Thu, 04 Apr 2019

Package geneHummus updated to version 1.0.11 with previous version 1.0.1 dated 2019-03-26

Title: A Pipeline to Define Gene Families in Legumes and Beyond
Description: A pipeline with high specificity and sensitivity in extracting proteins from the RefSeq database (National Center for Biotechnology Information). Manual identification of gene families is highly time-consuming and laborious, requiring an iterative process of manual and computational analysis to identify members of a given family. The pipelines implements an automatic approach for the identification of gene families based on the conserved domains that specifically define that family. See Die et al. (2018) <doi:10.1101/436659> for more information and examples.
Author: Jose V. Die [aut, cre] (<https://orcid.org/0000-0002-7506-8590>), Moamen M. Elmassry [ctb], Kimberly H. LeBlanc [ctb], Olaitan I. Awe [ctb], Allissa Dillman [ctb], Ben Busby [aut]
Maintainer: Jose V. Die <jose.die@uco.es>

Diff between geneHummus versions 1.0.1 dated 2019-03-26 and 1.0.11 dated 2019-04-04

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Package agricolae updated to version 1.3-1 with previous version 1.3-0 dated 2019-01-07

Title: Statistical Procedures for Agricultural Research
Description: Original idea was presented in the thesis "A statistical analysis tool for agricultural research" to obtain the degree of Master on science, National Engineering University (UNI), Lima-Peru. Some experimental data for the examples come from the CIP and others research. Agricolae offers extensive functionality on experimental design especially for agricultural and plant breeding experiments, which can also be useful for other purposes. It supports planning of lattice, Alpha, Cyclic, Complete Block, Latin Square, Graeco-Latin Squares, augmented block, factorial, split and strip plot designs. There are also various analysis facilities for experimental data, e.g. treatment comparison procedures and several non-parametric tests comparison, biodiversity indexes and consensus cluster.
Author: Felipe de Mendiburu
Maintainer: Felipe de Mendiburu <fmendiburu@lamolina.edu.pe>

Diff between agricolae versions 1.3-0 dated 2019-01-07 and 1.3-1 dated 2019-04-04

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Package collections updated to version 0.1.6 with previous version 0.1.5 dated 2019-03-07

Title: High Performance Container Data Types
Description: Provides high performance container data types such as Queue, Stack, Deque, Dict and OrderedDict. Benchmarks <https://randy3k.github.io/collections/articles/benchmark.html> have shown that these containers are asymptotically more efficient than those offered by other packages.
Author: Randy Lai [aut, cre]
Maintainer: Randy Lai <randy.cs.lai@gmail.com>

Diff between collections versions 0.1.5 dated 2019-03-07 and 0.1.6 dated 2019-04-04

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 24 files changed, 331 insertions(+), 400 deletions(-)

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Package adnuts updated to version 1.0.1 with previous version 1.0.0 dated 2018-02-08

Title: No-U-Turn MCMC Sampling for 'ADMB' and 'TMB' Models
Description: Bayesian inference using the no-U-turn (NUTS) algorithm by Hoffman and Gelman (2014) <http://www.jmlr.org/papers/v15/hoffman14a.html>. Designed for 'AD Model Builder' ('ADMB') models, or when R functions for log-density and log-density gradient are available, such as 'Template Model Builder' ('TMB') models and other special cases. Functionality is similar to 'Stan', and the 'rstan' and 'shinystan' packages are used for diagnostics and inference.
Author: Cole Monnahan [aut, cre]
Maintainer: Cole Monnahan <monnahc@uw.edu>

Diff between adnuts versions 1.0.0 dated 2018-02-08 and 1.0.1 dated 2019-04-04

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Package wevid updated to version 0.6 with previous version 0.5.2 dated 2018-12-16

Title: Quantifying Performance of a Binary Classifier Through Weight of Evidence
Description: The distributions of the weight of evidence (log Bayes factor) favouring case over noncase status in a test dataset (or test folds generated by cross-validation) can be used to quantify the performance of a diagnostic test (McKeigue (2018), <doi:10.1177/0962280218776989>). The package can be used with any test dataset on which you have observed case-control status and have computed prior and posterior probabilities of case status using a model learned on a training dataset. To quantify how the predictor will behave as a risk stratifier, the quantiles of the distributions of weight of evidence in cases and controls can be calculated and plotted.
Author: Paul McKeigue [aut] (<https://orcid.org/0000-0002-5217-1034>), Marco Colombo [ctb, cre] (<https://orcid.org/0000-0001-6672-0623>)
Maintainer: Marco Colombo <mar.colombo13@gmail.com>

Diff between wevid versions 0.5.2 dated 2018-12-16 and 0.6 dated 2019-04-04

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New package genpwr with initial version 1.0.0
Package: genpwr
Title: Power Calculations Under Genetic Model Misspecification
Version: 1.0.0
Authors@R: c(person("Camille", "Moore", email = "moorec@njhealth.org", role = c("aut", "cre")), person("Sean", "Jacobson", email = "jacobsons@njhealth.org", role = "aut"))
Description: Power and sample size calculations for genetic association studies allowing for misspecification of the model of genetic susceptibility. Power and/or sample size can be calculated for logistic (case/control study design) and linear (continuous phenotype) regression models, using additive, dominant, recessive or degree of freedom coding of the genetic covariate while assuming a true dominant, recessive or additive genetic effect. In addition, power and sample size calculations can be performed for gene by environment interactions. These methods are extensions of Gauderman (2002) <doi:10.1093/aje/155.5.478> and Gauderman (2002) <doi:10.1002/sim.973> and are described in: Moore CM, Jacobson S, Fingerlin TE. Power and Sample Size Calculations for Genetic Association Studies in the Presence of Genetic Model Misspecification. American Society of Human Genetics. October 2018, San Diego. Poster Presentation: <http://www.ashg.org/2018meeting/listing/PosterSessions.shtml>.
Depends: R (>= 3.5.0)
License: GPL-3
Imports: ggplot2, nleqslv, MASS, stats, utils
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-03 17:10:19 UTC; Sean
Author: Camille Moore [aut, cre], Sean Jacobson [aut]
Maintainer: Camille Moore <moorec@njhealth.org>
Repository: CRAN
Date/Publication: 2019-04-04 17:40:03 UTC

