Mon, 17 Feb 2020

New package collector with initial version 0.1.3
Package: collector
Title: Quantified Risk Assessment Data Collection
Version: 0.1.3
Authors@R: person("David", "Severski", email = "davidski@deadheaven.com", role = c("aut", "cre"), comment = c(ORCID ="0000-0001-7867-0459"))
Description: An open source process for collecting quantified data inputs from subject matter experts. Intended for feeding into an OpenFAIR analysis <https://www2.opengroup.org/ogsys/catalog/C13K> using a tool such as 'evaluator' <https://evaluator.tidyrisk.org>.
Depends: R (>= 3.4.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Imports: EnvStats, dplyr, evaluator (>= 0.4.0), flextable, ggplot2, ggpubr, magrittr, purrr, quanteda, readr, rlang, rmarkdown, stringr, tibble, tidyr (>= 1.0.0), officer, xaringan
Suggests: spelling, testthat, covr, knitr
SystemRequirements: pandoc
URL: https://collector.tidyrisk.org
BugReports: https://github.com/davidski/collector/issues
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-02-17 20:29:46 UTC; david
Author: David Severski [aut, cre] (<https://orcid.org/0000-0001-7867-0459>)
Maintainer: David Severski <davidski@deadheaven.com>
Repository: CRAN
Date/Publication: 2020-02-18 00:10:02 UTC

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New package did with initial version 1.2.3
Package: did
Title: Treatment Effects with Multiple Periods and Groups
Version: 1.2.3
Authors@R: c(person("Brantly", "Callaway", email = "bmcallaw@olemiss.edu", role = c("aut", "cre")), person("Pedro H.C.", "Sant\'Anna", email="pedro.h.santanna@vanderbilt.edu", role = c("aut")))
Description: The standard Difference-in-Differences (DID) setup involves two periods and two groups -- a treated group and untreated group. Many applications of DID methods involve more than two periods and have individuals that are treated at different points in time. This package contains tools for computing average treatment effect parameters in Difference in Differences models with more than two periods and with variation in treatment timing using the methods developed in Callaway and Sant'Anna (2019) <https://ssrn.com/abstract=3148250>. The main parameters are group-time average treatment effects which are the average treatment effect for a particular group at a a particular time. These can be aggregated into a fewer number of treatment effect parameters, and the package deals with the cases where there is selective treatment timing, dynamic treatment effects, calendar time effects, or combinations of these. There are also functions for testing the Difference in Differences assumption, and plotting group-time average treatment effects.
Depends: R (>= 2.10)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: BMisc (>= 1.3.1), MASS, pbapply, stats, ggplot2, knitr, utils, gridExtra
RoxygenNote: 7.0.2
VignetteBuilder: knitr
Suggests: rmarkdown
NeedsCompilation: no
Packaged: 2020-02-17 20:28:32 UTC; brant
Author: Brantly Callaway [aut, cre], Pedro H.C. Sant'Anna [aut]
Maintainer: Brantly Callaway <bmcallaw@olemiss.edu>
Repository: CRAN
Date/Publication: 2020-02-18 00:00:02 UTC

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Package rvg updated to version 0.2.4 with previous version 0.2.3 dated 2020-01-26

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

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Package rsvd updated to version 1.0.3 with previous version 1.0.2 dated 2019-07-29

Title: Randomized Singular Value Decomposition
Description: Low-rank matrix decompositions are fundamental tools and widely used for data analysis, dimension reduction, and data compression. Classically, highly accurate deterministic matrix algorithms are used for this task. However, the emergence of large-scale data has severely challenged our computational ability to analyze big data. The concept of randomness has been demonstrated as an effective strategy to quickly produce approximate answers to familiar problems such as the singular value decomposition (SVD). The rsvd package provides several randomized matrix algorithms such as the randomized singular value decomposition (rsvd), randomized principal component analysis (rpca), randomized robust principal component analysis (rrpca), randomized interpolative decomposition (rid), and the randomized CUR decomposition (rcur). In addition several plot functions are provided.
Author: N. Benjamin Erichson [aut, cre]
Maintainer: N. Benjamin Erichson <erichson@berkeley.edu>

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Package isdparser updated to version 0.4.0 with previous version 0.3.0 dated 2018-10-23

Title: Parse 'NOAA' Integrated Surface Data Files
Description: Tools for parsing 'NOAA' Integrated Surface Data ('ISD') files, described at <https://www.ncdc.noaa.gov/isd>. Data includes for example, wind speed and direction, temperature, cloud data, sea level pressure, and more. Includes data from approximately 35,000 stations worldwide, though best coverage is in North America/Europe/Australia. Data is stored as variable length ASCII character strings, with most fields optional. Included are tools for parsing entire files, or individual lines of data.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package sse updated to version 0.7-16 with previous version 0.7-15 dated 2019-12-10

Title: Sample Size Estimation
Description: Provides functions to evaluate user-defined power functions for a parameter range, and draws a sensitivity plot. It also provides a resampling procedure for semi-parametric sample size estimation and methods for adding information to a Sweave report.
Author: Thomas Fabbro [aut, cre]
Maintainer: Thomas Fabbro <thomas.fabbro@unibas.ch>

Diff between sse versions 0.7-15 dated 2019-12-10 and 0.7-16 dated 2020-02-17

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Package poisFErobust updated to version 2.0.0 with previous version 1.0.1 dated 2018-07-10

Title: Poisson Fixed Effects Robust
Description: Computation of robust standard errors of Poisson fixed effects models, following Wooldridge (1999).
Author: Evan Wright [aut, cre]
Maintainer: Evan Wright <enwright@umich.edu>

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Package MomTrunc updated to version 5.71 with previous version 5.69 dated 2020-01-24

Title: Moments of Folded and Doubly Truncated Multivariate Distributions
Description: It computes arbitrary products moments (mean vector and variance-covariance matrix), for some double truncated (and folded) multivariate distributions. These distributions belong to the family of selection elliptical distributions, which includes well known skewed distributions as the unified skew-t distribution (SUT) and its particular cases as the extended skew-t (EST), skew-t (ST) and the symmetric student-t (T) distribution. Analogous normal cases unified skew-normal (SUN), extended skew-normal (ESN), skew-normal (SN), and symmetric normal (N) are also included. Density, probabilities and random deviates are also offered for these members. References used for this package: Arellano-Valle, R. B. & Genton, M. G. (2005). On fundamental skew distributions. Journal of Multivariate Analysis, 96, 93-116. Galarza C.E., Matos L.A., Dey D.K. & Lachos V.H. (2019) On Moments of Folded and Truncated Multivariate Extended Skew-Normal Distributions. Technical report. ID 19-14. University of Connecticut. <https://stat.uconn.edu/tech-reports-2019/>.
Author: Christian E. Galarza, Raymond Kan and Victor H. Lachos
Maintainer: Christian E. Galarza <cgalarza88@gmail.com>

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Package SemNetCleaner updated to version 1.1.4 with previous version 1.1.3 dated 2019-12-01

Title: An Automated Cleaning Tool for Semantic and Linguistic Data
Description: Implements several functions that automates the cleaning and spell-checking of text data. Also converges, finalizes, removes plurals and continuous strings, and puts text data in binary format for semantic network analysis. Uses the 'SemNetDictionaries' package to make the cleaning process more accurate, efficient, and reproducible.
Author: Alexander P. Christensen [aut, cre] (<https://orcid.org/0000-0002-9798-7037>)
Maintainer: Alexander P. Christensen <alexpaulchristensen@gmail.com>

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Package MOEADr updated to version 1.1.1 with previous version 1.1.0 dated 2017-10-24

Title: Component-Wise MOEA/D Implementation
Description: Modular implementation of Multiobjective Evolutionary Algorithms based on Decomposition (MOEA/D) [Zhang and Li (2007), <DOI:10.1109/TEVC.2007.892759>] for quick assembling and testing of new algorithmic components, as well as easy replication of published MOEA/D proposals. The full framework is documented in a paper published in the Journal of Statistical Software [<doi:10.18637/jss.v092.i06>].
Author: Felipe Campelo [aut, cre], Lucas Batista [com], Claus Aranha [aut]
Maintainer: Felipe Campelo <fcampelo@ufmg.br>

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Package imager updated to version 0.42.1 with previous version 0.41.2 dated 2019-01-23

Title: Image Processing Library Based on 'CImg'
Description: Fast image processing for images in up to 4 dimensions (two spatial dimensions, one time/depth dimension, one colour dimension). Provides most traditional image processing tools (filtering, morphology, transformations, etc.) as well as various functions for easily analysing image data using R. The package wraps 'CImg', <http://cimg.eu>, a simple, modern C++ library for image processing.
Author: Simon Barthelme [aut], David Tschumperle [ctb], Jan Wijffels [ctb], Haz Edine Assemlal [ctb], Shota Ochi [cre]
Maintainer: Shota Ochi <shotaochi1990@gmail.com>

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Package devtools updated to version 2.2.2 with previous version 2.2.1 dated 2019-09-24

