/civis/man/enhancements_post_geocode_runs.Rd                        |only
 civis-2.0.0/civis/man/enhancements_post_table_deduplication.Rd                 |   14 
 civis-2.0.0/civis/man/enhancements_put_cass_ncoa.Rd                            |    4 
 civis-2.0.0/civis/man/enhancements_put_cass_ncoa_archive.Rd                    |    2 
 civis-2.0.0/civis/man/enhancements_put_cass_ncoa_projects.Rd                   |    4 
 civis-2.0.0/civis/man/enhancements_put_cass_ncoa_shares_groups.Rd              |    6 
 civis-2.0.0/civis/man/enhancements_put_cass_ncoa_shares_users.Rd               |    6 
 civis-2.0.0/civis/man/enhancements_put_civis_data_match.Rd                     |   19 
 civis-2.0.0/civis/man/enhancements_put_data_unification.Rd                     |   26 
 civis-2.0.0/civis/man/enhancements_put_geocode.Rd                              |only
 civis-2.0.0/civis/man/enhancements_put_geocode_archive.Rd                      |only
 civis-2.0.0/civis/man/enhancements_put_geocode_projects.Rd                     |only
 civis-2.0.0/civis/man/enhancements_put_geocode_shares_groups.Rd                |only
 civis-2.0.0/civis/man/enhancements_put_geocode_shares_users.Rd                 |only
 civis-2.0.0/civis/man/enhancements_put_table_deduplication.Rd                  |   14 
 civis-2.0.0/civis/man/fetch_and_generate_client.Rd                             |    2 
 civis-2.0.0/civis/man/fetch_output_file_ids.Rd                                 |only
 civis-2.0.0/civis/man/fetch_until.Rd                                           |    2 
 civis-2.0.0/civis/man/files_delete_projects.Rd                                 |    4 
 civis-2.0.0/civis/man/files_delete_shares_groups.Rd                            |    4 
 civis-2.0.0/civis/man/files_delete_shares_users.Rd                             |    4 
 civis-2.0.0/civis/man/files_list_projects.Rd                                   |    4 
 civis-2.0.0/civis/man/files_list_shares.Rd                                     |    2 
 civis-2.0.0/civis/man/files_put_projects.Rd                                    |    4 
 civis-2.0.0/civis/man/files_put_shares_groups.Rd                               |    6 
 civis-2.0.0/civis/man/files_put_shares_users.Rd                                |    6 
 civis-2.0.0/civis/man/get_script_fun.Rd                                        |only
 civis-2.0.0/civis/man/groups_list.Rd                                           |    2 
 civis-2.0.0/civis/man/imports_delete_files_csv.Rd                              |only
 civis-2.0.0/civis/man/imports_delete_projects.Rd                               |    4 
 civis-2.0.0/civis/man/imports_delete_shares_groups.Rd                          |    4 
 civis-2.0.0/civis/man/imports_delete_shares_users.Rd                           |    4 
 civis-2.0.0/civis/man/imports_get_files_csv.Rd                                 |only
 civis-2.0.0/civis/man/imports_list.Rd                                          |    6 
 civis-2.0.0/civis/man/imports_list_projects.Rd                                 |    4 
 civis-2.0.0/civis/man/imports_list_shares.Rd                                   |    2 
 civis-2.0.0/civis/man/imports_patch_files_csv.Rd                               |only
 civis-2.0.0/civis/man/imports_post_batches.Rd                                  |    4 
 civis-2.0.0/civis/man/imports_post_files.Rd                                    |    4 
 civis-2.0.0/civis/man/imports_post_files_csv.Rd                                |only
 civis-2.0.0/civis/man/imports_post_syncs.Rd                                    |    2 
 civis-2.0.0/civis/man/imports_put_files_csv.Rd                                 |only
 civis-2.0.0/civis/man/imports_put_files_csv_archive.Rd                         |only
 civis-2.0.0/civis/man/imports_put_projects.Rd                                  |    4 
 civis-2.0.0/civis/man/imports_put_shares_groups.Rd                             |    6 
 civis-2.0.0/civis/man/imports_put_shares_users.Rd                              |    6 
 civis-2.0.0/civis/man/imports_put_syncs.Rd                                     |    2 
 civis-2.0.0/civis/man/imports_put_syncs_archive.Rd                             |    1 
 civis-2.0.0/civis/man/jobs_delete_projects.Rd                                  |    4 
 civis-2.0.0/civis/man/jobs_delete_shares_groups.Rd                             |    4 
 civis-2.0.0/civis/man/jobs_delete_shares_users.Rd                              |    4 
 civis-2.0.0/civis/man/jobs_list_projects.Rd                                    |    4 
 civis-2.0.0/civis/man/jobs_list_runs.Rd                                        |only
 civis-2.0.0/civis/man/jobs_list_runs_logs.Rd                                   |only
 civis-2.0.0/civis/man/jobs_list_shares.Rd                                      |    2 
 civis-2.0.0/civis/man/jobs_put_projects.Rd                                     |    4 
 civis-2.0.0/civis/man/jobs_put_shares_groups.Rd                                |    6 
 civis-2.0.0/civis/man/jobs_put_shares_users.Rd                                 |    6 
 civis-2.0.0/civis/man/json_values_delete_shares_groups.Rd                      |only
 civis-2.0.0/civis/man/json_values_delete_shares_users.Rd                       |only
 civis-2.0.0/civis/man/json_values_get.Rd                                       |only
 civis-2.0.0/civis/man/json_values_list_shares.Rd                               |only
 civis-2.0.0/civis/man/json_values_patch.Rd                                     |only
 civis-2.0.0/civis/man/json_values_post.Rd                                      |only
 civis-2.0.0/civis/man/json_values_put_shares_groups.Rd                         |only
