Thu, 20 Sep 2018

Package unfoldr updated to version 0.6.9 with previous version 0.6.8.1 dated 2018-09-01

Title: Stereological Unfolding for Spheroidal Particles
Description: Stereological unfolding of the joint size-shape-orientation distribution of spheroidal shaped particles.
Author: Markus Baaske [aut, cre], Felix Ballani [ctb]
Maintainer: Markus Baaske <markus.baaske@uni-jena.de>

Diff between unfoldr versions 0.6.8.1 dated 2018-09-01 and 0.6.9 dated 2018-09-20

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More information about unfoldr at CRAN
Permanent link

Package simLife updated to version 0.5 with previous version 0.3 dated 2016-10-07

Title: Simulation of Fatigue Lifetimes
Description: Provides methods for simulation and analysis of a very general fatigue lifetime model for (metal matrix) composite materials.
Author: Markus Baaske [aut, cre], Felix Ballani [aut, ctb]
Maintainer: Markus Baaske <markus.baaske@uni-jena.de>

Diff between simLife versions 0.3 dated 2016-10-07 and 0.5 dated 2018-09-20

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More information about simLife at CRAN
Permanent link

Package ROptSpace updated to version 0.2.0 with previous version 0.1.2 dated 2017-12-04

Title: Matrix Reconstruction from a Few Entries
Description: Matrix reconstruction, also known as matrix completion, is the task of inferring missing entries of a partially observed matrix. This package provides a method called OptSpace, which was proposed by Keshavan, R.H., Oh, S., and Montanari, A. (2009) <doi:10.1109/ISIT.2009.5205567> for a case under low-rank assumption.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>

Diff between ROptSpace versions 0.1.2 dated 2017-12-04 and 0.2.0 dated 2018-09-20

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Package shinydashboardPlus updated to version 0.6.0 with previous version 0.5.0 dated 2018-07-05

Title: Add some 'AdminLTE2' Components to 'shinydashboard'
Description: Extend 'shinydashboard' with 'AdminLTE2' components. 'AdminLTE2' is a free 'Bootstrap 3' dashboard template available at <https://adminlte.io>. Customize boxes, add timelines and a lot more.
Author: David Granjon [aut, cre], Almasaeed Studio [ctb, cph] (AdminLTE2 theme for Bootstrap 3), Winston Chang [ctb, cph] (Functions from shinydashboard), Petr Tichy [ctb, cph] (CSS preloader), Victor Perrier [ctb] (improved the shinydashboardPlusGallery)
Maintainer: David Granjon <dgranjon@ymail.com>

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More information about shinydashboardPlus at CRAN
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Package rquery updated to version 1.1.0 with previous version 1.0.0 dated 2018-09-10

Title: Relational Query Generator for Data Manipulation at Scale
Description: A piped query generator based on Edgar F. Codd's relational algebra, and on production experience using 'SQL' and 'dplyr' at big data scale. The design represents an attempt to make 'SQL' more teachable by denoting composition by a sequential pipeline notation instead of nested queries or functions. The implementation delivers reliable high performance data processing on large data systems such as 'Spark', databases, and 'data.table'. Package features include: data processing trees or pipelines as observable objects (able to report both columns produced and columns used), optimized 'SQL' generation as an explicit user visible modeling step, explicit query reasoning and checking.
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between rquery versions 1.0.0 dated 2018-09-10 and 1.1.0 dated 2018-09-20

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Package robustrank updated to version 2018.10-1 with previous version 2017.12-2 dated 2017-12-03

Title: Robust Rank-Based Tests
Description: Implements two-sample tests for paired data with missing values (Fong, Huang, Lemos and McElrath 2018, Biostatics, <doi:10.1093/biostatistics/kxx039>) and modified Wilcoxon-Mann-Whitney two sample location test, also known as the Fligner-Policello test.
Author: Youyi Fong <youyifong@gmail.com>
Maintainer: Youyi Fong <youyifong@gmail.com>

Diff between robustrank versions 2017.12-2 dated 2017-12-03 and 2018.10-1 dated 2018-09-20

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Package eurostat updated to version 3.2.9 with previous version 3.2.2 dated 2018-07-22

Title: Tools for Eurostat Open Data
Description: Tools to download data from the Eurostat database <http://ec.europa.eu/eurostat> together with search and manipulation utilities.
Author: Leo Lahti [aut, cre], Janne Huovari [aut], Markus Kainu [aut], Przemyslaw Biecek [aut], Joona Lehtomaki [ctb], Francois Briatte [ctb], Oliver Reiter [ctb]
Maintainer: Leo Lahti <leo.lahti@iki.fi>

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Package bs4Dash updated to version 0.2.0 with previous version 0.1.0 dated 2018-07-05

Title: A 'Bootstrap 4' Version of 'shinydashboard'
Description: Make 'Bootstrap 4' dashboards. Use the full power of 'AdminLTE3', a dashboard template built on top of 'Bootstrap 4' <https://github.com/almasaeed2010/AdminLTE/tree/v3-dev>.
Author: David Granjon [aut, cre], Almasaeed Studio [ctb, cph] (AdminLTE3 theme for Bootstrap 4), Winston Chang [ctb, cph] (Utils functions from shinydashboard), Thomas Park [ctb, cph] (Bootswatch Sketchy theme CSS)
Maintainer: David Granjon <dgranjon@ymail.com>

Diff between bs4Dash versions 0.1.0 dated 2018-07-05 and 0.2.0 dated 2018-09-20

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Package rqdatatable updated to version 1.1.1 with previous version 1.0.0 dated 2018-09-10

Title: 'rquery' for 'data.table'
Description: Implements the 'rquery' piped Codd-style query algebra using 'data.table'. This allows for a high-speed in memory implementation of Codd-style data manipulation tools.
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between rqdatatable versions 1.0.0 dated 2018-09-10 and 1.1.1 dated 2018-09-20

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New package metadynminer with initial version 0.1.2
Package: metadynminer
Type: Package
Title: Tools to Read, Analyze and Visualize Metadynamics HILLS Files from 'Plumed'
Version: 0.1.2
Date: 2018-08-24
Authors@R: person("Vojtech", "Spiwok", email = "spiwokv@vscht.cz", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8108-2033"))
Depends: R (>= 3.3.0)
LinkingTo: Rcpp
Description: Metadynamics is a state of the art biomolecular simulation technique. 'Plumed' Tribello, G.A. et al. (2014) <doi:10.1016/j.cpc.2013.09.018> program makes it possible to perform metadynamics using various simulation codes. The results of metadynamics done in 'Plumed' can be analyzed by 'metadynminer'. The package 'metadynminer' reads 1D and 2D metadynamics hills files from 'Plumed' package. It uses a fast algorithm by Hosek, P. and Spiwok, V. (2016) <doi:10.1016/j.cpc.2015.08.037> to calculate a free energy surface from hills. Minima can be located and plotted on the free energy surface. Transition states can be analyzed by Nudged Elastic Band method by Henkelman, G. and Jonsson, H. (2000) <doi:10.1063/1.1323224>. Free energy surfaces, minima and transition paths can be plotted to produce publication quality images.
LazyData: true
License: GPL-3
RoxygenNote: 6.1.0
Imports: Rcpp
URL: http://www.metadynamics.cz/metadynminer
NeedsCompilation: yes
Packaged: 2018-09-14 07:26:56 UTC; spiwokv
Author: Vojtech Spiwok [aut, cre] (<https://orcid.org/0000-0001-8108-2033>)
Maintainer: Vojtech Spiwok <spiwokv@vscht.cz>
Repository: CRAN
Date/Publication: 2018-09-20 18:20:03 UTC

More information about metadynminer at CRAN
Permanent link

Package shazam updated to version 0.1.10 with previous version 0.1.9 dated 2018-03-31

Title: Immunoglobulin Somatic Hypermutation Analysis
Description: Provides a computational framework for analyzing mutations in immunoglobulin (Ig) sequences. Includes methods for Bayesian estimation of antigen-driven selection pressure, mutational load quantification, building of somatic hypermutation (SHM) models, and model-dependent distance calculations. Also includes empirically derived models of SHM for both mice and humans. Citations: Gupta and Vander Heiden, et al (2015) <doi:10.1093/bioinformatics/btv359>, Yaari, et al (2012) <doi:10.1093/nar/gks457>, Yaari, et al (2013) <doi:10.3389/fimmu.2013.00358>, Cui, et al (2016) <doi:10.4049/jimmunol.1502263>.
Author: Mohamed Uduman [aut], Gur Yaari [aut], Namita Gupta [aut], Jason Vander Heiden [aut, cre], Ang Cui [ctb], Susanna Marquez [ctb], Julian Zhou [ctb], Nima Nouri [ctb], Steven Kleinstein [aut, cph]
Maintainer: Jason Vander Heiden <jason.vanderheiden@yale.edu>

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Package sentometrics updated to version 0.5.1 with previous version 0.5 dated 2018-09-18

Title: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
Description: Optimized prediction based on textual sentiment, accounting for the intrinsic challenge that sentiment can be computed and pooled across texts and time in various ways. See Ardia et al. (2017) <doi:10.2139/ssrn.3067734>.
Author: David Ardia [aut], Keven Bluteau [aut], Samuel Borms [aut, cre], Kris Boudt [aut]
Maintainer: Samuel Borms <samuel.borms@unine.ch>

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Package intsvy updated to version 2.2 with previous version 2.1 dated 2017-11-08

Title: International Assessment Data Manager
Description: Provides tools for importing, merging, and analysing data from international assessment studies (TIMSS, PIRLS, PISA. ICILS, and PIAAC).
Author: Daniel Caro <dcarov@gmail.com>, Przemyslaw Biecek <przemyslaw.biecek@gmail.com>
Maintainer: Daniel Caro <dcarov@gmail.com>

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Package gravity updated to version 0.8.5 with previous version 0.6 dated 2017-12-14

Title: Estimation Methods for Gravity Models
Description: A wrapper of different standard estimation methods for gravity models. This package provides estimation methods for log-log models and multiplicative models.
Author: Anna-Lena Woelwer [aut], Jan Pablo Burgard [aut], Joshua Kunst [aut], Mauricio Vargas [aut, cre]
Maintainer: Mauricio Vargas <mvargas@dcc.uchile.cl>

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Package dispRity updated to version 1.2 with previous version 1.0.3 dated 2018-03-22

Title: Measuring Disparity in R
Description: A modular package for measuring disparity from multidimensional matrices. Disparity can be calculated from any matrix defining a multidimensional space. The package provides a set of implemented metrics to measure properties of the space and allows users to provide and test their own metrics. The package also provides functions for looking at disparity in a serial way (e.g. disparity through time) or per groups as well as visualising the results. Finally, this package provides several basic statistical tests for disparity analysis.
Author: Thomas Guillerme [aut, cre, cph], Mark N Puttick [aut, cph]
Maintainer: Thomas Guillerme <guillert@tcd.ie>

Diff between dispRity versions 1.0.3 dated 2018-03-22 and 1.2 dated 2018-09-20

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New package DIconvex with initial version 1.0.0
Package: DIconvex
Type: Package
Title: Finding Patterns of Monotonicity and Convexity in Data
Version: 1.0.0
Author: Paul Schneider [aut, ths], Liudmila Karagyaur [aut]
Maintainer: Liudmila Karagyaur <liudmila.karagyaur@usi.ch>
Description: Given an initial set of points, this package minimizes the number of elements to discard from this set such that there exists at least one monotonic and convex mapping within pre-specified upper and lower bounds.
Depends: lpSolveAPI
License: GPL-2
NeedsCompilation: no
Packaged: 2018-09-14 14:17:08 UTC; paultschi
Repository: CRAN
Date/Publication: 2018-09-20 18:00:15 UTC

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Package DensParcorr updated to version 1.1 with previous version 1.0 dated 2016-04-09

Title: Dens-Based Method for Partial Correlation Estimation in Large Scale Brain Networks
Description: Provide a Dens-based method for estimating functional connection in large scale brain networks using partial correlation.
Author: Yikai Wang, Jian Kang, Phebe Brenne Kemmer and Ying Guo
Maintainer: Yikai Wang <johnzon.wyk@gmail.com>

Diff between DensParcorr versions 1.0 dated 2016-04-09 and 1.1 dated 2018-09-20

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New package CutpointsOEHR with initial version 0.1.0
Package: CutpointsOEHR
Type: Package
Title: Optimal Equal-HR Method to Find Two Cutpoints for U-Shaped Relationships in Cox Model
Version: 0.1.0
Author: Yimin Chen, Zhang Jinxin
Maintainer: Yimin Chen <chenyimin0226@126.com>
Description: Use optimal equal-HR method to determine two optimal cutpoints of a continuous predictor that has a U-shaped relationship with survival outcomes based on Cox regression model. The optimal equal-HR method estimates two optimal cut-points that have approximately the same log hazard value based on Cox regression model and divides individuals into different groups according to their HR values.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: survival
NeedsCompilation: no
RoxygenNote: 6.1.0.9000
Packaged: 2018-09-14 00:39:58 UTC; ad
Repository: CRAN
Date/Publication: 2018-09-20 18:00:19 UTC

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Package crypto updated to version 1.0.3 with previous version 1.0.2 dated 2018-05-30

Title: Cryptocurrency Market Data
Description: Retrieves crypto currency current and historical information as well as information on the exchanges they are listed on. For current and historical it will retrieve the daily open, high, low and close values for all crypto currencies. This retrieves the historical market data by web scraping tables provided by 'Cryptocurrency Market Capitalizations' <https://coinmarketcap.com>.
Author: Jesse Vent [aut, cre]
Maintainer: Jesse Vent <cryptopackage@icloud.com>

Diff between crypto versions 1.0.2 dated 2018-05-30 and 1.0.3 dated 2018-09-20

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New package broom.mixed with initial version 0.2.2
Package: broom.mixed
Type: Package
Title: Tidying Methods for Mixed Models
Version: 0.2.2
Authors@R: c( person("Ben", "Bolker", email = "bolker@mcmaster.ca", role = c("aut", "cre")), person("David", "Robinson", email = "admiral.david@gmail.com", role = "aut"), person("Dieter", "Menne", role = "ctb"), person("Jonah", "Gabry", role = "ctb"), person("Paul", "Buerkner", role = "ctb"), person("Christopher", "Hua", role = "ctb"), person("Will", "Petry", role = "ctb"), person("Josh", "Wiley", role = "ctb"), person("Patrick", "Kennedy", role = "ctb") )
Maintainer: Ben Bolker <bolker@mcmaster.ca>
Description: Convert fitted objects from various R mixed-model packages into tidy data frames along the lines of the 'broom' package. The package provides three S3 generics for each model: tidy(), which summarizes a model's statistical findings such as coefficients of a regression; augment(), which adds columns to the original data such as predictions, residuals and cluster assignments; and glance(), which provides a one-row summary of model-level statistics.
Depends: R (>= 3.5.0)
Imports: broom, dplyr, tidyr, plyr, purrr, tibble, reshape2, nlme, methods, stringr, coda, glmmTMB, TMB
Suggests: knitr, testthat, ggplot2, Matrix, MCMCglmm, lme4, rstan, rstanarm, brms, mgcv, gamlss, lmerTest, glmmADMB
URL: http://github.com/bbolker/broom.mixed
BugReports: http://github.com/bbolker/broom.mixed/issues
License: GPL-3
RoxygenNote: 6.1.0
Encoding: UTF-8
Additional_repositories: http://bbolker.github.io/drat
NeedsCompilation: no
Packaged: 2018-09-14 14:43:38 UTC; bolker
Author: Ben Bolker [aut, cre], David Robinson [aut], Dieter Menne [ctb], Jonah Gabry [ctb], Paul Buerkner [ctb], Christopher Hua [ctb], Will Petry [ctb], Josh Wiley [ctb], Patrick Kennedy [ctb]
Repository: CRAN
Date/Publication: 2018-09-20 18:00:10 UTC

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Package adpss updated to version 0.1.1 with previous version 0.1.0 dated 2018-07-18

Title: Design and Analysis of Locally or Globally Efficient Adaptive Designs
Description: Provides the functions for planning and conducting a clinical trial with adaptive sample size determination. Maximal statistical efficiency will be exploited even when dramatic or multiple adaptations are made. Such a trial consists of adaptive determination of sample size at an interim analysis and implementation of frequentist statistical test at the interim and final analysis with a prefixed significance level. The required assumptions for the stage-wise test statistics are independent and stationary increments and normality. Predetermination of adaptation rule is not required.
Author: Kosuke Kashiwabara [aut, cre]
Maintainer: Kosuke Kashiwabara <kashiwabara-tky@umin.ac.jp>

Diff between adpss versions 0.1.0 dated 2018-07-18 and 0.1.1 dated 2018-09-20

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Package quantregGrowth updated to version 0.4-3 with previous version 0.4-2 dated 2018-05-21

Title: Growth Charts via Regression Quantiles
Description: Fits non-crossing regression quantiles as a function of linear covariates and multiple smooth terms via B-splines with L1-norm difference penalties. Monotonicity constraints on the fitted curves are allowed. See Muggeo, Sciandra, Tomasello and Calvo (2013) <doi:10.1007/s10651-012-0232-1> and <doi:10.13140/RG.2.2.12924.85122> for some code example.
Author: Vito M. R. Muggeo [aut, cre] (<https://orcid.org/0000-0002-3386-4054>)
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>

Diff between quantregGrowth versions 0.4-2 dated 2018-05-21 and 0.4-3 dated 2018-09-20

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Package strex updated to version 0.1.1 with previous version 0.1.0 dated 2018-08-31

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>

Diff between strex versions 0.1.0 dated 2018-08-31 and 0.1.1 dated 2018-09-20

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Package soiltexture updated to version 1.5.1 with previous version 1.4.6 dated 2018-05-01

Title: Functions for Soil Texture Plot, Classification and Transformation
Description: "The Soil Texture Wizard" is a set of R functions designed to produce texture triangles (also called texture plots, texture diagrams, texture ternary plots), classify and transform soil textures data. These functions virtually allows to plot any soil texture triangle (classification) into any triangle geometry (isosceles, right-angled triangles, etc.). This set of function is expected to be useful to people using soil textures data from different soil texture classification or different particle size systems. Many (> 15) texture triangles from all around the world are predefined in the package. A simple text based graphical user interface is provided: soiltexture_gui().
Author: Julien Moeys [aut, cre], Wei Shangguan [ctb], Rainer Petzold [ctb], Budiman Minasny [ctb], Bogdan Rosca [ctb], Nic Jelinski [ctb], Wiktor Zelazny [ctb], Rodolfo Marcondes Silva Souza [ctb], Jose Lucas Safanelli [ctb], Alexandre ten Caten [ctb]
Maintainer: Julien Moeys <jules_m78-soiltexture@yahoo.fr>

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Package LPKsample updated to version 2.0 with previous version 1.0 dated 2017-11-20

Title: LP Nonparametric High Dimensional K-Sample Comparison
Description: LP nonparametric high-dimensional K-sample comparison method that includes (i) confirmatory test, (ii) exploratory analysis, and (iii) options to output a data-driven LP-transformed matrix for classification. The primary reference is Mukhopadhyay, S. and Wang, K. (2018, Technical Report).
Author: Subhadeep Mukhopadhyay, Kaijun Wang
Maintainer: Kaijun Wang <kaijun.wang@temple.edu>

Diff between LPKsample versions 1.0 dated 2017-11-20 and 2.0 dated 2018-09-20

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Package datasauRus updated to version 0.1.4 with previous version 0.1.2 dated 2017-05-08

Title: Datasets from the Datasaurus Dozen
Description: The Datasaurus Dozen is a set of datasets with the same summary statistics. They retain the same summary statistics despite having radically different distributions. The datasets represent a larger and quirkier object lesson that is typically taught via Anscombe's Quartet (available in the 'datasets' package). Anscombe's Quartet contains four very different distributions with the same summary statistics and as such highlights the value of visualisation in understanding data, over and above summary statistics. As well as being an engaging variant on the Quartet, the data is generated in a novel way. The simulated annealing process used to derive datasets from the original Datasaurus is detailed in "Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing" <doi:10.1145/3025453.3025912>.
Author: Steph Locke [cre, aut], Alberto Cairo [dtc], Justin Matejka [dtc], George Fitzmaurice [dtc], Lucy D'Agostino McGowan [aut], Richard Cotton [ctb], Locke Data [fnd]
Maintainer: Steph Locke <stephanie.g.locke@gmail.com>

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Package generalhoslem updated to version 1.3.3 with previous version 1.3.2 dated 2017-12-02

Title: Goodness of Fit Tests for Logistic Regression Models
Description: Functions to assess the goodness of fit of binary, multinomial and ordinal logistic models. Included are the Hosmer-Lemeshow tests (binary, multinomial and ordinal) and the Lipsitz and Pulkstenis-Robinson tests (ordinal).
Author: Matthew Jay [aut, cre]
Maintainer: Matthew Jay <matthew.jay.15@ucl.ac.uk>

Diff between generalhoslem versions 1.3.2 dated 2017-12-02 and 1.3.3 dated 2018-09-20

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Package TTR updated to version 0.23-4 with previous version 0.23-3 dated 2018-01-24

Title: Technical Trading Rules
Description: Functions and data to construct technical trading rules with R.
Author: Joshua Ulrich
Maintainer: Joshua Ulrich <josh.m.ulrich@gmail.com>

Diff between TTR versions 0.23-3 dated 2018-01-24 and 0.23-4 dated 2018-09-20

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Package lmomco updated to version 2.3.2 with previous version 2.3.1 dated 2018-03-08

Title: L-Moments, Censored L-Moments, Trimmed L-Moments, L-Comoments, and Many Distributions
Description: Extensive functions for L-moments (LMs) and probability-weighted moments (PWMs), parameter estimation for distributions, LM computation for distributions, and L-moment ratio diagrams. Maximum likelihood and maximum product of spacings estimation are also available. LMs for right-tail and left-tail censoring by known or unknown threshold and by indicator variable are available. Asymmetric (asy) trimmed LMs (TL-moments, TLMs) are supported. LMs of residual (resid) and reversed (rev) resid life are implemented along with 13 quantile function operators for reliability and survival analyses. Exact analytical bootstrap estimates of order statistics, LMs, and variances- covariances of LMs are provided. The Harri-Coble Tau34-squared Normality Test is available. Distribution support with "L" (LMs), "TL" (TLMs) and added (+) support for right-tail censoring (RC) encompasses: Asy Exponential (Exp) Power [L], Asy Triangular [L], Cauchy [TL], Eta-Mu [L], Exp. [L], Gamma [L], Generalized (Gen) Exp Poisson [L], Gen Extreme Value [L], Gen Lambda [L,TL], Gen Logistic [L), Gen Normal [L], Gen Pareto [L+RC, TL], Govindarajulu [L], Gumbel [L], Kappa [L], Kappa-Mu [L], Kumaraswamy [L], Laplace [L], Linear Mean Resid. Quantile Function [L], Normal [L], 3-p log-Normal [L], Pearson Type III [L], Rayleigh [L], Rev-Gumbel [L+RC], Rice/Rician [L], Slash [TL], 3-p Student t [L], Truncated Exponential [L], Wakeby [L], and Weibull [L]. Multivariate sample L-comoments (LCMs) are implemented to measure asymmetric associations.
Author: William Asquith
Maintainer: William Asquith <william.asquith@ttu.edu>

Diff between lmomco versions 2.3.1 dated 2018-03-08 and 2.3.2 dated 2018-09-20

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Package ggpol updated to version 0.0.4 with previous version 0.0.3 dated 2018-07-15

Title: Visualizing Social Science Data with 'ggplot2'
Description: A 'ggplot2' extension for implementing parliament charts and several other useful visualizations.
Author: Frederik Tiedemann [aut, cre]
Maintainer: Frederik Tiedemann <fj.tiedemann@googlemail.com>

Diff between ggpol versions 0.0.3 dated 2018-07-15 and 0.0.4 dated 2018-09-20

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Package vardpoor updated to version 0.12.0 with previous version 0.11.0 dated 2018-09-12

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 0.11.0 dated 2018-09-12 and 0.12.0 dated 2018-09-20

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Package rsnps updated to version 0.3.0 with previous version 0.2.0 dated 2016-11-20

Title: Get 'SNP' ('Single-Nucleotide' 'Polymorphism') Data on the Web
Description: A programmatic interface to various 'SNP' 'datasets' on the web: 'OpenSNP' (<https://opensnp.org>), and 'NBCIs' 'dbSNP' database (<https://www.ncbi.nlm.nih.gov/projects/SNP>). Functions are included for searching for 'NCBI'. For 'OpenSNP', functions are included for getting 'SNPs', and data for 'genotypes', 'phenotypes', annotations, and bulk downloads of data by user.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Kevin Ushey [aut], Hao Zhu [aut]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between rsnps versions 0.2.0 dated 2016-11-20 and 0.3.0 dated 2018-09-20

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Package phuse updated to version 0.1.6 with previous version 0.1.5 dated 2018-01-05

Title: Web Application Framework for 'PhUSE' Scripts
Description: Make it easy to review, download and execute scripts stored in Github 'phuse-scripts' repository <https://github.com/phuse-org/phuse-scripts>. Some examples included show the web application framework using the script metadata. The 'PhUSE' is Pharmaceutical Users Software Exchange <http://www.phuse.eu>.
Author: Hanming Tu [aut, cre]
Maintainer: Hanming Tu <hanming.tu@gmail.com>

Diff between phuse versions 0.1.5 dated 2018-01-05 and 0.1.6 dated 2018-09-20

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Wed, 19 Sep 2018

Package NetworkToolbox updated to version 1.2.1 with previous version 1.2.0 dated 2018-07-25

Title: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis
Description: Implements network analysis and graph theory measures used in neuroscience, cognitive science, and psychology. Methods include various filtering methods and approaches such as threshold, dependency (Kenett, Tumminello, Madi, Gur-Gershogoren, Mantegna, & Ben-Jacob, 2010 <doi:10.1371/journal.pone.0015032>), Information Filtering Networks (Barfuss, Massara, Di Matteo, & Aste, 2016 <doi:10.1103/PhysRevE.94.062306>), and Efficiency-Cost Optimization (Fallani, Latora, & Chavez, 2017 <doi:10.1371/journal.pcbi.1005305>). Brain methods include the recently developed Connectome Predictive Modeling (see references in package). Also implements several network measures including local network characteristics (e.g., centrality), community-level network characteristics (e.g., community centrality), global network characteristics (e.g., clustering coefficient), and various other measures associated with the reliability and reproducibility of network analysis.
Author: Alexander Christensen
Maintainer: Alexander Christensen <alexpaulchristensen@gmail.com>