Title: Tools to Make Developing R Packages Easier
Description: Collection of package development tools.
Author: Hadley Wickham [aut], Jim Hester [aut, cre], Winston Chang [aut], RStudio [cph], R Core team [ctb] (Some namespace and vignette code extracted from base R)
Maintainer: Jim Hester <jim.hester@rstudio.com>

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Package wavelets updated to version 0.3-0.2 with previous version 0.3-0.1 dated 2019-01-27

Title: Functions for Computing Wavelet Filters, Wavelet Transforms and Multiresolution Analyses
Description: Contains functions for computing and plotting discrete wavelet transforms (DWT) and maximal overlap discrete wavelet transforms (MODWT), as well as their inverses. Additionally, it contains functionality for computing and plotting wavelet transform filters that are used in the above decompositions as well as multiresolution analyses.
Author: Eric Aldrich <ealdrich@gmail.com>
Maintainer: Eric Aldrich <ealdrich@gmail.com>

Diff between wavelets versions 0.3-0.1 dated 2019-01-27 and 0.3-0.2 dated 2020-02-17

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Package sdwd updated to version 1.0.3 with previous version 1.0.2 dated 2015-08-05

Title: Sparse Distance Weighted Discrimination
Description: Formulates a sparse distance weighted discrimination (SDWD) for high-dimensional classification and implements a very fast algorithm for computing its solution path with the L1, the elastic-net, and the adaptive elastic-net penalties.
Author: Boxiang Wang and Hui Zou
Maintainer: Boxiang Wang <boxiang-wang@uiowa.edu>

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New package osfr with initial version 0.2.8
Package: osfr
Title: Interface to the 'Open Science Framework' ('OSF')
Version: 0.2.8
Authors@R: c( person("Aaron", "Wolen",, "aaron@wolen.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-2542-2202")), person("Chris","Hartgerink",, "chjh@protonmail.com", role = "aut", comment = c(ORCID = "0000-0003-1050-6809")), person("Timothy", "York",, "timothypyork@gmail.com", role = "ctb", comment = c(ORCID = "0000-0003-4068-4286")), person("Ryan", "Hafen",, "rhafen@purdue.edu", role = "ctb"), person("Brian", "Richards",, "brian.g.richards@gmail.com", role = "ctb"), person("Courtney", "Soderberg",, "courtney@cos.io", role = "ctb", comment = c(ORCID = "0000-0003-1227-7042")), person("Carl", "Boettiger",, "cboettig@gmail.com", role = "rev", comment = c(ORCID = "0000-0002-1642-628X")), person("Heidi", "Seibold",, "heidi.seibold@stat.uni-muenchen.de", role = "rev") )
Description: An interface for interacting with 'OSF' (<https://osf.io>). 'osfr' enables you to access open research materials and data, or create and manage your own private or public projects.
Depends: R (>= 3.1.0)
Imports: crul (>= 0.7.4), jsonlite, stringi, purrr, tibble, rlang, fs (>= 1.3.0), memoise, httr
License: MIT + file LICENSE
URL: https://docs.ropensci.org/osfr, https://github.com/ropensci/osfr
BugReports: https://github.com/ropensci/osfr/issues
LazyData: true
Suggests: dplyr, logger, rprojroot, testthat, knitr, rmarkdown, lintr (>= 2.0), covr, spelling
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-02-17 16:30:20 UTC; aaronwolen
Author: Aaron Wolen [aut, cre] (<https://orcid.org/0000-0003-2542-2202>), Chris Hartgerink [aut] (<https://orcid.org/0000-0003-1050-6809>), Timothy York [ctb] (<https://orcid.org/0000-0003-4068-4286>), Ryan Hafen [ctb], Brian Richards [ctb], Courtney Soderberg [ctb] (<https://orcid.org/0000-0003-1227-7042>), Carl Boettiger [rev] (<https://orcid.org/0000-0002-1642-628X>), Heidi Seibold [rev]
Maintainer: Aaron Wolen <aaron@wolen.com>
Repository: CRAN
Date/Publication: 2020-02-17 19:50:05 UTC

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Package gwsem updated to version 0.1.15 with previous version 0.1.14 dated 2020-02-17

Title: Genome-Wide Structural Equation Modeling
Description: Melds genome-wide association tests with structural equation modeling (SEM) using 'OpenMx'. This package contains low-level C/C++ code to rapidly read genetic data encoded in U.K. Biobank or 'plink' formats. Prebuilt modeling options include one and two factor models. Alternately, analyses may utilize arbitrary, user-provided SEMs. See Verhulst, Maes, & Neale (2017) <doi:10.1007/s10519-017-9842-6> for details. An updated manuscript is in preparation.
Author: Joshua N. Pritikin [aut, cre], Bradley Verhulst [cph], Gavin Band [cph], Yann Collet [cph], Facebook, Inc. [cph], Yuta Mori [cph], Shaun Purcell [cph], Christopher Chang [cph], Wojciech Mula [cph], Kim Walisch [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>

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Package flextable updated to version 0.5.8 with previous version 0.5.7 dated 2020-02-03

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

Diff between flextable versions 0.5.7 dated 2020-02-03 and 0.5.8 dated 2020-02-17

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Package sirt updated to version 3.9-4 with previous version 3.8-11 dated 2020-02-15

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

Diff between sirt versions 3.8-11 dated 2020-02-15 and 3.9-4 dated 2020-02-17

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Package rWind updated to version 1.1.5 with previous version 1.1.3 dated 2019-07-24

Title: Download, Edit and Include Wind and Sea Currents Data in Ecological and Evolutionary Analysis
Description: Tools for download and manage surface wind and sea currents data from the Global Forecasting System <https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/global-forcast-system-gfs> and to compute connectivity between locations.
Author: Javier Fernández-López [aut, cre], Klaus Schliep [aut], Yurena Arjona [aut]
Maintainer: Javier Fernández-López <jflopez.bio@gmail.com>

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Package rscala updated to version 3.2.18 with previous version 3.2.17 dated 2020-02-07

Title: Bridge Between 'R' and 'Scala' with Callbacks
Description: 'Scala' <http://www.scala-lang.org/> is embedded in 'R' and callbacks from 'Scala' to 'R' are available. Support is provided to write 'R' packages that access 'Scala'. After installation, please run 'rscala::scalaConfig()'. The vignette provides an update of the original paper <doi:10.18637/jss.v092.i04>.
Author: David B. Dahl [aut, cre]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

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Package robin updated to version 1.0.0 with previous version 0.99.1 dated 2019-10-24

Title: ROBustness in Network
Description: In network analysis, many community detection algorithms have been developed. However, their applications leave unaddressed one important question: the statistical validation of the results. robin (ROBustness In Network) is an R package for the validation of community detection. It has a double aim: to study the robustness of a community detection algorithm and to compare the robustness of different community detection algorithms on the same network. Reference in Annamaria Carissimo, Luisa Cutillo, Italia De Feis (2018) <doi:10.1016/j.csda.2017.10.006>.
Author: Valeria Policastro [aut, cre]
Maintainer: Valeria Policastro <valeria.policastro@gmail.com>

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Package rerddapXtracto updated to version 0.4.7 with previous version 0.4.6 dated 2020-01-09

Title: Extracts Environmental Data from 'ERDDAP' Web Services
Description: Contains three functions that access environmental data from any 'ERDDAP' data web service. The rxtracto() function extracts data along a trajectory for a given "radius" around the point. The rxtracto_3D() function extracts data in a box. The rxtractogon() function extracts data in a polygon. All of those three function use the 'rerddap' package to extract the data, and should work with any 'ERDDAP' server. There are also two functions, plotBBox() and plotTrack() that use the 'plotdap' package to simplify the creation of maps of the data.
Author: Roy Mendelssohn [aut, cre]
Maintainer: Roy Mendelssohn <roy.mendelssohn@noaa.gov>

Diff between rerddapXtracto versions 0.4.6 dated 2020-01-09 and 0.4.7 dated 2020-02-17

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Package redcapAPI updated to version 2.3 with previous version 2.2 dated 2018-08-01

Title: Interface to 'REDCap'
Description: Access data stored in 'REDCap' databases using the Application Programming Interface (API). 'REDCap' (Research Electronic Data CAPture; <https://projectredcap.org>) is a web application for building and managing online surveys and databases developed at Vanderbilt University. The API allows users to access data and project meta data (such as the data dictionary) from the web programmatically. The 'redcapAPI' package facilitates the process of accessing data with options to prepare an analysis-ready data set consistent with the definitions in a database's data dictionary.
Author: Benjamin Nutter [aut, ctb, cre], Stephen Lane [ctb], Will Beasley [ctb], Jeffrey Horner [ctb], Will Gray [ctb], Jeremy Stephens [ctb], Marcus Lehr [ctb]
Maintainer: Benjamin Nutter <benjamin.nutter@gmail.com>

Diff between redcapAPI versions 2.2 dated 2018-08-01 and 2.3 dated 2020-02-17

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Package plotdap updated to version 0.0.6 with previous version 0.0.5 dated 2020-01-08