 civis-2.0.0/civis/man/json_values_put_shares_users.Rd                          |only
 civis-2.0.0/civis/man/match_targets_get.Rd                                     |    1 
 civis-2.0.0/civis/man/match_targets_list.Rd                                    |    1 
 civis-2.0.0/civis/man/match_targets_patch.Rd                                   |    5 
 civis-2.0.0/civis/man/match_targets_post.Rd                                    |   11 
 civis-2.0.0/civis/man/media_delete_optimizations_shares_groups.Rd              |    4 
 civis-2.0.0/civis/man/media_delete_optimizations_shares_users.Rd               |    4 
 civis-2.0.0/civis/man/media_delete_ratecards_shares_groups.Rd                  |    4 
 civis-2.0.0/civis/man/media_delete_ratecards_shares_users.Rd                   |    4 
 civis-2.0.0/civis/man/media_delete_spot_orders_shares_groups.Rd                |    4 
 civis-2.0.0/civis/man/media_delete_spot_orders_shares_users.Rd                 |    4 
 civis-2.0.0/civis/man/media_list_optimizations_shares.Rd                       |    2 
 civis-2.0.0/civis/man/media_list_ratecards_shares.Rd                           |    2 
 civis-2.0.0/civis/man/media_list_spot_orders_shares.Rd                         |    2 
 civis-2.0.0/civis/man/media_put_optimizations_shares_groups.Rd                 |    6 
 civis-2.0.0/civis/man/media_put_optimizations_shares_users.Rd                  |    6 
 civis-2.0.0/civis/man/media_put_ratecards_shares_groups.Rd                     |    6 
 civis-2.0.0/civis/man/media_put_ratecards_shares_users.Rd                      |    6 
 civis-2.0.0/civis/man/media_put_spot_orders_shares_groups.Rd                   |    6 
 civis-2.0.0/civis/man/media_put_spot_orders_shares_users.Rd                    |    6 
 civis-2.0.0/civis/man/models_delete_projects.Rd                                |    4 
 civis-2.0.0/civis/man/models_delete_shares_groups.Rd                           |    4 
 civis-2.0.0/civis/man/models_delete_shares_users.Rd                            |    4 
 civis-2.0.0/civis/man/models_list_projects.Rd                                  |    4 
 civis-2.0.0/civis/man/models_list_shares.Rd                                    |    2 
 civis-2.0.0/civis/man/models_put_projects.Rd                                   |    4 
 civis-2.0.0/civis/man/models_put_shares_groups.Rd                              |    6 
 civis-2.0.0/civis/man/models_put_shares_users.Rd                               |    6 
 civis-2.0.0/civis/man/notebooks_delete_projects.Rd                             |    4 
 civis-2.0.0/civis/man/notebooks_delete_shares_groups.Rd                        |    4 
 civis-2.0.0/civis/man/notebooks_delete_shares_users.Rd                         |    4 
 civis-2.0.0/civis/man/notebooks_list_deployments_logs.Rd                       |    4 
 civis-2.0.0/civis/man/notebooks_list_git.Rd                                    |    4 
 civis-2.0.0/civis/man/notebooks_list_git_commits.Rd                            |    4 
 civis-2.0.0/civis/man/notebooks_list_projects.Rd                               |    4 
 civis-2.0.0/civis/man/notebooks_list_shares.Rd                                 |    2 
 civis-2.0.0/civis/man/notebooks_put_git.Rd                                     |    4 
 civis-2.0.0/civis/man/notebooks_put_projects.Rd                                |    4 
 civis-2.0.0/civis/man/notebooks_put_shares_groups.Rd                           |    6 
 civis-2.0.0/civis/man/notebooks_put_shares_users.Rd                            |    6 
 civis-2.0.0/civis/man/projects_delete_shares_groups.Rd                         |    4 
 civis-2.0.0/civis/man/projects_delete_shares_users.Rd                          |    4 
 civis-2.0.0/civis/man/projects_list_shares.Rd                                  |    2 
 civis-2.0.0/civis/man/projects_put_shares_groups.Rd                            |    6 
 civis-2.0.0/civis/man/projects_put_shares_users.Rd                             |    6 
 civis-2.0.0/civis/man/read_civis.Rd                                            |   37 
 civis-2.0.0/civis/man/refresh_table.Rd                                         |    2 
 civis-2.0.0/civis/man/remote_hosts_list.Rd                                     |    4 
 civis-2.0.0/civis/man/remote_hosts_post.Rd                                     |    4 
 civis-2.0.0/civis/man/reports_delete_projects.Rd                               |    4 
 civis-2.0.0/civis/man/reports_delete_services_projects.Rd                      |only
 civis-2.0.0/civis/man/reports_delete_services_shares_groups.Rd                 |    4 
 civis-2.0.0/civis/man/reports_delete_services_shares_users.Rd                  |    4 
 civis-2.0.0/civis/man/reports_delete_shares_groups.Rd                          |    4 
 civis-2.0.0/civis/man/reports_delete_shares_users.Rd                           |    4 
 civis-2.0.0/civis/man/reports_list_git.Rd                                      |    4 
 civis-2.0.0/civis/man/reports_list_git_commits.Rd                              |    4 
 civis-2.0.0/civis/man/reports_list_projects.Rd                                 |    4 
 civis-2.0.0/civis/man/reports_list_services_projects.Rd                        |only
 civis-2.0.0/civis/man/reports_list_services_shares.Rd                          |    2 
 civis-2.0.0/civis/man/reports_list_shares.Rd                                   |    2 
 civis-2.0.0/civis/man/reports_put_git.Rd                                       |    4 
 civis-2.0.0/civis/man/reports_put_projects.Rd                                  |    4 
 civis-2.0.0/civis/man/reports_put_services_projects.Rd                         |only
 civis-2.0.0/civis/man/reports_put_services_shares_groups.Rd                    |    6 