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New package saotd with initial version 0.2.0
Package: saotd
Type: Package
Title: Sentiment Analysis of Twitter Data
Version: 0.2.0
Date: 2019-04-02
Authors@R: c( person("Evan", "Munson", email = "evan.l.munson@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9958-6800")), person("Christopher", "Smith", email = "Cms3am@virginia.edu", role = c("aut"), comment = c(ORCID = "0000-0002-8288-270X")), person("Bradley", "Boehmke", email = "bradleyboehmke@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0002-3611-8516")), person("Jason", "Freels", email = "auburngrads@live.com", role = c("aut"), comment = c(ORCID = "0000-0002-2415-0340")) )
Maintainer: Evan Munson <evan.l.munson@gmail.com>
BugReports: https://github.com/evan-l-munson/saotd/issues
Description: This analytic is an in initial foray into sentiment analysis. This analytic will allow a user to access the Twitter API (once they create their own developer account), ingest tweets of their interest, clean / tidy data, perform topic modeling if interested, compute sentiment scores utilizing the x bing Lexicon, and output visualizations.
License: GPL (>= 2)
Imports: plyr, dplyr, widyr, stringr, tidytext, twitteR, purrr, tidyr, igraph, maps, ggplot2, ggraph, scales, reshape2, lubridate, utils, stats, magrittr, ldatuning, topicmodels
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, httr, base64enc
Depends: R (>= 3.3.0)
VignetteBuilder: knitr
SystemRequirements: GSL (>=2.4), MPFR (>= 4.0.0), udunits2 (>=2.2.26-3)
Encoding: UTF-8
LazyLoad: true
NeedsCompilation: no
Packaged: 2019-04-03 02:50:23 UTC; eklm
Author: Evan Munson [aut, cre] (<https://orcid.org/0000-0002-9958-6800>), Christopher Smith [aut] (<https://orcid.org/0000-0002-8288-270X>), Bradley Boehmke [aut] (<https://orcid.org/0000-0002-3611-8516>), Jason Freels [aut] (<https://orcid.org/0000-0002-2415-0340>)
Repository: CRAN
Date/Publication: 2019-04-04 16:30:03 UTC

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New package llbayesireg with initial version 1.0.0
Package: llbayesireg
Title: The L-Logistic Bayesian Regression
Version: 1.0.0
Date: 2019-03-06
Authors@R: c(person("Sara", "Alexandre Fonsêca", role = "aut", email = "saralexandre@alu.ufc.br"), person("Rosineide", "Fernando da Paz", role = c("aut", "cre"), email = "rfpaz2@gmail.com"), person("Jorge Luís", "Bazán", role = "ctb"))
Author: Sara Alexandre Fonsêca [aut], Rosineide Fernando da Paz [aut, cre], Jorge Luís Bazán [ctb]
Maintainer: Rosineide Fernando da Paz <rfpaz2@gmail.com>
Description: R functions and data sets for the work Paz, R.F., Balakrishnan, N and Bazán, J.L. (2018). L-logistic regression models: Prior sensitivity analysis, robustness to outliers and applications. Brazilian Journal of Probability and Statistics, <https://www.imstat.org/wp-content/uploads/2018/05/BJPS397.pdf>.
Imports: llogistic, rstan, MCMCpack, MASS, coda, stats
Depends: R (>= 3.4.0), ggplot2 (>= 2.0.0), StanHeaders (>= 2.18.0), Rcpp (>= 0.12.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-04-02 22:08:18 UTC; Sara
Repository: CRAN
Date/Publication: 2019-04-04 16:20:03 UTC

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Package imputeTestbench updated to version 3.0.2 with previous version 3.0.1 dated 2017-06-23

Title: Test Bench for the Comparison of Imputation Methods
Description: Provides a test bench for the comparison of missing data imputation methods in uni-variate time series. Imputation methods are compared using different error metrics. Proposed imputation methods and alternative error metrics can be used.
Author: Neeraj Bokde [aut], Marcus W. Beck [cre, aut]
Maintainer: Marcus W. Beck <mbafs2012@gmail.com>

Diff between imputeTestbench versions 3.0.1 dated 2017-06-23 and 3.0.2 dated 2019-04-04

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 6 files changed, 54 insertions(+), 28 deletions(-)

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New package hydra with initial version 0.1.0
Package: hydra
Type: Package
Title: Hyperbolic Embedding
Version: 0.1.0
Author: Martin Keller-Ressel
Maintainer: Martin Keller-Ressel <martin.keller-ressel@tu-dresden.de>
Description: Calculate an optimal embedding of a set of data points into low-dimensional hyperbolic space. This uses the strain-minimizing hyperbolic embedding of Keller-Ressel and Nargang (2019), see <arXiv:1903.08977>.
Suggests: igraph, igraphdata, Matrix, RSpectra
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-01 14:55:36 UTC; mkeller
Repository: CRAN
Date/Publication: 2019-04-04 16:10:07 UTC

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New package hglm with initial version 2.2-1
Package: hglm
Type: Package
Title: Hierarchical Generalized Linear Models
Version: 2.2-1
Date: 2019-04-04
Author: Moudud Alam, Lars Ronnegard, Xia Shen
Maintainer: Xia Shen <xia.shen@ki.se>
Description: Implemented here are procedures for fitting hierarchical generalized linear models (HGLM). It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the mean model. As statistical models, HGLMs were initially developed by Lee and Nelder (1996) <https://www.jstor.org/stable/2346105?seq=1>. We provide an implementation (Ronnegard, Alam and Shen 2010) <https://journal.r-project.org/archive/2010-2/RJournal_2010-2_Roennegaard~et~al.pdf> following Lee, Nelder and Pawitan (2006) <ISBN: 9781420011340> with algorithms extended for spatial modeling (Alam, Ronnegard and Shen 2015) <https://journal.r-project.org/archive/2015/RJ-2015-017/RJ-2015-017.pdf>.
BugReports: https://r-forge.r-project.org/tracker/?group_id=558
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 3.0), utils, Matrix, MASS, hglm.data
Packaged: 2019-04-04 15:36:54 UTC; xia
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2019-04-04 16:20:07 UTC

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New package dynparam with initial version 1.0.0
Package: dynparam
Type: Package
Title: Creating Meta-Information for Parameters
Version: 1.0.0
Authors@R: c( person( "Robrecht", "Cannoodt", email = "rcannood@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3641-729X", github = "rcannood") ), person( "Wouter", "Saelens", email = "wouter.saelens@ugent.be", role = c("aut"), comment = c(ORCID = "0000-0002-7114-6248", github = "zouter") ) )
URL: https://github.com/dynverse/dynparam
BugReports: https://github.com/dynverse/dynparam/issues
Description: Provides tools for describing parameters of algorithms in an abstract way. Description can include an id, a description, a domain (range or list of values), and a default value. 'dynparam' can also convert parameter sets to a 'ParamHelpers' format, in order to be able to use 'dynparam' in conjunction with 'mlrMBO'.
License: GPL-3
LazyData: TRUE
RoxygenNote: 6.1.1
Encoding: UTF-8
Depends: R (>= 3.0.0)
Imports: assertthat, carrier, dplyr, dynutils (>= 1.0.2), Hmisc, magrittr, purrr, stringr, testthat, tibble, tidyr
Suggests: ParamHelpers, lhs
NeedsCompilation: no
Packaged: 2019-04-02 11:22:16 UTC; rcannood
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [aut] (<https://orcid.org/0000-0002-7114-6248>, zouter)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-04 16:10:10 UTC