Diff between NetworkToolbox versions 1.2.0 dated 2018-07-25 and 1.2.1 dated 2018-09-19

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Package Gmisc updated to version 1.6.4 with previous version 1.6.2 dated 2018-06-20

Title: Descriptive Statistics, Transition Plots, and More
Description: Tools for making the descriptive "Table 1" used in medical articles, a transition plot for showing changes between categories, flow charts by extending the grid package, a method for variable selection based on the SVD, Bézier lines with arrows complementing the ones in the 'grid' package, and more.
Author: Max Gordon <max@gforge.se>
Maintainer: Max Gordon <max@gforge.se>

Diff between Gmisc versions 1.6.2 dated 2018-06-20 and 1.6.4 dated 2018-09-19

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Package data.table updated to version 1.11.6 with previous version 1.11.4 dated 2018-05-27

Title: Extension of `data.frame`
Description: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
Author: Matt Dowle [aut, cre], Arun Srinivasan [aut], Jan Gorecki [ctb], Michael Chirico [ctb], Pasha Stetsenko [ctb], Tom Short [ctb], Steve Lianoglou [ctb], Eduard Antonyan [ctb], Markus Bonsch [ctb], Hugh Parsonage [ctb]
Maintainer: Matt Dowle <mattjdowle@gmail.com>

Diff between data.table versions 1.11.4 dated 2018-05-27 and 1.11.6 dated 2018-09-19

 DESCRIPTION                                                 |    6 
 MD5                                                         |  142 
 NAMESPACE                                                   |    3 
 NEWS.md                                                     |   97 
 R/IDateTime.R                                               |   91 
 R/as.data.table.R                                           |    6 
 R/between.R                                                 |   15 
 R/bmerge.R                                                  |   10 
 R/cedta.R                                                   |   19 
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 R/fcast.R                                                   |    4 
 R/foverlaps.R                                               |    2 
 R/fread.R                                                   |   80 
 R/fwrite.R                                                  |   19 
 R/onAttach.R                                                |    2 
 R/onLoad.R                                                  |    4 
 R/setkey.R                                                  |   73 
 R/setops.R                                                  |    9 
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New package binb with initial version 0.0.1
Package: binb
Type: Package
Title: 'binb' is not 'Beamer'
Version: 0.0.1
Date: 2018-09-19
Author: Dirk Eddelbuettel and Ista Zahn
Maintainer: Dirk Eddelbuettel <edd@debian.org>
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'), and the 'IQSS' by Ista Zahn (which is included here). Additional (free) fonts may be needed: 'Metropolis' prefers 'Fira', and 'IQSS' requires 'Libertinus'.
URL: https://github.com/eddelbuettel/binb
BugReports: https://github.com/eddelbuettel/binb/issues
Imports: rmarkdown, knitr
VignetteBuilder: knitr
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-19 12:26:29.858568 UTC; edd
Repository: CRAN
Date/Publication: 2018-09-19 22:30:03 UTC

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New package bcf with initial version 1.2.1
Package: bcf
Type: Package
Title: Causal Inference for a Binary Treatment and Continuous Outcome using Bayesian Causal Forests
Version: 1.2.1
Date: 2018-09-19
Author: P. Richard Hahn, Jared S. Murray, and Carlos Carvalho
Maintainer: Jared S. Murray <jared.murray@mccombs.utexas.edu>
Description: Causal inference for a binary treatment and continuous outcome using Bayesian Causal Forests. See Hahn, Murray and Carvalho (2017) <arXiv:1706.09523> for additional information. This implementation relies on code originally accompanying Pratola et. al. (2013) <arXiv:1309.1906>.
License: GPL-3
Depends: Rcpp (>= 0.10.4)
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2018-09-19 21:17:11 UTC; jared
Repository: CRAN
Date/Publication: 2018-09-19 22:20:02 UTC

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Package pssmooth updated to version 1.0.1 with previous version 1.0.0 dated 2018-07-29

Title: Flexible and Efficient Evaluation of Principal Surrogates/Treatment Effect Modifiers
Description: Implements estimation and testing procedures for evaluating an intermediate biomarker response as a principal surrogate of a clinical response to treatment (i.e., principal stratification effect modification analysis), as described in Juraska M, Huang Y, and Gilbert PB, Inference on treatment effect modification by biomarker response in a three-phase sampling design (under review). The methods avoid the restrictive 'placebo structural risk' modeling assumption common to past methods and further improve robustness by the use of nonparametric kernel smoothing for biomarker density estimation. A randomized controlled two-group clinical efficacy trial is assumed with an ordered categorical or continuous univariate biomarker response measured at a fixed timepoint post-randomization and with a univariate baseline surrogate measure allowed to be observed in only a subset of trial participants with an observed biomarker response (see the flexible three-phase sampling design in the paper for details). Bootstrap-based procedures are available for pointwise and simultaneous confidence intervals and testing of four relevant hypotheses. Summary and plotting functions are provided for estimation results.
Author: Michal Juraska [aut, cre]
Maintainer: Michal Juraska <mjuraska@fredhutch.org>

Diff between pssmooth versions 1.0.0 dated 2018-07-29 and 1.0.1 dated 2018-09-19

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Package droptest updated to version 0.1.3 with previous version 0.1.2 dated 2018-08-18

Title: Simulates LOX Drop Testing
Description: Generates simulated data representing the LOX drop testing process (also known as impact testing). A simulated process allows for accelerated study of test behavior. Functions are provided to simulate trials, test series, and groups of test series. Functions for creating plots specific to this process are also included. Test attributes and criteria can be set arbitrarily. This work is not endorsed by or affiliated with NASA. See "ASTM G86-17, Standard Test Method for Determining Ignition Sensitivity of Materials to Mechanical Impact in Ambient Liquid Oxygen and Pressurized Liquid and Gaseous Oxygen Environments" <doi:10.1520/G0086-17>.
Author: Chad Ross [aut, cre]
Maintainer: Chad Ross <chad.ross@gmail.com>

Diff between droptest versions 0.1.2 dated 2018-08-18 and 0.1.3 dated 2018-09-19

 DESCRIPTION |    6 +++---
 MD5         |    6 +++---
 NEWS.md     |    3 +++
 R/dtrials.R |    2 +-
 4 files changed, 10 insertions(+), 7 deletions(-)

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New package taipan with initial version 0.1.1
Package: taipan
Version: 0.1.1
Title: Tool for Annotating Images in Preparation for Analysis
Authors@R: c(person("Stephanie", "Kobakian", email = "stephanie.kobakian@gmail.com", role = c("aut", "cre")), person("Mitchell", "O'Hara-Wild", email = "mail@mitchelloharawild.com", role = c("aut")))
Description: A tool to help create shiny apps for selecting and annotating elements of images. Users must supply images, questions, and answer choices. The user interface is a dynamic shiny app, that displays the images and questions and answer choices. The data generated can be saved to a file that can be used for subsequent analysis. The original purpose was to annotate still images from tennis video for face recognition and emotion detection purposes.
Depends: R (>= 3.2.0)
Imports: shiny, utils
Suggests: testthat, knitr, rmarkdown, tidyverse
URL: https://github.com/srkob1/taipan
BugReports: https://github.com/srkob1/taipan/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-12 03:11:56 UTC; steff
Author: Stephanie Kobakian [aut, cre], Mitchell O'Hara-Wild [aut]
Maintainer: Stephanie Kobakian <stephanie.kobakian@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-19 15:10:03 UTC

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Package RTest updated to version 1.1.9.0 with previous version 1.1.8.0 dated 2018-08-24

Title: A XML-Based Testing Framework for Automated Component Tests of R Packages
Description: This provides a framework for R packages developed for a regulatory environment. It is based on the 'testthat' unit testing system and provides the adapter functionalities for XML-based test case definition as well as for standardized reporting of the test results.
Author: Sebastian Wolf [aut, cre], Matthias Pfeifer [aut, ctb], Sergej Potapov [ctb], Roche [cph, fnd]
Maintainer: Sebastian Wolf <sebastian.wolf.sw1@roche.com>

Diff between RTest versions 1.1.8.0 dated 2018-08-24 and 1.1.9.0 dated 2018-09-19

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 87 files changed, 3002 insertions(+), 3058 deletions(-)

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Package kst updated to version 0.5-0 with previous version 0.4-0 dated 2018-04-13

Title: Knowledge Space Theory
Description: Knowledge space theory by Doignon and Falmagne (1999) <doi:10.1007/978-3-642-58625-5> is a set- and order-theoretical framework, which proposes mathematical formalisms to operationalize knowledge structures in a particular domain. The 'kst' package provides basic functionalities to generate, handle, and manipulate knowledge structures and knowledge spaces.
Author: Christina Stahl [aut], David Meyer [aut], Cord Hockemeyer [aut, cre]
Maintainer: Cord Hockemeyer <cord.hockemeyer@uni-graz.at>

Diff between kst versions 0.4-0 dated 2018-04-13 and 0.5-0 dated 2018-09-19

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Package EffectTreat updated to version 0.4 with previous version 0.3 dated 2017-01-27

Title: Prediction of Therapeutic Success
Description: In personalized medicine, one wants to know, for a given patient and his or her outcome for a predictor (pre-treatment variable), how likely it is that a treatment will be more beneficial than an alternative treatment. This package allows for the quantification of the predictive causal association (i.e., the association between the predictor variable and the individual causal effect of the treatment) and related metrics. Part of this software has been developed using funding provided from the European Union's 7th Framework Programme for research, technological development and demonstration under Grant Agreement no 602552.
Author: Wim Van der Elst, Ariel Alonso & Geert Molenberghs
Maintainer: Wim Van der Elst <Wim.vanderelst@gmail.com>

Diff between EffectTreat versions 0.3 dated 2017-01-27 and 0.4 dated 2018-09-19

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New package distdichoR with initial version 0.1-0
Package: distdichoR
Type: Package
Title: Distributional Method for the Dichotomisation of Continuous Outcomes
Version: 0.1-0
Author: Odile Sauzet
Maintainer: Odile Sauzet <odile.sauzet@uni-bielefeld.de>
Description: Contains a range of functions covering the present development of the distributional method for the dichotomisation of continuous outcomes. The method provides estimates with standard error of a comparison of proportions (difference, odds ratio and risk ratio) derived, with similar precision, from a comparison of means. See the URL below or <arXiv:1809.03279> for more information.
URL: https://arxiv.org/abs/1809.03279
Encoding: UTF-8
LazyData: true
License: MIT + file LICENSE
Depends: R (>= 2.10)
Imports: boot, sn, lsmeans, stats, nlme
Suggests: knitr, rmarkdown
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-13 16:07:40 UTC; janne
Repository: CRAN
Date/Publication: 2018-09-19 15:20:06 UTC

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New package ddsPLS with initial version 1.0.0
Package: ddsPLS
Version: 1.0.0
Title: Multi-Data-Driven Sparse PLS Robust to Missing Samples
Description: Allows to build Multi-Data-Driven Sparse PLS models. Multi-blocks with high-dimensional settings are particularly sensible to this.
Authors@R: person("Hadrien","Lorenzo", role = c("aut", "cre"), email = "hadrien.lorenzo.2015@gmail.com")
Maintainer: Hadrien Lorenzo <hadrien.lorenzo.2015@gmail.com>
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.0
Imports: RColorBrewer,MASS,graphics,stats,utils,Rdpack,doParallel,foreach,parallel,iterators
RdMacros: Rdpack
Suggests: knitr,rmarkdown
Depends: R (>= 2.10)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-12 15:34:16 UTC; hl1
Author: Hadrien Lorenzo [aut, cre]
Repository: CRAN
Date/Publication: 2018-09-19 15:10:06 UTC

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Package zoo updated to version 1.8-4 with previous version 1.8-3 dated 2018-07-16

Title: S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations)
Description: An S3 class with methods for totally ordered indexed observations. It is particularly aimed at irregular time series of numeric vectors/matrices and factors. zoo's key design goals are independence of a particular index/date/time class and consistency with ts and base R by providing methods to extend standard generics.
Author: Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>), Gabor Grothendieck [aut], Jeffrey A. Ryan [aut], Joshua M. Ulrich [ctb], Felix Andrews [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

Diff between zoo versions 1.8-3 dated 2018-07-16 and 1.8-4 dated 2018-09-19

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Package rcmdcheck updated to version 1.3.0 with previous version 1.2.1 dated 2016-09-28

Title: Run 'R CMD check' from 'R' and Capture Results
Description: Run 'R CMD check' from 'R' programmatically, and capture the results of the individual checks.
Author: Gábor Csárdi
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between rcmdcheck versions 1.2.1 dated 2016-09-28 and 1.3.0 dated 2018-09-19

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Package MXM updated to version 1.4.0 with previous version 1.3.9 dated 2018-08-27

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. Reference: Feature Selection with the R Package MXM: Discovering Statistically Equivalent Feature Subsets, Lagani, V. and Athineou, G. and Farcomeni, A. and Tsagris, M. and Tsamardinos, I. (2017). Journal of Statistical Software, 80(7). <doi:10.18637/jss.v080.i07>.
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@csd.uoc.gr>

Diff between MXM versions 1.3.9 dated 2018-08-27 and 1.4.0 dated 2018-09-19

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Package maptools updated to version 0.9-4 with previous version 0.9-3 dated 2018-07-31

Title: Tools for Handling Spatial Objects
Description: Set of tools for manipulating geographic data. It includes binary access to 'GSHHG' shoreline files. The package also provides interface wrappers for exchanging spatial objects with packages such as 'PBSmapping', 'spatstat', 'maps', 'RArcInfo', 'Stata tmap', 'WinBUGS', 'Mondrian', and others.
Author: Roger Bivand [cre, aut] (<https://orcid.org/0000-0003-2392-6140>), Nicholas Lewin-Koh [aut], Edzer Pebesma [ctb], Eric Archer [ctb], Adrian Baddeley [ctb], Nick Bearman [ctb], Hans-Jörg Bibiko [ctb], Steven Brey [ctb], Jonathan Callahan [ctb], German Carrillo [ctb], Stéphane Dray [ctb], David Forrest [ctb], Michael Friendly [ctb], Patrick Giraudoux [ctb], Duncan Golicher [ctb], Virgilio Gómez Rubio [ctb], Patrick Hausmann [ctb], Karl Ove Hufthammer [ctb], Thomas Jagger [ctb], Kent Johnson [ctb], Sebastian Luque [ctb], Don MacQueen [ctb], Andrew Niccolai [ctb], Edzer Pebesma [ctb], Oscar Perpiñán Lamigueiro [ctb], Tom Short [ctb], Greg Snow [ctb], Ben Stabler [ctb], Murray Stokely [ctb], Rolf Turner [ctb]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

Diff between maptools versions 0.9-3 dated 2018-07-31 and 0.9-4 dated 2018-09-19

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Package KFAS updated to version 1.3.3 with previous version 1.3.2 dated 2018-05-21

Title: Kalman Filter and Smoother for Exponential Family State Space Models
Description: State space modelling is an efficient and flexible framework for statistical inference of a broad class of time series and other data. KFAS includes computationally efficient functions for Kalman filtering, smoothing, forecasting, and simulation of multivariate exponential family state space models, with observations from Gaussian, Poisson, binomial, negative binomial, and gamma distributions. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details.
Author: Jouni Helske <jouni.helske@iki.fi>
Maintainer: Jouni Helske <jouni.helske@iki.fi>

Diff between KFAS versions 1.3.2 dated 2018-05-21 and 1.3.3 dated 2018-09-19

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Package CIAAWconsensus updated to version 1.3 with previous version 1.2 dated 2017-08-18

Title: Isotope Ratio Meta-Analysis
Description: Calculation of consensus values for atomic weights, isotope amount ratios, and isotopic abundances with the associated uncertainties using multivariate meta-regression approach for consensus building.
Author: Juris Meija and Antonio Possolo
Maintainer: Juris Meija <juris.meija@nrc-cnrc.gc.ca>

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Package wilson updated to version 2.0.2 with previous version 2.0.1 dated 2018-07-20

Title: Web-Based Interactive Omics Visualization
Description: Tool-set of modules for creating web-based applications that use plot based strategies to visualize and analyze multi-omics data. This package utilizes the 'shiny' and 'plotly' frameworks to provide a user friendly dashboard for interactive plotting.
Author: Hendrik Schultheis [aut, cre], Jens Preussner [aut], Looso Mario [aut]
Maintainer: Hendrik Schultheis <hendrik.schultheis@mpi-bn.mpg.de>

Diff between wilson versions 2.0.1 dated 2018-07-20 and 2.0.2 dated 2018-09-19

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New package SplitSoftening with initial version 1.0-0
Package: SplitSoftening
Version: 1.0-0
Title: Softening Splits in Decision Trees
Author: Jakub Dvorak
Maintainer: Jakub Dvorak <JakubDvorak@email.cz>
Depends: R (>= 3.0.0)
Enhances: tree
Suggests: gsl
Description: Allows to produce and use classification trees with probability (soft) splits.
License: GPL (>= 2)
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-09-12 09:48:49 UTC; jdv01
Repository: CRAN
Date/Publication: 2018-09-19 10:00:06 UTC

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Package BayLum updated to version 0.1.3 with previous version 0.1.2 dated 2018-06-22

Title: Chronological Bayesian Models Integrating Optically Stimulated Luminescence and Radiocarbon Age Dating
Description: Bayesian analysis of luminescence data and C-14 age estimates. Bayesian models are based on the following publications: Combes, B. & Philippe, A. (2017) <doi:10.1016/j.quageo.2017.02.003> and Combes et al (2015) <doi:10.1016/j.quageo.2015.04.001>. This includes, amongst others, data import, export, application of age models and palaeodose model.
Author: Claire Christophe [aut], Anne Philippe [aut, cre], Sebastian Kreutzer [aut] (<https://orcid.org/0000-0002-0734-2199>), Guillaume Guerin [aut] (<https://orcid.org/0000-0001-6298-5579>)
Maintainer: Anne Philippe <anne.philippe@univ-nantes.fr>

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New package bayesdfa with initial version 0.1.0
Package: bayesdfa
Type: Package
Title: Bayesian Dynamic Factor Analysis (DFA) with 'Stan'
Version: 0.1.0
Authors@R: c( person(c("Eric", "J."), "Ward", role = c("aut", "cre"), email = "eric.ward@noaa.gov"), person(c("Sean", "C."), "Anderson", role = "aut"), person(c("Luis", "A."), "Damiano", role = "aut"), person(c("Mary", "E."), "Hunsicker,", role = "ctb"), person(c("Mike", "A."), "Litzow", role = "ctb"), person("Trustees of", "Columbia University", role = "cph"))
Description: Implements Bayesian dynamic factor analysis with 'Stan'. Dynamic factor analysis is a dimension reduction tool for multivariate time series. 'bayesdfa' extends conventional dynamic factor models in several ways. First, extreme events may be estimated in the latent trend by modeling process error with a student-t distribution. Second, autoregressive and moving average components can be optionally included. Third, the estimated dynamic factors can be analyzed with hidden Markov models to evaluate support for latent regimes.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0), Rcpp (>= 0.12.0)
Imports: rstan (>= 2.16.0), ggplot2 (>= 2.2.0), loo, dplyr (>= 0.7.0), methods, rlang, reshape2
LinkingTo: StanHeaders (>= 2.16.0), rstan (>= 2.16.0), BH (>= 1.62.0), Rcpp (>= 0.12.0), RcppEigen
Suggests: testthat, parallel, knitr, rmarkdown, MARSS
URL: https://github.com/fate-ewi/bayesdfa
BugReports: https://github.com/fate-ewi/bayesdfa/issues
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-09-10 12:15:54 UTC; eric.ward
Author: Eric J. Ward [aut, cre], Sean C. Anderson [aut], Luis A. Damiano [aut], Mary E. Hunsicker, [ctb], Mike A. Litzow [ctb], Trustees of Columbia University [cph]
Maintainer: Eric J. Ward <eric.ward@noaa.gov>
Repository: CRAN
Date/Publication: 2018-09-19 10:00:02 UTC

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Package auditor updated to version 0.3.1 with previous version 0.3.0 dated 2018-08-27

Title: Model Audit - Verification, Validation, and Error Analysis
Description: Provides an easy to use unified interface for creating validation plots for any model. The 'auditor' helps to avoid repetitive work consisting of writing code needed to create residual plots. This visualizations allow to asses and compare the goodness of fit, performance, and similarity of models.
Author: Alicja Gosiewska [aut, cre], Przemyslaw Biecek [aut, ths]
Maintainer: Alicja Gosiewska <alicjagosiewska@gmail.com>

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Package dataCompareR updated to version 0.1.2 with previous version 0.1.1 dated 2017-11-14

Title: Compare Two Data Frames and Summarise the Difference
Description: Easy comparison of two tabular data objects in R. Specifically designed to show differences between two sets of data in a useful way that should make it easier to understand the differences, and if necessary, help you work out how to remedy them. Aims to offer a more useful output than all.equal() when your two data sets do not match, but isn't intended to replace all.equal() as a way to test for equality.
Author: Rob Noble-Eddy [aut, cre], Sarah Johnston [aut], Sarah Pollicott [aut], Merlijn van Horssen [aut], Lukas Drapal [ctb], Nikolaos Perrakis [ctb], Nikhil Thomas Joy [ctb], Shahriar Asta [ctb], Karandeep Lidher [ctb], Dan Kellett [ctb], Kevin Chisholm [ctb], Laura Joy [ctb], Fergus Wadsley [ctb], Heather Hackett [ctb], David Robinson [ctb], Cheryl Renton [ctb], Matt Triggs [ctb], Krishan Bhasin [ctb], Carola Deppe [ctb], Ruijing Li [ctb], John Swift [ctb]
Maintainer: Rob Noble-Eddy <opensource@capitalone.com>

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Package personalized updated to version 0.2.1 with previous version 0.2.0 dated 2018-09-18

Title: Estimation and Validation Methods for Subgroup Identification and Personalized Medicine
Description: Provides functions for fitting and validation of models for subgroup identification and personalized medicine / precision medicine under the general subgroup identification framework of Chen et al. (2017) <doi:10.1111/biom.12676>. This package is intended for use for both randomized controlled trials and observational studies.
Author: Jared Huling [aut, cre], Aaron Potvien [ctb], Alexandros Karatzoglou [cph], Alex Smola [cph]
Maintainer: Jared Huling <jaredhuling@gmail.com>

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Package PAFit updated to version 1.0.0.7 with previous version 1.0.0.6 dated 2018-08-28

Title: Generative Mechanism Estimation in Temporal Complex Networks
Description: Statistical methods for estimating preferential attachment and node fitness generative mechanisms in temporal complex networks are provided. Thong Pham et al. (2015) <doi:10.1371/journal.pone.0137796>. Thong Pham et al.(2016) <doi:10.1038/srep32558>.
Author: Thong Pham, Paul Sheridan, Hidetoshi Shimodaira
Maintainer: Thong Pham <thongpham@thongpham.net>

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Package furniture updated to version 1.8.0 with previous version 1.7.9 dated 2018-06-01

Title: Tables for Quantitative Scientists
Description: Contains three main functions (i.e., three pieces of furniture): table1() which produces a well-formatted table of descriptives common as Table 1 in research articles, tableC() which produces a well-formatted table of correlations, tableF() which provides frequency counts, and washer() which is helpful in cleaning up the data. These furniture-themed functions are designed to simplify common tasks in quantitative analysis. Other data summary and cleaning tools are also available.
Author: Tyson S. Barrett [aut, cre] (<https://orcid.org/0000-0002-2137-1391>), Emily Brignone [aut], Daniel J. Laxman [aut]
Maintainer: Tyson S. Barrett <t.barrett@aggiemail.usu.edu>

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

Title: L1-Penalized Censored Gaussian Graphical Models
Description: The l1-penalized censored Gaussian graphical model is an extension of the graphical lasso estimator developed to handle datasets with censored observations. An EM-like algorithm is implemented to estimate the parameters of the censored Gaussian graphical models.
Author: Luigi Augugliaro
Maintainer: Luigi Augugliaro <luigi.augugliaro@unipa.it>

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Package seminr updated to version 0.5.2 with previous version 0.5.1 dated 2018-09-10

Title: Domain-Specific Language for Building PLS Structural Equation Models
Description: A powerful, easy to write and easy to modify syntax for specifying and estimating Partial Least Squares (PLS) path models allowing for the latest estimation methods for Consistent PLS as per Dijkstra & Henseler (2015, MISQ 39(2): 297-316), adjusted interactions as per Henseler & Chin (2010) <doi:10.1080/10705510903439003> and bootstrapping utilizing parallel processing as per Hair et al. (2017, ISBN:978-1483377445).
Author: Soumya Ray [aut, ths], Nicholas Danks [aut, cre], Juan Manuel Velasquez Estrada [aut]
Maintainer: Nicholas Danks <nicholasdanks@hotmail.com>

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Package replyr updated to version 0.9.8 with previous version 0.9.7 dated 2018-07-20

Title: Patches to Use 'dplyr' on Remote Data Sources
Description: Patches to use 'dplyr' on remote data sources ('SQL' databases, 'Spark' 2.0.0 and above) in a reliable "generic" fashion (generic meaning user code works similarly on all such sources, without needing per-source adaption). Due to the fluctuating nature of 'dplyr'/'dbplyr'/'rlang' 'APIs' this package is going into maintenance mode. Most of the 'replyr' functions are already done better by one of the non-monolithic replacement packages: 'wrapr', 'seplyr', 'rquery', or 'cdata'.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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Package IRISSeismic updated to version 1.4.9 with previous version 1.4.8 dated 2018-05-07

Title: Classes and Methods for Seismic Data Analysis
Description: Provides classes and methods for seismic data analysis. The base classes and methods are inspired by the python code found in the 'ObsPy' python toolbox <https://github.com/obsypy/obspy>. Additional classes and methods support data returned by web services provided by the 'IRIS DMC' <http://service.iris.edu/>.
Author: Jonathan Callahan [aut], Rob Casey [aut], Gillian Sharer [aut, cre], Mary Templeton [aut], Chad Trabant [ctb]
Maintainer: Gillian Sharer <gillian@iris.washington.edu>

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Permanent link

Package augSIMEX updated to version 3.0 with previous version 2.2 dated 2018-07-23