 civis-2.0.0/civis/man/reports_put_services_shares_users.Rd                     |    6 
 civis-2.0.0/civis/man/reports_put_shares_groups.Rd                             |    6 
 civis-2.0.0/civis/man/reports_put_shares_users.Rd                              |    6 
 civis-2.0.0/civis/man/results_delete_projects.Rd                               |    4 
 civis-2.0.0/civis/man/results_delete_services_projects.Rd                      |only
 civis-2.0.0/civis/man/results_delete_services_shares_groups.Rd                 |    4 
 civis-2.0.0/civis/man/results_delete_services_shares_users.Rd                  |    4 
 civis-2.0.0/civis/man/results_delete_shares_groups.Rd                          |    4 
 civis-2.0.0/civis/man/results_delete_shares_users.Rd                           |    4 
 civis-2.0.0/civis/man/results_list_git.Rd                                      |    4 
 civis-2.0.0/civis/man/results_list_git_commits.Rd                              |    4 
 civis-2.0.0/civis/man/results_list_projects.Rd                                 |    4 
 civis-2.0.0/civis/man/results_list_services_projects.Rd                        |only
 civis-2.0.0/civis/man/results_list_services_shares.Rd                          |    2 
 civis-2.0.0/civis/man/results_list_shares.Rd                                   |    2 
 civis-2.0.0/civis/man/results_put_git.Rd                                       |    4 
 civis-2.0.0/civis/man/results_put_projects.Rd                                  |    4 
 civis-2.0.0/civis/man/results_put_services_projects.Rd                         |only
 civis-2.0.0/civis/man/results_put_services_shares_groups.Rd                    |    6 
 civis-2.0.0/civis/man/results_put_services_shares_users.Rd                     |    6 
 civis-2.0.0/civis/man/results_put_shares_groups.Rd                             |    6 
 civis-2.0.0/civis/man/results_put_shares_users.Rd                              |    6 
 civis-2.0.0/civis/man/run_civis.Rd                                             |only
 civis-2.0.0/civis/man/run_template.Rd                                          |only
 civis-2.0.0/civis/man/scripts_delete_containers_projects.Rd                    |    4 
 civis-2.0.0/civis/man/scripts_delete_containers_shares_groups.Rd               |    4 
 civis-2.0.0/civis/man/scripts_delete_containers_shares_users.Rd                |    4 
 civis-2.0.0/civis/man/scripts_delete_custom_projects.Rd                        |    4 
 civis-2.0.0/civis/man/scripts_delete_custom_shares_groups.Rd                   |    4 
 civis-2.0.0/civis/man/scripts_delete_custom_shares_users.Rd                    |    4 
 civis-2.0.0/civis/man/scripts_delete_javascript_projects.Rd                    |    4 
 civis-2.0.0/civis/man/scripts_delete_javascript_shares_groups.Rd               |    4 
 civis-2.0.0/civis/man/scripts_delete_javascript_shares_users.Rd                |    4 
 civis-2.0.0/civis/man/scripts_delete_python3_projects.Rd                       |    4 
 civis-2.0.0/civis/man/scripts_delete_python3_shares_groups.Rd                  |    4 
 civis-2.0.0/civis/man/scripts_delete_python3_shares_users.Rd                   |    4 
 civis-2.0.0/civis/man/scripts_delete_r_projects.Rd                             |    4 
 civis-2.0.0/civis/man/scripts_delete_r_shares_groups.Rd                        |    4 
 civis-2.0.0/civis/man/scripts_delete_r_shares_users.Rd                         |    4 
 civis-2.0.0/civis/man/scripts_delete_sql_projects.Rd                           |    4 
 civis-2.0.0/civis/man/scripts_delete_sql_shares_groups.Rd                      |    4 
 civis-2.0.0/civis/man/scripts_delete_sql_shares_users.Rd                       |    4 
 civis-2.0.0/civis/man/scripts_get.Rd                                           |    2 
 civis-2.0.0/civis/man/scripts_get_containers.Rd                                |    6 
 civis-2.0.0/civis/man/scripts_get_custom.Rd                                    |    2 
 civis-2.0.0/civis/man/scripts_get_javascript.Rd                                |    2 
 civis-2.0.0/civis/man/scripts_get_python3.Rd                                   |    3 
 civis-2.0.0/civis/man/scripts_get_r.Rd                                         |    3 
 civis-2.0.0/civis/man/scripts_get_sql.Rd                                       |    2 
 civis-2.0.0/civis/man/scripts_list_containers_projects.Rd                      |    4 
 civis-2.0.0/civis/man/scripts_list_containers_shares.Rd                        |    2 
 civis-2.0.0/civis/man/scripts_list_custom_projects.Rd                          |    4 
 civis-2.0.0/civis/man/scripts_list_custom_shares.Rd                            |    2 
 civis-2.0.0/civis/man/scripts_list_javascript_git.Rd                           |    4 
 civis-2.0.0/civis/man/scripts_list_javascript_git_commits.Rd                   |    4 
 civis-2.0.0/civis/man/scripts_list_javascript_projects.Rd                      |    4 
 civis-2.0.0/civis/man/scripts_list_javascript_shares.Rd                        |    2 
 civis-2.0.0/civis/man/scripts_list_python3_git.Rd                              |    4 
 civis-2.0.0/civis/man/scripts_list_python3_git_commits.Rd                      |    4 
 civis-2.0.0/civis/man/scripts_list_python3_projects.Rd                         |    4 
 civis-2.0.0/civis/man/scripts_list_python3_shares.Rd                           |    2 
 civis-2.0.0/civis/man/scripts_list_r_git.Rd                                    |    4 
 civis-2.0.0/civis/man/scripts_list_r_git_commits.Rd                            |    4 
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Package plinkQC updated to version 0.2.2 with previous version 0.2.1 dated 2019-03-01

