Sun, 12 Jul 2020

Package keyATM updated to version 0.3.0 with previous version 0.2.2 dated 2020-06-02

Title: Keyword Assisted Topic Model
Description: Fits keyword assisted topic models (keyATM) using collapsed Gibbs samplers. The keyATM combines the latent dirichlet allocation (LDA) models with a small number of keywords selected by researchers in order to improve the interpretability and topic classification of the LDA. The keyATM can also incorporate covariates and directly model time trends. The keyATM is proposed in Eshima, Imai, and Sasaki (2020) <arXiv:2004.05964>.
Author: Shusei Eshima [aut, cre] (<https://orcid.org/0000-0003-3613-4046>), Tomoya Sasaki [aut], William Lowe [ctb], Kosuke Imai [aut], Chung-hong Chan [ctb] (<https://orcid.org/0000-0002-6232-7530>)
Maintainer: Shusei Eshima <shuseieshima@g.harvard.edu>

Diff between keyATM versions 0.2.2 dated 2020-06-02 and 0.3.0 dated 2020-07-12

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Package ggspatial updated to version 1.1.4 with previous version 1.1.3 dated 2020-06-09

Title: Spatial Data Framework for ggplot2
Description: Spatial data plus the power of the ggplot2 framework means easier mapping when input data are already in the form of spatial objects.
Author: Dewey Dunnington [aut, cre] (<https://orcid.org/0000-0002-9415-4582>), Brent Thorne [ctb] (<https://orcid.org/0000-0002-1099-3857>)
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

Diff between ggspatial versions 1.1.3 dated 2020-06-09 and 1.1.4 dated 2020-07-12

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New package TriadSim with initial version 0.2.0
Package: TriadSim
Title: Simulating Triad Genomewide Genotypes
Version: 0.2.0
Authors@R: person("Min", "Shi", email = "shi2@niehs.nih.gov", role = c("aut", "cre"))
Description: Simulate genotypes for case-parent triads, case-control, and quantitative trait samples with realistic linkage diequilibrium structure and allele frequency distribution. For studies of epistasis one can simulate models that involve specific SNPs at specific sets of loci, which we will refer to as "pathways". TriadSim generates genotype data by resampling triad genotypes from existing data. The details of the method is described in the manuscript under preparation "Simulating Autosomal Genotypes with Realistic Linkage Disequilibrium and a Spiked in Genetic Effect" Shi, M., Umbach, D.M., Wise A.S., Weinberg, C.R.
Depends: R (>= 3.2.2)
License: GPL-3
biocViews: snpStats
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: methods, parallel, snpStats, foreach, doParallel
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-07-12 03:18:13 UTC; shi2
Author: Min Shi [aut, cre]
Maintainer: Min Shi <shi2@niehs.nih.gov>
Repository: CRAN
Date/Publication: 2020-07-12 15:30:06 UTC

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New package applicable with initial version 0.0.1.2
Package: applicable
Title: A Compilation of Applicability Domain Methods
Version: 0.0.1.2
Authors@R: c( person(given = "Marly", family = "Gotti", email = "marlygotti@gmail.com", role = c("aut", "cre")), person(given = "Max", family = "Kuhn", email = "max@rstudio.com", role = c("aut")), person("RStudio", role = "cph"))
Description: A modeling package compiling applicability domain methods in R. It combines different methods to measure the amount of extrapolation new samples can have from the training set. See Netzeva et al (2005) <doi:10.1177/026119290503300209> for an overview of applicability domains.
URL: https://github.com/tidymodels/applicable, https://applicable.tidymodels.org
BugReports: https://github.com/tidymodels/applicable/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3), ggplot2
Imports: hardhat (>= 0.1.2), rlang, stats, glue, tibble, proxyC, Matrix, dplyr, utils, purrr, tidyselect, tidyr
Suggests: recipes (>= 0.1.7), testthat (>= 2.1.0), knitr, rmarkdown, covr, AmesHousing, spelling, xml2, modeldata
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2020-07-11 23:03:04 UTC; marlygotti
Author: Marly Gotti [aut, cre], Max Kuhn [aut], RStudio [cph]
Maintainer: Marly Gotti <marlygotti@gmail.com>
Repository: CRAN
Date/Publication: 2020-07-12 15:30:03 UTC