Title: Analysis of Data with Mixed Measurement Error and Misclassification in Covariates
Description: Implementation of the augmented Simulation-Extrapolation (SIMEX) algorithm proposed by Yi et al. (2015) <doi:10.1080/01621459.2014.922777> for analyzing the data with mixed measurement error and misclassification. The main function provides a similar summary output as that of glm() function. Both parametric and empirical SIMEX are considered in the package.
Author: Qihuang Zhang <qihuang.zhang@uwaterloo.ca>, Grace Y. Yi <yyi@uwaterloo.ca>
Maintainer: Qihuang Zhang <qihuang.zhang@uwaterloo.ca>

Diff between augSIMEX versions 2.2 dated 2018-07-23 and 3.0 dated 2018-09-19

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Permanent link

Tue, 18 Sep 2018

New package rmetalog with initial version 1.0.0
Package: rmetalog
Type: Package
Title: R Implementation of the Metalog Distribution
Version: 1.0.0
Authors@R: c( person("Isaac", "Faber", email = "isaacfab@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4478-9598")), person("Jongbin", "Jung", email = "me@jongbin.com", role = c("aut")))
Description: Implementation of the metalog distribution in R. The metalog distribution is a modern, highly flexible, data-driven distribution. Metalogs are developed by Keelin (2016) <doi:10.1287/deca.2016.0338>. This package provides functions to build these distributions from raw data. Resulting metalog objects are then useful for exploratory and probabilistic analysis.
Imports: lpSolve, ggplot2
Suggests: devtools, knitr, rmarkdown
Depends: R (>= 3.1.0)
BugReports: https://github.com/isaacfab/rmetalog/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-17 18:16:02 UTC; isaacfaber
Author: Isaac Faber [aut, cre] (<https://orcid.org/0000-0002-4478-9598>), Jongbin Jung [aut]
Maintainer: Isaac Faber <isaacfab@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-18 23:00:03 UTC

More information about rmetalog at CRAN
Permanent link

Package lifecontingencies updated to version 1.3.5 with previous version 1.3.2 dated 2017-12-09

Title: Financial and Actuarial Mathematics for Life Contingencies
Description: Classes and methods that allow the user to manage life table, actuarial tables (also multiple decrements tables). Moreover, functions to easily perform demographic, financial and actuarial mathematics on life contingencies insurances calculations are contained therein.
Author: Giorgio Alfredo Spedicato [cre,aut], Reinhold Kainhofer [ctb], Kevin J. Owens [ctb], Christophe Dutang [ctb], Ernesto Schirmacher[ctb], Gian Paolo Clemente [ctb]
Maintainer: Giorgio Alfredo Spedicato <spedicato_giorgio@yahoo.it>

Diff between lifecontingencies versions 1.3.2 dated 2017-12-09 and 1.3.5 dated 2018-09-18

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 lifecontingencies-1.3.5/lifecontingencies/NEWS                                                       |    6 
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 lifecontingencies-1.3.5/lifecontingencies/man/axn.Rd                                                 |   25 
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Package later updated to version 0.7.5 with previous version 0.7.4 dated 2018-08-31

Title: Utilities for Delaying Function Execution
Description: Executes arbitrary R or C functions some time after the current time, after the R execution stack has emptied.
Author: Joe Cheng [aut, cre], RStudio [cph], Marcus Geelnard [ctb, cph] (TinyCThread library, https://tinycthread.github.io/), Evan Nemerson [ctb, cph] (TinyCThread library, https://tinycthread.github.io/)
Maintainer: Joe Cheng <joe@rstudio.com>

Diff between later versions 0.7.4 dated 2018-08-31 and 0.7.5 dated 2018-09-18

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More information about later at CRAN
Permanent link

New package eivtools with initial version 0.1-8
Package: eivtools
Type: Package
Title: Measurement Error Modeling Tools
Version: 0.1-8
Date: 2018-09-16
Depends: R (>= 3.4.0), stats, grDevices, graphics, utils, R2jags
Author: J.R. Lockwood
Maintainer: J.R. Lockwood <jrlockwood@ets.org>
Description: This includes functions for analysis with error-prone covariates, including deconvolution, latent regression and errors-in-variables regression. It implements methods by Rabe-Hesketh et al. (2003) <doi:10.1191/1471082x03st056oa>, Lockwood and McCaffrey (2014) <doi:10.3102/1076998613509405>, and Lockwood and McCaffrey (2017) <doi:10.1007/s11336-017-9556-y>, among others.
License: GPL (>= 2) | file LICENSE
LazyData: true
NeedsCompilation: no
Packaged: 2018-09-17 14:52:19 UTC; jlock
Repository: CRAN
Date/Publication: 2018-09-18 22:30:08 UTC

More information about eivtools at CRAN
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New package conStruct with initial version 1.0.0
Package: conStruct
Version: 1.0.0
Title: Models Spatially Continuous and Discrete Population Genetic Structure
Description: A method for modeling genetic data as a combination of discrete layers, within each of which relatedness may decay continuously with geographic distance. This package contains code for running analyses (which are implemented in the modeling language 'rstan') and visualizing and interpreting output. See the paper for more details on the model and its utility.
Authors@R: person("Gideon", "Bradburd", email = "bradburd@msu.edu", role = c("aut", "cre"))
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 3.4.0), Rcpp (>= 0.12.18), methods
Imports: rstan (>= 2.17.3), rstantools (>= 1.5.0), caroline, gtools, foreach, parallel, doParallel
LinkingTo: StanHeaders (>= 2.17.2), rstan (>= 2.17.3), BH (>= 1.66.0-1), Rcpp (>= 0.12.18), RcppEigen (>= 0.3.3.4.0)
SystemRequirements: GNU make
NeedsCompilation: yes
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown, maps
VignetteBuilder: knitr
Packaged: 2018-09-17 14:08:03 UTC; bradburd
Author: Gideon Bradburd [aut, cre]
Maintainer: Gideon Bradburd <bradburd@msu.edu>
Repository: CRAN
Date/Publication: 2018-09-18 22:40:03 UTC

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Package rzmq updated to version 0.9.4 with previous version 0.9.3 dated 2017-10-02

Title: R Bindings for 'ZeroMQ'
Description: Interface to the 'ZeroMQ' lightweight messaging kernel (see <http://www.zeromq.org/> for more information).
Author: Whit Armstrong [aut], Michael Schubert [ctb], Jeroen Ooms [aut, cre]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between rzmq versions 0.9.3 dated 2017-10-02 and 0.9.4 dated 2018-09-18

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Package Cyclops updated to version 2.0.0 with previous version 1.3.4 dated 2018-06-15

Title: Cyclic Coordinate Descent for Logistic, Poisson and Survival Analysis
Description: This model fitting tool incorporates cyclic coordinate descent and majorization-minimization approaches to fit a variety of regression models found in large-scale observational healthcare data. Implementations focus on computational optimization and fine-scale parallelization to yield efficient inference in massive datasets. Please see: Suchard, Simpson, Zorych, Ryan and Madigan (2013) <doi:10.1145/2414416.2414791>.
Author: Marc A. Suchard [aut, cre], Martijn J. Schuemie [aut], Trevor R. Shaddox [aut], Yuxi Tian [aut], Jianxiao Yang [aut], Sushil Mittal [ctb], Observational Health Data Sciences and Informatics [cph], Marcus Geelnard [cph, ctb] (provided the TinyThread library), Rutgers University [cph, ctb] (provided the HParSearch routine), R Development Core Team [cph, ctb] (provided the ZeroIn routine)
Maintainer: Marc A. Suchard <msuchard@ucla.edu>

Diff between Cyclops versions 1.3.4 dated 2018-06-15 and 2.0.0 dated 2018-09-18

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More information about Cyclops at CRAN
Permanent link

Package sentometrics updated to version 0.5 with previous version 0.4 dated 2018-05-28

Title: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
Description: Optimized prediction based on textual sentiment, accounting for the intrinsic challenge that sentiment can be computed and pooled across texts and time in various ways. See Ardia et al. (2017) <doi:10.2139/ssrn.3067734>.
Author: David Ardia [aut], Keven Bluteau [aut], Samuel Borms [aut, cre], Kris Boudt [aut]
Maintainer: Samuel Borms <samuel.borms@unine.ch>

Diff between sentometrics versions 0.4 dated 2018-05-28 and 0.5 dated 2018-09-18

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Package docxtractr updated to version 0.5.0 with previous version 0.2.0 dated 2016-07-20

Title: Extract Data Tables and Comments from 'Microsoft' 'Word' Documents
Description: 'Microsoft Word' 'docx' files provide an 'XML' structure that is fairly straightforward to navigate, especially when it applies to 'Word' tables and comments. Tools are provided to determine table count/structure, comment count and also to extract/clean tables and comments from 'Microsoft Word' 'docx' documents. There is also nascent support for '.doc' files.
Author: Bob Rudis [aut, cre] (<https://orcid.org/0000-0001-5670-2640>), Mark Dulhunty [ctb], Karlo Guidoni-Martins [ctb], Chris Muir [aut, ctb]
Maintainer: Bob Rudis <bob@rud.is>

Diff between docxtractr versions 0.2.0 dated 2016-07-20 and 0.5.0 dated 2018-09-18

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More information about docxtractr at CRAN
Permanent link

Package cymruservices updated to version 0.5.0 with previous version 0.2.0 dated 2016-03-01

Title: Query 'Team Cymru' 'IP' Address, Autonomous System Number ('ASN'), Border Gateway Protocol ('BGP'), Bogon and 'Malware' Hash Data Services
Description: A toolkit for querying 'Team Cymru' <http://team-cymru.org> 'IP' address, Autonomous System Number ('ASN'), Border Gateway Protocol ('BGP'), Bogon and 'Malware' Hash Data Services.
Author: Bob Rudis [aut, cre] (<https://orcid.org/0000-0001-5670-2640>)
Maintainer: Bob Rudis <bob@rud.is>

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Package cAIC4 updated to version 0.5 with previous version 0.4 dated 2018-05-22

Title: Conditional Akaike Information Criterion for 'lme4'
Description: Provides functions for the estimation of the conditional Akaike information in generalized mixed-effect models fitted with (g)lmer() from 'lme4'.
Author: Benjamin Saefken and David Ruegamer, with contributions from Sonja Greven and Thomas Kneib
Maintainer: David Ruegamer <david.ruegamer@gmail.com>

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Package seplyr updated to version 0.8.1 with previous version 0.8.0 dated 2018-09-10

Title: Improved Standard Evaluation Interfaces for Common Data Manipulation Tasks
Description: The 'seplyr' (standard evaluation plying) package supplies improved standard evaluation adapter methods for important common 'dplyr' data manipulation tasks. In addition the 'seplyr' package supplies several new "key operations bound together" methods. These include 'group_summarize()' (which combines grouping, arranging and calculation in an atomic unit), 'add_group_summaries()' (which joins grouped summaries into a 'data.frame' in a well documented manner), 'add_group_indices()' (which adds per-group identifiers to a 'data.frame' without depending on row-order), 'partition_mutate_qt()' (which optimizes mutate sequences), and 'if_else_device()' (which simulates per-row if-else blocks in expression sequences).
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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Package hetGP updated to version 1.1.0 with previous version 1.0.2 dated 2018-02-06

Title: Heteroskedastic Gaussian Process Modeling and Design under Replication
Description: Performs Gaussian process regression with heteroskedastic noise following Binois, M., Gramacy, R., Ludkovski, M. (2016) <arXiv:1611.05902>. The input dependent noise is modeled as another Gaussian process. Replicated observations are encouraged as they yield computational savings. Sequential design procedures based on the integrated mean square prediction error and lookahead heuristics are provided, and notably fast update functions when adding new observations.
Author: Mickael Binois, Robert B. Gramacy
Maintainer: Mickael Binois <mbinois@mcs.anl.gov>

Diff between hetGP versions 1.0.2 dated 2018-02-06 and 1.1.0 dated 2018-09-18

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Package arsenal updated to version 1.4.0 with previous version 1.3.0 dated 2018-07-20

Title: An Arsenal of 'R' Functions for Large-Scale Statistical Summaries
Description: An Arsenal of 'R' functions for large-scale statistical summaries, which are streamlined to work within the latest reporting tools in 'R' and 'RStudio' and which use formulas and versatile summary statistics for summary tables and models. The primary functions include tableby(), a Table-1-like summary of multiple variable types 'by' the levels of a categorical variable; paired(), a Table-1-like summary of multiple variable types paired across two time points; modelsum(), which performs simple model fits on the same endpoint for many variables (univariate or adjusted for standard covariates); freqlist(), a powerful frequency table across many categorical variables; compare.data.frame(), the S3 method for comparing data.frames; and write2(), a function to output tables to a document.
Author: Ethan Heinzen [aut, cre], Jason Sinnwell [aut], Elizabeth Atkinson [aut], Tina Gunderson [aut], Gregory Dougherty [aut], Patrick Votruba [ctb], Ryan Lennon [ctb], Andrew Hanson [ctb], Krista Goergen [ctb], Emily Lundt [ctb], Brendan Broderick [ctb]
Maintainer: Ethan Heinzen <heinzen.ethan@mayo.edu>

Diff between arsenal versions 1.3.0 dated 2018-07-20 and 1.4.0 dated 2018-09-18

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Package pkgbuild updated to version 1.0.1 with previous version 1.0.0 dated 2018-06-27

Title: Find Tools Needed to Build R Packages
Description: Provides functions used to build R packages. Locates compilers needed to build R packages on various platforms and ensures the PATH is configured appropriately so R can use them.
Author: Hadley Wickham [aut], Jim Hester [aut, cre], RStudio [cph]
Maintainer: Jim Hester <james.hester@rstudio.com>

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Package molaR updated to version 4.4 with previous version 4.3 dated 2017-09-20

Title: Dental Surface Complexity Measurement Tools
Description: Surface topography calculations of Dirichlet's normal energy, relief index, surface slope, and orientation patch count for teeth using scans of enamel caps. Importantly, for the relief index and orientation patch count calculations to work, the scanned tooth files must be oriented with the occlusal plane parallel to the x and y axes, and perpendicular to the z axis. The files should also be simplified, and smoothed in some other software prior to uploading into R.
Author: James D. Pampush [aut, cre, cph], Julia M. Winchester [aut, cph], Paul E. Morse [aut, cph], Alexander Q. Vining [aut, cph]
Maintainer: James D. Pampush <jdpampush@gmail.com>

Diff between molaR versions 4.3 dated 2017-09-20 and 4.4 dated 2018-09-18

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Package asbio updated to version 1.5-3 with previous version 1.5-2 dated 2018-07-09

Title: A Collection of Statistical Tools for Biologists
Description: Contains functions from: Aho, K. (2014) Foundational and Applied Statistics for Biologists using R. CRC/Taylor and Francis, Boca Raton, FL, ISBN: 978-1-4398-7338-0.
Author: Ken Aho
Maintainer: Ken Aho <kenaho1@gmail.com>

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Package psychmeta updated to version 2.2.0 with previous version 2.1.9 dated 2018-08-23

Title: Psychometric Meta-Analysis Toolkit
Description: Tools for computing bare-bones and psychometric meta-analyses and for generating psychometric data for use in meta-analysis simulations. Supports bare-bones, individual-correction, and artifact-distribution methods for meta-analyzing correlations and d values. Includes tools for converting effect sizes, computing sporadic artifact corrections, reshaping meta-analytic databases, computing multivariate corrections for range variation, and more. Bugs can be reported to <https://github.com/psychmeta/psychmeta/issues> or <issues@psychmeta.com>.
Author: Jeffrey A. Dahlke [aut, cre], Brenton M. Wiernik [aut], Michael T. Brannick [ctb] (Testing), Jack Kostal [ctb] (Code for reshape_mat2dat function), Sean Potter [ctb] (Testing; Code for cumulative and leave1out plots), John Sakaluk [ctb] (Code for funnel and forest plots), Yuejia (Mandy) Teng [ctb] (Testing)
Maintainer: Jeffrey A. Dahlke <dahlk068@umn.edu>

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Package projpred updated to version 1.0.0 with previous version 0.8.0 dated 2018-04-16

Title: Projection Predictive Feature Selection
Description: Performs projection predictive feature selection for generalized linear models (see, e.g., Piironen and Vehtari, 2017, <doi:10.1007/s11222-016-9649-y>). The package is compatible with 'rstanarm' package, but other reference models can also be used. See the package vignette for more information and examples.
Author: Juho Piironen [cre, aut], Markus Paasiniemi [aut], Aki Vehtari [aut], Jonah Gabry [ctb]
Maintainer: Juho Piironen <juho.piironen@aalto.fi>

Diff between projpred versions 0.8.0 dated 2018-04-16 and 1.0.0 dated 2018-09-18

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Package OpenMx updated to version 2.11.3 with previous version 2.10.0 dated 2018-08-03

Title: Extended Structural Equation Modelling
Description: Facilitates treatment of statistical model specifications as things that can be generated and manipulated programmatically. Structural equation models may be specified with reticular action model matrices or paths, linear structural relations matrices or paths, or directly in matrix algebra. Fit functions include full information maximum likelihood, maximum likelihood, and weighted least squares. Example models include confirmatory factor, multiple group, mixture distribution, categorical threshold, modern test theory, differential equations, state space, and many others. MacOS users can download the most up-to-date package binaries from <http://openmx.ssri.psu.edu>. See Neale, Hunter, Pritikin, Zahery, Brick, Kirkpatrick, Estabrook, Bates, Maes, & Boker (2016) <doi:10.1007/s11336-014-9435-8>.
Author: Steven M. Boker [aut], Michael C. Neale [aut], Hermine H. Maes [aut], Michael J. Wilde [ctb], Michael Spiegel [aut], Timothy R. Brick [aut], Ryne Estabrook [aut], Timothy C. Bates [aut], Paras Mehta [ctb], Timo von Oertzen [ctb], Ross J. Gore [aut], Michael D. Hunter [aut], Daniel C. Hackett [ctb], Julian Karch [ctb], Andreas M. Brandmaier [ctb], Joshua N. Pritikin [aut, cre], Mahsa Zahery [aut], Robert M. Kirkpatrick [aut], Yang Wang [ctb], Charles Driver [ctb], Massachusetts Institute of Technology [cph], S. G. Johnson [cph], Association for Computing Machinery [cph], Dieter Kraft [cph], Stefan Wilhelm [cph], Sarah Medland [cph], Carl F. Falk [cph], Matt Keller [cph], Manjunath B G [cph], The Regents of the University of California [cph], Lester Ingber [cph], Wong Shao Voon [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>