Title: Genotype Quality Control with 'PLINK'
Description: Genotyping arrays enable the direct measurement of an individuals genotype at thousands of markers. 'plinkQC' facilitates genotype quality control for genetic association studies as described by Anderson and colleagues (2010) <doi:10.1038/nprot.2010.116>. It makes 'PLINK' basic statistics (e.g. missing genotyping rates per individual, allele frequencies per genetic marker) and relationship functions accessible from 'R' and generates a per-individual and per-marker quality control report. Individuals and markers that fail the quality control can subsequently be removed to generate a new, clean dataset. Removal of individuals based on relationship status is optimised to retain as many individuals as possible in the study.
Author: Hannah Meyer [aut, cre] (<https://orcid.org/0000-0003-4564-0899>)
Maintainer: Hannah Meyer <hannah.v.meyer@gmail.com>

Diff between plinkQC versions 0.2.1 dated 2019-03-01 and 0.2.2 dated 2019-06-19

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Permanent link

Package see updated to version 0.2.0 with previous version 0.1.0 dated 2019-05-24

Title: Visualisation Toolbox for 'easystats' and Extra Geoms, Themes and Color Palettes for 'ggplot2'
Description: Provides plotting utilities supporting easystats-packages (<https://github.com/easystats/easystats>) and some extra themes, geoms, and scales for 'ggplot2'. Color scales are based on <https://www.materialui.co/colors>.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut, inv] (<https://orcid.org/0000-0001-5375-9967>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package spc updated to version 0.6.1 with previous version 0.6.0 dated 2018-04-12

Title: Statistical Process Control -- Calculation of ARL and Other Control Chart Performance Measures
Description: Evaluation of control charts by means of the zero-state, steady-state ARL (Average Run Length) and RL quantiles. Setting up control charts for given in-control ARL. The control charts under consideration are one- and two-sided EWMA, CUSUM, and Shiryaev-Roberts schemes for monitoring the mean or variance of normally distributed independent data. ARL calculation of the same set of schemes under drift (in the mean) are added. Eventually, all ARL measures for the multivariate EWMA (MEWMA) are provided.
Author: Sven Knoth
Maintainer: Sven Knoth <Sven.Knoth@gmx.de>

Diff between spc versions 0.6.0 dated 2018-04-12 and 0.6.1 dated 2019-06-19

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Package ordinalClust updated to version 1.3.3 with previous version 1.3.1 dated 2018-08-06

Title: Ordinal Data Clustering, Co-Clustering and Classification
Description: Ordinal data classification, clustering and co-clustering using model-based approach with the Bos distribution for ordinal data (Christophe Biernacki and Julien Jacques (2016) <doi:10.1007/s11222-015-9585-2>).
Author: Margot Selosse, Julien Jacques, Christophe Biernacki
Maintainer: Margot Selosse <margot.selosse@gmail.com>

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Package CoRpower updated to version 1.0.2 with previous version 1.0.1 dated 2019-04-25

Title: Power Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials
Description: Calculates power for assessment of intermediate biomarker responses as correlates of risk in the active treatment group in clinical efficacy trials, as described in Gilbert, Janes, and Huang, Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials (2016, Statistics in Medicine). The methods differ from past approaches by accounting for the level of clinical treatment efficacy overall and in biomarker response subgroups, which enables the correlates of risk results to be interpreted in terms of potential correlates of efficacy/protection. The methods also account for inter-individual variability of the observed biomarker response that is not biologically relevant (e.g., due to technical measurement error of the laboratory assay used to measure the biomarker response), which is important because power to detect a specified correlate of risk effect size is heavily affected by the biomarker's measurement error. The methods can be used for a general binary clinical endpoint model with a univariate dichotomous, trichotomous, or continuous biomarker response measured in active treatment recipients at a fixed timepoint after randomization, with either case-cohort Bernoulli sampling or case-control without-replacement sampling of the biomarker (a baseline biomarker is handled as a trivial special case). In a specified two-group trial design, the computeN() function can initially be used for calculating additional requisite design parameters pertaining to the target population of active treatment recipients observed to be at risk at the biomarker sampling timepoint. Subsequently, the power calculation employs an inverse probability weighted logistic regression model fitted by the tps() function in the 'osDesign' package. Power results as well as the relationship between the correlate of risk effect size and treatment efficacy can be visualized using various plotting functions. To link power calculations for detecting a correlate of risk and a correlate of treatment efficacy, a baseline immunogenicity predictor (BIP) can be simulated according to a specified classification rule (for dichotomous or trichotomous BIPs) or correlation with the biomarker response (for continuous BIPs), then outputted along with biomarker response data under assignment to treatment, and clinical endpoint data for both treatment and placebo groups.
Author: Stephanie Wu [aut], Michal Juraska [aut, cre], Peter Gilbert [aut], Yunda Huang [aut]
Maintainer: Michal Juraska <mjuraska@fredhutch.org>