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Package distrEllipse updated to version 2.8.0 with previous version 2.7.0 dated 2018-07-23

Title: S4 Classes for Elliptically Contoured Distributions
Description: Distribution (S4-)classes for elliptically contoured distributions (based on package 'distr').
Author: Peter Ruckdeschel [aut, cre, cph]
Maintainer: Peter Ruckdeschel <peter.ruckdeschel@uni-oldenburg.de>

Diff between distrEllipse versions 2.7.0 dated 2018-07-23 and 2.8.0 dated 2019-04-04

 DESCRIPTION                  |   26 +++++++++++++-------------
 MD5                          |   10 +++++-----
 R/EllipticalDistribution.R   |    2 +-
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 inst/NEWS                    |   16 ++++++++++++++++
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 6 files changed, 75 insertions(+), 57 deletions(-)

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New package changedetection with initial version 0.1.0
Package: changedetection
Type: Package
Title: Nonparametric Change Detection in Multivariate Linear Relationships
Version: 0.1.0
Date: 2019-03-11
Author: Olga Gorskikh, Pekka Malo, Pauliina Ilmonen, Lauri Viitasaari, Joni Virta
Maintainer: Olga Gorskikh <olga.a.gorskikh@gmail.com>
Description: Contains implementation of the Nonparametric Splitting Algorithm (NSA), which estimates a set of structural change points (change dates) within a multivariate time-wise linear regression. Additionally, it contains utility functions to estimate corresponding changing linear model, moving energy distance and a change-detection test. For more information, see Malo et. al (2019) <arXiv:1805.08512>.
Encoding: UTF-8
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Imports: Rdpack, L1pack, glmnet
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2019-04-03 11:38:50 UTC; Olga
Repository: CRAN
Date/Publication: 2019-04-04 16:40:07 UTC

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New package sleepwalk with initial version 0.1.0
Package: sleepwalk
Type: Package
Title: Interactively Explore Dimension-Reduced Embeddings
Version: 0.1.0
Date: 2019-04-01
Authors@R: c( person( "Svetlana", "Ovchinnikova", role=c("aut","cre"), email = "s.ovchinnikova@zmbh.uni-heidelberg.de" ), person( "Simon", "Anders", role="aut", email = "sanders@fs.tum.de" ) )
Description: A tool to interactively explore the embeddings created by dimension reduction methods such as Principal Components Analysis (PCA), Multidimensional Scaling (MDS), T-distributed Stochastic Neighbour Embedding (t-SNE), Uniform Manifold Approximation and Projection (UMAP) or any other.
License: GPL-3
Imports: jrc, cowplot, httpuv, jsonlite, scales, ggplot2
RoxygenNote: 6.1.1
URL: https://anders-biostat.github.io/sleepwalk/
BugReports: https://github.com/anders-biostat/sleepwalk/issues
NeedsCompilation: no
Packaged: 2019-04-03 14:34:55 UTC; tyranchik
Author: Svetlana Ovchinnikova [aut, cre], Simon Anders [aut]
Maintainer: Svetlana Ovchinnikova <s.ovchinnikova@zmbh.uni-heidelberg.de>
Repository: CRAN
Date/Publication: 2019-04-04 15:10:03 UTC

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New package radsafer with initial version 1.0.0
Package: radsafer
Type: Package
Title: Radiation Safety
Version: 1.0.0
Author: Mark Hogue <mark.hogue.chp@gmail.com>
Maintainer: Mark Hogue <mark.hogue.chp@gmail.com>
Description: Provides functions for radiation safety, also known as "radiation protection" and "radiological control". The science of radiation protection is called "health physics" and its engineering functions are called "radiological engineering". Functions in this package cover many of the computations needed by radiation safety professionals. Examples include: obtaining updated calibration and source check values for radiation monitors to account for radioactive decay in a reference source, simulating instrument readings to better understand measurement uncertainty, correcting instrument readings for geometry and ambient atmospheric conditions. Many of these functions are described in Johnson and Kirby (2011, ISBN-13: 978-1609134198). Utilities are also included for developing inputs and processing outputs with radiation transport codes, such as MCNP, a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron, or coupled neutron/photon/electron transport (Werner et. al. (2018) <doi:10.2172/1419730>).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, tidyverse, scatterplot3d, dplyr
Imports: ggplot2, readr, stats, graphics
Depends: R (>= 3.3)
URL: https://github.com/markhogue/radsafer
BugReports: https://github.com/markhogue/radsafer/issues
NeedsCompilation: no
Packaged: 2019-04-02 02:20:17 UTC; mark
Repository: CRAN
Date/Publication: 2019-04-04 15:50:03 UTC

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New package flagr with initial version 0.3.2
Package: flagr
Type: Package
Title: Implementation of Flag Aggregation
Version: 0.3.2
Date: 2019-04-02
Authors@R: c(person("Mátyás", "Mészáros", email = "matyas.meszaros@ec.europa.eu", role = c("aut", "cre")), person("Matteo", "Salvati", email = "salvati.matteo@hotmail.fr", role = "aut"))
Description: Three methods are implemented in R to facilitate the aggregations of flags in official statistics. From the underlying flags the highest in the hierarchy, the most frequent, or with the highest total weight is propagated to the flag(s) for EU or other aggregates. Below there are some reference documents for the topic: <https://sdmx.org/wp-content/uploads/CL_OBS_STATUS_v2_1.docx>, <https://sdmx.org/wp-content/uploads/CL_CONF_STATUS_1_2_2018.docx>, <http://ec.europa.eu/eurostat/data/database/information>, <http://www.oecd.org/sdd/33869551.pdf>, <https://sdmx.org/wp-content/uploads/CL_OBS_STATUS_implementation_20-10-2014.pdf>.
License: EUPL-1.1
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: tidyr, eurostat, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-02 08:47:10 UTC; meszama
Author: Mátyás Mészáros [aut, cre], Matteo Salvati [aut]
Maintainer: Mátyás Mészáros <matyas.meszaros@ec.europa.eu>
Repository: CRAN
Date/Publication: 2019-04-04 16:00:02 UTC

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New package CRFCSD with initial version 1.0
Package: CRFCSD
Type: Package
Title: Mixture Cure Generalized Odds Ratio Frailty Models for Clustered Current Status Data
Version: 1.0
Date: 2019-03-24
Author: Tong Wang, Kejun He, Wei Ma, Dipankar Bandyopadhyay, Samiran Sinha
Maintainer: Tong Wang<tong@stat.tamu.edu>
Description: A methodology to estimate the parameters for the cure rate frailty models with clustered current status data.
License: GPL-2
Encoding: UTF-8
Imports: Rcpp (>= 0.12.18), numDeriv, splines2, orthopolynom
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-04-01 19:53:05 UTC; tong
Repository: CRAN
Date/Publication: 2019-04-04 15:40:14 UTC