Title: Easily Visualize Data from 'ERDDAP' Servers via the 'rerddap' Package
Description: Easily visualize and animate 'tabledap' and 'griddap' objects obtained via the 'rerddap' package in a simple one-line command, using either base graphics or 'ggplot2' graphics. 'plotdap' handles extracting and reshaping the data, map projections and continental outlines. Optionally the data can be animated through time using the 'gganmiate' package.
Author: Carson Sievert [aut], Roy Mendelssohn [aut, ctb, cre]
Maintainer: Roy Mendelssohn <roy.mendelssohn@noaa.gov>

Diff between plotdap versions 0.0.5 dated 2020-01-08 and 0.0.6 dated 2020-02-17

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More information about plotdap at CRAN
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Package miceadds updated to version 3.8-9 with previous version 3.7-6 dated 2019-12-15

Title: Some Additional Multiple Imputation Functions, Especially for 'mice'
Description: Contains functions for multiple imputation which complements existing functionality in R. In particular, several imputation methods for the mice package (van Buuren & Groothuis-Oudshoorn, 2011, <doi:10.18637/jss.v045.i03>) are included. Main features of the miceadds package include plausible value imputation (Mislevy, 1991, <doi:10.1007/BF02294457>), multilevel imputation for variables at any level or with any number of hierarchical and non-hierarchical levels (Grund, Luedtke & Robitzsch, 2018, <doi:10.1177/1094428117703686>; van Buuren, 2018, Ch.7, <doi:10.1201/9780429492259>), imputation using partial least squares (PLS) for high dimensional predictors (Robitzsch, Pham & Yanagida, 2016), nested multiple imputation (Rubin, 2003, <doi:10.1111/1467-9574.00217>) and substantive model compatible imputation (Bartlett et al., 2015, <doi:10.1177/0962280214521348>).
Author: Alexander Robitzsch [aut, cre], Simon Grund [aut], Thorsten Henke [ctb]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between miceadds versions 3.7-6 dated 2019-12-15 and 3.8-9 dated 2020-02-17

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Package labelVector updated to version 0.1.1 with previous version 0.1.0 dated 2018-07-28

Title: Label Attributes for Atomic Vectors
Description: Labels are a common construct in statistical software providing a human readable description of a variable. While variable names are succinct, quick to type, and follow a language's naming conventions, labels may be more illustrative and may use plain text and spaces. R does not provide native support for labels. Some packages, however, have made this feature available. Most notably, the 'Hmisc' package provides labelling methods for a number of different object. Due to design decisions, these methods are not all exported, and so are unavailable for use in package development. The 'labelVector' package supports labels for atomic vectors in a light-weight design that is suitable for use in other packages.
Author: Benjamin Nutter [aut, cre]
Maintainer: Benjamin Nutter <benjamin.nutter@gmail.com>

Diff between labelVector versions 0.1.0 dated 2018-07-28 and 0.1.1 dated 2020-02-17

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More information about labelVector at CRAN
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Package fda.usc updated to version 2.0.2 with previous version 2.0.1 dated 2019-12-16

Title: Functional Data Analysis and Utilities for Statistical Computing
Description: Routines for exploratory and descriptive analysis of functional data such as depth measurements, atypical curves detection, regression models, supervised classification, unsupervised classification and functional analysis of variance.
Author: Manuel Febrero Bande [aut], Manuel Oviedo de la Fuente [aut, cre], Pedro Galeano [ctb], Alicia Nieto [ctb], Eduardo Garcia-Portugues [ctb]
Maintainer: Manuel Oviedo de la Fuente <manuel.oviedo@usc.es>

Diff between fda.usc versions 2.0.1 dated 2019-12-16 and 2.0.2 dated 2020-02-17

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Package CompareCausalNetworks updated to version 0.2.6.2 with previous version 0.2.4 dated 2019-06-18

Title: Interface to Diverse Estimation Methods of Causal Networks
Description: Unified interface for the estimation of causal networks, including the methods 'backShift' (from package 'backShift'), 'bivariateANM' (bivariate additive noise model), 'bivariateCAM' (bivariate causal additive model), 'CAM' (causal additive model) (from package 'CAM'; the package is temporarily unavailable on the CRAN repository; formerly available versions can be obtained from the archive), 'hiddenICP' (invariant causal prediction with hidden variables), 'ICP' (invariant causal prediction) (from package 'InvariantCausalPrediction'), 'GES' (greedy equivalence search), 'GIES' (greedy interventional equivalence search), 'LINGAM', 'PC' (PC Algorithm), 'FCI' (fast causal inference), 'RFCI' (really fast causal inference) (all from package 'pcalg') and regression.
Author: Christina Heinze-Deml <heinzedeml@stat.math.ethz.ch>, Nicolai Meinshausen <meinshausen@stat.math.ethz.ch>
Maintainer: Christina Heinze-Deml <heinzedeml@stat.math.ethz.ch>

Diff between CompareCausalNetworks versions 0.2.4 dated 2019-06-18 and 0.2.6.2 dated 2020-02-17

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More information about CompareCausalNetworks at CRAN
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Package yaImpute updated to version 1.0-32 with previous version 1.0-31 dated 2019-01-09

Title: Nearest Neighbor Observation Imputation and Evaluation Tools
Description: Performs nearest neighbor-based imputation using one or more alternative approaches to processing multivariate data. These include methods based on canonical correlation analysis, canonical correspondence analysis, and a multivariate adaptation of the random forest classification and regression techniques of Leo Breiman and Adele Cutler. Additional methods are also offered. The package includes functions for comparing the results from running alternative techniques, detecting imputation targets that are notably distant from reference observations, detecting and correcting for bias, bootstrapping and building ensemble imputations, and mapping results.
Author: Nicholas L. Crookston, Andrew O. Finley, John Coulston (Sunil Arya and David Mount for ANN)
Maintainer: Nicholas L. Crookston <ncrookston.fs@gmail.com>

Diff between yaImpute versions 1.0-31 dated 2019-01-09 and 1.0-32 dated 2020-02-17

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More information about yaImpute at CRAN
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Package stringi updated to version 1.4.6 with previous version 1.4.5 dated 2020-01-11

Title: Character String Processing Facilities
Description: Fast, correct, consistent, portable and convenient character string/text processing in every locale and any native encoding. Owing to the use of the 'ICU' (International Components for Unicode) library, the package provides 'R' users with platform-independent functions known to 'Java', 'Perl', 'Python', 'PHP' and 'Ruby' programmers. Available features include: pattern searching (e.g., with 'Java'-like regular expressions or the 'Unicode' collation algorithm), random string generation, case mapping, string transliteration, concatenation, Unicode normalization, date-time formatting and parsing and many more.
Author: Marek Gagolewski [aut, cre] (<https://orcid.org/0000-0003-0637-6028>), Bartek Tartanus [ctb] and other contributors (stringi source code); IBM, Unicode, Inc. and other contributors (ICU4C source code); Unicode, Inc. (Unicode Character Database)
Maintainer: Marek Gagolewski <marek@gagolewski.com>

Diff between stringi versions 1.4.5 dated 2020-01-11 and 1.4.6 dated 2020-02-17

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Package PAFit updated to version 1.0.1.8 with previous version 1.0.1.7 dated 2020-02-07

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>. Thong Pham et al. (2020) <doi:10.18637/jss.v092.i03>.
Author: Thong Pham, Paul Sheridan, Hidetoshi Shimodaira
Maintainer: Thong Pham <thongphamthe@gmail.com>

Diff between PAFit versions 1.0.1.7 dated 2020-02-07 and 1.0.1.8 dated 2020-02-17

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Package chronosphere updated to version 0.2.2 with previous version 0.2.0 dated 2019-12-16

Title: Earth System History Variables
Description: The purpose of the 'chronosphere' project is to facilitate spatially explicit analyses of (paleo)environmental/ecological research. The package serves as a gateway to plate tectonic reconstructions, deep time global climate model results as well as fossil occurrence datasets such as the Paleobiology Database <https://www.paleobiodb.org/> and the PaleoReefs Database <https://www.paleo-reefs.pal.uni-erlangen.de/>. Environmental data stored on a remote server can be downloaded and imported directly to the R environment. Query functions to the GPlates <http://www.gplates.org/> desktop application or the GPlates Web Service <https://gws.gplates.org/> allow users to reconstruct coordinates, static plates, and Spatial objects. A wrapper class 'RasterArray' is implemented around the 'RasterLayer' class, allowing the organization of spatially explicit raster data in n-dimensional arrays. The project is developed under the umbrella of the DFG (Deutsche Forschungsgemeinschaft) Research Unit TERSANE2 (For 2332, TEmperature Related Stressors in ANcient Extinctions).
Author: Adam T. Kocsis, Nussaibah B. Raja
Maintainer: Adam T. Kocsis <adam.t.kocsis@gmail.com>

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Package statmod updated to version 1.4.34 with previous version 1.4.33 dated 2020-01-10

Title: Statistical Modeling
Description: A collection of algorithms and functions to aid statistical modeling. Includes limiting dilution analysis (aka ELDA), growth curve comparisons, mixed linear models, heteroscedastic regression, inverse-Gaussian probability calculations, Gauss quadrature and a secure convergence algorithm for nonlinear models. Also includes advanced generalized linear model functions including Tweedie and Digamma distributional families and a secure convergence algorithm.
Author: Gordon Smyth [cre, aut], Yifang Hu [ctb], Peter Dunn [ctb], Belinda Phipson [ctb], Yunshun Chen [ctb]
Maintainer: Gordon Smyth <smyth@wehi.edu.au>