Diff between OpenMx versions 2.10.0 dated 2018-08-03 and 2.11.3 dated 2018-09-18

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 OpenMx-2.11.3/OpenMx/DESCRIPTION                                                                       |   30 
 OpenMx-2.11.3/OpenMx/MD5                                                                               | 1241 +++++-----
 OpenMx-2.11.3/OpenMx/NAMESPACE                                                                         |    5 
 OpenMx-2.11.3/OpenMx/NEWS                                                                              |   28 
 OpenMx-2.11.3/OpenMx/R/0ClassUnion.R                                                                   |    2 
 OpenMx-2.11.3/OpenMx/R/DefinitionVars.R                                                                |    2 
 OpenMx-2.11.3/OpenMx/R/DiagMatrix.R                                                                    |    2 
 OpenMx-2.11.3/OpenMx/R/FullMatrix.R                                                                    |    2 
 OpenMx-2.11.3/OpenMx/R/IdenMatrix.R                                                                    |    2 
 OpenMx-2.11.3/OpenMx/R/LowerMatrix.R                                                                   |    2 
 OpenMx-2.11.3/OpenMx/R/MxAlgebra.R                                                                     |    2 
 OpenMx-2.11.3/OpenMx/R/MxAlgebraConvert.R                                                              |    2 
 OpenMx-2.11.3/OpenMx/R/MxAlgebraFunctions.R                                                            |   37 
 OpenMx-2.11.3/OpenMx/R/MxAlgebraObjective.R                                                            |    2 
 OpenMx-2.11.3/OpenMx/R/MxAlgebraTransform.R                                                            |    2 
 OpenMx-2.11.3/OpenMx/R/MxApply.R                                                                       |    2 
 OpenMx-2.11.3/OpenMx/R/MxAutoStart.R                                                                   |   30 
 OpenMx-2.11.3/OpenMx/R/MxBaseNamed.R                                                                   |    2 
 OpenMx-2.11.3/OpenMx/R/MxBounds.R                                                                      |    2 
 OpenMx-2.11.3/OpenMx/R/MxCommunication.R                                                               |    2 
 OpenMx-2.11.3/OpenMx/R/MxCompare.R                                                                     |   97 
 OpenMx-2.11.3/OpenMx/R/MxCompute.R                                                                     |  352 ++
 OpenMx-2.11.3/OpenMx/R/MxConstraint.R                                                                  |    2 
 OpenMx-2.11.3/OpenMx/R/MxCycleDetection.R                                                              |    2 
 OpenMx-2.11.3/OpenMx/R/MxData.R                                                                        |   13 
 OpenMx-2.11.3/OpenMx/R/MxDataWLS.R                                                                     |    5 
 OpenMx-2.11.3/OpenMx/R/MxDeparse.R                                                                     |    2 
 OpenMx-2.11.3/OpenMx/R/MxDependencies.R                                                                |    2 
 OpenMx-2.11.3/OpenMx/R/MxDetectCores.R                                                                 |    2 
 OpenMx-2.11.3/OpenMx/R/MxDiff.R                                                                        |    2 
 OpenMx-2.11.3/OpenMx/R/MxErrorHandling.R                                                               |    2 
 OpenMx-2.11.3/OpenMx/R/MxEval.R                                                                        |    4 
 OpenMx-2.11.3/OpenMx/R/MxExpectation.R                                                                 |   26 
 OpenMx-2.11.3/OpenMx/R/MxExpectationBA81.R                                                             |    2 
 OpenMx-2.11.3/OpenMx/R/MxExpectationGREML.R                                                            |    2 
 OpenMx-2.11.3/OpenMx/R/MxExpectationHiddenMarkov.R                                                     |    2 
 OpenMx-2.11.3/OpenMx/R/MxExpectationLISREL.R                                                           |    6 
 OpenMx-2.11.3/OpenMx/R/MxExpectationMixture.R                                                          |   25 
 OpenMx-2.11.3/OpenMx/R/MxExpectationNormal.R                                                           |  137 -
 OpenMx-2.11.3/OpenMx/R/MxExpectationRAM.R                                                              |    6 
 OpenMx-2.11.3/OpenMx/R/MxExpectationStateSpace.R                                                       |   40 
 OpenMx-2.11.3/OpenMx/R/MxFIMLObjective.R                                                               |    2 
 OpenMx-2.11.3/OpenMx/R/MxFactorScores.R                                                                |    2 
 OpenMx-2.11.3/OpenMx/R/MxFitFunction.R                                                                 |    2 
 OpenMx-2.11.3/OpenMx/R/MxFitFunctionAlgebra.R                                                          |    2 
 OpenMx-2.11.3/OpenMx/R/MxFitFunctionGREML.R                                                            |    2 
 OpenMx-2.11.3/OpenMx/R/MxFitFunctionML.R                                                               |    2 
 OpenMx-2.11.3/OpenMx/R/MxFitFunctionR.R                                                                |    2 
 OpenMx-2.11.3/OpenMx/R/MxFitFunctionRow.R                                                              |    2 
 OpenMx-2.11.3/OpenMx/R/MxFitFunctionWLS.R                                                              |    5 
 OpenMx-2.11.3/OpenMx/R/MxFlatModel.R                                                                   |    2 
 OpenMx-2.11.3/OpenMx/R/MxFlatSearchReplace.R                                                           |    2 
 OpenMx-2.11.3/OpenMx/R/MxGraph.R                                                                       |    2 
 OpenMx-2.11.3/OpenMx/R/MxGraphviz.R                                                                    |    2 
 OpenMx-2.11.3/OpenMx/R/MxInterval.R                                                                    |    6 
 OpenMx-2.11.3/OpenMx/R/MxLISRELModel.R                                                                 |    2 
 OpenMx-2.11.3/OpenMx/R/MxLISRELObjective.R                                                             |    2 
 OpenMx-2.11.3/OpenMx/R/MxMI.R                                                                          |    2 
 OpenMx-2.11.3/OpenMx/R/MxMLObjective.R                                                                 |    2 
 OpenMx-2.11.3/OpenMx/R/MxMMI.R                                                                         |only
 OpenMx-2.11.3/OpenMx/R/MxMatrix.R                                                                      |    7 
 OpenMx-2.11.3/OpenMx/R/MxMatrixFunctions.R                                                             |    2 
 OpenMx-2.11.3/OpenMx/R/MxModel.R                                                                       |   10 
 OpenMx-2.11.3/OpenMx/R/MxModelDisplay.R                                                                |    2 
 OpenMx-2.11.3/OpenMx/R/MxModelFunctions.R                                                              |   20 
 OpenMx-2.11.3/OpenMx/R/MxModelParameters.R                                                             |   39 
 OpenMx-2.11.3/OpenMx/R/MxMultiModel.R                                                                  |   14 
 OpenMx-2.11.3/OpenMx/R/MxNamespace.R                                                                   |    7 
 OpenMx-2.11.3/OpenMx/R/MxObjectiveMetaData.R                                                           |    2 
 OpenMx-2.11.3/OpenMx/R/MxOptions.R                                                                     |   14 
 OpenMx-2.11.3/OpenMx/R/MxPath.R                                                                        |    5 
 OpenMx-2.11.3/OpenMx/R/MxRAMMetaData.R                                                                 |    2 
 OpenMx-2.11.3/OpenMx/R/MxRAMModel.R                                                                    |    2 
 OpenMx-2.11.3/OpenMx/R/MxRAMObjective.R                                                                |    2 
 OpenMx-2.11.3/OpenMx/R/MxRAMtoML.R                                                                     |    2 
 OpenMx-2.11.3/OpenMx/R/MxRObjective.R                                                                  |    2 
 OpenMx-2.11.3/OpenMx/R/MxRename.R                                                                      |   36 
 OpenMx-2.11.3/OpenMx/R/MxReservedNames.R                                                               |    2 
 OpenMx-2.11.3/OpenMx/R/MxRestore.R                                                                     |    2 
 OpenMx-2.11.3/OpenMx/R/MxRetro.R                                                                       |    2 
 OpenMx-2.11.3/OpenMx/R/MxRobustSE.R                                                                    |   28 
 OpenMx-2.11.3/OpenMx/R/MxRowObjective.R                                                                |    2 
 OpenMx-2.11.3/OpenMx/R/MxRun.R                                                                         |    9 
 OpenMx-2.11.3/OpenMx/R/MxRunHelperFunctions.R                                                          |    2 
 OpenMx-2.11.3/OpenMx/R/MxSE.R                                                                          |   46 
 OpenMx-2.11.3/OpenMx/R/MxSaturatedModel.R                                                              |    2 
 OpenMx-2.11.3/OpenMx/R/MxSearchReplace.R                                                               |    2 
 OpenMx-2.11.3/OpenMx/R/MxSquareBracket.R                                                               |    2 
 OpenMx-2.11.3/OpenMx/R/MxSummary.R                                                                     |  109 
 OpenMx-2.11.3/OpenMx/R/MxSwift.R                                                                       |    2 
 OpenMx-2.11.3/OpenMx/R/MxThreshold.R                                                                   |    2 
 OpenMx-2.11.3/OpenMx/R/MxTryHard.R                                                                     |  204 +
 OpenMx-2.11.3/OpenMx/R/MxTypes.R                                                                       |    2 
 OpenMx-2.11.3/OpenMx/R/MxUnitTesting.R                                                                 |    2 
 OpenMx-2.11.3/OpenMx/R/MxUntitled.R                                                                    |    2 
 OpenMx-2.11.3/OpenMx/R/MxVersion.R                                                                     |    4 
 OpenMx-2.11.3/OpenMx/R/MxVersion.R.in                                                                  |    2 
 OpenMx-2.11.3/OpenMx/R/OriginalMx.R                                                                    |    2 
 OpenMx-2.11.3/OpenMx/R/SdiagMatrix.R                                                                   |    2 
 OpenMx-2.11.3/OpenMx/R/StandMatrix.R                                                                   |    2 
 OpenMx-2.11.3/OpenMx/R/SymmMatrix.R                                                                    |    2 
 OpenMx-2.11.3/OpenMx/R/UnitMatrix.R                                                                    |    2 
 OpenMx-2.11.3/OpenMx/R/ZeroMatrix.R                                                                    |    2 
 OpenMx-2.11.3/OpenMx/R/omxBrownie.R                                                                    |    9 
 OpenMx-2.11.3/OpenMx/R/omxConstrainThresholds.R                                                        |    2 
 OpenMx-2.11.3/OpenMx/R/omxGetNPSOL.R                                                                   |    2 
 OpenMx-2.11.3/OpenMx/R/sysdata.rda                                                                     |binary
 OpenMx-2.11.3/OpenMx/R/zzz.R                                                                           |   21 
 OpenMx-2.11.3/OpenMx/configure                                                                         |    3 
 OpenMx-2.11.3/OpenMx/demo/AlternativeApproaches.R                                                      |    8 
 OpenMx-2.11.3/OpenMx/demo/BivariateCorrelation.R                                                       |    2 
 OpenMx-2.11.3/OpenMx/demo/BivariateHeterogeneity_MatrixRaw.R                                           |   27 
 OpenMx-2.11.3/OpenMx/demo/BivariateHeterogeneity_PathRaw.R                                             |   40 
 OpenMx-2.11.3/OpenMx/demo/BivariateSaturated.R                                                         |   32 
 OpenMx-2.11.3/OpenMx/demo/BivariateSaturated_MatrixCov.R                                               |    8 
 OpenMx-2.11.3/OpenMx/demo/BivariateSaturated_MatrixCovCholesky.R                                       |    8 
 OpenMx-2.11.3/OpenMx/demo/BivariateSaturated_MatrixRaw.R                                               |    6 
 OpenMx-2.11.3/OpenMx/demo/BivariateSaturated_MatrixRawCholesky.R                                       |    2 
 OpenMx-2.11.3/OpenMx/demo/BivariateSaturated_PathCov.R                                                 |   12 
 OpenMx-2.11.3/OpenMx/demo/BivariateSaturated_PathRaw.R                                                 |    6 
 OpenMx-2.11.3/OpenMx/demo/DefinitionMeans_MatrixRaw.R                                                  |    2 
 OpenMx-2.11.3/OpenMx/demo/DefinitionMeans_PathRaw.R                                                    |    2 
 OpenMx-2.11.3/OpenMx/demo/GrowthMixtureModel_MatrixRaw.R                                               |   33 
 OpenMx-2.11.3/OpenMx/demo/GrowthMixtureModel_PathRaw.R                                                 |   24 
 OpenMx-2.11.3/OpenMx/demo/LISRELJointFactorModel.R                                                     |    2 
 OpenMx-2.11.3/OpenMx/demo/LatentGrowthCurveModel_MatrixRaw.R                                           |   20 
 OpenMx-2.11.3/OpenMx/demo/LatentGrowthCurveModel_PathRaw.R                                             |   14 
 OpenMx-2.11.3/OpenMx/demo/LatentGrowthCurveModel_PathRaw_ModelRec.R                                    |   14 
 OpenMx-2.11.3/OpenMx/demo/LatentGrowthCurveModel_PathRaw_ObjectAdd.R                                   |   14 
 OpenMx-2.11.3/OpenMx/demo/MatrixAlgebra.R                                                              |    2 
 OpenMx-2.11.3/OpenMx/demo/MultipleRegression_MatrixCov.R                                               |   20 
 OpenMx-2.11.3/OpenMx/demo/MultipleRegression_MatrixRaw.R                                               |   22 
 OpenMx-2.11.3/OpenMx/demo/MultipleRegression_PathCov.R                                                 |   20 
 OpenMx-2.11.3/OpenMx/demo/MultipleRegression_PathRaw.R                                                 |   22 
 OpenMx-2.11.3/OpenMx/demo/MultivariateRegression_MatrixCov.R                                           |   28 
 OpenMx-2.11.3/OpenMx/demo/MultivariateRegression_MatrixRaw.R                                           |   30 
 OpenMx-2.11.3/OpenMx/demo/MultivariateRegression_PathCov.R                                             |   28 
 OpenMx-2.11.3/OpenMx/demo/MultivariateRegression_PathRaw.R                                             |   30 
 OpenMx-2.11.3/OpenMx/demo/OneFactorJoint_MatrixRawRAM.R                                                |    2 
 OpenMx-2.11.3/OpenMx/demo/OneFactorJoint_PathRaw.R                                                     |    2 
 OpenMx-2.11.3/OpenMx/demo/OneFactorMatrixDemo.R                                                        |    2 
 OpenMx-2.11.3/OpenMx/demo/OneFactorModel_LikelihoodVector.R                                            |   38 
 OpenMx-2.11.3/OpenMx/demo/OneFactorModel_MatrixCov.R                                                   |   38 
 OpenMx-2.11.3/OpenMx/demo/OneFactorModel_MatrixRaw.R                                                   |   38 
 OpenMx-2.11.3/OpenMx/demo/OneFactorModel_PathCov.R                                                     |   38 
 OpenMx-2.11.3/OpenMx/demo/OneFactorModel_PathRaw.R                                                     |   38 
 OpenMx-2.11.3/OpenMx/demo/OneFactorOrdinal01_MatrixRaw.R                                               |    2 
 OpenMx-2.11.3/OpenMx/demo/OneFactorOrdinal_MatrixRaw.R                                                 |    2 
 OpenMx-2.11.3/OpenMx/demo/OneFactorOrdinal_MatrixRawRAM.R                                              |    2 
 OpenMx-2.11.3/OpenMx/demo/OneFactorOrdinal_PathRaw.R                                                   |    2 
 OpenMx-2.11.3/OpenMx/demo/OneFactorPathDemo.R                                                          |    2 
 OpenMx-2.11.3/OpenMx/demo/OneLocusLikelihood.R                                                         |    2 
 OpenMx-2.11.3/OpenMx/demo/RObjectiveLISRELFactorRegression.R                                           |   14 
 OpenMx-2.11.3/OpenMx/demo/RowObjectiveFIMLBivariateSaturated.R                                         |    2 
 OpenMx-2.11.3/OpenMx/demo/RowObjectiveSimpleExamples.R                                                 |   10 
 OpenMx-2.11.3/OpenMx/demo/SimpleCheckpoint.R                                                           |    2 
 OpenMx-2.11.3/OpenMx/demo/SimpleRegression_MatrixCov.R                                                 |   12 
 OpenMx-2.11.3/OpenMx/demo/SimpleRegression_MatrixRaw.R                                                 |   14 
 OpenMx-2.11.3/OpenMx/demo/SimpleRegression_PathCov.R                                                   |   12 
 OpenMx-2.11.3/OpenMx/demo/SimpleRegression_PathRaw.R                                                   |   12 
 OpenMx-2.11.3/OpenMx/demo/TwoFactorModel_MatrixCov.R                                                   |   40 
 OpenMx-2.11.3/OpenMx/demo/TwoFactorModel_MatrixRaw.R                                                   |   40 
 OpenMx-2.11.3/OpenMx/demo/TwoFactorModel_PathCov.R                                                     |   40 
 OpenMx-2.11.3/OpenMx/demo/TwoFactorModel_PathRaw.R                                                     |   40 
 OpenMx-2.11.3/OpenMx/demo/TwoLocusLikelihood.R                                                         |    2 
 OpenMx-2.11.3/OpenMx/demo/UnivariateSaturated.R                                                        |   24 
 OpenMx-2.11.3/OpenMx/demo/UnivariateSaturated_MatrixCov.R                                              |    8 
 OpenMx-2.11.3/OpenMx/demo/UnivariateSaturated_MatrixRaw.R                                              |    6 
 OpenMx-2.11.3/OpenMx/demo/UnivariateSaturated_PathCov.R                                                |    8 
 OpenMx-2.11.3/OpenMx/demo/UnivariateSaturated_PathRaw.R                                                |    6 
 OpenMx-2.11.3/OpenMx/demo/UnivariateTwinAnalysis.R                                                     |    2 
 OpenMx-2.11.3/OpenMx/demo/UnivariateTwinAnalysis_MatrixRaw.R                                           |    2 
 OpenMx-2.11.3/OpenMx/demo/UnivariateTwinAnalysis_PathRaw.R                                             |    2 
 OpenMx-2.11.3/OpenMx/demo/mxThreshold.R                                                                |    2 
 OpenMx-2.11.3/OpenMx/demo/omxConstrainMLThresholds.R                                                   |    2 
 OpenMx-2.11.3/OpenMx/inst/CITATION                                                                     |    4 
 OpenMx-2.11.3/OpenMx/inst/models/failing/MultilevelLongFormatFailing.R                                 |    2 
 OpenMx-2.11.3/OpenMx/inst/models/failing/SimpleConfidenceIntervals.R                                   |    2 
 OpenMx-2.11.3/OpenMx/inst/models/failing/mice.R                                                        |only
 OpenMx-2.11.3/OpenMx/inst/models/failing/no_longer_able_to_be_run/BivariateSaturated_WLSMatrixCov.R    |    2 
 OpenMx-2.11.3/OpenMx/inst/models/failing/no_longer_able_to_be_run/ExtraOrdinalVars.R                   |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWith2LevelModerator-a.R                        |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWith2LevelModerator-b.R                        |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWith2LevelModerator-c.R                        |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWith2LevelModeratorAndMissing-a.R              |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWith2LevelModeratorAndMissing-b.R              |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWith2LevelModeratorAndMissing-c.R              |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWithContinuousModerator-a.R                    |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWithContinuousModerator-b.R                    |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWithContinuousModerator-c.R                    |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWithContinuousModerator-d.R                    |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/3LatentMultiRegWithContinuousModerator-e.R                    |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/BootLRT.R                                                     |    4 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/BootstrapParallelNightly.R                                    |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/ETC88.R                                                       |    5 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/FactorScores.R                                                |   10 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/GREML_monophenotype_1GRM.R                                    |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/GREML_monophenotype_1GRM_GradDesc.R                           |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/GrowthMixtureModelRandomStarts.R                              |    6 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/InvalidComparisonDetection.R                                  |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/JointWLS.R                                                    |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/ModelIdentification.R                                         |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/ModificationIndexCheck.R                                      |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/MultigroupRobustSE_test.R                                     |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/MultilevelStateSpaceEx5.R                                     |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/NelderMeadUnitTesting.R                                       |   19 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/OneFactorOrdinal01_MatrixRaw.R                                |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/OneFactorOrdinal_MatrixRaw.R                                  |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/PPML_100days.R                                                |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/PPML_100days_cov.R                                            |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/PPML_100days_cov_baseline.R                                   |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/PPML_100days_raw.R                                            |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/PPML_100days_raw_baseline.R                                   |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/PPML_test1L2M.R                                               |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/PPML_test1L3M.R                                               |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RAM-3Factor-12Indicators-covdata-a.R                          |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RAM-3Factor-12Indicators-rawdata-a.R                          |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RAM-3Factor-24Indicators-covdata-a-intervals.R                |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RAM-3Factor-24Indicators-covdata-a.R                          |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RAM-3Factor-24Indicators-megadata-a.R                         |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RAM-3Factor-24Indicators-rawdata-a.R                          |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RAM-3Factor-48Indicators-covdata-a.R                          |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RAM-3Factor-48Indicators-rawdata-a.R                          |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RAM-3Factor-96Indicators-covdata-a.R                          |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RegimeSwitching_MatrixRawNoCholDifferentTransitions.R         |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/RegimeSwitching_MatrixRawNoCholDifferentTransitionsAllFixed.R |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/StateSpaceContinuous.R                                        |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/multimodelInferenceTest.R                                     |only
 OpenMx-2.11.3/OpenMx/inst/models/nightly/mxPowerDetail.R                                               |only
 OpenMx-2.11.3/OpenMx/inst/models/nightly/startsTestMissing.R                                           |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/startsTestNoMissing.R                                         |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/thresholdModel1Factor3Variate.R                               |   15 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/thresholdModel1Factor5Variate.R                               |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/thresholdModel1Factor5VariateWLS.R                            |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/thresholdModel1Factor8Variate.R                               |    2 
 OpenMx-2.11.3/OpenMx/inst/models/nightly/univACErSEM.R                                                 |    2 
 OpenMx-2.11.3/OpenMx/inst/models/passing/ACEDuplicateMatrices.R                                        |    2 
 OpenMx-2.11.3/OpenMx/inst/models/passing/ACELRTCI20160808.R                                            |    2 
 OpenMx-2.11.3/OpenMx/inst/models/passing/Acemix.R                                                      |    2 
 OpenMx-2.11.3/OpenMx/inst/models/passing/Acemix2.R                                                     |    2 
 OpenMx-2.11.3/OpenMx/inst/models/passing/AlgebraComputePassing.R                                       |    6 
 OpenMx-2.11.3/OpenMx/inst/models/passing/AlgebraDeriv.R                                                |    2 
 OpenMx-2.11.3/OpenMx/inst/models/passing/AlgebraErrorDetection.R                                       |    2 
 OpenMx-2.11.3/OpenMx/inst/models/passing/AlgebraTransformations.R                                      |    2 
 OpenMx-2.11.3/OpenMx/inst/models/passing/AnalyticConstraintJacobians--Eq_and_Ineq.R                    |    2 
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 OpenMx-2.11.3/OpenMx/man/mxFitFunctionRow.Rd                                                           |    2 
 OpenMx-2.11.3/OpenMx/man/mxFitFunctionWLS.Rd                                                           |    2 
 OpenMx-2.11.3/OpenMx/man/mxGenerateData.Rd                                                             |   11 
 OpenMx-2.11.3/OpenMx/man/mxGetExpected.Rd                                                              |    2 
 OpenMx-2.11.3/OpenMx/man/mxKalmanScores.Rd                                                             |    2 
 OpenMx-2.11.3/OpenMx/man/mxLISRELObjective.Rd                                                          |    2 
 OpenMx-2.11.3/OpenMx/man/mxMI.Rd                                                                       |    2 
 OpenMx-2.11.3/OpenMx/man/mxMLObjective.Rd                                                              |    2 
 OpenMx-2.11.3/OpenMx/man/mxMatrix.Rd                                                                   |    5 
 OpenMx-2.11.3/OpenMx/man/mxModel.Rd                                                                    |    2 
 OpenMx-2.11.3/OpenMx/man/mxOption.Rd                                                                   |    9 
 OpenMx-2.11.3/OpenMx/man/mxPath.Rd                                                                     |    2 
 OpenMx-2.11.3/OpenMx/man/mxPearsonSelCov.Rd                                                            |only
 OpenMx-2.11.3/OpenMx/man/mxPower.Rd                                                                    |    7 
 OpenMx-2.11.3/OpenMx/man/mxRAMObjective.Rd                                                             |    2 
 OpenMx-2.11.3/OpenMx/man/mxRObjective.Rd                                                               |    2 
 OpenMx-2.11.3/OpenMx/man/mxRename.Rd                                                                   |    2 
 OpenMx-2.11.3/OpenMx/man/mxRestore.Rd                                                                  |    2 
 OpenMx-2.11.3/OpenMx/man/mxRowObjective.Rd                                                             |    2 
 OpenMx-2.11.3/OpenMx/man/mxRun.Rd                                                                      |   41 
 OpenMx-2.11.3/OpenMx/man/mxSE.Rd                                                                       |   24 
 OpenMx-2.11.3/OpenMx/man/mxSave.Rd                                                                     |    2 
 OpenMx-2.11.3/OpenMx/man/mxStandardizeRAMpaths.Rd                                                      |   18 
 OpenMx-2.11.3/OpenMx/man/mxThreshold.Rd                                                                |    2 
 OpenMx-2.11.3/OpenMx/man/mxTryHard.Rd                                                                  |   12 
 OpenMx-2.11.3/OpenMx/man/mxTypes.Rd                                                                    |    2 
 OpenMx-2.11.3/OpenMx/man/mxVersion.Rd                                                                  |    2 
 OpenMx-2.11.3/OpenMx/man/myFADataRaw.Rd                                                                |    2 
 OpenMx-2.11.3/OpenMx/man/omxAllInt.Rd                                                                  |    2 
 OpenMx-2.11.3/OpenMx/man/omxApply.Rd                                                                   |    2 
 OpenMx-2.11.3/OpenMx/man/omxAssignFirstParameters.Rd                                                   |    2 
 OpenMx-2.11.3/OpenMx/man/omxBrownie.Rd                                                                 |    2 
 OpenMx-2.11.3/OpenMx/man/omxCheckEquals.Rd                                                             |    2 
 OpenMx-2.11.3/OpenMx/man/omxCheckIdentical.Rd                                                          |    2 
 OpenMx-2.11.3/OpenMx/man/omxCheckSetEquals.Rd                                                          |    2 
 OpenMx-2.11.3/OpenMx/man/omxCheckTrue.Rd                                                               |    2 
 OpenMx-2.11.3/OpenMx/man/omxCheckWithinPercentError.Rd                                                 |    2 
 OpenMx-2.11.3/OpenMx/man/omxGetParameters.Rd                                                           |   30 
 OpenMx-2.11.3/OpenMx/man/omxGraphviz.Rd                                                                |    2 
 OpenMx-2.11.3/OpenMx/man/omxLapply.Rd                                                                  |    2 
 OpenMx-2.11.3/OpenMx/man/omxLocateParameters.Rd                                                        |   24 
 OpenMx-2.11.3/OpenMx/man/omxLogical.Rd                                                                 |    2 
 OpenMx-2.11.3/OpenMx/man/omxMatrixOperations.Rd                                                        |    2 
 OpenMx-2.11.3/OpenMx/man/omxMnor.Rd                                                                    |    2 
 OpenMx-2.11.3/OpenMx/man/omxModelDeleteData.Rd                                                         |    2 
 OpenMx-2.11.3/OpenMx/man/omxParallelCI.Rd                                                              |   44 
 OpenMx-2.11.3/OpenMx/man/omxRMSEA.Rd                                                                   |    2 
 OpenMx-2.11.3/OpenMx/man/omxSapply.Rd                                                                  |    2 
 OpenMx-2.11.3/OpenMx/man/omxSaturatedModel.Rd                                                          |    2 
 OpenMx-2.11.3/OpenMx/man/omxSelectRowsAndCols.Rd                                                       |    2 
 OpenMx-2.11.3/OpenMx/man/omxSetParameters.Rd                                                           |    2 
 OpenMx-2.11.3/OpenMx/man/rvectorize.Rd                                                                 |    2 
 OpenMx-2.11.3/OpenMx/man/summary.MxModel.Rd                                                            |    2 
 OpenMx-2.11.3/OpenMx/man/tr.Rd                                                                         |    2 
 OpenMx-2.11.3/OpenMx/man/twinData.Rd                                                                   |    2 
 OpenMx-2.11.3/OpenMx/man/vec2diag.Rd                                                                   |    2 
 OpenMx-2.11.3/OpenMx/man/vech.Rd                                                                       |    2 
 OpenMx-2.11.3/OpenMx/man/vech2full.Rd                                                                  |    2 
 OpenMx-2.11.3/OpenMx/man/vechs.Rd                                                                      |    2 
 OpenMx-2.11.3/OpenMx/man/vechs2full.Rd                                                                 |    2 
 OpenMx-2.11.3/OpenMx/src/AlgebraFunctions.h                                                            |  175 +
 OpenMx-2.11.3/OpenMx/src/Compute.cpp                                                                   |  695 +++++
 OpenMx-2.11.3/OpenMx/src/Compute.h                                                                     |   11 
 OpenMx-2.11.3/OpenMx/src/ComputeGD.cpp                                                                 |  628 ++++-
 OpenMx-2.11.3/OpenMx/src/ComputeGD.h                                                                   |    6 
 OpenMx-2.11.3/OpenMx/src/ComputeNM.cpp                                                                 |   28 
 OpenMx-2.11.3/OpenMx/src/ComputeNM.h                                                                   |    2 
 OpenMx-2.11.3/OpenMx/src/ComputeNR.cpp                                                                 |    9 
 OpenMx-2.11.3/OpenMx/src/ComputeSD.cpp                                                                 |    2 
 OpenMx-2.11.3/OpenMx/src/Connectedness.h                                                               |    2 
 OpenMx-2.11.3/OpenMx/src/EnableWarnings.h                                                              |    5 
 OpenMx-2.11.3/OpenMx/src/FellnerFitFunction.cpp                                                        |    2 
 OpenMx-2.11.3/OpenMx/src/Makevars.in                                                                   |    2 
 OpenMx-2.11.3/OpenMx/src/Makevars.win                                                                  |    5 
 OpenMx-2.11.3/OpenMx/src/MarkovExpectation.cpp                                                         |   16 
 OpenMx-2.11.3/OpenMx/src/MarkovFF.cpp                                                                  |    2 
 OpenMx-2.11.3/OpenMx/src/asa.c                                                                         |only
 OpenMx-2.11.3/OpenMx/src/asa.h                                                                         |only
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 OpenMx-2.11.3/OpenMx/src/ba81quad.cpp                                                                  |    2 
 OpenMx-2.11.3/OpenMx/src/finiteDifferences.h                                                           |   27 
 OpenMx-2.11.3/OpenMx/src/glue.cpp                                                                      |   14 
 OpenMx-2.11.3/OpenMx/src/glue.h                                                                        |    2 
 OpenMx-2.11.3/OpenMx/src/jsoncons                                                                      |only
 OpenMx-2.11.3/OpenMx/src/jsoncons_ext                                                                  |only
 OpenMx-2.11.3/OpenMx/src/minicsv.h                                                                     |only
 OpenMx-2.11.3/OpenMx/src/nloptcpp.cpp                                                                  |   30 
 OpenMx-2.11.3/OpenMx/src/omxAlgebra.cpp                                                                |    2 
 OpenMx-2.11.3/OpenMx/src/omxAlgebra.h                                                                  |    2 
 OpenMx-2.11.3/OpenMx/src/omxAlgebraFitFunction.cpp                                                     |    2 
 OpenMx-2.11.3/OpenMx/src/omxCsolnp.h                                                                   |    2 
 OpenMx-2.11.3/OpenMx/src/omxData.cpp                                                                   |  247 +
 OpenMx-2.11.3/OpenMx/src/omxData.h                                                                     |   11 
 OpenMx-2.11.3/OpenMx/src/omxDefines.h                                                                  |    4 
 OpenMx-2.11.3/OpenMx/src/omxExpectation.cpp                                                            |   82 
 OpenMx-2.11.3/OpenMx/src/omxExpectation.h                                                              |    7 
 OpenMx-2.11.3/OpenMx/src/omxExportBackendState.cpp                                                     |    2 
 OpenMx-2.11.3/OpenMx/src/omxFIMLFitFunction.cpp                                                        |   50 
 OpenMx-2.11.3/OpenMx/src/omxFIMLFitFunction.h                                                          |   12 
 OpenMx-2.11.3/OpenMx/src/omxFitFunction.cpp                                                            |    3 
 OpenMx-2.11.3/OpenMx/src/omxFitFunction.h                                                              |    3 
 OpenMx-2.11.3/OpenMx/src/omxFitFunctionBA81.cpp                                                        |    5 
 OpenMx-2.11.3/OpenMx/src/omxGREMLExpectation.cpp                                                       |   19 
 OpenMx-2.11.3/OpenMx/src/omxGREMLExpectation.h                                                         |    2 
 OpenMx-2.11.3/OpenMx/src/omxGREMLfitfunction.cpp                                                       |   76 
 OpenMx-2.11.3/OpenMx/src/omxHessianCalculation.cpp                                                     |    6 
 OpenMx-2.11.3/OpenMx/src/omxImportFrontendState.cpp                                                    |    5 
 OpenMx-2.11.3/OpenMx/src/omxLISRELExpectation.cpp                                                      |    2 
 OpenMx-2.11.3/OpenMx/src/omxLISRELExpectation.h                                                        |    2 
 OpenMx-2.11.3/OpenMx/src/omxMLFitFunction.cpp                                                          |   20 
 OpenMx-2.11.3/OpenMx/src/omxMatrix.cpp                                                                 |   79 
 OpenMx-2.11.3/OpenMx/src/omxMatrix.h                                                                   |   14 
 OpenMx-2.11.3/OpenMx/src/omxNPSOLSpecific.cpp                                                          |    4 
 OpenMx-2.11.3/OpenMx/src/omxNPSOLSpecific.h                                                            |    2 
 OpenMx-2.11.3/OpenMx/src/omxNormalExpectation.cpp                                                      |    7 
 OpenMx-2.11.3/OpenMx/src/omxRAMExpectation.cpp                                                         |    2 
 OpenMx-2.11.3/OpenMx/src/omxRFitFunction.cpp                                                           |    2 
 OpenMx-2.11.3/OpenMx/src/omxRFitFunction.h                                                             |    2 
 OpenMx-2.11.3/OpenMx/src/omxRowFitFunction.cpp                                                         |    2 
 OpenMx-2.11.3/OpenMx/src/omxRowFitFunction.h                                                           |    2 
 OpenMx-2.11.3/OpenMx/src/omxSadmvnWrapper.h                                                            |    2 
 OpenMx-2.11.3/OpenMx/src/omxState.cpp                                                                  |   24 
 OpenMx-2.11.3/OpenMx/src/omxState.h                                                                    |    8 
 OpenMx-2.11.3/OpenMx/src/omxStateSpaceExpectation.cpp                                                  |    2 
 OpenMx-2.11.3/OpenMx/src/omxSymbolTable.cpp                                                            |    2 
 OpenMx-2.11.3/OpenMx/src/omxSymbolTable.h                                                              |    2 
 OpenMx-2.11.3/OpenMx/src/omxWLSFitFunction.cpp                                                         |    2 
 OpenMx-2.11.3/OpenMx/src/sadmvn.f                                                                      |    1 
 OpenMx-2.11.3/OpenMx/src/slsqp.c                                                                       |    2 
 OpenMx-2.11.3/OpenMx/src/ssMLFit.cpp                                                                   |   20 
 OpenMx-2.11.3/OpenMx/src/subnp.cpp                                                                     |   17 
 613 files changed, 5258 insertions(+), 2305 deletions(-)