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Package reactR updated to version 0.4.3 with previous version 0.4.2 dated 2020-01-24

Title: React Helpers
Description: Make it easy to use 'React' in R with 'htmlwidget' scaffolds, helper dependency functions, an embedded 'Babel' 'transpiler', and examples.
Author: Facebook Inc [aut, cph] (React library in lib, https://facebook.github.io/react; see AUTHORS for full list of contributors), Michel Weststrate [aut, cph] (mobx library in lib, https://github.com/mobxjs), Kent Russell [aut, cre] (R interface), Alan Dipert [aut] (R interface)
Maintainer: Kent Russell <kent.russell@timelyportfolio.com>

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Package waiter updated to version 0.1.2 with previous version 0.1.0 dated 2020-01-14

Title: Loading Screen for 'Shiny'
Description: Full screen and partial loading screens for 'Shiny' with spinners, progress bars, and notifications.
Author: John Coene [aut, cre], Jinhwan Kim [ctb]
Maintainer: John Coene <jcoenep@gmail.com>

Diff between waiter versions 0.1.0 dated 2020-01-14 and 0.1.2 dated 2020-07-12

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Package metap updated to version 1.4 with previous version 1.3 dated 2020-01-23

Title: Meta-Analysis of Significance Values
Description: The canonical way to perform meta-analysis involves using effect sizes. When they are not available this package provides a number of methods for meta-analysis of significance values including the methods of Edgington, Fisher, Lancaster, Stouffer, Tippett, and Wilkinson; a number of data-sets to replicate published results; and a routine for graphical display.
Author: Michael Dewey [aut, cre] (<https://orcid.org/0000-0002-7522-3677>)
Maintainer: Michael Dewey <lists@dewey.myzen.co.uk>

Diff between metap versions 1.3 dated 2020-01-23 and 1.4 dated 2020-07-12

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Package trundler updated to version 0.1.16 with previous version 0.1.15 dated 2020-07-11

Title: Historical Retail Data from the 'Trundler' API
Description: A wrapper around the 'Trundler' API, which gives access to historical retail product and pricing data, and can be found at <https://api.trundler.dev/>.
Author: Andrew B. Collier [aut, cre], Megan Beckett [aut, pbl]
Maintainer: Andrew B. Collier <andrew@exegetic.biz>

Diff between trundler versions 0.1.15 dated 2020-07-11 and 0.1.16 dated 2020-07-12

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Package chest updated to version 0.3.3 with previous version 0.3.2 dated 2020-07-09

Title: Change-in-Estimate Approach to Assess Confounding Effects
Description: Applies the change-in-effect estimate method to assess confounding effects in medical and epidemiological research (Greenland & Pearce (2016) <doi:10.1146/annurev-publhealth-031914-122559> ). It starts with a crude model including only the outcome and exposure variables. At each of the subsequent steps, one variable which creates the largest change among the remaining variables is selected. This process is repeated until all variables have been entered into the model (Wang Z (2007) <doi:10.1177/1536867X0700700203> ). Currently, the 'chest' package has functions for linear regression, logistic regression, negative binomial regression, Cox proportional hazards model and conditional logistic regression.
Author: Zhiqiang Wang [aut, cre]
Maintainer: Zhiqiang Wang <zhiqiang.wang@menzies.edu.au>

Diff between chest versions 0.3.2 dated 2020-07-09 and 0.3.3 dated 2020-07-12

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Package allestimates updated to version 0.1.8 with previous version 0.1.7 dated 2020-07-09