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New package chartql with initial version 0.1.0
Package: chartql
Type: Package
Title: Simplified Language for Plots and Charts
Version: 0.1.0
Imports: ggplot2 (>= 2.1.0), stringr, stats
Maintainer: Rohail Syed <rohailsyed@gmail.com>
Authors@R: person("Rohail", "Syed", email = "rohailsyed@gmail.com", role = c("aut", "cre"))
Description: Provides a very simple syntax for the user to generate custom plot(s) without having to remember complicated 'ggplot2' syntax. The 'chartql' package uses 'ggplot2' and manages all the syntax complexities internally. As an example, to generate a bar chart of company sales faceted by product category further faceted by season of the year, we simply write: "CHART bar X category, season Y sales".
License: GPL-3
Encoding: UTF-8
URL: https://github.com/rmsyed/chartql
LazyData: true
NeedsCompilation: no
Packaged: 2019-04-01 18:46:44 UTC; rohailsyed
Author: Rohail Syed [aut, cre]
Repository: CRAN
Date/Publication: 2019-04-04 15:40:03 UTC

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New package CeRNASeek with initial version 1.0
Package: CeRNASeek
Type: Package
Title: Identification and Analysis of ceRNA Regulation
Version: 1.0
Date: 2019-03-28
Author: Mengying Zhang,Yongsheng Li,Juan Xu*,Xia Li*
Maintainer: Mengying Zhang <zhangmengying@hrbmu.edu.cn>
Description: Provides several functions to identify and analyse miRNA sponge, including popular methods for identifying miRNA sponge interactions, two types of global ceRNA regulation prediction methods and three types of context-specific prediction methods( Li Y et al.(2017) <doi:10.1093/bib/bbx137>), which are based on miRNA-messenger RNA regulation alone, or by integrating heterogeneous data, respectively. In addition, this package provides several network analysis modules for viewing the constructed ceRNA-ceRNA network and analysis of the topological features.
License: GPL-3
Encoding: UTF-8
LazyData: true
biocViews: competing endogenous RNA (ceRNA), GeneExpression,triplet,function,Software
Depends: R (>= 3.1.0)
Imports: gtools ,igraph
Packaged: 2019-04-02 00:49:23 UTC; dell
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2019-04-04 15:50:07 UTC

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New package armspp with initial version 0.0.1
Package: armspp
Title: Adaptive Rejection Metropolis Sampling (ARMS) via 'Rcpp'
Version: 0.0.1
Authors@R: person("Michael", "Bertolacci", email = "m.bertolacci@gmail.com", role = c("aut", "cre"))
Description: An efficient 'Rcpp' implementation of the Adaptive Rejection Metropolis Sampling (ARMS) algorithm proposed by Gilks, W. R., Best, N. G. and Tan, K. K. C. (1995) <doi:10.2307/2986138>. This allows for sampling from a univariate target probability distribution specified by its (potentially unnormalised) log density.
Depends: R (>= 3.2.3)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, progress
Imports: Rcpp, progress
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, covr, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-04-01 08:09:23 UTC; mgnb
Author: Michael Bertolacci [aut, cre]
Maintainer: Michael Bertolacci <m.bertolacci@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-04 15:40:10 UTC

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New package armada with initial version 0.1.0
Package: armada
Type: Package
Title: A Statistical Methodology to Select Covariates in High-Dimensional Data under Dependence
Version: 0.1.0
Authors@R: c(person("Aurelie", "Gueudin", email = "aurelie.gueudin@univ-lorraine.fr", role = c("aut", "cre")), person("Anne", "Gegout-Petit", email = "anne.gegout-petit@univ-lorraine.fr", role = c("aut")))
Description: Two steps variable selection procedure in a context of high-dimensional dependent data but few observations. First step is dedicated to eliminate dependence between variables (clustering of variables, followed by factor analysis inside each cluster). Second step is a variable selection using by aggregation of adapted methods. Bastien B., Chakir H., Gegout-Petit A., Muller-Gueudin A., Shi Y. A statistical methodology to select covariates in high-dimensional data under dependence. Application to the classification of genetic profiles associated with outcome of a non-small-cell lung cancer treatment. 2018. <https://hal.archives-ouvertes.fr/hal-01939694>.
License: GPL-3
LazyData: true
RoxygenNote: 6.1.1
Imports: stats, mvtnorm, ClustOfVar, FAMT, graphics, VSURF, glmnet, anapuce, qvalue, parallel, doParallel, impute, ComplexHeatmap, circlize
NeedsCompilation: no
Packaged: 2019-04-04 13:14:39 UTC; muller16
Author: Aurelie Gueudin [aut, cre], Anne Gegout-Petit [aut]
Maintainer: Aurelie Gueudin <aurelie.gueudin@univ-lorraine.fr>
Repository: CRAN
Date/Publication: 2019-04-04 16:00:06 UTC

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Package vardpoor updated to version 0.15.0 with previous version 0.14.0 dated 2019-02-14

Title: Variance Estimation for Sample Surveys by the Ultimate Cluster Method
Description: Generation of domain variables, linearization of several nonlinear population statistics (the ratio of two totals, weighted income percentile, relative median income ratio, at-risk-of-poverty rate, at-risk-of-poverty threshold, Gini coefficient, gender pay gap, the aggregate replacement ratio, the relative median income ratio, median income below at-risk-of-poverty gap, income quintile share ratio, relative median at-risk-of-poverty gap), computation of regression residuals in case of weight calibration, variance estimation of sample surveys by the ultimate cluster method (Hansen, Hurwitz and Madow,Theory, vol. I: Methods and Applications; vol. II: Theory. 1953, New York: John Wiley and Sons), variance estimation for longitudinal, cross-sectional measures and measures of change for single and multistage stage cluster sampling designs (Berger, Y. G., 2015, <doi:10.1111/rssa.12116>). Several other precision measures are derived - standard error, the coefficient of variation, the margin of error, confidence interval, design effect.
Author: Juris Breidaks [aut, cre], Martins Liberts [aut], Santa Ivanova [aut]
Maintainer: Juris Breidaks <Juris.Breidaks@csb.gov.lv>

Diff between vardpoor versions 0.14.0 dated 2019-02-14 and 0.15.0 dated 2019-04-04

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Package foieGras updated to version 0.2.1 with previous version 0.2.0 dated 2019-04-02