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New package mhurdle with initial version 1.1-8
Package: mhurdle
Version: 1.1-8
Date: 2018-09-17
Title: Multiple Hurdle Tobit Models
Authors@R: c(person("Yves", "Croissant", role = c("aut", "cre"), email = "yves.croissant@univ-reunion.fr"), person("Fabrizio", "Carlevaro", role = "aut", email = "fabrizio.carlevaro@unige.ch"), person("Stephane", "Hoareau", role = "aut", email = "sjlhoaro@univ-reunion.fr"))
Depends: R (>= 2.10), methods, Formula, truncreg, maxLik, survival, texreg
Description: Estimation of models with zero left-censored variables. Null values may be caused by a selection process (Cragg (1971) <doi:10.2307/1909582>), insufficient resources (Tobin (1958) <doi:10.2307/1907382>) or infrequency of purchase (Deaton and Irish (1984) <doi:10.1016/0047-2727(84)90067-7>).
License: GPL (>= 2)
URL: https://www.R-project.org
Author: Yves Croissant [aut, cre], Fabrizio Carlevaro [aut], Stephane Hoareau [aut]
Maintainer: Yves Croissant <yves.croissant@univ-reunion.fr>
Repository: CRAN
Repository/R-Forge/Project: mhurdle
Repository/R-Forge/Revision: 75
Repository/R-Forge/DateTimeStamp: 2018-09-18 13:53:04
Date/Publication: 2018-09-18 17:00:07 UTC
NeedsCompilation: yes
Packaged: 2018-09-18 14:10:42 UTC; rforge

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Package EValue updated to version 1.1.5 with previous version 1.1.4 dated 2018-05-18

Title: Sensitivity Analyses for Unmeasured Confounding in Observational Studies and Meta-Analyses
Description: Conducts sensitivity analyses for unmeasured confounding for either an observational study or a meta-analysis of observational studies. For a single observational study, the package reports E-values, defined as the minimum strength of association on the risk ratio scale that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment-outcome association, conditional on the measured covariates. You can use one of the evalues.XX() functions to compute E-values for the relevant outcome types. Outcome types include risk ratios, odds ratio with common or rare outcomes, hazard ratios with common or rare outcomes, and standardized differences in outcomes. Optionally, you can use the bias_plot() function to plot the bias factor as a function of two sensitivity parameters. (See VanderWeele & Ding, 2017 [<http://annals.org/aim/article/2643434>] for details.) For a meta-analysis, use the function confounded_meta to compute point estimates and inference for: (1) the proportion of studies with true causal effect sizes more extreme than a specified threshold of scientific importance; and (2) the minimum bias factor and confounding strength required to reduce to less than a specified threshold the proportion of studies with true effect sizes of scientifically significant size. The functions sens_plot() and sens_table() create plots and tables for visualizing these meta-analysis metrics across a range of bias values, and scrape_meta helps scrape study-level data from a published forest plot or summary table to obtain the needed estimates when these are not reported. (See Mathur & VanderWeele [<https://osf.io/jkhfg/>] for details.) Most of the analyses available in this package can also be conducted using web-based graphical interfaces (for a single observational study: [<https://evalue.hmdc.harvard.edu/app/>]; for a meta-analysis: [<https://mmathur.shinyapps.io/meta_gui_2/>]).
Author: Maya B. Mathur, Peng Ding, Tyler J. VanderWeele
Maintainer: Maya B. Mathur <mmathur@stanford.edu>

Diff between EValue versions 1.1.4 dated 2018-05-18 and 1.1.5 dated 2018-09-18

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Package SPUTNIK updated to version 1.0.3.4 with previous version 1.0.3.3 dated 2018-08-22

Title: SPatially aUTomatic deNoising for Ims toolKit
Description: A set of tools for the peak filtering of mass spectrometry imaging data (MSI or IMS) based on spatial distribution of signal. Given a region-of-interest (ROI), representing the spatial region where the informative signal is expected to be localized, a series of filters determine which peak signals are characterized by an implausible spatial distribution. The filters reduce the dataset dimensionality and increase its information vs noise ratio, improving the quality of the unsupervised analysis results, reducing data dimensionality and simplifying the chemical interpretation.
Author: Paolo Inglese [aut, cre], Goncalo Correia [aut, ctb]
Maintainer: Paolo Inglese <p.inglese14@imperial.ac.uk>

Diff between SPUTNIK versions 1.0.3.3 dated 2018-08-22 and 1.0.3.4 dated 2018-09-18

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Package cartography updated to version 2.1.2 with previous version 2.1.1 dated 2018-06-25

Title: Thematic Cartography
Description: Create and integrate maps in your R workflow. This package allows various cartographic representations such as proportional symbols, choropleth, typology, flows or discontinuities maps. It also offers several features enhancing the graphic presentation of maps like cartographic palettes, layout elements (scale, north arrow, title...), labels, legends or access to some cartographic APIs. See Giraud and Lambert (2017) <doi:10.1007/978-3-319-57336-6_13>.
Author: Timothée Giraud [cre, aut], Nicolas Lambert [aut], Ian Fellows [cph] (no overlap algorithm for labels, from wordcloud package)
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>

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Package ReIns updated to version 1.0.8 with previous version 1.0.7 dated 2018-04-24

Title: Functions from "Reinsurance: Actuarial and Statistical Aspects"
Description: Functions from the book "Reinsurance: Actuarial and Statistical Aspects" (2017) by Hansjoerg Albrecher, Jan Beirlant and Jef Teugels <http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470772689.html>.
Author: Tom Reynkens [aut, cre] (<https://orcid.org/0000-0002-5516-5107>), Roel Verbelen [aut] (R code for Mixed Erlang distribution, <https://orcid.org/0000-0002-2347-9240>), Anastasios Bardoutsos [ctb] (Original R code for cEPD estimator), Dries Cornilly [ctb] (Original R code for EVT estimators for truncated data), Yuri Goegebeur [ctb] (Original S-Plus code for basic EVT estimators), Klaus Herrmann [ctb] (Original R code for GPD estimator)
Maintainer: Tom Reynkens <tomreynkens@hotmail.com>

Diff between ReIns versions 1.0.7 dated 2018-04-24 and 1.0.8 dated 2018-09-18

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Package tram updated to version 0.2-3 with previous version 0.2-2 dated 2018-06-22

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 polmineR updated to version 0.7.10 with previous version 0.7.9 dated 2018-07-09

Title: Toolkit for Corpus Analysis
Description: Library for corpus analysis using the Corpus Workbench as an efficient back end for indexing and querying large corpora. The package offers functionality to flexibly create partitions and to carry out basic statistical operations (count, co-occurrences etc.). The original full text of documents can be reconstructed and inspected at any time. Beyond that, the package is intended to serve as an interface to packages implementing advanced statistical procedures. Respective data structures (document term matrices, term co- occurrence matrices etc.) can be created based on the indexed corpora.
Author: Andreas Blaette [aut, cre] (<https://orcid.org/0000-0001-8970-8010>)
Maintainer: Andreas Blaette <andreas.blaette@uni-due.de>

Diff between polmineR versions 0.7.9 dated 2018-07-09 and 0.7.10 dated 2018-09-18

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Package miceadds updated to version 2.14-26 with previous version 2.13-63 dated 2018-07-05

Title: Some Additional Multiple Imputation Functions, Especially for 'mice'
Description: Contains some auxiliary functions for multiple imputation which complements existing functionality in R. In addition to some utility functions, main features include plausible value imputation, multilevel imputation functions (arbitrary number of levels, hierarchical and non-hierarchical datasets), imputation using partial least squares (PLS) for high dimensional predictors, and nested multiple imputation.
Author: Alexander Robitzsch [aut, cre], Simon Grund [aut], Thorsten Henke [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between miceadds versions 2.13-63 dated 2018-07-05 and 2.14-26 dated 2018-09-18

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Package VineCopula updated to version 2.1.8 with previous version 2.1.7 dated 2018-08-31

Title: Statistical Inference of Vine Copulas
Description: Provides tools for the statistical analysis of vine copula models. The package includes tools for parameter estimation, model selection, simulation, goodness-of-fit tests, and visualization. Tools for estimation, selection and exploratory data analysis of bivariate copula models are also provided.
Author: Ulf Schepsmeier [aut], Jakob Stoeber [aut], Eike Christian Brechmann [aut], Benedikt Graeler [aut], Thomas Nagler [aut, cre], Tobias Erhardt [aut], Carlos Almeida [ctb], Aleksey Min [ctb, ths], Claudia Czado [ctb, ths], Mathias Hofmann [ctb], Matthias Killiches [ctb], Harry Joe [ctb], Thibault Vatter [ctb]
Maintainer: Thomas Nagler <thomas.nagler@tum.de>

Diff between VineCopula versions 2.1.7 dated 2018-08-31 and 2.1.8 dated 2018-09-18

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More information about VineCopula at CRAN
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Package trtf updated to version 0.3-3 with previous version 0.3-2 dated 2018-06-23

Title: Transformation Trees and Forests
Description: Recursive partytioning of transformation models with corresponding random forest for conditional transformation models as described in 'Transformation Forests' (Hothorn and Zeileis, 2017, <arXiv:1701.02110>) and 'Top-Down Transformation Choice' (Hothorn, 2018, <DOI:10.1177/1471082X17748081>).
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between trtf versions 0.3-2 dated 2018-06-23 and 0.3-3 dated 2018-09-18

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More information about trtf at CRAN
Permanent link

Package shinyFiles updated to version 0.7.1 with previous version 0.7.0 dated 2018-07-05

Title: A Server-Side File System Viewer for Shiny
Description: Provides functionality for client-side navigation of the server side file system in shiny apps. In case the app is running locally this gives the user direct access to the file system without the need to "download" files to a temporary location. Both file and folder selection as well as file saving is available.
Author: Thomas Lin Pedersen [cre, aut], Vincent Nijs [aut], Eric Nantz [aut]
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>

Diff between shinyFiles versions 0.7.0 dated 2018-07-05 and 0.7.1 dated 2018-09-18

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Permanent link

New package shiny.router with initial version 0.1.1
Package: shiny.router
Type: Package
Title: Basic Routing for Shiny Web Applications
Version: 0.1.1
Author: Filip Stachura <filip@appsilon.com>
Maintainer: Dominik Krzemiński <dominik@appsilon.com>
Description: The minimal router for your Shiny apps. It allows you to create dynamic web applications with real-time user interface and easily share URLs to pages within your Shiny apps.
Encoding: UTF-8
LazyData: true
License: MIT + file LICENSE
Imports: magrittr, shiny
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-09-17 08:17:25 UTC; dominik
Repository: CRAN
Date/Publication: 2018-09-18 08:50:07 UTC

More information about shiny.router at CRAN
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New package RSelenium with initial version 1.7.4
Package: RSelenium
Type: Package
Title: R Bindings for 'Selenium WebDriver'
Version: 1.7.4
Authors@R: c( person("John", "Harrison", , "johndharrison0@gmail.com", role = "aut", comment = "original author"), person("Ju Yeong", "Kim", , "jkim2345@fredhutch.org", role = "cre", comment = "rOpenSci maintainer"))
Description: Provides a set of R bindings for the 'Selenium 2.0 WebDriver' (see <https://seleniumhq.github.io/docs/wd.html> for more information) using the 'JsonWireProtocol' (see <https://github.com/SeleniumHQ/selenium/wiki/JsonWireProtocol> for more information). 'Selenium 2.0 WebDriver' allows driving a web browser natively as a user would either locally or on a remote machine using the Selenium server it marks a leap forward in terms of web browser automation. Selenium automates web browsers (commonly referred to as browsers). Using RSelenium you can automate browsers locally or remotely.
License: AGPL-3
URL: http://ropensci.github.io/RSelenium
BugReports: http://github.com/ropensci/RSelenium/issues
Additional_repositories: http://www.omegahat.net/R
Depends: R (>= 3.0.0)
Imports: XML, methods, caTools, tools, utils, openssl, httr, wdman(>= 0.2.2), binman
Suggests: testthat, knitr, Rcompression, covr, rmarkdown
VignetteBuilder: knitr
LazyData: true
Collate: 'RSelenium.R' 'errorHandler.R' 'remoteDriver.R' 'rsDriver.R' 'selKeys-data.R' 'util.R' 'webElement.R' 'zzz.R'
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-17 18:43:13 UTC; jkim2345
Author: John Harrison [aut] (original author), Ju Yeong Kim [cre] (rOpenSci maintainer)
Maintainer: Ju Yeong Kim <jkim2345@fredhutch.org>
Repository: CRAN
Date/Publication: 2018-09-18 08:30:12 UTC

More information about RSelenium at CRAN
Permanent link

Package personalized updated to version 0.2.0 with previous version 0.1.5 dated 2018-04-11

Title: Estimation and Validation Methods for Subgroup Identification and Personalized Medicine
Description: Provides functions for fitting and validation of subgroup identification and personalized medicine models under the general subgroup identification framework of Chen et al. (2017) <doi:10.1111/biom.12676>. This package is intended for use for both randomized controlled trials and observational studies.
Author: Jared Huling [aut, cre], Aaron Potvien [ctb], Alexandros Karatzoglou [cph], Alex Smola [cph]
Maintainer: Jared Huling <jaredhuling@gmail.com>

Diff between personalized versions 0.1.5 dated 2018-04-11 and 0.2.0 dated 2018-09-18

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Package netrankr updated to version 0.2.1 with previous version 0.2.0 dated 2018-01-08

Title: Analyzing Partial Rankings in Networks
Description: Implements methods for centrality related analyses of networks. While the package includes the possibility to build more than 20 indices, its main focus lies on index-free assessment of centrality via partial rankings obtained by neighborhood-inclusion or positional dominance. These partial rankings can be analyzed with different methods, including probabilistic methods like computing expected node ranks and relative rank probabilities (how likely is it that a node is more central than another?). The methodology is described in depth in the vignettes and in Schoch (2018) <doi:10.1016/j.socnet.2017.12.003>.
Author: David Schoch [aut, cre], Julian Müller [ctb]
Maintainer: David Schoch <david.schoch@manchester.ac.uk>

Diff between netrankr versions 0.2.0 dated 2018-01-08 and 0.2.1 dated 2018-09-18

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Package ndjson updated to version 0.7.0 with previous version 0.6.0 dated 2018-03-05

Title: Wicked-Fast Streaming 'JSON' ('ndjson') Reader
Description: Streaming 'JSON' ('ndjson') has one 'JSON' record per-line and many modern 'ndjson' files contain large numbers of records. These constructs may not be columnar in nature, but it is often useful to read in these files and "flatten" the structure out to enable working with the data in an R 'data.frame'-like context. Functions are provided that make it possible to read in plain 'ndjson' files or compressed ('gz') 'ndjson' files and either validate the format of the records or create "flat" 'data.table' structures from them.
Author: Bob Rudis [aut, cre] (<https://orcid.org/0000-0001-5670-2640>), Niels Lohmann [aut] (C++ json parser), Deepak Bandyopadhyay [aut] (C++ gzstream), Lutz Kettner [aut] (C++ gzstream))
Maintainer: Bob Rudis <bob@rud.is>

Diff between ndjson versions 0.6.0 dated 2018-03-05 and 0.7.0 dated 2018-09-18

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Package mlvocab updated to version 0.1 with previous version 0.0.1 dated 2018-04-13

Title: Vocabulary and Corpus Preprocessing for Natural Language Pipelines
Description: Utilities for preprocessing of text corpora into data structures suitable for natural language models: integer sequences or matrices, vocabulary embedding matrices, term-doc, doc-term, term co-occurrence matrices etc. All functions allow for full or partial hashing of the terms in the vocabulary.
Author: Vitalie Spinu [aut, cre]
Maintainer: Vitalie Spinu <spinuvit@gmail.com>

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Package GAS updated to version 0.2.9 with previous version 0.2.8 dated 2018-08-30

Title: Generalized Autoregressive Score Models
Description: Simulate, estimate and forecast using univariate and multivariate GAS models as described in Ardia et al. (2016) <https://ssrn.com/abstract=2825380>.
Author: Leopoldo Catania [aut,cre], Kris Boudt [ctb], David Ardia [ctb]
Maintainer: Leopoldo Catania <leopoldo.catania@econ.au.dk>

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New package ccfa with initial version 1.1.0
Package: ccfa
Type: Package
Title: Continuous Counterfactual Analysis
Version: 1.1.0
Authors@R: c(person("Weige", "Huang", role=c("aut","cre"), email="weige.huang@temple.edu"), person("Brantly", "Callaway", role="aut", email="brantly.callaway@temple.edu"))
Description: Contains methods for computing counterfactuals with a continuous treatment variable as in Callaway and Huang (2017) <https://ssrn.com/abstract=3078187>. In particular, the package can be used to calculate the expected value, the variance, the interquantile range, the fraction of observations below or above a particular cutoff, or other user-supplied functions of an outcome of interest conditional on a continuous treatment. The package can also be used for computing these same functionals after adjusting for differences in covariates at different values of the treatment. Further, one can use the package to conduct uniform inference for each parameter of interest across all values of the treatment, uniformly test whether adjusting for covariates makes a difference at any value of the treatment, and test whether a parameter of interest is different from its average value at an value of the treatment.
Depends: R (>= 2.1.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: quantreg, stats, pbapply, BMisc, tidyr, ggplot2, TempleMetrics, doParallel, foreach, formula.tools
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-17 20:25:10 UTC; weigehuang
Author: Weige Huang [aut, cre], Brantly Callaway [aut]
Maintainer: Weige Huang <weige.huang@temple.edu>
Repository: CRAN
Date/Publication: 2018-09-18 08:20:08 UTC

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Package bivariate updated to version 0.2.2 with previous version 0.1.6 dated 2018-09-11

Title: Bivariate Probability Distributions
Description: Contains convenience functions for constructing and plotting bivariate probability distributions (probability mass functions, probability density functions and cumulative distribution functions). Currently supports uniform (discrete and continuous), binomial, Poisson, normal, bimodal and kernel distributions.
Author: Abby Spurdle
Maintainer: Abby Spurdle <spurdle.a@gmail.com>

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Package packcircles updated to version 0.3.3 with previous version 0.3.2 dated 2018-04-28

Title: Circle Packing
Description: Simple algorithms for circle packing.
Author: Michael Bedward [aut, cre], David Eppstein [aut] (Author of Python code for graph-based circle packing ported to C++ for this package), Peter Menzel [aut] (Author of C code for progressive circle packing ported to C++ for this package)
Maintainer: Michael Bedward <michael.bedward@gmail.com>

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Package sunburstR updated to version 2.1.0 with previous version 2.0.0 dated 2018-03-12

Title: 'Htmlwidget' for 'Kerry Rodden' 'd3.js' Sequence and 'd2b' Sunburst
Description: Make interactive 'd3.js' sequence sunburst diagrams in R with the convenience and infrastructure of an 'htmlwidget'.
Author: Mike Bostock [aut, cph] (d3.js library, http://d3js.org), Kerry Rodden [aut, cph] (sequences library in htmlwidgets/lib, https://gist.github.com/kerryrodden/7090426), Kevin Warne [aut, cph] (d2b sunburst library in htmlwidgets/lib, https://github.com/d2bjs/d2b), Kent Russell [aut, cre] (R interface), Florian Breitwieser [ctb] (R interface), CJ Yetman [ctb] (R interface, <https://orcid.org/0000-0001-5099-9500>)
Maintainer: Kent Russell <kent.russell@timelyportfolio.com>

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Package MazamaSpatialUtils updated to version 0.5.4 with previous version 0.5.2 dated 2017-12-07

Title: Spatial Data Download and Utility Functions
Description: A suite of conversion scripts to create internally standardized spatial polygons data frames. Utility scripts use these data sets to return values such as country, state, timezone, watershed, etc. associated with a set of longitude/latitude pairs. (They also make cool maps.)
Author: Jonathan Callahan [aut, cre], Ruby Fore [aut], Will Leahy [aut], Helen Miller [aut], Henry Nguyen [aut], Robin Winstanley [aut], Alice Yang [aut]
Maintainer: Jonathan Callahan <jonathan.s.callahan@gmail.com>

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Package jmv updated to version 0.9.4 with previous version 0.9.2.0 dated 2018-08-12

Title: The 'jamovi' Analyses
Description: A suite of common statistical methods such as descriptives, t-tests, ANOVAs, regression, correlation matrices, proportion tests, contingency tables, and factor analysis. This package is also useable from the 'jamovi' statistical spreadsheet (see <https://www.jamovi.org> for more information).
Author: Ravi Selker, Jonathon Love, Damian Dropmann
Maintainer: Jonathon Love <jon@thon.cc>

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Package cowsay updated to version 0.7.0 with previous version 0.6.0 dated 2018-05-15

Title: Messages, Warnings, Strings with Ascii Animals
Description: Allows printing of character strings as messages/warnings/etc. with ASCII animals, including cats, cows, frogs, chickens, ghosts, and more.
Author: Scott Chamberlain [aut, cre], Amanda Dobbyn [aut], Tyler Rinker [ctb], Thomas Leeper [ctb], Noam Ross [ctb], Rich FitzJohn [ctb], Carson Sievert [ctb], Kiyoko Gotanda [ctb], Andy Teucher [ctb], Karl Broman [ctb], Franz-Sebastian Krah [ctb], Lucy D'Agostino McGowan [ctb], Guangchuang Yu [ctb], Philipp Boersch-Supan [ctb], Andreas Brandmaier [ctb]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Mon, 17 Sep 2018

Package variables updated to version 1.0-1 with previous version 1.0-0 dated 2018-03-08

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>

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Package mlt updated to version 1.0-3 with previous version 1.0-2 dated 2018-06-22

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 sigr updated to version 1.0.0 with previous version 0.2.8 dated 2018-07-19

Title: Succinct and Correct Statistical Summaries for Reports
Description: Succinctly and correctly format statistical summaries of various models and tests (F-test, Chi-Sq-test, Fisher-test, T-test, and rank-significance). The main purpose is unified reporting of experimental results, working around issue such as the difficulty of extracting model summary facts (such as with 'lm'/'glm'). This package also includes empirical tests, such as bootstrap estimates.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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Package processanimateR updated to version 0.2.0 with previous version 0.1.1 dated 2018-04-20

Title: Process Map Token Replay Animation
Description: Token replay animation for process maps created with 'processmapR' by using SVG animations ('SMIL') and the 'htmlwidget' package.
Author: Felix Mannhardt [aut, cre], Gert Janssenswillen [ctb]
Maintainer: Felix Mannhardt <felix.mannhardt@sintef.no>

Diff between processanimateR versions 0.1.1 dated 2018-04-20 and 0.2.0 dated 2018-09-17

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Package spatsoc updated to version 0.1.1 with previous version 0.1.0 dated 2018-07-20

Title: Group Animal Relocation Data by Spatial and Temporal Relationship
Description: Detects spatial and temporal groups in GPS relocations. It can be used to convert GPS relocations to gambit-of-the-group format to build proximity-based social networks. In addition, the randomizations function provides data-stream randomization methods suitable for GPS data.
Author: Alec L. Robitaille [aut, cre], Quinn Webber [aut], Eric Vander Wal [aut]
Maintainer: Alec L. Robitaille <robit.alec@gmail.com>

Diff between spatsoc versions 0.1.0 dated 2018-07-20 and 0.1.1 dated 2018-09-17

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New package echarts4r with initial version 0.1.1
Package: echarts4r
Title: Create Interactive Graphs with 'Echarts JavaScript' Version 4
Date: 2018-09-12
Version: 0.1.1
Authors@R: person("John", "Coene", email = "jcoenep@gmail.com", role = c("aut", "cre"))
Description: Easily create interactive charts by leveraging the 'Echarts Javascript' library which includes 33 chart types, themes, 'Shiny' proxies and animations.
License: Apache License (>= 2.0)
Encoding: UTF-8
LazyData: true
Imports: htmlwidgets, magrittr, dplyr, purrr, data.tree, crosstalk, base64enc, countrycode, d3r, broom
RoxygenNote: 6.1.0
Suggests: jsonlite, shiny, quantmod, png, tibble, htmltools
URL: http://echarts4r.john-coene.com/
BugReports: https://github.com/JohnCoene/echarts4r/issues
NeedsCompilation: no
Packaged: 2018-09-12 12:06:38 UTC; JCOE
Author: John Coene [aut, cre]
Maintainer: John Coene <jcoenep@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-17 16:40:03 UTC

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Package WVPlots updated to version 1.0.3 with previous version 1.0.2 dated 2018-07-20

Title: Common Plots for Analysis
Description: Select data analysis plots, under a standardized calling interface implemented on top of 'ggplot2' and 'plotly'. Plots of interest include: 'ROC', gain curve, scatter plot with marginal distributions, conditioned scatter plot with marginal densities, box and stem with matching theoretical distribution, and density with matching theoretical distribution.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between WVPlots versions 1.0.2 dated 2018-07-20 and 1.0.3 dated 2018-09-17