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Package tidyqwi updated to version 0.1.1 with previous version 0.1.0 dated 2019-03-06

Title: A Convenient API for Accessing United States Census Bureau's Quarterly Workforce Indicator
Description: The purpose of this package is to access the United States Census Bureau's Quarterly Workforce Indicator data. Additionally, the data will be retrieved in a tidy format for further manipulation with full variable descriptions added if desired. Information about the United States Census Bureau's Quarterly Workforce Indicator is available at <https://www.census.gov/data/developers/data-sets/qwi.html>.
Author: Michael DeWitt [aut, cre] (<https://orcid.org/0000-0001-8940-1967>), Mona Ahmadiani [aut] (<https://orcid.org/0000-0002-1269-5685>), Adam S. Hyde [aut] (<https://orcid.org/0000-0003-1205-0032>)
Maintainer: Michael DeWitt <me.dewitt.jr@gmail.com>

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Package rspa updated to version 0.2.5 with previous version 0.2.4 dated 2019-05-17

Title: Adapt Numerical Records to Fit (in)Equality Restrictions
Description: Minimally adjust the values of numerical records in a data.frame, such that each record satisfies a predefined set of equality and/or inequality constraints. The constraints can be defined using the 'validate' package. The core algorithms have recently been moved to the 'lintools' package, refer to 'lintools' for a more basic interface and access to a version of the algorithm that works with sparse matrices.
Author: Mark van der Loo
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>

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Package rfacebookstat updated to version 1.9.1 with previous version 1.9.0 dated 2019-05-21

Title: Load Data from Facebook API Marketing
Description: Load data by campaigns, ads, ad sets and insights, ad account and business manager from Facebook Marketing API into R. For more details see official documents by Facebook Marketing API <https://developers.facebook.com/docs/marketing-apis/>.
Author: Alexey Seleznev <selesnow@gmail.com>
Maintainer: Alexey Seleznev <selesnow@gmail.com>

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Package ggdemetra updated to version 0.2.0 with previous version 0.1.0 dated 2019-04-24

Title: 'ggplot2' Extension for Seasonal and Trading Day Adjustment with 'RJDemetra'
Description: Provides 'ggplot2' functions to return the results of seasonal and trading day adjustment made by 'RJDemetra'. 'RJDemetra' is an 'R' interface around 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System and the European System of Central Banks.
Author: Alain Quartier-la-Tente [aut, cre]
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>

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Package QUALYPSO updated to version 1.1 with previous version 1.0.1 dated 2019-05-24

Title: Partitioning Uncertainty Components of an Incomplete Ensemble of Climate Projections
Description: These functions use data augmentation and Bayesian techniques for the assessment of single-member and incomplete ensembles of climate projections. It provides unbiased estimates of climate change responses of all simulation chains and of all uncertainty variables. It additionally propagates uncertainty due to missing information in the estimates. - Evin, G., B. Hingray, J. Blanchet, N. Eckert, S. Morin, and D. Verfaillie. (2019) <doi:10.1175/JCLI-D-18-0606.1>.
Author: Guillaume Evin [aut, cre]
Maintainer: Guillaume Evin <guillaume.evin@irstea.fr>

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Package qgraph updated to version 1.6.3 with previous version 1.6.2 dated 2019-05-09

Title: Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation
Description: Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>.
Author: Sacha Epskamp [aut, cre], Giulio Costantini [aut], Jonas Haslbeck [aut], Adela Isvoranu [aut], Angelique O. J. Cramer [ctb], Lourens J. Waldorp [ctb], Verena D. Schmittmann [ctb], Denny Borsboom [ctb]
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package MXM updated to version 1.4.4 with previous version 1.4.3 dated 2019-05-27

Title: Feature Selection (Including Multiple Solutions) and Bayesian Networks
Description: Many feature selection methods for a wide range of response variables, including minimal, statistically-equivalent and equally-predictive feature subsets. Bayesian network algorithms and related functions are also included. The package name 'MXM' stands for "Mens eX Machina", meaning "Mind from the Machine" in Latin. References: a) Lagani, V. and Athineou, G. and Farcomeni, A. and Tsagris, M. and Tsamardinos, I. (2017). Feature Selection with the R Package MXM: Discovering Statistically Equivalent Feature Subsets. Journal of Statistical Software, 80(7). <doi:10.18637/jss.v080.i07>. b) Tsagris, M., Lagani, V. and Tsamardinos, I. (2018). Feature selection for high-dimensional temporal data. BMC Bioinformatics, 19:17. <doi:10.1186/s12859-018-2023-7>. c) Tsagris, M., Borboudakis, G., Lagani, V. and Tsamardinos, I. (2018). Constraint-based causal discovery with mixed data. International Journal of Data Science and Analytics, 6(1): 19-30. <doi:10.1007/s41060-018-0097-y>. d) Tsagris, M., Papadovasilakis, Z., Lakiotaki, K. and Tsamardinos, I. (2018). Efficient feature selection on gene expression data: Which algorithm to use? BioRxiv. <doi:10.1101/431734>. e) Tsagris, M. (2019). Bayesian Network Learning with the PC Algorithm: An Improved and Correct Variation. Applied Artificial Intelligence, 33(2):101-123. <doi:10.1080/08839514.2018.1526760>. f) Borboudakis, G. and Tsamardinos, I. (2019). Forward-Backward Selection with Early Dropping. Journal of Machine Learning Research 20: 1-39.
Author: Michail Tsagris [aut, cre], Ioannis Tsamardinos [aut, cph], Vincenzo Lagani [aut, cph], Giorgos Athineou [aut], Giorgos Borboudakis [ctb], Anna Roumpelaki [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package CSTools updated to version 1.0.1 with previous version 1.0.0 dated 2019-04-24