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New package Superpower with initial version 0.0.3
Package: Superpower
Title: Simulation-Based Power Analysis for Factorial Designs
Version: 0.0.3
Authors@R: c(person(given = "Aaron", family = "Caldwell", role = c("aut", "cre"), email = "arcaldwell49@gmail.com"), person(given = "Daniel",family = "Lakens", role = c("aut"), email = "D.Lakens@tue.nl"), person(given = "Lisa", family = "DeBruine", role = c("ctb"), email = "debruine@gmail.com"), person(given = "Jonathon", family = "Love", role = c("ctb"), email = "jon@thon.cc"))
Description: Functions to perform simulations of ANOVA designs of up to three factors. Calculates the observed power and average observed effect size for all main effects and interactions in the ANOVA, and all simple comparisons between conditions. Includes functions for analytic power calculations and additional helper functions that compute effect sizes for ANOVA designs, observed error rates in the simulations, and functions to plot power curves. Please see Lakens, D., & Caldwell, A. R. (2019). "Simulation-Based Power-Analysis for Factorial ANOVA Designs". <doi:10.31234/osf.io/baxsf>.
URL: https://arcaldwell49.github.io/SuperpowerBook/
BugReports: https://github.com/arcaldwell49/Superpower/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Imports: mvtnorm, MASS, afex, emmeans, ggplot2, gridExtra, reshape2, stats, dplyr, magrittr
Suggests: knitr, rmarkdown, pwr, testthat, covr, jmvcore
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-02-06 15:42:32 UTC; megro
Author: Aaron Caldwell [aut, cre], Daniel Lakens [aut], Lisa DeBruine [ctb], Jonathon Love [ctb]
Maintainer: Aaron Caldwell <arcaldwell49@gmail.com>
Repository: CRAN
Date/Publication: 2020-02-17 16:20:03 UTC

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Package RNewsflow updated to version 1.2.3 with previous version 1.2.1 dated 2019-11-11

Title: Tools for Comparing Text Messages Across Time and Media
Description: A collection of tools for measuring the similarity of text messages and tracing the flow of messages over time and across media.
Author: Kasper Welbers & Wouter van Atteveldt
Maintainer: Kasper Welbers <kasperwelbers@gmail.com>

Diff between RNewsflow versions 1.2.1 dated 2019-11-11 and 1.2.3 dated 2020-02-17

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Package pcFactorStan updated to version 1.4.0 with previous version 1.3.0 dated 2020-01-19

Title: Stan Models for the Paired Comparison Factor Model
Description: Provides convenience functions and pre-programmed Stan models related to the paired comparison factor model. Its purpose is to make fitting paired comparison data using Stan easy.
Author: Joshua N. Pritikin [aut, cre] (<https://orcid.org/0000-0002-9862-5484>), Daniel C. Furr [ctb], Trustees of Columbia University [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>

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Package memuse updated to version 4.1-0 with previous version 4.0-0 dated 2017-11-10

Title: Memory Estimation Utilities
Description: How much ram do you need to store a 100,000 by 100,000 matrix? How much ram is your current R session using? How much ram do you even have? Learn the scintillating answer to these and many more such questions with the 'memuse' package.
Author: Drew Schmidt [aut, cre], Christian Heckendorf [ctb] (FreeBSD improvements to meminfo), Wei-Chen Chen [ctb] (Windows build fixes), Dan Burgess [ctb] (donation of a Mac for development and testing)
Maintainer: Drew Schmidt <wrathematics@gmail.com>

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Package jmv updated to version 1.2.5 with previous version 1.0.8 dated 2019-10-23

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 freesurferformats updated to version 0.1.8 with previous version 0.1.7 dated 2020-01-07

Title: Read and Write 'FreeSurfer' Neuroimaging File Formats
Description: Provides functions to read and write data from neuroimaging files in 'FreeSurfer' <http://freesurfer.net/> binary formats. This includes the following file formats: 1) MGH/MGZ format files, which can contain multi-dimensional images or other data. Typically they contain time-series of three-dimensional brain scans acquired by magnetic resonance imaging (MRI). They can also contain vertex-wise measures of surface morphometry data. The MGH format is named after the Massachusetts General Hospital, and the MGZ format is a compressed version of the same format. 2) 'FreeSurfer' morphometry data files in binary 'curv' format. These contain vertex-wise surface measures, i.e., one scalar value for each vertex of a brain surface mesh. These are typically values like the cortical thickness or brain surface area at each vertex. 3) Annotation file format. This contains a brain surface parcellation derived from a cortical atlas. 4) Surface file format. Contains a brain surface mesh, given by a list of vertices and a list of faces.
Author: Tim Schäfer [aut, cre] (<https://orcid.org/0000-0002-3683-8070>)
Maintainer: Tim Schäfer <ts+code@rcmd.org>

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Package CHNOSZ updated to version 1.3.5 with previous version 1.3.4 dated 2019-12-15

Title: Thermodynamic Calculations and Diagrams for Geochemistry
Description: An integrated set of tools for thermodynamic calculations in aqueous geochemistry and geobiochemistry. Functions are provided for writing balanced reactions to form species from user-selected basis species and for calculating the standard molal properties of species and reactions, including the standard Gibbs energy and equilibrium constant. Calculations of the non-equilibrium chemical affinity and equilibrium chemical activity of species can be portrayed on diagrams as a function of temperature, pressure, or activity of basis species; in two dimensions, this gives a maximum affinity or predominance diagram. The diagrams have formatted chemical formulas and axis labels, and water stability limits can be added to Eh-pH, oxygen fugacity- temperature, and other diagrams with a redox variable. The package has been developed to handle common calculations in aqueous geochemistry, such as solubility due to complexation of metal ions, mineral buffers of redox or pH, and changing the basis species across a diagram ("mosaic diagrams"). CHNOSZ also has unique capabilities for comparing the compositional and thermodynamic properties of different proteins.
Author: Jeffrey Dick [aut, cre] (<https://orcid.org/0000-0002-0687-5890>), R Core Team [ctb] (code derived from R's pmax())
Maintainer: Jeffrey Dick <j3ffdick@gmail.com>

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Package AMR updated to version 1.0.0 with previous version 0.9.0 dated 2019-11-29

Title: Antimicrobial Resistance Analysis
Description: Functions to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods, like those defined by Leclercq et al. (2013) <doi:10.1111/j.1469-0691.2011.03703.x> and the Clinical and Laboratory Standards Institute (2014) <isbn: 1-56238-899-1>.
Author: Matthijs S. Berends [aut, cre] (<https://orcid.org/0000-0001-7620-1800>), Christian F. Luz [aut, ctb] (<https://orcid.org/0000-0001-5809-5995>), Alexander W. Friedrich [aut, ths] (<https://orcid.org/0000-0003-4881-038X>), Bhanu N. M. Sinha [aut, ths] (<https://orcid.org/0000-0003-1634-0010>), Casper J. Albers [aut, ths] (<https://orcid.org/0000-0002-9213-6743>), Corinna Glasner [aut, ths] (<https://orcid.org/0000-0003-1241-1328>), Judith M. Fonville [ctb], Erwin E. A. Hassing [ctb], Eric H. L. C. M. Hazenberg [ctb], Annick Lenglet [ctb], Bart C. Meijer [ctb], Sofia Ny [ctb], Dennis Souverein [ctb]
Maintainer: Matthijs S. Berends <m.s.berends@umcg.nl>

Diff between AMR versions 0.9.0 dated 2019-11-29 and 1.0.0 dated 2020-02-17

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 AMR-1.0.0/AMR/NAMESPACE                                   |    5 
 AMR-1.0.0/AMR/NEWS.md                                     |   48 
 AMR-1.0.0/AMR/R/ab.R                                      |   73 -
 AMR-1.0.0/AMR/R/ab_property.R                             |   62 
 AMR-1.0.0/AMR/R/age.R                                     |   10 
 AMR-1.0.0/AMR/R/amr.R                                     |   16 
 AMR-1.0.0/AMR/R/atc_online.R                              |   13 
 AMR-1.0.0/AMR/R/availability.R                            |   11 
 AMR-1.0.0/AMR/R/bug_drug_combinations.R                   |    9 
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 AMR-1.0.0/AMR/R/count.R                                   |    9 
 AMR-1.0.0/AMR/R/data.R                                    |   67 
 AMR-1.0.0/AMR/R/deprecated.R                              |   11 
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 AMR-1.0.0/AMR/R/extended.R                                |    9 
 AMR-1.0.0/AMR/R/filter_ab_class.R                         |   20 
 AMR-1.0.0/AMR/R/first_isolate.R                           |    8 
 AMR-1.0.0/AMR/R/freq.R                                    |   14 
 AMR-1.0.0/AMR/R/g.test.R                                  |    9 
 AMR-1.0.0/AMR/R/ggplot_rsi.R                              |   11 
 AMR-1.0.0/AMR/R/globals.R                                 |   12 
 AMR-1.0.0/AMR/R/guess_ab_col.R                            |   13 
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 AMR-1.0.0/AMR/R/misc.R                                    |   62 
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 AMR-1.0.0/AMR/inst/doc/EUCAST.R                           |   27 
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 167 files changed, 2687 insertions(+), 1957 deletions(-)