Title: Fit Continuous-Time State-Space Models for Filtering Argos Satellite (and Other) Telemetry Data
Description: Fits continuous-time random walk and correlated random walk state-space models to filter Argos satellite location data. Template Model Builder ('TMB') is used for fast estimation. The Argos data can be: (older) least squares-based locations; (newer) Kalman filter-based locations with error ellipse information; or a mixture of both. Separate measurement models are used for these two data types. The models estimate two sets of location states corresponding to: 1) each observation, which are (usually) irregularly timed; and 2) user-specified time intervals (regular or irregular). Jonsen I, McMahon CR, Patterson TA, Auger-Methe M, Harcourt R, Hindell MA, Bestley S (2019) Movement responses to environment: fast inference of variation among southern elephant seals with a mixed effects model. Ecology 100:e02566 <doi:10.1002/ecy.2566>.
Author: Ian Jonsen [aut, cre], Toby Patterson [aut, ctb]
Maintainer: Ian Jonsen <ian.jonsen@mq.edu.au>

Diff between foieGras versions 0.2.0 dated 2019-04-02 and 0.2.1 dated 2019-04-04

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Package CoxPhLb updated to version 1.2.0 with previous version 1.0.0 dated 2018-03-14

Title: Analyzing Right-Censored Length-Biased Data
Description: Performs analysis of right-censored length-biased data using Cox model. It contains model fitting and checking, and the stationarity assumption test. The model fitting and checking methods are described in Qin and Shen (2010) <doi:10.1111/j.1541-0420.2009.01287.x> and Lee, Ning, and Shen (2018) <doi:10.1007/s10985-018-9422-y>.
Author: Lee, C.H., Liu, D.D., Ning, J., Zhou, H., and Shen, Y.
Maintainer: Chi Hyun Lee <chihyunlee@umass.edu>

Diff between CoxPhLb versions 1.0.0 dated 2018-03-14 and 1.2.0 dated 2019-04-04

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Package BioMedR updated to version 1.1.2 with previous version 1.1.1 dated 2019-01-15

Title: Generating Various Molecular Representations for Chemicals, Proteins, DNAs, RNAs and Their Interactions
Description: Calculating 293 chemical descriptors and 14 kinds of chemical fingerprints, 9920 protein descriptors based on protein sequences, more than 6000 DNA/RNA descriptors from nucleotide sequences, and six types of interaction descriptors using three different combining strategies.
Author: Min-feng Zhu <wind2zhu@163.com>, Jie Dong <biomed@csu.edu.cn>, Dong-sheng Cao <oriental-cds@163.com>
Maintainer: Min-feng Zhu <wind2zhu@163.com>

Diff between BioMedR versions 1.1.1 dated 2019-01-15 and 1.1.2 dated 2019-04-04

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Package TSEtools updated to version 0.1.3 with previous version 0.1.2 dated 2019-01-25

Title: Download and Manage Data from Tehran Stock Exchange
Description: Tools for downloading and organizing data from Tehran Stock Exchange (TSE) <http://new.tse.ir/en/>. It also performs some descriptive data analysis for assets.
Author: Ali Saeb
Maintainer: Ali Saeb <ali.saeb@gmail.com>

Diff between TSEtools versions 0.1.2 dated 2019-01-25 and 0.1.3 dated 2019-04-04

 DESCRIPTION |    6 +++---
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 4 files changed, 23 insertions(+), 15 deletions(-)

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Package tidyLPA updated to version 1.0.2 with previous version 1.0.0 dated 2019-03-21

Title: Easily Carry Out Latent Profile Analysis (LPA) Using Open-Source or Commercial Software
Description: An interface to the 'mclust' package to easily carry out latent profile analysis ("LPA"). Provides functionality to estimate commonly-specified models. Follows a tidy approach, in that output is in the form of a data frame that can subsequently be computed on. Also has functions to interface to the commercial 'MPlus' software via the 'MplusAutomation' package.
Author: Joshua M Rosenberg [aut, cre], Caspar van Lissa [aut], Jennifer A Schmidt [ctb], Patrick N Beymer [ctb], Daniel Anderson [ctb], Matthew J. Schell [ctb]
Maintainer: Joshua M Rosenberg <jmichaelrosenberg@gmail.com>

Diff between tidyLPA versions 1.0.0 dated 2019-03-21 and 1.0.2 dated 2019-04-04

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New package SparkR with initial version 2.4.1
Package: SparkR
Type: Package
Version: 2.4.1
Title: R Front End for 'Apache Spark'
Description: Provides an R Front end for 'Apache Spark' <https://spark.apache.org>.
Authors@R: c(person("Shivaram", "Venkataraman", role = c("aut", "cre"), email = "shivaram@cs.berkeley.edu"), person("Xiangrui", "Meng", role = "aut", email = "meng@databricks.com"), person("Felix", "Cheung", role = "aut", email = "felixcheung@apache.org"), person(family = "The Apache Software Foundation", role = c("aut", "cph")))
License: Apache License (== 2.0)
URL: https://www.apache.org/ https://spark.apache.org/
BugReports: https://spark.apache.org/contributing.html
SystemRequirements: Java (== 8)
Depends: R (>= 3.0), methods
Suggests: knitr, rmarkdown, testthat, e1071, survival
Collate: 'schema.R' 'generics.R' 'jobj.R' 'column.R' 'group.R' 'RDD.R' 'pairRDD.R' 'DataFrame.R' 'SQLContext.R' 'WindowSpec.R' 'backend.R' 'broadcast.R' 'catalog.R' 'client.R' 'context.R' 'deserialize.R' 'functions.R' 'install.R' 'jvm.R' 'mllib_classification.R' 'mllib_clustering.R' 'mllib_fpm.R' 'mllib_recommendation.R' 'mllib_regression.R' 'mllib_stat.R' 'mllib_tree.R' 'mllib_utils.R' 'serialize.R' 'sparkR.R' 'stats.R' 'streaming.R' 'types.R' 'utils.R' 'window.R'
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-04 12:39:14 UTC; ligges
Author: Shivaram Venkataraman [aut, cre], Xiangrui Meng [aut], Felix Cheung [aut], The Apache Software Foundation [aut, cph]
Maintainer: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Repository: CRAN
Date/Publication: 2019-04-04 12:50:05 UTC