Title: Assessing Skill of Climate Forecasts on Seasonal-to-Decadal Timescales
Description: Exploits dynamical seasonal forecasts in order to provide information relevant to stakeholders at the seasonal timescale. The package contains process-based methods for forecast calibration, bias correction, statistical and stochastic downscaling, optimal forecast combination and multivariate verification, as well as basic and advanced tools to obtain tailored products. This package was developed in the context of the ERA4CS project MEDSCOPE. Doblas-Reyes et al. (2005) <doi:10.1111/j.1600-0870.2005.00104.x>. Mishra et al. (2018) <doi:10.1007/s00382-018-4404-z>. Terzago et al. (2018) <doi:10.5194/nhess-18-2825-2018>. Torralba et al. (2017) <doi:10.1175/JAMC-D-16-0204.1>. D'Onofrio et al. (2014) <doi:10.1175/JHM-D-13-096.1>.
Author: BSC-CNS [cph], Louis-Philippe Caron [aut] (<https://orcid.org/0000-0001-5221-0147>), Jost von Hardenberg [aut] (<https://orcid.org/0000-0002-5312-8070>), Nuria Perez-Zanon [aut, cre] (<https://orcid.org/0000-0001-8568-3071>), Llorenç LLedo [aut], Nicolau Manubens [aut], Niti Mishra [ctb], Veronica Torralba [aut], Deborah Verfaillie [aut], Lauriane Batte [ctb], Jesus Peña [ctb], Bert van Schaeybroeck [ctb]
Maintainer: Nuria Perez-Zanon <nuria.perez@bsc.es>

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New package ui with initial version 0.1.0
Package: ui
Title: Uncertainty Intervals and Sensitivity Analysis for Missing Data
Version: 0.1.0
Author: Minna Genbaeck [aut, cre],
Maintainer: Minna Genbaeck <minna.genback@umu.se>
Description: Implements functions to derive uncertainty intervals for (i) regression (linear and probit) parameters when outcome is missing not at random (non-ignorable missingness) introduced in Genbaeck, M., Stanghellini, E., de Luna, X. (2015) <doi:10.1007/s00362-014-0610-x> and Genbaeck, M., Ng, N., Stanghellini, E., de Luna, X. (2018) <doi:10.1007/s10433-017-0448-x>; and (ii) double robust and outcome regression estimators of average causal effects (on the treated) with possibly unobserved confounding introduced in Genbaeck, M., de Luna, X. (2018) <doi:10.1111/biom.13001>.
Depends: R (>= 3.5)
Imports: Matrix, maxLik, mvtnorm, numDeriv, graphics, stats
Suggests: MASS
Encoding: UTF-8
LazyData: true
License: GPL-2
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-19 09:28:53 UTC; miahjr04
Repository: CRAN
Date/Publication: 2019-06-19 12:10:03 UTC

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New package shrinkTVP with initial version 1.0.0
Package: shrinkTVP
Type: Package
Title: Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage
Version: 1.0.0
Authors@R: c( person("Peter", "Knaus", email = "peter.knaus@wu.ac.at", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-6498-7084")), person("Angela", "Bitto-Nemling", role = "aut"), person("Annalisa", "Cadonna", email = "annalisa.cadonna@wu.ac.at", role = "aut", comment = c(ORCID = "0000-0003-0360-7628")), person("Sylvia", "Frühwirth-Schnatter", email = "sylvia.fruehwirth-schnatter@wu.ac.at", role = "aut", comment = c(ORCID = "0000-0003-0516-5552")), person("Daniel", "Winkler", email = "daniel.winkler@wu.ac.at", role = "ctb"), person("Kemal", "Dingic", role = "ctb"))
Description: Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter models with shrinkage priors. Details on the algorithms used are provided in Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3.0)
Imports: Rcpp, GIGrvg, stochvol, coda, methods, utils
LinkingTo: Rcpp, RcppArmadillo, GIGrvg, RcppProgress, stochvol
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: yes
Packaged: 2019-06-19 09:59:04 UTC; pknaus
Author: Peter Knaus [aut, cre] (<https://orcid.org/0000-0001-6498-7084>), Angela Bitto-Nemling [aut], Annalisa Cadonna [aut] (<https://orcid.org/0000-0003-0360-7628>), Sylvia Frühwirth-Schnatter [aut] (<https://orcid.org/0000-0003-0516-5552>), Daniel Winkler [ctb], Kemal Dingic [ctb]
Maintainer: Peter Knaus <peter.knaus@wu.ac.at>
Repository: CRAN
Date/Publication: 2019-06-19 12:10:07 UTC

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Package mvtnorm updated to version 1.0-11 with previous version 1.0-10 dated 2019-03-04