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New package treestructure with initial version 0.1.0
Package: treestructure
Type: Package
Title: Detect Population Structure Within Phylogenetic Trees
Version: 0.1.0
Date: 2020-01-20
Author: Erik Volz
Maintainer: Erik Volz <erik.volz@gmail.com>
Description: Algorithms for detecting population structure from the history of coalescent events recorded in phylogenetic trees. This method classifies each tip and internal node of a tree into disjoint sets characterized by similar coalescent patterns. The methods are described in Volz, E., Wiuf, C., Grad, Y., Frost, S., Dennis, A., & Didelot, X. (2020) <doi:10.1093/sysbio/syaa009>.
License: GPL (>= 2)
Suggests: ggtree,ggplot2,knitr
Imports: ape (>= 5.0)
LinkingTo: Rcpp
VignetteBuilder: knitr
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2020-02-06 13:41:39 UTC; erikvolz
Repository: CRAN
Date/Publication: 2020-02-17 15:20:02 UTC

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Package sitar updated to version 1.1.2 with previous version 1.1.1 dated 2019-03-12

Title: Super Imposition by Translation and Rotation Growth Curve Analysis
Description: Functions for fitting and plotting SITAR (Super Imposition by Translation And Rotation) growth curve models. SITAR is a shape-invariant model with a regression B-spline mean curve and subject-specific random effects on both the measurement and age scales. The model was first described by Lindstrom (1995) <doi:10.1002/sim.4780141807> and developed as the SITAR method by Cole et al (2010) <doi:10.1093/ije/dyq115>.
Author: Tim Cole [aut, cre] (<https://orcid.org/0000-0001-5711-8200>)
Maintainer: Tim Cole <tim.cole@ucl.ac.uk>

Diff between sitar versions 1.1.1 dated 2019-03-12 and 1.1.2 dated 2020-02-17

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 56 files changed, 1363 insertions(+), 731 deletions(-)

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New package rModeling with initial version 0.0.3
Package: rModeling
Type: Package
Title: A Framework of Cross-Validation
Version: 0.0.3
Date: 2020-02-06
Authors@R: c( person("Shuxia", "Guo", email = "shuxia.guo@uni-jena.de", role = c("cre","aut")), person("Thomas", "Bocklitz", role = "aut"), person("Juergen", "Popp", role = c("ctb","cph")))
Author: Shuxia Guo [cre, aut], Thomas Bocklitz [aut], Juergen Popp [ctb, cph]
Maintainer: Shuxia Guo <shuxia.guo@uni-jena.de>
Description: A framework of cross-validation for spectral data analysis that allows for automatic tuning of model parameters and for model evaluation. It is particularly useful for applications where intra-group heterogeneity is significant due to inter individual differences. S. Guo, T. Bocklitz, U. Neugebauer, J.Popp (2017) <doi:10.1039/C7AY01363A>.
License: GPL-2
Depends: R (>= 2.10)
Imports: MASS, caret, e1071
RoxygenNote: 6.1.0
LazyData: false
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-02-06 08:36:26 UTC; shuxi
Repository: CRAN
Date/Publication: 2020-02-17 15:10:02 UTC

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New package REndo with initial version 2.3.1
Package: REndo
Title: Fitting Linear Models with Endogenous Regressors using Latent Instrumental Variables
Version: 2.3.1
Date: 2020-02-15
Authors@R: c( person(given="Raluca", family="Gui", email = "raluca.gui@business.uzh.ch", role = c("cre","aut")), person(given="Markus", family="Meierer", email = "markus.meierer@business.uzh.ch", role = "aut"), person(given="Rene", family="Algesheimer", email = "market-research@business.uzh.ch", role = "aut"), person(given="Patrik", family="Schilter", email = "patrik.schilter@gmail.com",role = "aut"))
Description: Fits linear models with endogenous regressor using latent instrumental variable approaches. The methods included in the package are Lewbel's (1997) <doi:10.2307/2171884> higher moments approach as well as Lewbel's (2012) <doi:10.1080/07350015.2012.643126> heteroscedasticity approach, Park and Gupta's (2012) <doi:10.1287/mksc.1120.0718> joint estimation method that uses Gaussian copula and Kim and Frees's (2007) <doi:10.1007/s11336-007-9008-1> multilevel generalized method of moment approach that deals with endogeneity in a multilevel setting. These are statistical techniques to address the endogeneity problem where no external instrumental variables are needed. Note that with version 2.0.0 sweeping changes were introduced which greatly improve functionality and usability but break backwards compatibility.
License: GPL-3
URL: https://github.com/mmeierer/REndo
BugReports: https://github.com/mmeierer/REndo/issues
NeedsCompilation: no
Depends: R (>= 3.4)
Imports: methods (>= 3.4), stats (>= 3.4), utils (>= 3.4), Formula (>= 1.2), optimx (>= 2013.8.7), mvtnorm (>= 1.0-8), AER (>= 1.2-5), Matrix (>= 1.2-14), lme4 (>= 1.1-18-1), data.table (>= 1.11.8), corpcor (>= 1.6.9)
Suggests: testthat, covr, R.rsp
Encoding: UTF-8
RoxygenNote: 7.0.2
VignetteBuilder: R.rsp
Packaged: 2020-02-16 23:13:05 UTC; patrik
Author: Raluca Gui [cre, aut], Markus Meierer [aut], Rene Algesheimer [aut], Patrik Schilter [aut]
Maintainer: Raluca Gui <raluca.gui@business.uzh.ch>
Repository: CRAN
Date/Publication: 2020-02-17 15:50:02 UTC

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New package neo2R with initial version 2.0.0
Package: neo2R
Type: Package
Title: Neo4j to R
Version: 2.0.0
Author: Patrice Godard
Maintainer: Patrice Godard <patrice.godard@gmail.com>
Description: The aim of the neo2R is to provide simple and low level connectors for querying neo4j graph databases (<https://neo4j.com/>). The objects returned by the query functions are either lists or data.frames with very few post-processing. It allows fast processing of queries returning many records. And it let the user handle post-processing according to the data model and his needs.
URL: https://github.com/patzaw/neo2r
BugReports: https://github.com/patzaw/neo2r/issues
Depends: R (>= 3.6)
Imports: base64enc, jsonlite, RCurl, utils
SystemRequirements: neo4j (==3 OR ==4) <https://neo4j.com/>
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-02-06 14:03:20 UTC; pgodard
Repository: CRAN
Date/Publication: 2020-02-17 15:40:06 UTC

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Package icosa updated to version 0.10.0 with previous version 0.9.81 dated 2017-04-18

Title: Global Triangular and Penta-Hexagonal Grids Based on Tessellated Icosahedra
Description: Employs triangular tessellation to refine icosahedra defined in 3d space. The procedures can be set to provide a grid with a custom resolution. Both the primary triangular and their inverted penta- hexagonal grids are available for implementation. Additional functions are provided to position points (latitude-longitude data) on the grids, to allow 2D and 3D plotting, use raster data and shapefiles.
Author: Adam T. Kocsis [aut, cre]
Maintainer: Adam T. Kocsis <adam.t.kocsis@gmail.com>

Diff between icosa versions 0.9.81 dated 2017-04-18 and 0.10.0 dated 2020-02-17

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Package GeneralizedUmatrix updated to version 1.1.8 with previous version 1.1.6 dated 2019-11-20

Title: Credible Visualization for Two-Dimensional Projections of Data
Description: Projections are common dimensionality reduction methods, which represent high-dimensional data in a two-dimensional space. However, when restricting the output space to two dimensions, which results in a two dimensional scatter plot (projection) of the data, low dimensional similarities do not represent high dimensional distances coercively [Thrun, 2018]. This could lead to a misleading interpretation of the underlying structures [Thrun, 2018]. By means of the 3D topographic map the generalized Umatrix is able to depict errors of these two-dimensional scatter plots. The package is based on the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9>.
Author: Michael Thrun [aut, cre, cph] (<https://orcid.org/0000-0001-9542-5543>), Felix Pape [ctb, ctr], Tim Schreier [ctb, ctr], Luis Winckelman [ctb, ctr], Alfred Ultsch [ths]
Maintainer: Michael Thrun <m.thrun@gmx.net>

Diff between GeneralizedUmatrix versions 1.1.6 dated 2019-11-20 and 1.1.8 dated 2020-02-17

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Package geex updated to version 1.0.12 with previous version 1.0.11 dated 2018-09-23

Title: An API for M-Estimation
Description: Provides a general, flexible framework for estimating parameters and empirical sandwich variance estimator from a set of unbiased estimating equations (i.e., M-estimation in the vein of Stefanski & Boos (2002) <doi:10.1198/000313002753631330>). All examples from Stefanski & Boos (2002) are published in the corresponding Journal of Statistical Software paper <doi:10.18637/jss.v092.i02>. Also provides an API to compute finite-sample variance corrections.
Author: Bradley Saul [aut, cre], Brian Barkley [ctb]
Maintainer: Bradley Saul <bradleysaul@gmail.com>