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New package RBesT with initial version 1.3-8
Package: RBesT
Type: Package
Title: R Bayesian Evidence Synthesis Tools
Description: Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases). Please refer to Neuenschwander et al. (2010) <doi:10.1177/1740774509356002> and Schmidli et al. (2014) <doi:10.1111/biom.12242> for details on the methodology.
Version: 1.3-8
Date: 2019-04-03
Authors@R: c(person("Novartis", "Pharma AG", role = "cph") ,person("Sebastian", "Weber", email="sebastian.weber@novartis.com", role=c("aut", "cre")) ,person("Beat", "Neuenschwander", email="beat.neuenschwander@novartis.com", role="ctb") ,person("Heinz", "Schmidli", email="heinz.schmidli@novartis.com", role="ctb") ,person("Baldur", "Magnusson", email="baldur.magnusson@novartis.com", role="ctb") ,person("Yue", "Li", email="yue-1.li@novartis.com", role="ctb") ,person("Satrajit", "Roychoudhury", email="satrajit.roychoudhury@novartis.com", role="ctb") ,person("Trustees of", "Columbia University", role="cph", comment="src/init.cpp, tools/make_cc.R, R/stanmodels.R, src/Makevars, src/Makevars.win") )
Depends: R (>= 3.4.0), Rcpp (>= 0.12.0), methods
Imports: assertthat, mvtnorm, Formula, checkmate, rstan (>= 2.18.1), bayesplot (>= 1.4.0), ggplot2, dplyr, stats, utils
LinkingTo: StanHeaders (>= 2.18.0), rstan (>= 2.18.1), BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0)
License: GPL (>= 3) | file LICENSE
LazyData: true
NeedsCompilation: yes
Suggests: rmarkdown, knitr, testthat (>= 2.0.0), foreach, tidyverse, purrr, rstanarm (>= 2.17.2), scales, tools, broom, tidyr
VignetteBuilder: knitr
SystemRequirements: GNU make, pandoc (>= 1.12.3), pandoc-citeproc
Encoding: UTF-8
RoxygenNote: 6.1.1
Packaged: 2019-04-04 07:48:14 UTC;
Author: Novartis Pharma AG [cph], Sebastian Weber [aut, cre], Beat Neuenschwander [ctb], Heinz Schmidli [ctb], Baldur Magnusson [ctb], Yue Li [ctb], Satrajit Roychoudhury [ctb], Trustees of Columbia University [cph] (src/init.cpp, tools/make_cc.R, R/stanmodels.R, src/Makevars, src/Makevars.win)
Maintainer: Sebastian Weber <sebastian.weber@novartis.com>
Repository: CRAN
Date/Publication: 2019-04-04 12:10:10 UTC

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New package muRty with initial version 0.1.2
Package: muRty
Type: Package
Title: Murty's Algorithm for k-Best Assignments
Version: 0.1.2
Author: Aljaz Jelenko <aljaz.jelenko@amis.net>
Maintainer: Aljaz Jelenko <aljaz.jelenko@amis.net>
BugReports: https://github.com/arg0naut91/muRty/issues
Description: Calculates k-best solutions and costs for an assignment problem following the method outlined in Murty (1968) <doi:10.1287/opre.16.3.682>.
URL: https://github.com/arg0naut91/muRty
License: MIT + file LICENSE
Depends: R (>= 3.1.0)
Imports: lpSolve
Encoding: UTF-8
LazyData: true
Suggests: testthat
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-03 08:49:59 UTC; Aljaz
Repository: CRAN
Date/Publication: 2019-04-04 12:50:03 UTC

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New package iBreakDown with initial version 0.9.5
Package: iBreakDown
Title: Model Agnostic Instance Level Variable Attributions
Version: 0.9.5
Authors@R: c(person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut", "cre")), person("Alicja", "Gosiewska", email = "alicjagosiewska@gmail.com", role = c("aut")), person("Dariusz", "Komosinski", role = c("ctb")))
Description: Model agnostic tool for decomposition of predictions from black boxes. Supports additive attributions and attributions with interactions. The Break Down Table shows contributions of every variable to a final prediction. The Break Down Plot presents variable contributions in a concise graphical way. This package works for classification and regression models. It is an extension of the 'breakDown' package (Staniak and Biecek 2018) <doi:10.32614/RJ-2018-072>, with new and faster strategies for orderings. It supports interactions in explanations and has interactive visuals (implemented with 'D3.js' library). The methodology behind is described in the 'iBreakDown' article (Gosiewska and Biecek 2019) <arXiv:1903.11420> This package is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.
Depends: R (>= 3.0)
Date: 2019-04-01
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: ggplot2, DALEX
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, caret, randomForest, e1071, xgboost, ranger, nnet, testthat, r2d3
VignetteBuilder: knitr
URL: https://ModelOriented.github.io/iBreakDown/
BugReports: https://github.com/ModelOriented/iBreakDown/issues
NeedsCompilation: no
Packaged: 2019-04-01 20:19:10 UTC; pbiecek
Author: Przemyslaw Biecek [aut, cre], Alicja Gosiewska [aut], Dariusz Komosinski [ctb]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-04 12:20:03 UTC

More information about iBreakDown at CRAN
Permanent link

New package glmdisc with initial version 0.1
Package: glmdisc
Type: Package
Title: Discretization and Grouping for Logistic Regression
Version: 0.1
Date: 2019-04-01
Authors@R: c(person("Adrien", "Ehrhardt", email = "adrien.ehrhardt@inria.fr", role = c("aut", "cre")), person("Vincent", "Vandewalle", email = "vincent.vandewalle@inria.fr", role = c("aut")), person("Christophe", "Biernacki", email = "christophe.biernacki@inria.fr", role = c("ctb")), person("Philippe", "Heinrich", email = "philippe.heinrich@univ-lille1.fr", role = c("ctb")))
Maintainer: Adrien Ehrhardt <adrien.ehrhardt@inria.fr>
Description: A Stochastic-Expectation-Maximization (SEM) algorithm (Celeux et al. (1995) <https://hal.inria.fr/inria-00074164>) associated with a Gibbs sampler which purpose is to learn a constrained representation for logistic regression that is called quantization (Ehrhardt et al. (2019) <arXiv:1903.08920>). Continuous features are discretized and categorical features' values are grouped to produce a better logistic regression model. Pairwise interactions between quantized features are dynamically added to the model through a Metropolis-Hastings algorithm (Hastings, W. K. (1970) <doi:10.1093/biomet/57.1.97>).
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: caret (>= 6.0-82), gam, nnet, RcppNumerical, methods, MASS, graphics, Rcpp (>= 0.12.13)
LinkingTo: Rcpp, RcppEigen, RcppNumerical
URL: https://adimajo.github.io
BugReports: https://github.com/adimajo/glmdisc/issues
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Collate: 'RcppExports.R' 'allClasses.R' 'cut.dataset.R' 'discretize.link.R' 'generic_cutpoints.R' 'generic_discretize.R' 'glmdisc.R' 'method_cutpoints.R' 'method_discretize.R' 'method_plot.R' 'method_predict.R' 'methods_disc.R' 'normalizedGini.R' 'semDiscretization.R'
NeedsCompilation: yes
Packaged: 2019-04-01 20:18:50 UTC; adrien
Author: Adrien Ehrhardt [aut, cre], Vincent Vandewalle [aut], Christophe Biernacki [ctb], Philippe Heinrich [ctb]
Repository: CRAN
Date/Publication: 2019-04-04 12:10:03 UTC