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New package UKgrid with initial version 0.1.0
Package: UKgrid
Type: Package
Title: The UK National Electricity Transmission System Dataset
Version: 0.1.0
Author: Rami Krispin
Maintainer: Rami Krispin <rami.krispin@gmail.com>
Description: A time series of the national grid demand (high-voltage electric power transmission network) in the UK since 2011.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.2)
Imports: data.table(>= 1.11.2), dplyr(>= 0.7.5), lubridate (>= 1.6.0), magrittr (>= 1.5), rlang (>= 0.2.1), xts (>= 0.10-1), zoo (>= 1.8-0)
Suggests: knitr, rmarkdown, devtools, TSstudio
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-11 05:23:33 UTC; rami
Repository: CRAN
Date/Publication: 2018-09-17 15:10:07 UTC

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New package stuart with initial version 0.7.3
Package: stuart
Type: Package
Title: Subtests Using Algorithmic Rummaging Techniques
Version: 0.7.3
Date: 2018-09-11
Authors@R: person("Martin", "Schultze", email="martin.schultze@fu-berlin.de", role=c('aut','cre'))
Description: Construct subtests from a pool of items by using ant-colony-optimization, genetic algorithms, brute force, or random sampling. Schultze (2017) <doi:10.17169/refubium-622>.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: stats, utils
Suggests: parallel, lavaan (>= 0.5.18), MplusAutomation (>= 0.7-2), graphics
RoxygenNote: 6.0.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-09-11 20:00:37 UTC; martin
Author: Martin Schultze [aut, cre]
Maintainer: Martin Schultze <martin.schultze@fu-berlin.de>
Repository: CRAN
Date/Publication: 2018-09-17 15:30:03 UTC

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New package rlmDataDriven with initial version 0.1.0
Package: rlmDataDriven
Type: Package
Title: Robust Regression with Data Driven Tuning Parameter
Version: 0.1.0
Author: You-Gan Wang
Maintainer: The package maintainer <you-gan.wang@qut.edu.au>
Imports: stats, MASS
Description: Data driven approach for robust regression estimation. See Wang et al. (2007), <doi:10.1198/106186007X180156>.
License: GPL (>= 2.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-08-10 04:37:08 UTC; wangy
Repository: CRAN
Date/Publication: 2018-09-17 15:10:03 UTC

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New package radix with initial version 0.5
Type: Package
Package: radix
Title: 'R Markdown' Format for Scientific and Technical Writing
Version: 0.5
Authors@R: c( person("JJ", "Allaire", role = c("aut", "cre"), email = "jj@rstudio.com"), person("Rich", "Iannone", role = c("aut")), person("Yihui", "Xie", role = c("aut")), person(family = "RStudio, Inc.", role = "cph"), person(family = "Google LLC", role = c("ctb", "cph"), comment = "https://distill.pub/guide/"), person("Nick", "Williams", role = c("ctb", "cph"), comment = "https://wicky.nillia.ms/headroom.js/"), person("Denis", "Demchenko", role = c("ctb", "cph"), comment = "https://github.com/lancedikson/bowser"), person(family = "The Polymer Authors", role = c("ctb", "cph"), comment = "https://www.webcomponents.org/polyfills/"), person("Gábor", "Csárdi", role = c("ctb", "cph"), comment = "whoami") )
Description: Scientific and technical article format for the web. 'Radix' articles feature attractive, reader-friendly typography, flexible layout options for visualizations, and full support for footnotes and citations.
License: Apache License 2.0
URL: https://github.com/rstudio/radix
BugReports: https://github.com/rstudio/radix/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: utils, stats, tools, rmarkdown (>= 1.10), htmltools, jsonlite (>= 1.3), lubridate, png, mime, rstudioapi, rprojroot, xml2, base64enc, whisker, downloader, progress, stringr, knitr (>= 1.15.6), digest, yaml
Suggests: htmlwidgets, r2d3, DiagrammeR, shiny, rsconnect, testthat
Language: en-US
NeedsCompilation: no
Packaged: 2018-09-17 13:54:10 UTC; jjallaire
Author: JJ Allaire [aut, cre], Rich Iannone [aut], Yihui Xie [aut], RStudio, Inc. [cph], Google LLC [ctb, cph] (https://distill.pub/guide/), Nick Williams [ctb, cph] (https://wicky.nillia.ms/headroom.js/), Denis Demchenko [ctb, cph] (https://github.com/lancedikson/bowser), The Polymer Authors [ctb, cph] (https://www.webcomponents.org/polyfills/), Gábor Csárdi [ctb, cph] (whoami)
Maintainer: JJ Allaire <jj@rstudio.com>
Repository: CRAN
Date/Publication: 2018-09-17 15:40:02 UTC

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New package HMMextra0s with initial version 1.0.0
Package: HMMextra0s
Type: Package
Title: Hidden Markov Models with Extra Zeros
Version: 1.0.0
Imports: mvtnorm, ellipse
Suggests: HiddenMarkov
Depends: methods
Date: 2018-09-12
Author: Ting Wang - I am grateful to Jiancang Zhuang for some helpful suggestions and contributions
Maintainer: Ting Wang <ting.wang@otago.ac.nz>
Description: Contains functions for hidden Markov models with observations having extra zeros as defined in the following two publications, Wang, T., Zhuang, J., Obara, K. and Tsuruoka, H. (2016) <doi:10.1111/rssc.12194>; Wang, T., Zhuang, J., Buckby, J., Obara, K. and Tsuruoka, H. (2018) <doi:10.1029/2017JB015360>. The observed response variable is either univariate or bivariate Gaussian conditioning on presence of events, and extra zeros mean that the response variable takes on the value zero if nothing is happening. Hence the response is modelled as a mixture distribution of a Bernoulli variable and a continuous variable. That is, if the Bernoulli variable takes on the value 1, then the response variable is Gaussian, and if the Bernoulli variable takes on the value 0, then the response is zero too. This package includes functions for simulation, parameter estimation, goodness-of-fit, the Viterbi algorithm, and plotting the classified 2-D data. Some of the functions in the package are based on those of the R package 'HiddenMarkov' by David Harte.
License: GPL (>= 2)
URL: http://www.stats.otago.ac.nz/?people=ting_wang
Packaged: 2018-09-11 20:49:19 UTC; twang
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2018-09-17 15:30:07 UTC

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New package farver with initial version 1.0
Package: farver
Type: Package
Title: Vectorised Colour Conversion and Comparison
Version: 1.0
Date: 2018-09-17
Authors@R: c(person(given = "Thomas Lin", family = "Pedersen", role = c("cre", "aut"), email = "thomasp85@gmail.com"), person(given = "Berendea", family = "Nicolae", role = "aut", comment = "Author of the ColorSpace C++ library"), person(given = "Romain", family = "François", role = "aut", email = "romain@purrple.cat", comment = c(ORCID = "0000-0002-2444-4226")) )
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>
Description: The encoding of colour can be handled in many different ways, using different colour spaces. As different colour spaces have different uses, efficient conversion between these representations are important. The 'farver' package provides a set of functions that gives access to very fast colour space conversion and comparisons implemented in C++, and offers 100-fold speed improvements over the 'convertColor' function in the 'grDevices' package.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: C++11
Imports: Rcpp (>= 0.12.15)
LinkingTo: Rcpp
RoxygenNote: 6.1.0
URL: https://github.com/thomasp85/farver
BugReports: https://github.com/thomasp85/farver/issues
Suggests: testthat, covr
NeedsCompilation: yes
Packaged: 2018-09-17 09:12:47 UTC; thomas
Author: Thomas Lin Pedersen [cre, aut], Berendea Nicolae [aut] (Author of the ColorSpace C++ library), Romain François [aut] (<https://orcid.org/0000-0002-2444-4226>)
Repository: CRAN
Date/Publication: 2018-09-17 15:20:02 UTC

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Package basefun updated to version 1.0-2 with previous version 1.0-1 dated 2018-03-29

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 1.0-1 dated 2018-03-29 and 1.0-2 dated 2018-09-17

 DESCRIPTION            |    8 ++++----
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New package VICmodel with initial version 0.1.0
Package: VICmodel
Type: Package
Title: The Variable Infiltration Capacity (VIC) Model
Version: 0.1.0
Authors@R: c(person("Ruida", "Zhong", email = "zrd2017@163.com", role = c("aut", "cre")), person("Xiaohong", "Chen", role = c("aut", "ctb")), person("Joseph J", "Hamman", role = c("ctb"), comment = "Contributor and maintainer of VIC source code"), person("Keith", "Cherkauer", role = c("ctb"), comment = "Contributer of codes of src/vic/vic_run/src/write_vegvar.c and src/vic/drivers/shared_all/src/cmd_proc.c") )
Description: The Variable Infiltration Capacity (VIC) model is a macroscale hydrologic model that solves full water and energy balances, originally developed by Xu Liang at the University of Washington (UW). The version of VIC source code used is of 5.0.1 on <https://github.com/UW-Hydro/VIC/>, see Hamman et al. (2018). Development and maintenance of the current official version of the VIC model at present is led by the UW Hydro (Computational Hydrology group) in the Department of Civil and Environmental Engineering at UW. VIC is a research model and in its various forms it has been applied to most of the major river basins around the world, as well as globally. If you make use of this model, please acknowledge the appropriate references listed in the help page of this package or on the references page <http://vic.readthedocs.io/en/master/Documentation/References/> of the VIC official documentation website. These should include Liang et al. (1994) plus any references relevant to the features you are using Reference: Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415-14428, <doi:10.1029/94JD00483>. Hamman et al. (2018) about VIC 5.0.1 also can be considered: Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. (2018), The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility, Geosci. Model Dev., 11, 3481-3496, <doi:10.5194/gmd-11-3481-2018>.
License: GPL-3
Copyright: file inst/COPYRIGHTS
URL: https://github.com/Sibada/VICmodel
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.0)
Imports: stats, utils, Rcpp (>= 0.12.0), foreach
Suggests: doParallel
LinkingTo: Rcpp
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2018-09-11 05:22:49 UTC; Da
Author: Ruida Zhong [aut, cre], Xiaohong Chen [aut, ctb], Joseph J Hamman [ctb] (Contributor and maintainer of VIC source code), Keith Cherkauer [ctb] (Contributer of codes of src/vic/vic_run/src/write_vegvar.c and src/vic/drivers/shared_all/src/cmd_proc.c)
Maintainer: Ruida Zhong <zrd2017@163.com>
Repository: CRAN
Date/Publication: 2018-09-17 14:20:06 UTC

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Package sabre updated to version 0.2.1 with previous version 0.2.0 dated 2018-04-23

Title: Spatial Association Between Regionalizations
Description: Calculates a degree of spatial association between regionalizations or categorical maps using the information-theoretical V-measure (Nowosad and Stepinski (2018) <doi:10.1080/13658816.2018.1511794>). It also offers an R implementation of the MapCurve method (Hargrove et al. (2006) <doi:10.1007/s10109-006-0025-x>).
Author: Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>), Tomasz Stepinski [aut], Space Informatics Lab [cph]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

Diff between sabre versions 0.2.0 dated 2018-04-23 and 0.2.1 dated 2018-09-17

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New package MSPRT with initial version 1.0
Package: MSPRT
Type: Package
Title: Modified Sequential Probability Ratio Test (MSPRT)
Version: 1.0
Date: 2018-09-11
Authors@R: c(person("Sandipan", "Pramanik", email = "sandy@stat.tamu.edu", role = c("aut", "cre")), person("Valen E.", "Johnson", role = "aut"), person("Anirban", "Bhattacharya", role = "aut") )
Author: Sandipan Pramanik [aut, cre], Valen E. Johnson [aut], Anirban Bhattacharya [aut]
Maintainer: Sandipan Pramanik <sandy@stat.tamu.edu>
Description: A modified SPRT (MSPRT) can be designed and implemented with the help of this package. In a MSPRT design, the maximum sample size of an experiment is fixed prior to the start of an experiment, the alternative hypothesis used to define the rejection region of the test is derived from the size of the test (Type I error), the maximum available sample size (N), and the targeted Type 2 error (equal to 1 minus the power) is also prespecified. Given these values, the MSPRT is defined in a manner very similar to Wald's initial proposal. This test can reduce the average sample size required to perform statistical hypothesis tests at the specified levels of significance and power. This package facilitates the carrying out of one sample Z tests, T Tests and tests of binomial success probabilities. A user guidance for this software package is provided here and also in the supplemental information.
Imports: nleqslv, ggplot2, foreach, iterators, parallel, doParallel, datasets, graphics, grDevices, methods, stats, utils
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-09-11 16:56:52 UTC; sandipanpramanik
Repository: CRAN
Date/Publication: 2018-09-17 14:50:03 UTC

More information about MSPRT at CRAN
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Package gdns updated to version 0.3.1 with previous version 0.2.1 dated 2017-07-02

Title: Tools to Work with Google's 'DNS-over-HTTPS' ('DoH') 'API'
Description: To address the problem of insecurity of 'UDP'-based 'DNS' requests, 'Google Public DNS' offers 'DNS' resolution over an encrypted 'HTTPS' connection. 'DNS-over-HTTPS' greatly enhances privacy and security between a client and a recursive resolver, and complements 'DNSSEC' to provide end-to-end authenticated 'DNS' lookups. Functions that enable querying individual requests that bulk requests that return detailed responses and bulk requests are both provided. Support for reverse lookups is also provided. See <https://developers.google.com/speed/public-dns/docs/dns-over-https> for more information.
Author: Bob Rudis [aut, cre] (<https://orcid.org/0000-0001-5670-2640>)
Maintainer: Bob Rudis <bob@rud.is>

Diff between gdns versions 0.2.1 dated 2017-07-02 and 0.3.1 dated 2018-09-17

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Package frailtypack updated to version 2.13.1 with previous version 2.12.7 dated 2018-07-30

Title: General Frailty Models: Shared, Joint and Nested Frailty Models with Prediction
Description: The following several classes of frailty models using a penalized likelihood estimation on the hazard function but also a parametric estimation can be fit using this R package: 1) A shared frailty model (with gamma or log-normal frailty distribution) and Cox proportional hazard model. Clustered and recurrent survival times can be studied. 2) Additive frailty models for proportional hazard models with two correlated random effects (intercept random effect with random slope). 3) Nested frailty models for hierarchically clustered data (with 2 levels of clustering) by including two iid gamma random effects. 4) Joint frailty models in the context of the joint modelling for recurrent events with terminal event for clustered data or not. A joint frailty model for two semi-competing risks and clustered data is also proposed. 5) Joint general frailty models in the context of the joint modelling for recurrent events with terminal event data with two independent frailty terms. 6) Joint Nested frailty models in the context of the joint modelling for recurrent events with terminal event, for hierarchically clustered data (with two levels of clustering) by including two iid gamma random effects. 7) Multivariate joint frailty models for two types of recurrent events and a terminal event. 8) Joint models for longitudinal data and a terminal event. 9) Trivariate joint models for longitudinal data, recurrent events and a terminal event. Prediction values are available (for a terminal event or for a new recurrent event). Left-truncated (not for Joint model), right-censored data, interval-censored data (only for Cox proportional hazard and shared frailty model) and strata are allowed. In each model, the random effects have the gamma or normal distribution. Now, you can also consider time-varying covariates effects in Cox, shared and joint frailty models (1-5). The package includes concordance measures for Cox proportional hazards models and for shared frailty models.
Author: Virginie Rondeau, Juan R. Gonzalez, Yassin Mazroui, Audrey Mauguen, Agnieszka Krol, Amadou Diakite, Alexandre Laurent and Myriam Lopez
Maintainer: Virginie Rondeau <Virginie.Rondeau@inserm.fr>

Diff between frailtypack versions 2.12.7 dated 2018-07-30 and 2.13.1 dated 2018-09-17

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New package emhawkes with initial version 0.9.0
Package: emhawkes
Title: Exponential Multivariate Hawkes Model
Version: 0.9.0
Authors@R: person("Kyungsub", "Lee", email = "kyungsub@gmail.com", role = c("aut", "cre"))
Maintainer: Kyungsub Lee <kyungsub@gmail.com>
Description: Simulate and fitting exponential multivariate Hawkes model. This package simulates a multivariate Hawkes model, introduced by Hawkes (1971) <doi:10.1093/biomet/58.1.83>, with an exponential kernel and fits the parameters from the data. Models with the constant parameters, as well as complex dependent structures, can also be simulated and estimated. The estimation is based on the maximum likelihood method, introduced by introduced by Ozaki (1979) <doi:10.1007/BF02480272>, with 'maxLik' package.
Depends: R (>= 3.4.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: maxLik, methods
Collate: 'harrival.R' 'hspec.R' 'hmoment.R' 'hllf.R' 'hfit.R' 'utilities.R' 'hreal.R' 'hsim.R' 'script.R'
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-03 01:25:13 UTC; user
Author: Kyungsub Lee [aut, cre]
Repository: CRAN
Date/Publication: 2018-09-17 14:20:02 UTC

More information about emhawkes at CRAN
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Package bamdit updated to version 3.2.1 with previous version 3.2.0 dated 2018-08-24

Title: Bayesian Meta-Analysis of Diagnostic Test Data
Description: Functions for Bayesian meta-analysis of diagnostic test data which are based on a scale mixtures bivariate random-effects model.
Author: Pablo Emilio Verde [aut, cre]
Maintainer: Pablo Emilio Verde <pabloemilio.verde@hhu.de>

Diff between bamdit versions 3.2.0 dated 2018-08-24 and 3.2.1 dated 2018-09-17

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New package xopen with initial version 1.0.0
Package: xopen
Title: Open System Files, 'URLs', Anything
Version: 1.0.0
Authors@R: c( person("Gábor", "Csárdi",, "csardi.gabor@gmail.com", c("aut", "cre")), person("Fathi", "Boudra", role = "aut"), person("Rex", "Dieter", role = "aut"), person("Kevin", "Krammer", role = "aut"), person("Jeremy", "White", role = "aut"))
Description: Cross platform solution to open files, directories or 'URLs' with their associated programs.
License: MIT + file LICENSE
LazyData: true
URL: https://github.com/r-lib/xopen#readme
BugReports: https://github.com/r-lib/xopen/issues
RoxygenNote: 6.1.0
Imports: processx
Suggests: ps, testthat
Encoding: UTF-8
Depends: R (>= 3.1)
NeedsCompilation: no
Packaged: 2018-09-10 20:47:53 UTC; gaborcsardi
Author: Gábor Csárdi [aut, cre], Fathi Boudra [aut], Rex Dieter [aut], Kevin Krammer [aut], Jeremy White [aut]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-17 13:10:03 UTC

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Package PythonInR updated to version 0.1-6 with previous version 0.1-4 dated 2018-01-17

Title: Use 'Python' from Within 'R'
Description: Interact with 'Python' <https://www.python.org/> from within 'R'.
Author: Florian Schwendinger [aut, cre], Kimyen Truong [ctb]
Maintainer: Florian Schwendinger <FlorianSchwendinger@gmx.at>

Diff between PythonInR versions 0.1-4 dated 2018-01-17 and 0.1-6 dated 2018-09-17

 ChangeLog          |    4 +++
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Package kergp updated to version 0.4.0 with previous version 0.2.0 dated 2015-12-23

Title: Gaussian Process Laboratory
Description: Gaussian Process models with customised covariance kernels.
Author: Yves Deville, David Ginsbourger, Olivier Roustant. Contributors: Nicolas Durrande.
Maintainer: Olivier Roustant <roustant@emse.fr>

Diff between kergp versions 0.2.0 dated 2015-12-23 and 0.4.0 dated 2018-09-17

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New package ipc with initial version 0.1.0
Package: ipc
Type: Package
Title: Tools for Message Passing Between Processes
Version: 0.1.0
Author: Ian E. Fellows
Maintainer: Ian E. Fellows <ian@fellstat.com>
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.
Imports: R6, shiny, txtq, redux
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: testthat, knitr, rmarkdown, future, promises
VignetteBuilder: knitr
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-11 00:29:27 UTC; ianfellows
Repository: CRAN
Date/Publication: 2018-09-17 13:20:03 UTC

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New package empirical with initial version 0.1.0
Package: empirical
Title: Empirical Probability Density Functions and Empirical Cumulative Distribution Functions
Version: 0.1.0
Date: 2018-09-11
Author: Abby Spurdle
Maintainer: Abby Spurdle <spurdle.a@gmail.com>
Description: Implements empirical probability density functions (continuous functions) and empirical cumulative distribution functions (step functions or continuous). Currently, univariate only.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-09-11 01:13:54 UTC; Student9
Repository: CRAN
Date/Publication: 2018-09-17 13:20:06 UTC

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New package CorDiff with initial version 1.0
Package: CorDiff
Type: Package
Imports: mcc
Title: Set-Based Differential Covariance Testing for Genomics
Version: 1.0
Date: 2018-09-05
Author: Yi-Hui Zhou
Maintainer: Yi-Hui Zhou <yihui_zhou@ncsu.edu>
Description: We describe four different summary statistics, to ensure power and flexibility under various settings, including a new connectivity statistic that is sensitive to changes in overall covariance magnitude.
License: GPL-2
LazyLoad: yes
NeedsCompilation: no
Packaged: 2018-09-05 14:16:01 UTC; yzhou19
Repository: CRAN
Date/Publication: 2018-09-17 13:10:10 UTC

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Package xmlparsedata updated to version 1.0.2 with previous version 1.0.1 dated 2016-06-18

Title: Parse Data of 'R' Code as an 'XML' Tree
Description: Convert the output of 'utils::getParseData()' to an 'XML' tree, that one can search via 'XPath', and easier to manipulate in general.
Author: Gábor Csárdi
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between xmlparsedata versions 1.0.1 dated 2016-06-18 and 1.0.2 dated 2018-09-17

 DESCRIPTION                |   17 +++++++++--------
 MD5                        |   16 ++++++++--------
 NEWS.md                    |    7 +++++++
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 9 files changed, 63 insertions(+), 31 deletions(-)

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Package spikeSlabGAM updated to version 1.1-14 with previous version 1.1-11 dated 2016-02-29

Title: Bayesian Variable Selection and Model Choice for Generalized Additive Mixed Models
Description: Bayesian variable selection, model choice, and regularized estimation for (spatial) generalized additive mixed regression models via stochastic search variable selection with spike-and-slab priors.
Author: Fabian Scheipl [aut, cre], Bettina Gruen [ctb]
Maintainer: Fabian Scheipl <fabian.scheipl@stat.uni-muenchen.de>

Diff between spikeSlabGAM versions 1.1-11 dated 2016-02-29 and 1.1-14 dated 2018-09-17

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 spikeSlabGAM-1.1-14/spikeSlabGAM/R/bugs.R                          |   43 
 spikeSlabGAM-1.1-14/spikeSlabGAM/R/plot.R                          |  973 ++++++----
 spikeSlabGAM-1.1-14/spikeSlabGAM/R/predict.R                       |  172 +
 spikeSlabGAM-1.1-14/spikeSlabGAM/R/spikeAndSlab.R                  |  684 ++++---
 spikeSlabGAM-1.1-14/spikeSlabGAM/R/spikeSlabGAM.R                  |   38 
 spikeSlabGAM-1.1-14/spikeSlabGAM/R/ssGAMDesign.R                   |  224 +-
 spikeSlabGAM-1.1-14/spikeSlabGAM/R/summary.R                       |  189 +
 spikeSlabGAM-1.1-14/spikeSlabGAM/R/terms.R                         |  257 +-
 spikeSlabGAM-1.1-14/spikeSlabGAM/R/utils.R                         |  466 ++--
 spikeSlabGAM-1.1-14/spikeSlabGAM/build/vignette.rds                |binary
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 spikeSlabGAM-1.1-14/spikeSlabGAM/man/fct.Rd                        |    1 
 spikeSlabGAM-1.1-14/spikeSlabGAM/man/getPosteriorTerm.Rd           |    1 
 spikeSlabGAM-1.1-14/spikeSlabGAM/man/lin.Rd                        |    1 
 spikeSlabGAM-1.1-14/spikeSlabGAM/man/mrf.Rd                        |   10 
 spikeSlabGAM-1.1-14/spikeSlabGAM/man/plot.spikeSlabGAM.Rd          |   11 
 spikeSlabGAM-1.1-14/spikeSlabGAM/man/plotTerm.Rd                   |    6 
 spikeSlabGAM-1.1-14/spikeSlabGAM/man/predict.spikeSlabGAM.Rd       |    8 
 spikeSlabGAM-1.1-14/spikeSlabGAM/man/print.summary.spikeSlabGAM.Rd |    7 
 spikeSlabGAM-1.1-14/spikeSlabGAM/man/rnd.Rd                        |    1 
 spikeSlabGAM-1.1-14/spikeSlabGAM/man/sm.Rd                         |   13 
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Permanent link

New package salty with initial version 0.1.0
Type: Package
Package: salty
Title: Turn Clean Data into Messy Data
Version: 0.1.0
Authors@R: c( person("Matthew Lincoln", email = "matthew.d.lincoln@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4387-3384")))
Description: Take real or simulated data and salt it with errors commonly found in the wild, such as pseudo-OCR errors, Unicode problems, numeric fields with nonsensical punctuation, bad dates, etc.
License: MIT + file LICENSE
Depends: R (>= 2.10)
Imports: assertthat, purrr, stringr
Suggests: charlatan, testthat (>= 2.0.0), tibble, covr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
URL: https://github.com/mdlincoln/salty
BugReports: https://github.com/mdlincoln/salty/issues
NeedsCompilation: no
Packaged: 2018-09-10 11:49:31 UTC; mlincoln
Author: Matthew Lincoln [aut, cre] (<https://orcid.org/0000-0002-4387-3384>)
Maintainer: Matthew Lincoln <matthew.d.lincoln@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-17 11:40:03 UTC

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Package googleway updated to version 2.7.1 with previous version 2.7.0 dated 2018-05-25

Title: Accesses Google Maps APIs to Retrieve Data and Plot Maps
Description: Provides a mechanism to plot a 'Google Map' from 'R' and overlay it with shapes and markers. Also provides access to 'Google Maps' APIs, including places, directions, roads, distances, geocoding, elevation and timezone.
Author: David Cooley [aut, cre], Paulo Barcelos [ctb] (Author of c++ decode_pl), Rstudio [ctb] (Functions written for the Leaflet pacakge)
Maintainer: David Cooley <dcooley@symbolix.com.au>

Diff between googleway versions 2.7.0 dated 2018-05-25 and 2.7.1 dated 2018-09-17