Diff between geex versions 1.0.11 dated 2018-09-23 and 1.0.12 dated 2020-02-17

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New package arulesSequences with initial version 0.2-24
Package: arulesSequences
Version: 0.2-24
Title: Mining Frequent Sequences
Author: Christian Buchta and Michael Hahsler, with contributions from Daniel Diaz
Maintainer: Christian Buchta <christian.buchta@wu.ac.at>
Description: Add-on for arules to handle and mine frequent sequences. Provides interfaces to the C++ implementation of cSPADE by Mohammed J. Zaki.
Depends: R (>= 3.3.2), methods, arules (>= 1.5-1)
License: GPL-2
NeedsCompilation: yes
Packaged: 2020-02-15 16:17:31 UTC; hornik
Repository: CRAN
Date/Publication: 2020-02-17 15:56:46 UTC

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New package readtextgrid with initial version 0.1.1
Package: readtextgrid
Type: Package
Title: Read in a 'Praat' 'TextGrid' File
Version: 0.1.1
Authors@R: person(given = "Tristan", family = "Mahr", role = c("aut", "cre"), email = "tristan.mahr@wisc.edu", comment = c(ORCID = "0000-0002-8890-5116"))
Description: 'Praat' is a widely used tool for manipulating, annotating and analyzing speech and acoustic data. It stores annotation data in a format called a 'TextGrid'. This package provides a way to read these files into R.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 2.1.0)
RoxygenNote: 7.0.2
Imports: magrittr, stats, utils, tibble, purrr, readr, stringr, plyr
URL: https://github.com/tjmahr/readtextgrid
BugReports: https://github.com/tjmahr/readtextgrid/issues
NeedsCompilation: no
Packaged: 2020-02-05 21:27:39 UTC; Tristan
Author: Tristan Mahr [aut, cre] (<https://orcid.org/0000-0002-8890-5116>)
Maintainer: Tristan Mahr <tristan.mahr@wisc.edu>
Repository: CRAN
Date/Publication: 2020-02-17 14:30:02 UTC

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New package PHInfiniteEstimates with initial version 1.0
Package: PHInfiniteEstimates
Type: Package
Title: Tools for Inference in the Presence of a Monotone Likelihood
Version: 1.0
Date: 2020-01-22
Author: John E. Kolassa and Juan Zhang
Maintainer: John E. Kolassa <kolassa@stat.rutgers.edu>
Description: Proportional hazards estimation in the presence of a partially monotone likelihood has difficulties, in that finite estimators do not exist. These difficulties are related to those arising from logistic and multinomial regression. References for methods are given in the separate function documents.
License: GPL-3
Depends: survival, lpSolve, mlogit, coxphf, NADA
Imports: Rdpack (>= 0.7)
RdMacros: Rdpack
Encoding: UTF-8
RoxygenNote: 7.0.1
NeedsCompilation: no
Packaged: 2020-02-05 20:36:17 UTC; kolassa
Repository: CRAN
Date/Publication: 2020-02-17 14:30:05 UTC

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New package influential with initial version 0.1.0
Package: influential
Type: Package
Title: Identification of the Most Influential Nodes (Hubs)
Version: 0.1.0
Author: Adrian (Abbas) Salavaty
Maintainer: Adrian Salavaty <abbas.salavaty@gmail.com>
Description: Contains functions for reconstruction of networks from adjacency matrices and data frames, analysis of the topology of the network and calculation of centrality measures, and identification of the most influential nodes (network hubs). Also, some functions have been provided for the assessment of dependence and correlation of two network centrality measures as well as the conditional probability of deviation from their corresponding means in opposite direction. Fred Viole and David Nawrocki (2013, ISBN:1490523995).
Imports: igraph
Suggests: Hmisc (>= 4.3-0), mgcv (>= 1.8-31), nortest (>= 1.0-4), NNS (>= 0.4.7.1), parallel, knitr, rmarkdown
Depends: R (>= 2.10)
URL: http://github.com/asalavaty/influential
BugReports: http://github.com/asalavaty/influential/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2.9000
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-02-06 00:25:14 UTC; asal0019
Repository: CRAN
Date/Publication: 2020-02-17 14:50:02 UTC

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New package hergm with initial version 4.1-6
Package: hergm
Version: 4.1-6
Date: 2020-02-15
Title: Hierarchical Exponential-Family Random Graph Models
Author: Michael Schweinberger <michael.schweinberger@rice.edu> [aut, cre], Mark S. Handcock <handcock@ucla.edu> [aut], Sergii Babkin <babkin.sergii@gmail.com> [aut], Jonathan Stewart <jonathan.stewart@rice.edu> [aut], Duy Vu <duy.vu@unimelb.edu.au> [aut], Pamela Luna <pamela.luna@rice.edu> [ctb]
Maintainer: Michael Schweinberger <michael.schweinberger@rice.edu>
Depends: ergm, latentnet, mcgibbsit, network, sna
Imports: methods, mlergm, Rcpp (>= 0.12.7), Matrix, igraph, intergraph, parallel, stringr
Description: Hierarchical exponential-family random graph models with local dependence.
License: GPL-3
LinkingTo: Rcpp
NeedsCompilation: yes
BugReports: http://www.stat.rice.edu/~ms88/hergm/issues.html
Packaged: 2020-02-17 02:02:59 UTC; gilgamesh
Repository: CRAN
Date/Publication: 2020-02-17 15:00:03 UTC

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New package discourseGT with initial version 1.0.0
Package: discourseGT
Type: Package
Title: Analyze Group Patterns using Graph Theory in Educational Settings
Version: 1.0.0
Date: 2020-02-05
Authors@R: c( person("Albert","Chai", role=c("aut"), email = "albertchai@ucsd.edu"), person("Andrew","Lee", role="aut", email = "aleet383@ucla.edu"), person("Joshua","Le", role=c("aut", "cre"), email = "jpl038@ucsd.edu"), person("Stanley","Lo", role=c("aut"), email = "smlo@ucsd.edu"))
Description: Analyzes group patterns using discourse analysis data with graph theory mathematics. Takes the order of which individuals talk and converts it to a network edge and weight list. Returns the density, centrality, centralization, and subgroup information for each group. Based on the analytical framework laid out in Chai et al. (2019) <doi:10.1187/cbe.18-11-0222>.
License: MIT + file LICENSE
LazyData: true
Encoding: UTF-8
Depends: R (>= 2.10)
Suggests: sna
RoxygenNote: 7.0.0
Imports: igraph, ggpubr, GGally, network, ggplot2
NeedsCompilation: no
Packaged: 2020-02-06 05:34:38 UTC; Josh
Author: Albert Chai [aut], Andrew Lee [aut], Joshua Le [aut, cre], Stanley Lo [aut]
Maintainer: Joshua Le <jpl038@ucsd.edu>
Repository: CRAN
Date/Publication: 2020-02-17 15:00:06 UTC

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Package DetSel updated to version 1.0.4 with previous version 1.0.3 dated 2019-05-14

Title: A Computer Program to Detect Markers Responding to Selection
Description: In the new era of population genomics, surveys of genetic polymorphism ("genome scans") offer the opportunity to distinguish locus-specific from genome wide effects at many loci. Identifying presumably neutral regions of the genome that are assumed to be influenced by genome-wide effects only, and excluding presumably selected regions, is therefore critical to infer population demography and phylogenetic history reliably. Conversely, detecting locus-specific effects may help identify those genes that have been, or still are, targeted by natural selection. The software package DetSel has been developed to identify markers that show deviation from neutral expectation in pairwise comparisons of diverging populations.
Author: Renaud Vitalis <renaud.vitalis@inrae.fr>.
Maintainer: Renaud Vitalis <renaud.vitalis@inrae.fr>

Diff between DetSel versions 1.0.3 dated 2019-05-14 and 1.0.4 dated 2020-02-17

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More information about DetSel at CRAN
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New package CluMP with initial version 0.8
Package: CluMP
Title: Clustering of Micro Panel Data
Version: 0.8
Authors@R: c( person("Jan", "Fojtik", email = "9afojtik@gmail.com", role = "aut"), person("Anna", "Grishko", email = "anja.grishko@gmail.com", role = c("aut", "cre")), person("Lukas", "Sobisek", email = "Lukas.Sobisek@yahoo.com", role = c("aut", "cph", "rev")))
Description: Two-step feature-based clustering method designed for micro panel (longitudinal) data with the artificial panel data generator. See Sobisek, Stachova, Fojtik (2018) <arXiv:1807.05926>.
URL: https://arxiv.org/ftp/arxiv/papers/1807/1807.05926.pdf
Depends: R (>= 3.4.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: MASS, ggplot2 (>= 3.0.0), dplyr (>= 0.7.6), NbClust (>= 3.0), amap (>= 0.8-16), tableone, rlang, stats, data.table
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-02-05 19:26:37 UTC; Анна
Author: Jan Fojtik [aut], Anna Grishko [aut, cre], Lukas Sobisek [aut, cph, rev]
Maintainer: Anna Grishko <anja.grishko@gmail.com>
Repository: CRAN
Date/Publication: 2020-02-17 14:10:05 UTC