More information about glmdisc at CRAN
Permanent link

Package DSAIRM updated to version 0.8.0 with previous version 0.5.5 dated 2019-02-11

Title: Dynamical Systems Approach to Immune Response Modeling
Description: A collection of 'shiny' apps that allow for the simulation and exploration of various within-host immune response scenarios. The purpose of the package is to help individuals learn about within-host infection and immune response modeling from a dynamical systems perspective. All apps include explanations of the underlying models and instructions on what to do with the models. The development of this package was partially supported by NIH grant U19AI117891.
Author: Andreas Handel [aut, cre] (<https://orcid.org/0000-0002-4622-1146>), Yang Ge [ctb], Spencer Hall [ctb], Sina Solaimanpour [ctb], Henok Woldu [ctb]
Maintainer: Andreas Handel <ahandel@uga.edu>

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Package calcWOI updated to version 1.0.2 with previous version 1.0.1 dated 2019-04-02

Title: Calculates the Wavelet-Based Organization Index
Description: Calculates the wavelet-based organization index following Brune et al (2018) (<doi:10.1002/qj.3409>), the modified wavelet-based organization index and the local wavelet-based organization index of an arbitrary 2D array using Wavelet Transforms of the LS2W package by Eckley et al (2010) (<doi:10.1111/j.1467-9876.2009.00721.x>) and Eckley and Nason (2011) (<doi:10.18637/jss.v043.i03>).
Author: Sebastian Brune, Sebastian Buschow, Florian Kapp, Petra Friederichs
Maintainer: Sebastian Brune <sbrune@uni-bonn.de>

Diff between calcWOI versions 1.0.1 dated 2019-04-02 and 1.0.2 dated 2019-04-04

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More information about calcWOI at CRAN
Permanent link

New package fhidata with initial version 2019.4.2
Package: fhidata
Title: Structural Data for Norway
Version: 2019.4.2
Authors@R: person("Richard", "White", email = "w@rwhite.no", role = c("aut", "cre"))
Description: Provides structural data for Norway. Datasets relating to maps, population in municipalities, municipality/county matching, and how different municipalities have merged/redistricted over time from 2006 to 2019.
Depends: R (>= 3.3.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: data.table
Suggests: testthat, knitr, rmarkdown, geojsonio, broom, rmapshaper, rgeos, mapproj, ggplot2, stringr, glue, lubridate, readxl, zoo, crayon, fs, utils
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-02 14:39:19 UTC; rstudio
Author: Richard White [aut, cre]
Maintainer: Richard White <w@rwhite.no>
Repository: CRAN
Date/Publication: 2019-04-04 10:10:03 UTC

More information about fhidata at CRAN
Permanent link

Package PWFSLSmoke updated to version 1.2.2 with previous version 1.1.3 dated 2018-10-05

Title: Utilities for Working with Air Quality Monitoring Data
Description: Utilities for working with air quality monitoring data with a focus on small particulates (PM2.5) generated by wildfire smoke. Functions are provided for downloading available data from the United States 'EPA' <https://www.epa.gov/outdoor-air-quality-data> and it's 'AirNow' air quality site <https://www.airnow.gov>. Additional sources of PM2.5 data made accessible by the package include: 'AIRSIS' (password protected) <https://www.oceaneering.com/data-management/> and 'WRCC' <https://wrcc.dri.edu/cgi-bin/smoke.pl>. Data compilations are provided by 'PWFSL' <https://www.fs.fed.us/pnw/pwfsl/>.
Author: Jonathan Callahan [aut, cre], Rohan Aras [aut], Zach Dingels [aut], Jon Hagg [aut], Jimin Kim [aut], Hans Martin [aut], Helen Miller [aut], Spencer Pease [aut], Rex Thompson [aut], Alice Yang [aut]
Maintainer: Jonathan Callahan <jonathan.s.callahan@gmail.com>

Diff between PWFSLSmoke versions 1.1.3 dated 2018-10-05 and 1.2.2 dated 2019-04-04

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Package ProFit updated to version 1.2.7 with previous version 1.2.6 dated 2019-01-15

Title: Fit Projected 2D Profiles to Galaxy Images
Description: Get data / Define model / ??? / Profit! 'ProFit' is a Bayesian galaxy fitting tool that uses a fast 'C++' image generation library and a flexible interface to a large number of likelihood samplers.
Author: Aaron Robotham [aut, cre] (<https://orcid.org/0000-0003-0429-3579>), Dan Taranu [aut] (<https://orcid.org/0000-0001-6268-1882>), Rodrigo Tobar [aut] (<https://orcid.org/0000-0002-1052-0611>)
Maintainer: Aaron Robotham <aaron.robotham@uwa.edu.au>

Diff between ProFit versions 1.2.6 dated 2019-01-15 and 1.2.7 dated 2019-04-04

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New package hglm.data with initial version 1.0-1
Package: hglm.data
Type: Package
Title: Data for the 'hglm' Package
Version: 1.0-1
Date: 2019-03-03
Author: Xia Shen, Moudud Alam, Lars Ronnegard
Maintainer: Xia Shen <xia.shen@ki.se>
Description: This data-only package was created for distributing data used in the examples of the 'hglm' package.
BugReports: https://r-forge.r-project.org/tracker/?group_id=558
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 3.0), utils, Matrix, MASS, sp
Packaged: 2019-04-03 12:09:31 UTC; xia
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2019-04-04 09:20:03 UTC

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New package ebirdst with initial version 0.1.0
Type: Package
Package: ebirdst
Title: Access and Analyze eBird Status and Trends Data
Version: 0.1.0
Authors@R: c(person(given = "Tom", family = "Auer", role = c("aut", "cre"), email = "mta45@cornell.edu", comment = c(ORCID = "0000-0001-8619-7147")), person(given = "Daniel", family = "Fink", role = "aut", email = "df36@cornell.edu", comment = c(ORCID = "0000-0002-8368-1248")), person(given = "Matthew", family = "Strimas-Mackey", role = "aut", email = "mes335@cornell.edu", comment = c(ORCID = "0000-0001-8929-7776")), person(given = "Cornell Lab of Ornithology", role = "cph"))
Description: Tools to download, map, plot and analyze eBird Status and Trends data (<https://ebird.org/science/status-and-trends>). eBird (<https://ebird.org>) is a global database of bird observations collected by citizen scientists. eBird Status and Trends uses these data to analyse continental bird abundances, range boundaries, habitats, and trends.
License: GPL-3
URL: https://github.com/CornellLabofOrnithology/ebirdst
BugReports: https://github.com/CornellLabofOrnithology/ebirdst/issues
Depends: R (>= 3.3.0)
Imports: car, data.table, dplyr (>= 0.7.0), fasterize, gbm (>= 2.1.5), ggplot2, grDevices, gridExtra, methods, mgcv, PresenceAbsence, rappdirs, raster, scales, sf, stats, stringr, tidyr, tools, utils, viridisLite, xml2, rgdal
Suggests: covr, fields, knitr, rmarkdown, rnaturalearth, smoothr, testthat, velox
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-02 20:43:32 UTC; mes335
Author: Tom Auer [aut, cre] (<https://orcid.org/0000-0001-8619-7147>), Daniel Fink [aut] (<https://orcid.org/0000-0002-8368-1248>), Matthew Strimas-Mackey [aut] (<https://orcid.org/0000-0001-8929-7776>), Cornell Lab of Ornithology [cph]
Maintainer: Tom Auer <mta45@cornell.edu>
Repository: CRAN
Date/Publication: 2019-04-04 09:50:03 UTC