Title: Multivariate Normal and t Distributions
Description: Computes multivariate normal and t probabilities, quantiles, random deviates and densities.
Author: Alan Genz [aut], Frank Bretz [aut], Tetsuhisa Miwa [aut], Xuefei Mi [aut], Friedrich Leisch [ctb], Fabian Scheipl [ctb], Bjoern Bornkamp [ctb] (<https://orcid.org/0000-0002-6294-8185>), Martin Maechler [ctb], Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between mvtnorm versions 1.0-10 dated 2019-03-04 and 1.0-11 dated 2019-06-19

 DESCRIPTION                  |   12 ++--
 MD5                          |   20 +++---
 R/mvt.R                      |    4 -
 R/noisy-root.R               |    3 +
 build/vignette.rds           |binary
 inst/NEWS                    |    5 +
 inst/doc/MVT_Rnews.pdf       |binary
 man/pmvnorm.Rd               |    2 
 src/mvt.f                    |  123 +++++++++++++++++++++----------------------
 tests/bugfix-tests.R         |   25 ++++++++
 tests/bugfix-tests.Rout.save |   33 ++++++++++-
 11 files changed, 145 insertions(+), 82 deletions(-)

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Package metaheuristicOpt updated to version 2.0.0 with previous version 1.0.0 dated 2017-10-16

Title: Metaheuristic for Optimization
Description: An implementation of metaheuristic algorithms for continuous optimization. Currently, the package contains the implementations of 21 algorithms, as follows: particle swarm optimization (Kennedy and Eberhart, 1995), ant lion optimizer (Mirjalili, 2015 <doi:10.1016/j.advengsoft.2015.01.010>), grey wolf optimizer (Mirjalili et al., 2014 <doi:10.1016/j.advengsoft.2013.12.007>), dragonfly algorithm (Mirjalili, 2015 <doi:10.1007/s00521-015-1920-1>), firefly algorithm (Yang, 2009 <doi:10.1007/978-3-642-04944-6_14>), genetic algorithm (Holland, 1992, ISBN:978-0262581110), grasshopper optimisation algorithm (Saremi et al., 2017 <doi:10.1016/j.advengsoft.2017.01.004>), harmony search algorithm (Mahdavi et al., 2007 <doi:10.1016/j.amc.2006.11.033>), moth flame optimizer (Mirjalili, 2015 <doi:10.1016/j.knosys.2015.07.006>, sine cosine algorithm (Mirjalili, 2016 <doi:10.1016/j.knosys.2015.12.022>), whale optimization algorithm (Mirjalili and Lewis, 2016 <doi:10.1016/j.advengsoft.2016.01.008>), clonal selection algorithm (Castro, 2002 <doi:10.1109/TEVC.2002.1011539>), differential evolution (Das & Suganthan, 2011), shuffled frog leaping (Eusuff, Landsey & Pasha, 2006), cat swarm optimization (Chu et al., 2006), artificial bee colony algorithm (Karaboga & Akay, 2009), krill-herd algorithm (Gandomi & Alavi, 2012), cuckoo search (Yang & Deb, 2009), bat algorithm (Yang, 2012), gravitational based search (Rashedi et al., 2009) and black hole optimization (Hatamlou, 2013).
Author: Lala Septem Riza [aut, cre], Iip [aut], Eddy Prasetyo Nugroho [aut], Muhammad Bima Adi Prabowo [aut], Enjun Junaeti [aut], Ade Gafar Abdullah [aut]
Maintainer: Lala Septem Riza <lala.s.riza@upi.edu>

Diff between metaheuristicOpt versions 1.0.0 dated 2017-10-16 and 2.0.0 dated 2019-06-19

 DESCRIPTION                    |   28 +-
 MD5                            |   72 ++++--
 NAMESPACE                      |   14 +
 R/ABC.Algorithm.R              |only
 R/ALO.Algorithm.R              |   99 ++++----
 R/BA.Algorithm.R               |only
 R/BHO.Algorithm.R              |only
 R/CLONALG.Algorithm.R          |only
 R/CS.Algorithm.R               |only
 R/CSO.Algorithm.R              |only
 R/DA.Algorithm.R               |  122 +++++-----
 R/DE.Algorithm.R               |only
 R/FFA.Algorithm.R              |  108 ++++-----
 R/GA.Algorithm.R               |   99 ++++----
 R/GBS.Algorithm.R              |only
 R/GOA.Algorithm.R              |   92 ++++----
 R/GWO.Algorithm.R              |  124 +++++-----
 R/IHS.Algorithm.R              |  113 +++++----
 R/KH.Algorithm.R               |only
 R/MFO.Algorithm.R              |  107 ++++-----
 R/PSO.Algorithm.R              |   94 ++++----
 R/SCA.Algorithm.R              |  106 ++++-----
 R/SFL.Algorithm.R              |only
 R/WOA.Algorithm.R              |   97 ++++----
 R/metaheuristic.mainFunction.R |  468 ++++++++++++++++++++++++++++++++++-------
 man/ABC.Rd                     |only
 man/ALO.Rd                     |   63 ++---
 man/BA.Rd                      |only
 man/BHO.Rd                     |only
 man/CLONALG.Rd                 |only
 man/CS.Rd                      |only
 man/CSO.Rd                     |only
 man/DA.Rd                      |   74 +++---
 man/DE.Rd                      |only
 man/FFA.Rd                     |   80 +++----
 man/GA.Rd                      |   65 ++---
 man/GBS.Rd                     |only
 man/GOA.Rd                     |   64 +++--
 man/GWO.Rd                     |   72 +++---
 man/HS.Rd                      |   73 +++---
 man/KH.Rd                      |only
 man/MFO.Rd                     |   67 ++---
 man/PSO.Rd                     |   71 +++---
 man/SCA.Rd                     |   66 ++---
 man/SFL.Rd                     |only
 man/WOA.Rd                     |   57 ++--
 man/metaOpt.Rd                 |  243 +++++++++++++++++----
 47 files changed, 1660 insertions(+), 1078 deletions(-)