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New package scpm with initial version 2.0.0
Package: scpm
Type: Package
Title: An R Package for Spatial Smoothing
Version: 2.0.0
Date: 2020-02-14
Author: Mario A. Martinez Araya [aut,cre,cph]
Maintainer: Mario A. Martinez Araya <r@marioma.me>
Description: Group of functions for spatial smoothing using cubic splines and variogram maximum likelihood estimation. Also allow the inclusion of linear parametric terms and change-points for segmented smoothing splines models.
License: GPL (>= 2)
Depends: R (>= 2.10), stats, Matrix, RandomFields, interp
Imports: methods, rgl, lattice, mvtnorm, MASS, graphics, grDevices
Enhances: fields
URL: https://marioma.me?i=soft
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-02-14 14:16:30 UTC; mma
Repository: CRAN
Date/Publication: 2020-02-17 13:30:02 UTC

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Package PoissonBinomial updated to version 1.0.2 with previous version 1.0.1 dated 2020-02-05

Title: Exact and Approximate Implementations of the Poisson Binomial Distribution
Description: Implementations of multiple exact and approximate methods as described in Hong (2013) <doi:10.1016/j.csda.2012.10.006> and Biscarri et al. (2018) <doi:10.1016/j.csda.2018.01.007> for computing the probability mass, cumulative distribution and quantile functions, as well as generating random numbers for the Poisson binomial distribution.
Author: Florian Junge [aut, cre]
Maintainer: Florian Junge <florian.junge@h-da.de>

Diff between PoissonBinomial versions 1.0.1 dated 2020-02-05 and 1.0.2 dated 2020-02-17

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New package joineRML with initial version 0.4.3
Package: joineRML
Type: Package
Title: Joint Modelling of Multivariate Longitudinal Data and Time-to-Event Outcomes
Version: 0.4.3
Date: 2020-02-17
Authors@R: c( person("Graeme L.", "Hickey", email = "graemeleehickey@gmail.com", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-4989-0054")), person("Pete", "Philipson", email = "peter.philipson1@newcastle.ac.uk", role = "aut", comment = c(ORCID = "0000-0001-7846-0208")), person("Andrea", "Jorgensen", email = "aljorgen@liverpool.ac.uk", role = "ctb", comment = c(ORCID = "0000-0002-6977-9337")), person("Ruwanthi", "Kolamunnage-Dona", email = "kdrr@liverpool.ac.uk", role = "aut", comment = c(ORCID = "0000-0003-3886-6208")), person("Paula", "Williamson", email = "p.r.williamson@liverpool.ac.uk", role = "ctb", comment = c(ORCID = "0000-0001-9802-6636")), person("Dimitris", "Rizopoulos", email = "d.rizopoulos@erasmusmc.nl", role = c("ctb", "dtc"), comment = "data/renal.rda, R/hessian.R, R/vcov.R"), person("Alessandro", "Gasparini", email = "alessandro.gasparini@ki.se", role = "ctb", comment = c(ORCID = "0000-0002-8319-7624")), person("Medical Research Council", role = "fnd", comment = "Grant number: MR/M013227/1") )
Encoding: UTF-8
Description: Fits the joint model proposed by Henderson and colleagues (2000) <doi:10.1093/biostatistics/1.4.465>, but extended to the case of multiple continuous longitudinal measures. The time-to-event data is modelled using a Cox proportional hazards regression model with time-varying covariates. The multiple longitudinal outcomes are modelled using a multivariate version of the Laird and Ware linear mixed model. The association is captured by a multivariate latent Gaussian process. The model is estimated using a Monte Carlo Expectation Maximization algorithm. This project is funded by the Medical Research Council (Grant number MR/M013227/1).
License: GPL-3 | file LICENSE
URL: https://github.com/petephilipson/joineRML
BugReports: https://github.com/graemeleehickey/joineRML/issues
LazyData: true
Depends: R (>= 3.6.0), nlme, survival
Imports: cobs, doParallel, foreach, ggplot2, graphics, lme4 (>= 1.1-8), MASS, Matrix, mvtnorm, parallel, randtoolbox, Rcpp (>= 0.12.7), stats, utils
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.0.2
Suggests: JM, joineR, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-02-17 11:04:02 UTC; hickeg3
Author: Graeme L. Hickey [cre, aut] (<https://orcid.org/0000-0002-4989-0054>), Pete Philipson [aut] (<https://orcid.org/0000-0001-7846-0208>), Andrea Jorgensen [ctb] (<https://orcid.org/0000-0002-6977-9337>), Ruwanthi Kolamunnage-Dona [aut] (<https://orcid.org/0000-0003-3886-6208>), Paula Williamson [ctb] (<https://orcid.org/0000-0001-9802-6636>), Dimitris Rizopoulos [ctb, dtc] (data/renal.rda, R/hessian.R, R/vcov.R), Alessandro Gasparini [ctb] (<https://orcid.org/0000-0002-8319-7624>), Medical Research Council [fnd] (Grant number: MR/M013227/1)
Maintainer: Graeme L. Hickey <graemeleehickey@gmail.com>
Repository: CRAN
Date/Publication: 2020-02-17 11:50:02 UTC

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Package fastpos updated to version 0.3.0 with previous version 0.2.0 dated 2020-01-10

Title: Finds the Critical Sequential Point of Stability for a Pearson Correlation
Description: Finds the critical sample size ("critical point of stability") for a correlation to stabilize in Schoenbrodt and Perugini's definition of sequential stability (see <doi:10.1016/j.jrp.2013.05.009>).
Author: Johannes Titz [aut, cre, cph]
Maintainer: Johannes Titz <johannes.titz@gmail.com>

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Package spant updated to version 1.0.0 with previous version 0.19.0 dated 2019-12-06

Title: MR Spectroscopy Analysis Tools
Description: Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data.
Author: Martin Wilson [cre, aut], John Muschelli [ctb]
Maintainer: Martin Wilson <martin@pipegrep.co.uk>

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Package KernSmoothIRT updated to version 6.4 with previous version 6.3 dated 2020-02-11

Title: Nonparametric Item Response Theory
Description: Fits nonparametric item and option characteristic curves using kernel smoothing. It allows for optimal selection of the smoothing bandwidth using cross-validation and a variety of exploratory plotting tools. The kernel smoothing is based on methods described in Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.
Author: Angelo Mazza, Antonio Punzo, Brian McGuire
Maintainer: Brian McGuire <mcguirebc@gmail.com>

Diff between KernSmoothIRT versions 6.3 dated 2020-02-11 and 6.4 dated 2020-02-17

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Package kangar00 updated to version 1.4 with previous version 1.3 dated 2019-02-09

Title: Kernel Approaches for Nonlinear Genetic Association Regression
Description: Methods to extract information on pathways, genes and various single-nucleotid polymorphisms (SNPs) from online databases. It provides functions for data preparation and evaluation of genetic influence on a binary outcome using the logistic kernel machine test (LKMT). Three different kernel functions are offered to analyze genotype information in this variance component test: A linear kernel, a size-adjusted kernel and a network-based kernel (Friedrichs et al., 2017, <doi:10.1155/2017/6742763>).
Author: Juliane Manitz [aut], Stefanie Friedrichs [aut], Patricia Burger [aut], Benjamin Hofner [aut], Ngoc Thuy Ha [aut], Saskia Freytag [ctb], Heike Bickeboeller [ctb]
Maintainer: Juliane Manitz <r@manitz.org>

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Package gravitas updated to version 0.1.2 with previous version 0.1.0 dated 2019-11-05

Title: Explore Probability Distributions for Bivariate Temporal Granularities
Description: Provides tools for systematically exploring large quantities of temporal data across nonlinear temporal granularities (deconstructions of time) by visualizing probability distributions. Nonlinear time granularities can be circular, quasi-circular or aperiodic. 'gravitas' computes nonlinear single-order-up or multiple-order-up granularities, check the feasibility of creating plots for any two nonlinear granularities and recommend probability distributions plots for exploring periodicity in the data.
Author: Sayani Gupta [aut, cre] (<https://orcid.org/0000-0003-0643-5358>), Rob Hyndman [aut, ths] (<https://orcid.org/0000-0002-2140-5352>), Di Cook [aut, ths] (<https://orcid.org/0000-0002-3813-7155>), Antony Unwin [aut] (<https://orcid.org/0000-0002-5841-5757>)
Maintainer: Sayani Gupta <gupta.sayani@gmail.com>

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Package jsmodule updated to version 1.0.5 with previous version 1.0.4 dated 2019-12-02

Title: 'RStudio' Addins and 'Shiny' Modules for Medical Research
Description: 'RStudio' addins and 'Shiny' modules for descriptive statistics, regression and survival analysis.
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>), Zarathu [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

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Package httk updated to version 2.0.0 with previous version 1.10.1 dated 2019-09-10