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Package dsa updated to version 0.70.3 with previous version 0.61.7 dated 2019-01-28

Title: Seasonal Adjustment of Daily Time Series
Description: Seasonal- and calendar adjustment of time series with daily frequency using the DSA approach developed by Ollech, Daniel (2018): Seasonal adjustment of daily time series. Bundesbank Discussion Paper 41/2018.
Author: Daniel Ollech [aut, cre]
Maintainer: Daniel Ollech <daniel.ollech@bundesbank.de>

Diff between dsa versions 0.61.7 dated 2019-01-28 and 0.70.3 dated 2019-04-04

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Package barsurf updated to version 0.2.0 with previous version 0.1.0 dated 2018-10-26

Title: Bar, Surface and Other Plots
Description: Produces heat maps, contour plots, bar plots (in 3D) and surface plots (also, in 3D). Is designed for plotting functions of two variables, however, can plot relatively arbitrary matrices. Uses HCL color space, extensively. Also, supports triangular plots and nested matrices.
Author: Abby Spurdle
Maintainer: Abby Spurdle <spurdle.a@gmail.com>

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Package TreeBUGS updated to version 1.4.3 with previous version 1.4.1 dated 2018-12-18

Title: Hierarchical Multinomial Processing Tree Modeling
Description: User-friendly analysis of hierarchical multinomial processing tree (MPT) models that are often used in cognitive psychology. Implements the latent-trait MPT approach (Klauer, 2010) <DOI:10.1007/s11336-009-9141-0> and the beta-MPT approach (Smith & Batchelder, 2010) <DOI:10.1016/j.jmp.2009.06.007> to model heterogeneity of participants. MPT models are conveniently specified by an .eqn-file as used by other MPT software and data are provided by a .csv-file or directly in R. Models are either fitted by calling JAGS or by an MPT-tailored Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides tests of heterogeneity and MPT-tailored summaries and plotting functions. A detailed documentation is available in Heck, Arnold, & Arnold (2018) <DOI:10.3758/s13428-017-0869-7>.
Author: Daniel W. Heck [aut, cre], Nina R. Arnold [aut, dtc], Denis Arnold [aut], Alexander Ly [ctb], Marius Barth [ctb]
Maintainer: Daniel W. Heck <heck@uni-mannheim.de>

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Package SADISA updated to version 1.1 with previous version 1.0 dated 2017-04-21

Title: Species Abundance Distributions with Independent-Species Assumption
Description: Computes the probability of a set of species abundances of a single or multiple samples of individuals with one or more guilds under a mainland-island model. One must specify the mainland (metacommunity) model and the island (local) community model. It assumes that species fluctuate independently. The package also contains functions to simulate under this model. See Haegeman, B. & R.S. Etienne (2017). A general sampling formula for community structure data. Methods in Ecology & Evolution 8: 1506-1519 <doi:10.1111/2041-210X.12807>.
Author: Rampal S. Etienne & Bart Haegeman
Maintainer: Rampal S. Etienne <r.s.etienne@rug.nl>

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Package unifDAG updated to version 1.0.2 with previous version 1.0.1 dated 2017-09-12

Title: Uniform Sampling of Directed Acyclic Graphs
Description: Uniform sampling of Directed Acyclic Graphs (DAG) using exact enumeration by relating each DAG to a sequence of outpoints (nodes with no incoming edges) and then to a composition of integers as suggested by Kuipers, J. and Moffa, G. (2015) <doi:10.1007/s11222-013-9428-y>.
Author: Markus Kalisch [aut, cre], Manuel Schuerch [ctb]
Maintainer: Markus Kalisch <kalisch@stat.math.ethz.ch>

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Package rioja (with last version 0.9-15.2) was removed from CRAN

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

2019-03-08 0.9-15.2
2018-01-04 0.9-15.1
2017-06-18 0.9-15
2017-06-14 0.9-14
2016-07-13 0.9-9
2016-05-24 0.9-7
2016-04-04 0.9-6
2015-05-06 0.9-5
2014-12-17 0.9-3
2014-06-30 0.8-7
2013-11-18 0.8-5
2013-07-09 0.8-4
2013-06-15 0.8-3
2012-01-05 0.7-3
2011-12-25 0.7-2
2009-11-13 0.5-6
2009-10-28 0.5-5
2009-10-27 0.5-4
2009-08-13 0.5-3
2009-08-08 0.5-2

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Package wikisourcer updated to version 0.1.4 with previous version 0.1.3 dated 2019-03-17

Title: Download Public Domain Works from Wikisource
Description: Download public domain works from Wikisource <https://wikisource.org/>, a free library from the Wikimedia Foundation project.
Author: Félix Luginbuhl [aut, cre]
Maintainer: Félix Luginbuhl <felix.luginbuhl@protonmail.ch>

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Package RSpectra updated to version 0.14-0 with previous version 0.13-1 dated 2018-05-22

Title: Solvers for Large-Scale Eigenvalue and SVD Problems
Description: R interface to the 'Spectra' library <https://spectralib.org/> for large-scale eigenvalue and SVD problems. It is typically used to compute a few eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues, which is usually more efficient than eigen() if k << n. This package provides the 'eigs()' function that does the similar job as in 'Matlab', 'Octave', 'Python SciPy' and 'Julia'. It also provides the 'svds()' function to calculate the largest k singular values and corresponding singular vectors of a real matrix. The matrix to be computed on can be dense, sparse, or in the form of an operator defined by the user.
Author: Yixuan Qiu [aut, cre], Jiali Mei [aut] (Function interface of matrix operation), Gael Guennebaud [ctb] (Eigenvalue solvers from the 'Eigen' library), Jitse Niesen [ctb] (Eigenvalue solvers from the 'Eigen' library)
Maintainer: Yixuan Qiu <yixuan.qiu@cos.name>

Diff between RSpectra versions 0.13-1 dated 2018-05-22 and 0.14-0 dated 2019-04-04

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