 DESCRIPTION                               |   10 
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 NAMESPACE                                 |    2 
 R/google_directions.R                     |   24 -
 R/google_distance.R                       |   24 -
 R/google_keys.R                           |    3 
 R/google_map.R                            |    6 
 R/google_map_layer_marker.R               |    1 
 R/google_map_layer_polyline.R             |    7 
 R/google_places.R                         |  242 +++++++++---
 R/google_utilities.R                      |    1 
 R/googleway-package.R                     |   12 
 R/legend.R                                |    2 
 R/onLoad.R                                |    1 
 R/parameter_checks.R                      |  140 +++++--
 inst/doc/googleway-vignette.Rmd           |    5 
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 tests/manual_tests.R                      |   44 ++
 tests/testthat/test-google_directions.R   |    3 
 tests/testthat/test-google_distances.R    |   17 
 tests/testthat/test-google_keys.R         |   63 ---
 tests/testthat/test-google_map.R          |    3 
 tests/testthat/test-google_places.R       |   38 +
 tests/testthat/test-onLoad.R              |    2 
 tests/testthat/test-parameter_checks.R    |   25 +
 vignettes/googleway-vignette.Rmd          |    5 
 46 files changed, 970 insertions(+), 747 deletions(-)

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New package EloOptimized with initial version 0.3.0
Package: EloOptimized
Title: Optimized Elo Rating Method for Obtaining Dominance Ranks
Version: 0.3.0
Date: 2018-09-05
Authors@R: c( person("Joseph", "Feldblum", email = "feldblum@umich.edu", role = c("aut", "cre")), person("Steffen", "Foerster", email = "sf2041@gmail.com", role = c("aut")), person("Mathias", "Franz", email = "m.franz@izw-berlin.de", role = c("aut")))
Description: Provides an implementation of the maximum likelihood methods for deriving Elo scores as published in Foerster, Franz et al. (2016) <DOI:10.1038/srep35404>.
Depends: R (>= 3.3.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: dplyr, reshape2, BAMMtools, tcltk, rlist, magrittr, lubridate, rlang
URL: https://github.com/jtfeld/EloOptimized
BugReports: https://github.com/jtfeld/EloOptimized/issues
NeedsCompilation: no
Packaged: 2018-09-10 21:35:33 UTC; Joseph Feldblum
Author: Joseph Feldblum [aut, cre], Steffen Foerster [aut], Mathias Franz [aut]
Maintainer: Joseph Feldblum <feldblum@umich.edu>
Repository: CRAN
Date/Publication: 2018-09-17 11:50:08 UTC

More information about EloOptimized at CRAN
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Package treeman updated to version 1.1.3 with previous version 1.1.2 dated 2018-04-06

Title: Phylogenetic Tree Manipulation Class and Methods
Description: S4 class and methods for intuitive and efficient phylogenetic tree manipulation.
Author: D.J. Bennett
Maintainer: D.J. Bennett <dominic.john.bennett@gmail.com>

Diff between treeman versions 1.1.2 dated 2018-04-06 and 1.1.3 dated 2018-09-17

 DESCRIPTION                            |    6 +--
 MD5                                    |   21 +++++++------
 NAMESPACE                              |    1 
 R/calc-methods.R                       |   39 ++++++-------------------
 R/get-spcl-methods.R                   |   50 +++++++++++++++++++++++++++++++++
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 12 files changed, 111 insertions(+), 55 deletions(-)

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Package n1qn1 updated to version 6.0.1-3 with previous version 6.0.0-1 dated 2017-10-30

Title: Port of the 'Scilab' 'n1qn1' and 'qnbd' Modules for (Un)constrained BFGS Optimization
Description: Provides 'Scilab' 'n1qn1', or Quasi-Newton BFGS "qn" without constraints and 'qnbd' or Quasi-Newton BFGS with constraints. This takes more memory than traditional L-BFGS. The n1qn1 routine is useful since it allows prespecification of a Hessian. If the Hessian is near enough the truth in optimization it can speed up the optimization problem. Both algorithms are described in the 'Scilab' optimization documentation located at <http://www.scilab.org/content/download/250/1714/file/optimization_in_scilab.pdf>.
Author: Matthew Fidler [aut, cre], Wenping Wang [aut], Claude Lemarechal [aut, ctb], Joseph Bonnans [ctb], Jean-Charles Gilbert [ctb], Claudia Sagastizabal [ctb], Stephen L. Campbell, [ctb], Jean-Philippe Chancelier [ctb], Ramine Nikoukhah [ctb], Dirk Eddelbuettel [ctb], Bruno Jofret [ctb], INRIA [cph]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

Diff between n1qn1 versions 6.0.0-1 dated 2017-10-30 and 6.0.1-3 dated 2018-09-17

 DESCRIPTION        |   17 +-
 MD5                |   24 ++-
 NAMESPACE          |    1 
 R/n1qn1.R          |  338 +++++++++++++++++++++++++++++++----------------------
 README.md          |    2 
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Package magic updated to version 1.5-9 with previous version 1.5-8 dated 2018-01-26

Title: Create and Investigate Magic Squares
Description: A collection of efficient, vectorized algorithms for the creation and investigation of magic squares and hypercubes, including a variety of functions for the manipulation and analysis of arbitrarily dimensioned arrays. The package includes methods for creating normal magic squares of any order greater than 2. The ultimate intention is for the package to be a computerized embodiment all magic square knowledge, including direct numerical verification of properties of magic squares (such as recent results on the determinant of odd-ordered semimagic squares). Some antimagic functionality is included. The package also serves as a rebuttal to the often-heard comment "I thought R was just for statistics".
Author: Robin K. S. Hankin
Maintainer: "Robin K. S. Hankin" <hankin.robin@gmail.com>

Diff between magic versions 1.5-8 dated 2018-01-26 and 1.5-9 dated 2018-09-17

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New package CA3variants with initial version 1.0
Package: CA3variants
Type: Package
Title: Three-Way Correspondence Analysis Variants
Version: 1.0
Date: 2018-08-20
Author: Rosaria Lombardo and Eric J Beh
Maintainer: Rosaria Lombardo <rosaria.lombardo@unicampania.it>
Description: Provides three variants of three-way correspondence analysis (ca) three-way symmetrical ca, three-way non-symmetrical ca, three-way ordered symmetrical ca.
Depends: R (> 3.0.1), methods, tools, ggplot2, gridExtra, ggrepel
LazyData: true
License: GPL (> 2)
URL: https://www.R-project.org
NeedsCompilation: no
Packaged: 2018-09-10 16:57:56 UTC; Amministratore
Repository: CRAN
Date/Publication: 2018-09-17 09:00:13 UTC

More information about CA3variants at CRAN
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Package jmvcore updated to version 0.9.4 with previous version 0.9.2.0 dated 2018-08-12

Title: Dependencies for the 'jamovi' Framework
Description: A framework for creating rich interactive analyses for the jamovi platform (see <https://www.jamovi.org> for more information).
Author: Jonathon Love
Maintainer: Jonathon Love <jon@thon.cc>

Diff between jmvcore versions 0.9.2.0 dated 2018-08-12 and 0.9.4 dated 2018-09-17

 DESCRIPTION |    8 ++++----
 MD5         |    6 +++---
 R/group.R   |    5 +++++
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 4 files changed, 14 insertions(+), 11 deletions(-)

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Package mbir updated to version 1.3.4 with previous version 1.3.2 dated 2018-07-06

Title: Magnitude-Based Inferences
Description: Allows practitioners and researchers a wholesale approach for deriving magnitude-based inferences from raw data. A major goal of 'mbir' is to programmatically detect appropriate statistical tests to run in lieu of relying on practitioners to determine correct stepwise procedures independently.
Author: Kyle Peterson [aut, cre], Aaron Caldwell [aut]
Maintainer: Kyle Peterson <petersonkdon@gmail.com>

Diff between mbir versions 1.3.2 dated 2018-07-06 and 1.3.4 dated 2018-09-17

 DESCRIPTION                 |   14 +++++++-------
 MD5                         |   24 ++++++++++++------------
 R/aipe_smd.R                |    5 +++++
 R/boot_test.R               |   16 ++++++++++++++--
 R/es_convert.R              |    2 ++
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Package globals updated to version 0.12.3 with previous version 0.12.2 dated 2018-08-25

Title: Identify Global Objects in R Expressions
Description: Identifies global ("unknown" or "free") objects in R expressions by code inspection using various strategies, e.g. conservative or liberal. The objective of this package is to make it as simple as possible to identify global objects for the purpose of exporting them in distributed compute environments.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between globals versions 0.12.2 dated 2018-08-25 and 0.12.3 dated 2018-09-17

 DESCRIPTION       |    6 +--
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 NEWS              |  108 ++++++++++++++++++++++++++++++------------------------
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 R/cleanup.R       |    2 -
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 R/globalsOf.R     |   64 +++++++++++++++++---------------
 R/packagesOf.R    |    6 +--
 R/utils.R         |    3 +
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 11 files changed, 181 insertions(+), 136 deletions(-)

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Sun, 16 Sep 2018

Package hIRT updated to version 0.1.3 with previous version 0.1.2 dated 2017-08-01

Title: Hierarchical Item Response Theory Models
Description: Implementation of a class of hierarchical item response theory (IRT) models where both the mean and the variance of latent preferences (ability parameters) may depend on observed covariates. The current implementation includes both the two-parameter latent trait model for binary data and the graded response model for ordinal data. Both are fitted via the Expectation-Maximization (EM) algorithm. Asymptotic standard errors are derived from the observed information matrix.
Author: Xiang Zhou [aut, cre]
Maintainer: Xiang Zhou <xiang_zhou@fas.harvard.edu>

Diff between hIRT versions 0.1.2 dated 2017-08-01 and 0.1.3 dated 2018-09-16

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 7 files changed, 41 insertions(+), 44 deletions(-)

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Package filling updated to version 0.2.0 with previous version 0.1.0 dated 2017-12-11

Title: Matrix Completion, Imputation, and Inpainting Methods
Description: Filling in the missing entries of a partially observed data is one of fundamental problems in various disciplines of mathematical science. For many cases, data at our interests have canonical form of matrix in that the problem is posed upon a matrix with missing values to fill in the entries under preset assumptions and models. We provide a collection of methods from multiple disciplines under Matrix Completion, Imputation, and Inpainting. See Davenport and Romberg (2016) <doi:10.1109/JSTSP.2016.2539100> for an overview of the topic.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>

Diff between filling versions 0.1.0 dated 2017-12-11 and 0.2.0 dated 2018-09-16

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 NAMESPACE              |    2 ++
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Package bWGR updated to version 1.5.5 with previous version 1.5.4 dated 2018-08-08

Title: Bayesian Whole-Genome Regression
Description: Whole-genome regression methods on Bayesian framework fitted via EM or Gibbs sampling, with optional sampling techniques and kernel term.
Author: Alencar Xavier, William Muir, Shizhong Xu, Katy Rainey.
Maintainer: Alencar Xavier <alenxav@gmail.com>

Diff between bWGR versions 1.5.4 dated 2018-08-08 and 1.5.5 dated 2018-09-16

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Package tvR updated to version 0.3.0 with previous version 0.2.0 dated 2018-05-15

Title: Total Variation Regularization
Description: Provides tools for denoising noisy signal and images via Total Variation Regularization. Reducing the total variation of the given signal is known to remove spurious detail while preserving essential structural details. For the seminal work on the topic, see Rudin et al (1992) <doi:10.1016/0167-2789(92)90242-F>.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>

Diff between tvR versions 0.2.0 dated 2018-05-15 and 0.3.0 dated 2018-09-16

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 tvR-0.3.0/tvR/src/Makevars        |    2 +-
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 tvR-0.3.0/tvR/src/RcppExports.cpp |   11 -----------
 19 files changed, 26 insertions(+), 43 deletions(-)

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Package sparr updated to version 2.2-13 with previous version 2.2-12 dated 2018-07-22

Title: Spatial and Spatiotemporal Relative Risk
Description: Provides functions to estimate kernel-smoothed spatial and spatio-temporal densities and relative risk functions, and perform subsequent inference. Methodological details can be found in the accompanying tutorial: Davies et al. (2018) <DOI:10.1002/sim.7577>.
Author: Tilman M. Davies [aut, cre], Jonathan C. Marshall [aut]
Maintainer: Tilman M. Davies <tdavies@maths.otago.ac.nz>

Diff between sparr versions 2.2-12 dated 2018-07-22 and 2.2-13 dated 2018-09-16

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 R/plot.bivden.R           |    2 +
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 R/tolerance.R             |    2 -
 man/BOOT.density.Rd       |    2 -
 man/CV.Rd                 |   19 ++++++++--------
 man/LSCV.risk.Rd          |    8 +++---
 man/NS.Rd                 |    5 +---
 man/OS.Rd                 |    5 +---
 man/SLIK.adapt.Rd         |    4 +--
 man/bivariate.density.Rd  |    2 -
 man/multiscale.density.Rd |    2 -
 man/multiscale.slice.Rd   |    2 -
 man/plotsparr.Rd          |   21 +++++++++--------
 man/printsparr.Rd         |    4 ---
 man/risk.Rd               |    4 +--
 man/sparr-package.Rd      |    6 ++---
 man/summarysparr.Rd       |    4 ---
 man/tolerance.Rd          |    7 +++--
 28 files changed, 142 insertions(+), 94 deletions(-)

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Package aiRthermo updated to version 1.2.1 with previous version 1.2 dated 2018-07-02

Title: Atmospheric Thermodynamics and Visualization
Description: Deals with many computations related to the thermodynamics of atmospheric processes. It includes many functions designed to consider the density of air with varying degrees of water vapour in it, saturation pressures and mixing ratios, conversion of moisture indices, computation of atmospheric states of parcels subject to dry or pseudoadiabatic vertical evolutions and atmospheric instability indices that are routinely used for operational weather forecasts or meteorological diagnostics.
Author: Jon Sáenz, Santos J. González-Rojí, Sheila Carreno-Madinabeitia and Gabriel Ibarra-Berastegi
Maintainer: Santos J. González-Rojí <santosjose.gonzalez@ehu.eus>

Diff between aiRthermo versions 1.2 dated 2018-07-02 and 1.2.1 dated 2018-09-16

 DESCRIPTION                  |    8 
 MD5                          |   22 +-
 NEWS.md                      |    6 
 R/CAPE_CIN.R                 |  384 +++++++++++++++++++++----------------------
 R/aiRthermo-internal.R       |  250 +++++++++++++--------------
 R/stuve_diagram.R            |  152 ++++++++++-------
 data/RadiosondeA.rda         |binary
 data/RadiosondeD.rda         |binary
 data/RadiosondeDavenport.rda |binary
 data/aiRthermoConstants.rda  |binary
 data/fixedlines.rda          |binary
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 12 files changed, 443 insertions(+), 396 deletions(-)

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Package voteogram updated to version 0.3.1 with previous version 0.2.0 dated 2017-11-27

Title: United States House and Senate Voting Cartogram Generators
Description: 'ProPublica' <https://projects.propublica.org/represent/> makes United States Congress member votes available and has developed their own unique cartogram to visually represent this data. Tools are provided to retrieve voting data, prepare voting data for plotting with 'ggplot2', create vote cartograms and theme them.
Author: Bob Rudis [aut, cre] (<https://orcid.org/0000-0001-5670-2640>), ProPublica [cph] (Cartogram SVGs used to make the plot data.frames), GovTrack [cph] (Cartogram SVG used to make the plot data.frame)
Maintainer: Bob Rudis <bob@rud.is>

Diff between voteogram versions 0.2.0 dated 2017-11-27 and 0.3.1 dated 2018-09-16

 DESCRIPTION                      |   16 +
 MD5                              |   12 -
 build/vignette.rds               |binary
 inst/doc/intro_to_voteogram.R    |    4 
 inst/doc/intro_to_voteogram.Rmd  |    4 
 inst/doc/intro_to_voteogram.html |  316 ++++++++++++++++++++++++---------------
 vignettes/intro_to_voteogram.Rmd |    4 
 7 files changed, 222 insertions(+), 134 deletions(-)

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Package graphon updated to version 0.3.0 with previous version 0.2.0 dated 2017-11-08

Title: A Collection of Graphon Estimation Methods
Description: Provides a not-so-comprehensive list of methods for estimating graphon, a symmetric measurable function, from a single or multiple of observed networks. For a detailed introduction on graphon and popular estimation techniques, see the paper by Orbanz, P. and Roy, D.M.(2014) <doi:10.1109/TPAMI.2014.2334607>. It also contains several auxiliary functions for generating sample networks using various network models and graphons.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>

Diff between graphon versions 0.2.0 dated 2017-11-08 and 0.3.0 dated 2018-09-16

 graphon-0.2.0/graphon/man/graphon.Rd         |only
 graphon-0.3.0/graphon/DESCRIPTION            |   15 ++++----
 graphon-0.3.0/graphon/MD5                    |   50 ++++++++++++++-------------
 graphon-0.3.0/graphon/NAMESPACE              |    2 +
 graphon-0.3.0/graphon/R/cv.SBA.R             |   18 ++++-----
 graphon-0.3.0/graphon/R/est.LG.R             |   21 +++++------
 graphon-0.3.0/graphon/R/est.SBA.R            |   21 +++++------
 graphon-0.3.0/graphon/R/est.USVT.R           |   10 ++---
 graphon-0.3.0/graphon/R/est.completion.R     |   12 +++---
 graphon-0.3.0/graphon/R/est.nbdsmooth.R      |   10 +++--
 graphon-0.3.0/graphon/R/gmodel.ER.R          |   17 ++++-----
 graphon-0.3.0/graphon/R/gmodel.P.R           |    8 ++--
 graphon-0.3.0/graphon/R/gmodel.block.R       |   12 +++---
 graphon-0.3.0/graphon/R/gmodel.preset.R      |   13 ++++---
 graphon-0.3.0/graphon/R/graphon-package.R    |   25 ++-----------
 graphon-0.3.0/graphon/build                  |only
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 graphon-0.3.0/graphon/man/graphon-package.Rd |only
 28 files changed, 176 insertions(+), 190 deletions(-)

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New package VBTree with initial version 0.1.0
Package: VBTree
Type: Package
Title: Vector Binary Tree to Make Your Data Management More Efficient
Version: 0.1.0
Date: 2018-09-05
Author: ZHANG Chen
Maintainer: ZHANG Chen <447974102@qq.com>
Description: Provides a new data structure, vector binary tree, to make your data visiting and management more efficient. if your data has very structurized column names with specific connecting pattern, it can read, split, and factorize these names, then build the mapping from all string objects to an array or tensor, through vector binary tree, by which the batched data processing can be implemented easily. The methods of array and tensor are also applicable.
Imports: tensorA
Depends: R (>= 2.10)
License: GPL-3
URL: https://github.com/CubicZebra/VBTree
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-10 12:06:20 UTC; chen_zhang
Repository: CRAN
Date/Publication: 2018-09-16 18:10:09 UTC

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New package taxotools with initial version 0.0.3
Package: taxotools
Type: Package
Title: Tools to Handle Taxonomic Lists
Version: 0.0.3
Date: 2018-09-10
Authors@R: c( person("Vijay", "Barve", ,"vijay.barve@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4852-2567")))
Maintainer: Vijay Barve <vijay.barve@gmail.com>
Description: Some tools to work with taxonomic name lists.
License: CC0
Imports: taxize, wikitaxa
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
BugReports: https://github.com/vijaybarve/taxotools/issues
NeedsCompilation: no
Packaged: 2018-09-10 14:44:36 UTC; vijaybarve
Author: Vijay Barve [aut, cre] (<https://orcid.org/0000-0002-4852-2567>)
Repository: CRAN
Date/Publication: 2018-09-16 18:20:03 UTC

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New package stylest with initial version 0.1.0
Package: stylest
Version: 0.1.0
Title: Estimating Speaker Style Distinctiveness
Authors@R: c( person("Leslie", "Huang", role = c("aut", "cph", "cre"), email = "lesliehuang@nyu.edu"), person(c("Patrick", "O."), "Perry", role = c("aut", "cph")), person("Arthur", "Spirling", role = c("aut", "cph")))
Depends: R (>= 2.10)
Imports: corpus, Matrix, stats
Suggests: knitr, rmarkdown, testthat, kableExtra
Description: Estimates distinctiveness in speakers' (authors') style. Fits models that can be used for predicting speakers of new texts. Methods developed in Spirling et al (2018) <doi:10.2139/ssrn.3235506> (working paper).
License: GPL-3
URL: https://github.com/leslie-huang/stylest
BugReports: https://github.com/leslie-huang/stylest/issues
LazyData: true
Encoding: UTF-8
VignetteBuilder: knitr, rmarkdown
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-09-10 12:50:57 UTC; lesliehuang
Author: Leslie Huang [aut, cph, cre], Patrick O. Perry [aut, cph], Arthur Spirling [aut, cph]
Maintainer: Leslie Huang <lesliehuang@nyu.edu>
Repository: CRAN
Date/Publication: 2018-09-16 18:10:03 UTC

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New package roundhouse with initial version 0.0.1
Package: roundhouse
Type: Package
Title: An R Wrapper to the 'ICNDb' API
Version: 0.0.1
Authors@R: person("Brandon", "Greenwell", email = "greenwell.brandon@gmail.com", role = c("aut", "cre"))
Description: An R wrapper to the 'Internet Chuck Norris database' ('ICNDb') API for generating random Chuck Norris facts.
License: GPL (>= 2)
URL: ttps://github.com/bgreenwell/roundhouse
BugReports: https://github.com/bgreenwell/roundhouse/issues
Imports: httr, jsonlite
Suggests: covr, magick, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-16 18:02:59 UTC; bgreenwell
Author: Brandon Greenwell [aut, cre]
Maintainer: Brandon Greenwell <greenwell.brandon@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-16 18:30:02 UTC

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New package ojUtils with initial version 0.1.0
Package: ojUtils
Type: Package
Title: A Collection of Utility Functions
Version: 0.1.0
Date: 2018-08-27
Author: Owe Jessen
Maintainer: Owe Jessen <post@owejessen.de>
Description: This is a collection of utility functions. Currently, it provides alternatives to base ifelse() and base combn() functions utilizing 'Rcpp', and providing a significant speedup compared to base.
License: GPL-3
Imports: Rcpp (>= 0.11.0), testthat
LinkingTo: Rcpp
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2018-09-10 19:04:44 UTC; Owe
Repository: CRAN
Date/Publication: 2018-09-16 18:30:06 UTC

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New package NTsets with initial version 1.0
Package: NTsets
Type: Package
Title: Normality Test Sets Integrated Function and Figure Methods for Continuous Variables
Version: 1.0
Date: 2018-08-25
Author: Wenlong Ren,Jing Xiao,Yawen Zhang and Zhikai Liang
Maintainer: Wenlong Ren<wenlongren@ntu.edu.cn>
Description: Conduct normality test with nine different function methods and three different figure methods for continuous variables with a friendly GUI. For different data types, provide a more comprehensive means of judgement.
Depends: gWidgets,gWidgetsRGtk2,RGtk2Extras
Imports: RGtk2,methods,nortest,tseries,fBasics
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-09-02 13:01:57 UTC; 78165
Repository: CRAN
Date/Publication: 2018-09-16 18:20:06 UTC

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New package MPN with initial version 0.1.0
Package: MPN
Title: Most Probable Number for Serial Dilutions
Version: 0.1.0
Authors@R: c( person("Martine", "Ferguson", email = "Martine.Ferguson@fda.hhs.gov", role = "aut", comment = "original R code"), person("John", "Ihrie", email = "John.Ihrie@fda.hhs.gov", role = c("cre", "aut")))
Maintainer: John Ihrie <John.Ihrie@fda.hhs.gov>
Description: Calculates the Most Probable Number for serial dilutions to quantify the concentration (density) of microbes in a laboratory sample. Currently implements the confidence interval approach described in Jarvis (2010) <doi:10.1111/j.1365-2672.2010.04792.x>.
Depends: R (>= 3.4.0)
License: Unlimited
URL: https://mpncalc.galaxytrakr.org/
LazyData: TRUE
RoxygenNote: 6.1.0
Imports: stats (>= 3.4.0)
Suggests: knitr (>= 1.20), rmarkdown (>= 1.10), testthat (>= 2.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-09-04 13:54:02 UTC; John.Ihrie
Author: Martine Ferguson [aut] (original R code), John Ihrie [cre, aut]
Repository: CRAN
Date/Publication: 2018-09-16 18:20:09 UTC

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New package caMST with initial version 0.1.0
Package: caMST
Type: Package
Title: Mixed Computerized Adaptive Multistage Testing
Version: 0.1.0
Date: 2018-08-22
Authors@R: person("Anthony", "Raborn", email = "anthony.w.raborn@gmail.com", role = c("aut","cre"))
Description: Provides functions to more easily analyze computerized adaptive tests. Currently, functions for computerized adaptive tests (CAT), computer adaptive multistage tests (CMT), and mixed computer adaptive multistage tests (McaMST) utilizing CAT item-level adaptation for the initial stage and traditional MST module-level adaptation for the subsequent stages have been created, and a variation of Hybrid computer adaptive MST is planned as well. For an in-depth look at CAT and MST, see Weiss & Kingsbury (1984) <doi:10.1111/j.1745-3984.1984.tb01040.x> and Luecht & Nungester (2000) <doi:10.1007/0-306-47531-6_6> respectively.
License: LGPL (>= 2.0, < 3) | Mozilla Public License
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2.3)
Imports: catR, mstR
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-10 14:45:18 UTC; chika
Author: Anthony Raborn [aut, cre]
Maintainer: Anthony Raborn <anthony.w.raborn@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-16 18:10:06 UTC