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New package MatchIt.mice with initial version 1.0.3
Type: Package
Package: MatchIt.mice
Title: Selecting Matched Samples from Multiply Imputed Datasets
Description: Selects matched samples from the control and treatment groups of each imputed datasets and estimates the weight of each individual in the complete distribution of control and treatment groups of the imputed datasets. Please see the package GitHub page <https://github.com/FarhadPishgar/MatchIt.mice/> for more details.
Version: 1.0.3
Author: Farhad Pishgar
Maintainer: Farhad Pishgar <Farhad.Pishgar@Gmail.com>
URL: https://github.com/FarhadPishgar/MatchIt.mice
BugReports: https://github.com/FarhadPishgar/MatchIt.mice/issues
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: mice, MatchIt
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-19 09:35:45 UTC; Farhad
Repository: CRAN
Date/Publication: 2019-06-19 12:10:19 UTC

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New package shinymanager with initial version 1.0
Package: shinymanager
Title: Authentication Management for 'Shiny' Applications
Version: 1.0
Authors@R: c( person("Benoit", "Thieurmel", email = "benoit.thieurmel@datastorm.fr", role = c("aut", "cre")), person("Victor", "Perrier", email = "victor.perrier@dreamRs.fr", role = c("aut")) )
Description: Simple and secure authentification mechanism for single 'Shiny' applications. Credentials are stored in an encrypted 'SQLite' database. Source code of main application is protected until authentication is successful.
License: GPL-3
URL: https://github.com/datastorm-open/shinymanager
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: R6, shiny, htmltools, DT (>= 0.5), DBI, RSQLite, openssl, R.utils, billboarder
Suggests: keyring, testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2019-06-18 09:15:34 UTC; Datastorm
Author: Benoit Thieurmel [aut, cre], Victor Perrier [aut]
Maintainer: Benoit Thieurmel <benoit.thieurmel@datastorm.fr>
Repository: CRAN
Date/Publication: 2019-06-19 11:20:04 UTC

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New package portfolioBacktest with initial version 0.1.0
Package: portfolioBacktest
Title: Automated Backtesting of Portfolios over Multiple Datasets
Version: 0.1.0
Date: 2019-06-19
Description: Automated backtesting of multiple portfolios over multiple datasets of stock prices in a rolling-window fashion. Intended for researchers and practitioners to backtest a set of different portfolios, as well as by a course instructor to assess the students in their portfolio design in a fully automated and convenient manner, with results conveniently formatted in tables and plots. Each portfolio design is easily defined as a function that takes as input a window of the stock prices and outputs the portfolio weights. Multiple portfolios can be easily specified as a list of functions or as files in a folder. Multiple datasets can be conveniently extracted randomly from different markets, different time periods, and different subsets of the stock universe. The results can be later assessed and ranked with tables based on a number of performance criteria (e.g., expected return, volatility, Sharpe ratio, drawdown, turnover rate, return on investment, computational time, etc.), as well as plotted in a number of ways with nice barplots and boxplots.
Authors@R: c( person(c("Daniel", "P."), "Palomar", role = c("cre", "aut"), email = "daniel.p.palomar@gmail.com"), person("Rui", "Zhou", role = "aut", email = "rzhouae@connect.ust.hk") )
Maintainer: Daniel P. Palomar <daniel.p.palomar@gmail.com>
URL: https://CRAN.R-project.org/package=portfolioBacktest, https://github.com/dppalomar/portfolioBacktest
BugReports: https://github.com/dppalomar/portfolioBacktest/issues
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Imports: doSNOW, evaluate, foreach, PerformanceAnalytics, quantmod, R.utils, snow, utils, xts, zoo
Suggests: CVXR, DT, ggplot2, gridExtra, knitr, prettydoc, readtext, rmarkdown, R.rsp, stringi, testthat
VignetteBuilder: knitr, rmarkdown, R.rsp
NeedsCompilation: no
Packaged: 2019-06-19 05:30:35 UTC; palomar
Author: Daniel P. Palomar [cre, aut], Rui Zhou [aut]
Repository: CRAN
Date/Publication: 2019-06-19 11:40:02 UTC

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New package nlMS with initial version 1.0
Package: nlMS
Type: Package
Title: Non-Linear Model Selection
Version: 1.0
Author: Carme Font <carme.font.moragon@gmail.com>
Maintainer: Carme Font <carme.font.moragon@gmail.com>
Description: Package to select best model among several linear and nonlinear models. The main function uses the gnls() function from the 'nlme' package to fit the data to nine regression models, named: "linear", "quadratic", "cubic", "logistic", "exponential", "power", "monod", "haldane", "logit".
License: GPL-3
Imports: nlme, stats, graphics, grDevices
NeedsCompilation: no
Packaged: 2019-06-03 10:07:56 UTC; cfont
Repository: CRAN
Date/Publication: 2019-06-19 11:50:02 UTC

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