Title: Effect Estimates from All Models
Description: Estimates and plots effect estimates from models with all possible combinations of a list of variables. It can be used for assessing treatment effects in clinical trials or risk factors in bio-medical and epidemiological research. Like Stata command 'confall' (Wang Z (2007) <doi:10.1177/1536867X0700700203> ), 'allestimates' calculates and stores all effect estimates, and plots them against p values or Akaike information criterion (AIC) values. It currently has functions for linear regression: all_lm(), logistic and Poisson regression: all_glm() and all_speedglm(), and Cox proportional hazards regression: all_cox().
Author: Zhiqiang Wang [aut, cre]
Maintainer: Zhiqiang Wang <zhiqiang.wang@menzies.edu.au>

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Package DTSg updated to version 0.6.0 with previous version 0.5.0 dated 2020-06-09

Title: A Class for Working with Time Series Based on 'data.table' and 'R6' with Largely Optional Reference Semantics
Description: Basic time series functionalities such as listing of missing values, application of arbitrary aggregation as well as rolling (asymmetric) window functions and automatic detection of periodicity. As it is mainly based on 'data.table', it is fast and - in combination with the 'R6' package - offers reference semantics. In addition to its native R6 interface, it provides an S3 interface inclusive an S3 wrapper method generator for those who prefer the latter. Finally yet importantly, its functional approach allows incorporating functionalities from many other packages.
Author: Gerold Hepp [aut, cre]
Maintainer: Gerold Hepp <ghepp@iwag.tuwien.ac.at>

Diff between DTSg versions 0.5.0 dated 2020-06-09 and 0.6.0 dated 2020-07-12

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Package GpGp updated to version 0.2.2 with previous version 0.2.1 dated 2019-07-09

Title: Fast Gaussian Process Computation Using Vecchia's Approximation
Description: Functions for fitting and doing predictions with Gaussian process models using Vecchia's (1988) approximation. Package also includes functions for reordering input locations, finding ordered nearest neighbors (with help from 'FNN' package), grouping operations, and conditional simulations. Covariance functions for spatial and spatial-temporal data on Euclidean domains and spheres are provided. The original approximation is due to Vecchia (1988) <http://www.jstor.org/stable/2345768>, and the reordering and grouping methods are from Guinness (2018) <doi:10.1080/00401706.2018.1437476>. Model fitting employs a Fisher scoring algorithm described in Guinness (2019) <arXiv:1905.08374>.
Author: Joseph Guinness [aut, cre], Matthias Katzfuss [aut]
Maintainer: Joseph Guinness <joeguinness@gmail.com>

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More information about GpGp at CRAN
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Package ggdist updated to version 2.2.0 with previous version 2.1.1 dated 2020-06-14

Title: Visualizations of Distributions and Uncertainty
Description: Provides primitives for visualizing distributions using 'ggplot2' that are particularly tuned for visualizing uncertainty in either a frequentist or Bayesian mode. Both analytical distributions (such as frequentist confidence distributions or Bayesian priors) and distributions represented as samples (such as bootstrap distributions or Bayesian posterior samples) are easily visualized. Visualization primitives include but are not limited to: points with multiple uncertainty intervals, eye plots (Spiegelhalter D., 1999) <doi:10.1111/1467-985X.00120>, density plots, gradient plots, dot plots (Wilkinson L., 1999) <doi:10.1080/00031305.1999.10474474>, quantile dot plots (Kay M., Kola T., Hullman J., Munson S., 2016) <doi:10.1145/2858036.2858558>, complementary cumulative distribution function barplots (Fernandes M., Walls L., Munson S., Hullman J., Kay M., 2018) <doi:10.1145/3173574.3173718>, and fit curves with multiple uncertainty ribbons.
Author: Matthew Kay [aut, cre]
Maintainer: Matthew Kay <mjskay@umich.edu>