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New package ahpsurvey with initial version 0.2.1
Package: ahpsurvey
Type: Package
Title: Analytic Hierarchy Process for Survey Data
Version: 0.2.1
Authors@R: person("Frankie", "Cho", email = "htcho@connect.hku.hk", role = c("aut", "cre"))
Description: The Analytic Hierarchy Process is a versatile multi-criteria decision-making tool introduced by Saaty (1987) <doi:10.1016/0270-0255(87)90473-8> that allows decision-makers to weigh attributes and evaluate alternatives presented to them. This package provides a consistent methodology for researchers to reformat data and run analytic hierarchy process in R on data that are formatted using the survey data entry mode. It is optimized for performing the analytic hierarchy process with many decision-makers, and provides tools and options for researchers to aggregate individual preferences and test multiple options. It also allows researchers to quantify, visualize and correct for inconsistency in the decision-maker's comparisons.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: Rdpack, stats, magrittr, knitr, tidyr, dplyr
Suggests: ggplot2, tidyverse, scales
RdMacros: Rdpack
Collate: 'ahp_mat.R' 'ahp_aggjudge.R' 'ahp_aggpref.R' 'ahp_bweight.R' 'ahp_cr.R' 'ahp_indpref.R' 'ahp_error.R' 'ahp_harker.R' 'ahp_missing.R' 'ahp_pwerror.R' 'ahpsurvey.R' 'data.R'
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-10 16:24:00 UTC; chohinting
Author: Frankie Cho [aut, cre]
Maintainer: Frankie Cho <htcho@connect.hku.hk>
Repository: CRAN
Date/Publication: 2018-09-16 18:40:03 UTC

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Package simstudy updated to version 0.1.10 with previous version 0.1.9 dated 2018-05-11

Title: Simulation of Study Data
Description: Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR).
Author: Keith Goldfeld [aut, cre]
Maintainer: Keith Goldfeld <Keith.Goldfeld@nyumc.org>

Diff between simstudy versions 0.1.9 dated 2018-05-11 and 0.1.10 dated 2018-09-16

 DESCRIPTION            |   15 
 MD5                    |  125 +++----
 NAMESPACE              |    3 
 NEWS.md                |    9 
 R/addColumns.R         |    4 
 R/addCondition.R       |    6 
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 R/int_evalDef.R        |   11 
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 R/int_genNegBinom.R    |    4 
 R/int_genPosSkew.R     |    4 
 R/int_genQuantU.R      |   12 
 R/int_genUnifInt.R     |    4 
 R/int_genbasisdt.R     |    4 
 R/int_genbeta.R        |only
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 R/int_generate.R       |   30 -
 R/int_genexp.R         |    4 
 R/int_gengamma.R       |    8 
 R/int_gennorm.R        |    8 
 R/int_genpois.R        |    8 
 R/int_genpoistrunc.R   |    4 
 R/int_genunif.R        |    4 
 R/int_isError.R        |    4 
 R/int_loProb.R         |    2 
 R/int_rmult.R          |    2 
 R/trtAssign.R          |    2 
 R/updateDef.R          |    4 
 R/viewBasis.R          |    2 
 R/viewSplines.R        |    2 
 build/vignette.rds     |binary
 inst/doc/simstudy.R    |  183 ++++++++++
 inst/doc/simstudy.Rmd  |  274 ++++++++++++++-
 inst/doc/simstudy.html |  852 +++++++++++++++++++++++++++++--------------------
 man/addCorData.Rd      |    4 
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 man/genFactor.Rd       |    3 
 man/genMiss.Rd         |    3 
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 man/genOrdCat.Rd       |    2 
 vignettes/simstudy.Rmd |  274 ++++++++++++++-
 68 files changed, 1718 insertions(+), 685 deletions(-)

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Package nnTensor updated to version 0.99.4 with previous version 0.99.1 dated 2018-06-04

Title: Non-Negative Tensor Decomposition
Description: Some functions for performing non-negative matrix factorization, non-negative CANDECOMP/PARAFAC (CP) decomposition, non-negative Tucker decomposition, and generating toy model data. See Andrzej Cichock et al (2009) <doi:10.1002/9780470747278> and the reference section of GitHub README.md <https://github.com/rikenbit/nnTensor>, for details of the methods.
Author: Koki Tsuyuzaki, Manabu Ishii, Itoshi Nikaido
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>

Diff between nnTensor versions 0.99.1 dated 2018-06-04 and 0.99.4 dated 2018-09-16

 DESCRIPTION               |   12 +++----
 MD5                       |   30 +++++++++---------
 NAMESPACE                 |    2 -
 R/NMF.R                   |   53 +++++++++++++++++++-------------
 R/NTD.R                   |   61 ++++++++++++++++++++++---------------
 R/NTF.R                   |   74 ++++++++++++++++++++++++++--------------------
 R/toyModel.R              |   45 +++++++++++++++------------
 build/partial.rdb         |binary
 inst/NEWS                 |   13 ++++++++
 man/NMF.Rd                |    2 +
 man/NTD.Rd                |    2 +
 man/NTF.Rd                |    2 +
 man/toyModel.Rd           |   11 ++++--
 tests/testthat/test_NMF.R |   50 ++++++++++++++-----------------
 tests/testthat/test_NTD.R |   22 ++++++-------
 tests/testthat/test_NTF.R |   50 ++++++++++++++++---------------
 16 files changed, 244 insertions(+), 185 deletions(-)

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New package duawranglr with initial version 0.6.3
Package: duawranglr
Title: Securely Wrangle Dataset According to Data Usage Agreement
Version: 0.6.3
Authors@R: person("Benjamin", "Skinner", email = "btskinner@virginia.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0337-7415"))
URL: https://github.com/btskinner/duawranglr
BugReports: https://github.com/btskinner/duawranglr/issues
Description: Create shareable data sets from raw data files that contain protected elements. Relying on master crosswalk files that list restricted variables, package functions warn users about possible violations of data usage agreement and prevent writing protected elements.
Depends: R (>= 3.1.2)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: haven, readxl, readr, digest, dplyr
RoxygenNote: 6.1.0
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-10 13:05:52 UTC; bts4h
Author: Benjamin Skinner [aut, cre] (<https://orcid.org/0000-0002-0337-7415>)
Maintainer: Benjamin Skinner <btskinner@virginia.edu>
Repository: CRAN
Date/Publication: 2018-09-16 18:00:02 UTC

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Package mapview updated to version 2.6.0 with previous version 2.5.0 dated 2018-08-16

Title: Interactive Viewing of Spatial Data in R
Description: Quickly and conveniently create interactive visualisations of spatial data with or without background maps. Attributes of displayed features are fully queryable via pop-up windows. Additional functionality includes methods to visualise true- and false-color raster images, bounding boxes, small multiples and 3D raster data cubes.
Author: Tim Appelhans [cre, aut], Florian Detsch [aut], Christoph Reudenbach [aut], Stefan Woellauer [aut], Spaska Forteva [ctb], Thomas Nauss [ctb], Edzer Pebesma [ctb], Kenton Russell [ctb], Michael Sumner [ctb], Jochen Darley [ctb], Pierre Roudier [ctb], Patrick Schratz [ctb], Environmental Informatics Marburg [ctb]
Maintainer: Tim Appelhans <tim.appelhans@gmail.com>

Diff between mapview versions 2.5.0 dated 2018-08-16 and 2.6.0 dated 2018-09-16

 DESCRIPTION                           |   92 +++++++++++++-----
 MD5                                   |   36 +++----
 NEWS                                  |   14 ++
 NEWS.md                               |   14 ++
 R/extent.R                            |    1 
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 R/mapView.R                           |  167 +++++++++++++++++++---------------
 R/mapshot.R                           |   25 +++--
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 R/popup.R                             |   17 ++-
 R/raster.R                            |    8 +
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 R/stars.R                             |    3 
 README.md                             |    1 
 data/breweries.rda                    |binary
 man/mapView.Rd                        |   36 ++++---
 man/popup.Rd                          |    4 
 man/viewExtent.Rd                     |    1 
 tests/testthat/test-mapviewControls.R |  118 ++++++++++++++++++++++--
 19 files changed, 488 insertions(+), 216 deletions(-)

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Package knockoff updated to version 0.3.2 with previous version 0.3.0 dated 2017-10-17

Title: The Knockoff Filter for Controlled Variable Selection
Description: The knockoff filter is a general procedure for controlling the false discovery rate (FDR) when performing variable selection. For more information, see the website below and the accompanying paper: Candes et al., "Panning for Gold: Model-X Knockoffs for High-dimensional Controlled Variable Selection", 2016, <arXiv:1610.02351>.
Author: Rina Foygel Barber [ctb] (Development of the original Fixed-X Knockoffs), Emmanuel Candes [ctb] (Development of Model-X Knockoffs and original Fixed-X Knockoffs), Lucas Janson [ctb] (Development of Model-X Knockoffs), Evan Patterson [aut] (Original R package for the original Fixed-X Knockoffs), Matteo Sesia [aut, cre] (R package for Model-X Knockoffs)
Maintainer: Matteo Sesia <msesia@stanford.edu>

Diff between knockoff versions 0.3.0 dated 2017-10-17 and 0.3.2 dated 2018-09-16

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Package fieldRS updated to version 0.1.1 with previous version 0.1.0 dated 2018-08-02

Title: Remote Sensing Field Work Tools
Description: In remote sensing, designing a field campaign to collect ground-truth data can be a challenging task. We need to collect representative samples while accounting for issues such as budget constraints and limited accessibility created by e.g. poor infrastructure. As suggested by Olofsson et al. (2014) <doi:10.1016/j.rse.2014.02.015>, this demands the establishment of best-practices to collect ground-truth data that avoid the waste of time and funds. 'fieldRS' addresses this issue by helping scientists and practitioners design field campaigns through the identification of priority sampling sites, the extraction of potential sampling plots and the conversion of plots into consistent training and validation samples that can be used in e.g. land cover classification.
Author: Ruben Remelgado [aut, cre]
Maintainer: Ruben Remelgado <ruben.remelgado@uni-wuerzburg.de>

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Package dynr updated to version 0.1.13-3 with previous version 0.1.13-2 dated 2018-09-15

Title: Dynamic Modeling in R
Description: Intensive longitudinal data have become increasingly prevalent in various scientific disciplines. Many such data sets are noisy, multivariate, and multi-subject in nature. The change functions may also be continuous, or continuous but interspersed with periods of discontinuities (i.e., showing regime switches). The package 'dynr' (Dynamic Modeling in R) is an R package that implements a set of computationally efficient algorithms for handling a broad class of linear and nonlinear discrete- and continuous-time models with regime-switching properties under the constraint of linear Gaussian measurement functions. The discrete-time models can generally take on the form of a state- space or difference equation model. The continuous-time models are generally expressed as a set of ordinary or stochastic differential equations. All estimation and computations are performed in C, but users are provided with the option to specify the model of interest via a set of simple and easy-to-learn model specification functions in R. Model fitting can be performed using single- subject time series data or multiple-subject longitudinal data.
Author: Lu Ou [aut], Michael D. Hunter [aut, cre], Sy-Miin Chow [aut]
Maintainer: Michael D. Hunter <mhunter.ou@gmail.com>

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Package divest updated to version 0.6.1 with previous version 0.6.0 dated 2018-04-26

Title: Get Images Out of DICOM Format Quickly
Description: Provides tools to sort DICOM-format medical image files, and convert them to NIfTI-1 format.
Author: Jon Clayden [aut, cre], Chris Rorden [aut], Martin J Fiedler [cph], Cong Xu [cph], Pascal Gloor [cph]
Maintainer: Jon Clayden <code@clayden.org>

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Package DHS.rates updated to version 0.4.0 with previous version 0.3.1 dated 2018-06-10

Title: Calculate Key DHS Indicators
Description: Calculates key indicators such as fertility rates (Total Fertility Rate (TFR), General Fertility Rate (GFR), and Age Specific Fertility Rate (ASFR)) using Demographic and Health Survey (DHS) women/individual data, and childhood mortality rates such as Neonatal Mortality Rate (NNMR), Post-neonatal Mortality Rate (PNNMR), Infant Mortality Rate (IMR), Child Mortality Rate (CMR), and Under-five Mortality Rate (U5MR). In addition to the indicators, the 'DHS.rates' package estimates sampling errors indicators such as Standard Error (SE), Design Effect (DEFT), Relative Standard Error (RSE) and Confidence Interval (CI). The package is developed according to the DHS methodology of calculating the fertility indicators and the childhood mortality rates outlined in the "Guide to DHS Statistics" (Croft, Trevor N., Aileen M. J. Marshall, Courtney K. Allen, et al. 2018, <https://dhsprogram.com/Data/Guide-to-DHS-Statistics/index.cfm>) and the DHS methodology of estimating the sampling errors indicators outlined in the "DHS Sampling and Household Listing Manual" (ICF International 2012, <https://dhsprogram.com/pubs/pdf/DHSM4/DHS6_Sampling_Manual_Sept2012_DHSM4.pdf>).
Author: Mahmoud Elkasabi
Maintainer: Mahmoud Elkasabi <mahmoud.elkasabi@icf.com>

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Package brms updated to version 2.5.0 with previous version 2.4.0 dated 2018-07-20

Title: Bayesian Regression Models using 'Stan'
Description: Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include non-linear and smooth terms, auto-correlation structures, censored data, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with posterior predictive checks and leave-one-out cross-validation. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
Author: Paul-Christian Bürkner [aut, cre]
Maintainer: Paul-Christian Bürkner <paul.buerkner@gmail.com>

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Package recmap updated to version 1.0.0 with previous version 0.5.37 dated 2018-08-28

Title: Compute the Rectangular Statistical Cartogram
Description: Provides an interface and a C++ implementation of the RecMap MP2 construction heuristic (see 'citation("recmap")' for details). This algorithm draws maps according to a given statistical value (e.g., election results, population or epidemiological data). The basic idea of the RecMap algorithm is that each map region (e.g., different countries) is represented by a rectangle. The area of each rectangle represents the statistical value given as input (maintain zero cartographic error). Documentation about RecMap is provided by a vignette included in this package.
Author: Christian Panse [aut, cre] (<https://orcid.org/0000-0003-1975-3064>)
Maintainer: Christian Panse <Christian.Panse@gmail.com>

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Package psychReport updated to version 0.2 with previous version 0.1 dated 2018-08-11

Title: Reproducible Reports in Psychology
Description: Helper functions for producing reports in Psychology (Reproducible Research). Provides required formatted strings (APA style) for use in 'Sweave'/'Knitr' 'Latex' integration within *.Rnw files.
Author: Ian G Mackenzie
Maintainer: Ian G Mackenzie <ian.mackenzie@uni-tuebingen.de>

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Package rgeopat2 updated to version 0.2.6 with previous version 0.2.5 dated 2018-06-15

Title: Additional Functions for 'GeoPAT' 2
Description: Supports analysis of spatial data processed with the 'GeoPAT' 2 software <http://sil.uc.edu/cms/index.php?id=geopat2>. Available features include creation of a grid based on the 'GeoPAT' 2 grid header file and reading a 'GeoPAT' 2 text outputs.
Author: Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>), Space Informatics Lab [cph]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

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Package usmap updated to version 0.4.0 with previous version 0.3.0 dated 2018-06-03

Title: US Maps Including Alaska and Hawaii
Description: Obtain United States map data frames of varying region types (e.g. county, state). The map data frames include Alaska and Hawaii conveniently placed to the bottom left, as they appear in most maps of the US. Convenience functions for plotting choropleths and working with FIPS codes are also provided.
Author: Paolo Di Lorenzo [aut, cre]
Maintainer: Paolo Di Lorenzo <paolo@dilorenzo.pl>

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Package reprex updated to version 0.2.1 with previous version 0.2.0 dated 2018-06-22

Title: Prepare Reproducible Example Code via the Clipboard
Description: Convenience wrapper that uses the 'rmarkdown' package to render small snippets of code to target formats that include both code and output. The goal is to encourage the sharing of small, reproducible, and runnable examples on code-oriented websites, such as <https://stackoverflow.com> and <https://github.com>, or in email. The user's clipboard is the default source of input code and the default target for rendered output. 'reprex' also extracts clean, runnable R code from various common formats, such as copy/paste from an R session.
Author: Jennifer Bryan [aut, cre] (<https://orcid.org/0000-0002-6983-2759>), Jim Hester [aut] (<https://orcid.org/0000-0002-2739-7082>), David Robinson [aut], Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>), RStudio [cph, fnd]
Maintainer: Jennifer Bryan <jenny@rstudio.com>

Diff between reprex versions 0.2.0 dated 2018-06-22 and 0.2.1 dated 2018-09-16

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 reprex-0.2.1/reprex/NAMESPACE                                                 |    1 
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Package arrangements updated to version 1.1.3 with previous version 1.1.2 dated 2018-08-24

Title: Fast Generators and Iterators for Permutations, Combinations and Partitions
Description: Fast generators and iterators for permutations, combinations and partitions. The iterators allow users to generate arrangements in a memory efficient manner and the generated arrangements are in lexicographical (dictionary) order. Permutations and combinations can be drawn with/without replacement and support multisets. It has been demonstrated that 'arrangements' outperforms most of the existing packages of similar kind. Some benchmarks could be found at <https://randy3k.github.io/arrangements/articles/benchmark.html>.
Author: Randy Lai [aut, cre]
Maintainer: Randy Lai <randy.cs.lai@gmail.com>

Diff between arrangements versions 1.1.2 dated 2018-08-24 and 1.1.3 dated 2018-09-16

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Sat, 15 Sep 2018

Package spData updated to version 0.2.9.4 with previous version 0.2.9.3 dated 2018-08-01

Title: Datasets for Spatial Analysis
Description: Diverse spatial datasets for demonstrating, benchmarking and teaching spatial data analysis. It includes R data of class sf (defined by the package 'sf'), Spatial ('sp'), and nb ('spdep'). Unlike other spatial data packages such as 'rnaturalearth' and 'maps', it also contains data stored in a range of file formats including GeoJSON, ESRI Shapefile and GeoPackage. Some of the datasets are designed to illustrate specific analysis techniques. cycle_hire() and cycle_hire_osm(), for example, is designed to illustrate point pattern analysis techniques.
Author: Roger Bivand [aut] (<https://orcid.org/0000-0003-2392-6140>), Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>), Robin Lovelace [aut] (<https://orcid.org/0000-0001-5679-6536>), Mark Monmonier [ctb] (author of the state.vbm dataset), Greg Snow [ctb] (author of the state.vbm dataset)
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

Diff between spData versions 0.2.9.3 dated 2018-08-01 and 0.2.9.4 dated 2018-09-15

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Package estimatr updated to version 0.12 with previous version 0.10.0 dated 2018-07-12

Title: Fast Estimators for Design-Based Inference
Description: Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regression, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>.
Author: Graeme Blair [aut, cre], Jasper Cooper [aut], Alexander Coppock [aut], Macartan Humphreys [aut], Luke Sonnet [aut], Neal Fultz [ctb]
Maintainer: Graeme Blair <graeme.blair@ucla.edu>

Diff between estimatr versions 0.10.0 dated 2018-07-12 and 0.12 dated 2018-09-15

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Package JWileymisc updated to version 0.3.1 with previous version 0.3.0 dated 2018-08-26

Title: Miscellaneous Utilities and Functions
Description: A collection of miscellaneous tools and functions, such as tools to generate descriptive statistics tables, format output, visualize relations among variables or check distributions.
Author: Joshua F. Wiley <jwiley.psych@gmail.com>
Maintainer: Joshua F. Wiley <jwiley.psych@gmail.com>

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Package rdnb updated to version 0.1-2 with previous version 0.1-1 dated 2017-02-14

Title: R Interface to the 'Deutsche Nationalbibliothek (German National Library) API'
Description: A wrapper for the 'Deutsche Nationalbibliothek (German National Library) API', available at <http://www.dnb.de>. The German National Library is the German central archival library, collecting, archiving, bibliographically classifying all German and German-language publications, foreign publications about Germany, translations of German works, and the works of German-speaking emigrants published abroad between 1933 and 1945. A personal access token is required for usage.
Author: Christian Graul [aut, cre]
Maintainer: Christian Graul <christian.graul@gmail.com>

Diff between rdnb versions 0.1-1 dated 2017-02-14 and 0.1-2 dated 2018-09-15

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Package rtsplot updated to version 0.1.1 with previous version 0.1.0 dated 2018-05-29

Title: Time Series Plot
Description: A fast and elegant time series visualization package. In addition to the standard R plot types, this package supports candle sticks, open-high-low-close, and volume plots. Useful for visualizing any time series data, e.g., stock prices and technical indicators.
Author: RTSVizTeam [aut, cph], Irina Kapler [cre]
Maintainer: Irina Kapler <irkapler@gmail.com>

Diff between rtsplot versions 0.1.0 dated 2018-05-29 and 0.1.1 dated 2018-09-15

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Package conflicted updated to version 1.0.0 with previous version 0.1.0 dated 2018-05-31

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>

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Package fitODBOD updated to version 1.2.0 with previous version 1.1.0 dated 2018-02-27

Title: Modeling Over Dispersed Binomial Outcome Data Using BMD and ABD
Description: Contains Probability Mass Functions, Cumulative Mass Functions, Negative Log Likelihood value, parameter estimation and modeling data using Binomial Mixture Distributions (BMD) (Manoj et al (2013) <doi:10.5539/ijsp.v2n2p24>) and Alternate Binomial Distributions (ABD) (Paul (1985) <doi:10.1080/03610928508828990>).
Author: Amalan Mahendran [aut, cre], Pushpakanthie Wijekoon [aut, ctb]
Maintainer: Amalan Mahendran <amalan0595@gmail.com>

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Package FENmlm updated to version 2.2.1 with previous version 2.2.0 dated 2018-08-04

Title: Fixed Effects Nonlinear Maximum Likelihood Models
Description: Efficient estimation of multiple fixed-effects maximum likelihood models with, possibly, non-linear in parameters right hand sides. Standard-errors can easily be clustered. It also includes tools to seamlessly export (to Latex) the results of various estimations.
Author: Laurent Berge [aut, cre]
Maintainer: Laurent Berge <laurent.berge@uni.lu>

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Package PropClust updated to version 1.4-6 with previous version 1.4-3 dated 2018-01-21

Title: Propensity Clustering and Decomposition
Description: Implementation of propensity clustering and decomposition as described in Ranola et al. (2013) <doi:10.1186/1752-0509-7-21>. Propensity decomposition can be viewed on the one hand as a generalization of the eigenvector-based approximation of correlation networks, and on the other hand as a generalization of random multigraph models and conformity-based decompositions.
Author: John Michael O Ranola, Kenneth Lange, Steve Horvath, Peter Langfelder
Maintainer: Peter Langfelder <Peter.Langfelder@gmail.com>

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Package mcbiopi updated to version 1.1.5 with previous version 1.1.2 dated 2012-01-04

Title: Matrix Computation Based Identification of Prime Implicants
Description: Computes the prime implicants or a minimal disjunctive normal form for a logic expression presented by a truth table or a logic tree. Has been particularly developed for logic expressions resulting from a logic regression analysis, i.e. logic expressions typically consisting of up to 16 literals, where the prime implicants are typically composed of a maximum of 4 or 5 literals.
Author: Holger Schwender
Maintainer: Holger Schwender <holger.schw@gmx.de>

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Package ggetho updated to version 0.3.3 with previous version 0.3.2 dated 2018-05-28

Title: Visualisation of High-Throughput Behavioural (i.e. Ethomics) Data
Description: Extension of 'ggplot2' providing layers, scales and preprocessing functions useful to represent behavioural variables that are recorded over multiple animals and days. This package is part of the rethomics framework <http://rethomics.github.io/>.
Author: Quentin Geissmann [aut, cre]
Maintainer: Quentin Geissmann <qgeissmann@gmail.com>

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Package ftsa updated to version 5.0 with previous version 4.9 dated 2018-08-23

Title: Functional Time Series Analysis
Description: Functions for visualizing, modeling, forecasting and hypothesis testing of functional time series.
Author: Rob J Hyndman and Han Lin Shang
Maintainer: Han Lin Shang <hanlin.shang@anu.edu.au>

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Package FFTrees updated to version 1.4.0 with previous version 1.3.5 dated 2017-11-01

Title: Generate, Visualise, and Evaluate Fast-and-Frugal Decision Trees
Description: Create, visualize, and test fast-and-frugal decision trees (FFTs). FFTs are very simple decision trees for binary classification problems. FFTs can be preferable to more complex algorithms because they are easy to communicate, require very little information, and are robust against overfitting.
Author: Nathaniel Phillips [aut, cre], Hansjoerg Neth [aut], Jan Woike [aut], Wolfgang Gaissmaer [aut]
Maintainer: Nathaniel Phillips <Nathaniel.D.Phillips.is@gmail.com>

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Package cobalt updated to version 3.4.1 with previous version 3.4.0 dated 2018-08-14

Title: Covariate Balance Tables and Plots
Description: Generate balance tables and plots for covariates of groups preprocessed through matching, weighting or subclassification, for example, using propensity scores. Includes integration with 'MatchIt', 'twang', 'Matching', 'optmatch', 'CBPS', 'ebal', 'WeightIt', and 'designmatch' for assessing balance on the output of their preprocessing functions. Users can also specify data for balance assessment not generated through the above packages. Also included are methods for assessing balance in clustered or multiply imputed data sets or data sets with longitudinal treatments.
Author: Noah Greifer [aut, cre]
Maintainer: Noah Greifer <noah.greifer@gmail.com>

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New package BLPestimatoR with initial version 0.2.5
Package: BLPestimatoR
Type: Package
Title: Performs a BLP Demand Estimation
Version: 0.2.5
Author: Daniel Brunner (aut), Constantin Weiser (ctr), Andre Romahn (ctr)
Maintainer: Daniel Brunner <daniel.brunner@hhu.de>
Description: Provides the estimation algorithm to perform the demand estimation described in Berry, Levinsohn and Pakes (1995) <DOI:10.2307/2171802> . The routine uses analytic gradients and offers a large number of implemented integration methods and optimization routines.
License: GPL-3
LazyData: TRUE
Imports: Rcpp (>= 0.11.0), mvQuad, numDeriv, randtoolbox, Formula, stats
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.0
NeedsCompilation: yes
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Packaged: 2018-09-14 17:43:13 UTC; brubu
Repository: CRAN
Date/Publication: 2018-09-15 07:20:16 UTC

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Package chebpol updated to version 2.0 with previous version 1.7 dated 2018-08-23

Title: Multivariate Interpolation
Description: Contains methods for creating multivariate interpolations of functions on a hypercube. If available through fftw3, the DCT-II/FFT is used to compute coefficients for a Chebyshev interpolation. Other interpolation methods for arbitrary Cartesian grids are also provided, a piecewise multilinear, and the Floater-Hormann barycenter method. For scattered data polyharmonic splines with a linear term is provided. The time-critical parts are written in C for speed. All interpolants are parallelized if used to evaluate more than one point.
Author: Simen Gaure [aut, cre] (Ragnar Frisch Centre for Economic Research)
Maintainer: Simen Gaure <Simen.Gaure@frisch.uio.no>

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