Title: High-Throughput Toxicokinetics
Description: Functions and data tables for simulation and statistical analysis of chemical toxicokinetics ("TK") as in Pearce et al. (2017) <doi:10.18637/jss.v079.i04>. Chemical-specific in vitro data have been obtained from relatively high throughput experiments. Both physiologically-based ("PBTK") and empirical (e.g., one compartment) "TK" models can be parameterized for several hundred chemicals and multiple species. These models are solved efficiently, often using compiled (C-based) code. A Monte Carlo sampler is included for simulating biological variability (Ring et al., 2017 <doi:10.1016/j.envint.2017.06.004>) and measurement limitations. Calibrated methods are included for predicting tissue:plasma partition coefficients and volume of distribution (Pearce et al., 2017 <doi:10.1007/s10928-017-9548-7>). These functions and data provide a set of tools for in vitro-in vivo extrapolation ("IVIVE") of high throughput screening data (e.g., Tox21, ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK") (Wetmore et al., 2015 <doi:10.1093/toxsci/kfv171>).
Author: John Wambaugh [aut, cre] (<https://orcid.org/0000-0002-4024-534X>), Robert Pearce [aut] (<https://orcid.org/0000-0003-3168-4049>), Caroline Ring [aut] (<https://orcid.org/0000-0002-0463-1251>), Greg Honda [aut] (<https://orcid.org/0000-0001-7713-9850>), Mark Sfeir [aut], Matt Linakis [aut] (<https://orcid.org/0000-0003-0526-2395>), Jimena Davis [ctb], James Sluka [ctb] (<https://orcid.org/0000-0002-5901-1404>), Nisha Sipes [ctb] (<https://orcid.org/0000-0003-4203-6426>), Barbara Wetmore [ctb], Woodrow Setzer [ctb] (<https://orcid.org/0000-0002-6709-9186>)
Maintainer: John Wambaugh <wambaugh.john@epa.gov>

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Package CUSUMdesign updated to version 1.1.4 with previous version 1.1.3 dated 2016-05-19

Title: Compute Decision Interval and Average Run Length for CUSUM Charts
Description: Computation of decision intervals (H) and average run lengths (ARL) for CUSUM charts.
Author: Douglas M. Hawkins, David H. Olwell, and Boxiang Wang
Maintainer: Boxiang Wang <boxiang-wang@uiowa.edu>

Diff between CUSUMdesign versions 1.1.3 dated 2016-05-19 and 1.1.4 dated 2020-02-17

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New package rgexf with initial version 0.16.0
Package: rgexf
Type: Package
Encoding: UTF-8
Title: Build, Import and Export GEXF Graph Files
Version: 0.16.0
Date: 2020-02-10
Authors@R: c( person("George", "Vega Yon", email="g.vegayon@gmail.com", role=c("aut", "cre"), comment = structure("0000-0002-3171-0844", .Names = "ORCID")), person("Jorge", "Fábrega Lacoa", role=c("ctb")), person("Joshua", "Kunst", role=c("ctb")), person("Raphaël", "Velt", role=c("cph"), comment="gexf-js library"), person(family="Gephi Consortium", role=c("cph"), comment="GEXF language"))
Description: Create, read and write 'GEXF' (Graph Exchange 'XML' Format) graph files (used in 'Gephi' and others). Using the 'XML' package, it allows the user to easily build/read graph files including attributes, 'GEXF' visual attributes (such as color, size, and position), network dynamics (for both edges and nodes) and edge weighting. Users can build/handle graphs element-by-element or massively through data-frames, visualize the graph on a web browser through 'gexf-js' (a 'javascript' library) and interact with the 'igraph' package.
URL: https://gvegayon.github.io/rgexf
BugReports: http://github.com/gvegayon/rgexf/issues
Imports: XML, igraph, grDevices, utils, servr
License: MIT + file LICENSE
LazyLoad: yes
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown, testthat, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-02-13 22:56:03 UTC; george
Author: George Vega Yon [aut, cre] (<https://orcid.org/0000-0002-3171-0844>), Jorge Fábrega Lacoa [ctb], Joshua Kunst [ctb], Raphaël Velt [cph] (gexf-js library), Gephi Consortium [cph] (GEXF language)
Maintainer: George Vega Yon <g.vegayon@gmail.com>
Repository: CRAN
Date/Publication: 2020-02-17 06:00:02 UTC

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Package onemap updated to version 2.1.3 with previous version 2.1.2 dated 2020-02-12

Title: Construction of Genetic Maps in Experimental Crosses: Full-Sib, RILs, F2 and Backcrosses
Description: Analysis of molecular marker data from model (backcrosses, F2 and recombinant inbred lines) and non-model systems (i. e. outcrossing species). For the later, it allows statistical analysis by simultaneously estimating linkage and linkage phases (genetic map construction) according to Wu et al. (2002) <doi:10.1006/tpbi.2002.1577>. All analysis are based on multipoint approaches using hidden Markov models.
Author: Gabriel Margarido [aut], Marcelo Mollinari [aut], Karl Broman [ctb], Getulio Ferreira [ctb], Rodrigo Amadeu [ctb], Cristiane Taniguti [ctb, cre], Augusto Garcia [aut, ctb]
Maintainer: Cristiane Taniguti <chtaniguti@usp.br>

Diff between onemap versions 2.1.2 dated 2020-02-12 and 2.1.3 dated 2020-02-17

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Package ICcforest updated to version 0.5.1 with previous version 0.5.0 dated 2019-02-08

Title: An Ensemble Method for Interval-Censored Survival Data
Description: Implements the conditional inference forest approach to modeling interval-censored survival data. It also provides functions to tune the parameters and evaluate the model fit. See Yao et al. (2019) <arXiv:1901.04599>.
Author: Weichi Yao [aut, cre], Halina Frydman [aut], Jeffrey S. Simonoff [aut]
Maintainer: Weichi Yao <wy635@stern.nyu.edu>

Diff between ICcforest versions 0.5.0 dated 2019-02-08 and 0.5.1 dated 2020-02-17

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New package gwsem with initial version 0.1.14
Package: gwsem
Type: Package
Title: Genome-Wide Structural Equation Modeling
Version: 0.1.14
Authors@R: c(person(c("Joshua", "N."), "Pritikin", email="jpritikin@pobox.com", role=c("aut", 'cre')), person("Bradley", "Verhulst", role="cph", email="brad.verhulst@gmail.com"), person("Gavin", "Band", role="cph"), person("Yann", "Collet", role="cph"), person("Facebook, Inc.", role="cph"), person("Yuta", "Mori", role="cph"), person("Shaun", "Purcell", role="cph"), person("Christopher", "Chang", role="cph"), person("Wojciech", "Mula", role="cph"), person("Kim", "Walisch", role="cph"))
Description: Melds genome-wide association tests with structural equation modeling (SEM) using 'OpenMx'. This package contains low-level C/C++ code to rapidly read genetic data encoded in U.K. Biobank or 'plink' formats. Prebuilt modeling options include one and two factor models. Alternately, analyses may utilize arbitrary, user-provided SEMs. See Verhulst, Maes, & Neale (2017) <doi:10.1007/s10519-017-9842-6> for details. An updated manuscript is in preparation.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Language: en-US
LinkingTo: BH (>= 1.69.0-1), Rcpp
Depends: R (>= 3.5), OpenMx (>= 2.15.5)
Imports: data.table, methods, qqman, Rcpp
Suggests: testthat (>= 2.1.0), MASS, covr, knitr, rmarkdown
RoxygenNote: 7.0.2
SystemRequirements: GNU make
URL: https://github.com/jpritikin/gwsem
BugReports: https://github.com/jpritikin/gwsem/issues
NeedsCompilation: yes
VignetteBuilder: knitr
Packaged: 2020-02-04 14:43:22 UTC; joshua
Author: Joshua N. Pritikin [aut, cre], Bradley Verhulst [cph], Gavin Band [cph], Yann Collet [cph], Facebook, Inc. [cph], Yuta Mori [cph], Shaun Purcell [cph], Christopher Chang [cph], Wojciech Mula [cph], Kim Walisch [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>
Repository: CRAN
Date/Publication: 2020-02-17 06:00:08 UTC

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Package GVARX updated to version 1.3 with previous version 1.2 dated 2019-12-20

Title: Perform Global Vector Autoregression Estimation and Inference
Description: Perform the estimation and inference of Global Vector Autoregression model (GVAR) of Pesaran, Schuermann and Weiner (2004) <DOI:10.1198/073500104000000019> and Dees, di Mauro, Pesaran and Smith (2007) <DOI:10.1002/jae.932>.
Author: Ho Tsung-wu
Maintainer: Ho Tsung-wu <tsungwu@ntnu.edu.tw>

Diff between GVARX versions 1.2 dated 2019-12-20 and 1.3 dated 2020-02-17

 DESCRIPTION   |    8 ++++----
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Package BayesLCA updated to version 1.8 with previous version 1.7 dated 2015-04-10

Title: Bayesian Latent Class Analysis
Description: Bayesian Latent Class Analysis using several different methods.
Author: Arthur White [aut, cre] (Previous email address: arthur.white@ucdconnect.ie), Thomas Brendan Murphy [aut, ths]
Maintainer: Arthur White <arwhite@tcd.ie>

Diff between BayesLCA versions 1.7 dated 2015-04-10 and 1.8 dated 2020-02-17

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