Diff between ggdist versions 2.1.1 dated 2020-06-14 and 2.2.0 dated 2020-07-12

 DESCRIPTION                                                                             |   23 
 MD5                                                                                     |  172 +-
 NAMESPACE                                                                               |    6 
 NEWS.md                                                                                 |    9 
 R/geom_dotsinterval.R                                                                   |   12 
 R/geom_interval.R                                                                       |  254 +--
 R/geom_lineribbon.R                                                                     |    7 
 R/geom_pointinterval.R                                                                  |  252 +--
 R/geom_slabinterval.R                                                                   |   15 
 R/lkjcorr_marginal.R                                                                    |  378 ++--
 R/parse_dist.R                                                                          |  386 ++--
 R/point_interval.R                                                                      |  810 +++++-----
 R/scales.R                                                                              |  622 +++----
 R/stat.R                                                                                |   58 
 R/stat_dist_slabinterval.R                                                              |  148 +
 R/stat_dotsinterval.R                                                                   |  568 +++----
 R/stat_interval.R                                                                       |    4 
 R/stat_lineribbon.R                                                                     |    3 
 R/stat_pointinterval.R                                                                  |    4 
 R/stat_sample_slabinterval.R                                                            |  810 +++++-----
 R/stat_slabinterval.R                                                                   |  762 ++++-----
 R/student_t.R                                                                           |  162 +-
 R/theme_ggdist.R                                                                        |  138 -
 R/tidy_format_translators.R                                                             |  242 +-
 R/util.R                                                                                |  167 +-
 build/partial.rdb                                                                       |binary
 build/vignette.rds                                                                      |binary
 inst/doc/freq-uncertainty-vis.R                                                         |   10 
 inst/doc/freq-uncertainty-vis.Rmd                                                       |   12 
 inst/doc/freq-uncertainty-vis.html                                                      |   32 
 inst/doc/slabinterval.R                                                                 |   34 
 inst/doc/slabinterval.Rmd                                                               |   54 
 inst/doc/slabinterval.html                                                              |  409 ++---
 man/geom_dotsinterval.Rd                                                                |   10 
 man/geom_interval.Rd                                                                    |    6 
 man/geom_lineribbon.Rd                                                                  |    2 
 man/geom_pointinterval.Rd                                                               |    6 
 man/geom_slabinterval.Rd                                                                |    6 
 man/scales.Rd                                                                           |    2 
 man/stat_dist_slabinterval.Rd                                                           |   51 
 man/stat_interval.Rd                                                                    |   10 
 man/stat_lineribbon.Rd                                                                  |    5 
 man/stat_pointinterval.Rd                                                               |   10 
 man/stat_sample_slabinterval.Rd                                                         |    6 
 man/stat_slabinterval.Rd                                                                |    4 
 man/theme_ggdist.Rd                                                                     |    4 
 tests/figs/deps.txt                                                                     |    2 
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 tests/testthat/test.geom_dotsinterval.R                                                 |  193 +-
 tests/testthat/test.geom_interval.R                                                     |    6 
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 tests/testthat/test.point_interval.R                                                    |  670 ++++----
 tests/testthat/test.stat_dist_slabinterval.R                                            |  414 ++---
 tests/testthat/test.stat_eye.R                                                          |   10 
 vignettes/freq-uncertainty-vis.Rmd                                                      |   12 
 vignettes/slabinterval.Rmd                                                              |   54 
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More information about ggdist at CRAN
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Package psychmeta updated to version 2.4.0 with previous version 2.3.10 dated 2020-06-07

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], Wesley Gardiner [ctb] (Unit tests), 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 <jdahlke@humrro.org>

Diff between psychmeta versions 2.3.10 dated 2020-06-07 and 2.4.0 dated 2020-07-12

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More information about psychmeta at CRAN
Permanent link

Package grpCox (with last version 1.0) was removed from CRAN

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

2020-06-03 1.0

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