Tue, 13 Jul 2021

Package flexmet updated to version 1.1 with previous version 1.0.0.0 dated 2018-04-06

Title: Flexible Latent Trait Metrics using the Filtered Monotonic Polynomial Item Response Model
Description: Application of the filtered monotonic polynomial (FMP) item response model to flexibly fit item response models. The package includes tools that allow the item response model to be build on any monotonic transformation of the latent trait metric, as described by Feuerstahler (2019) <doi:10.1007/s11336-018-9642-9>.
Author: Leah Feuerstahler [aut, cre]
Maintainer: Leah Feuerstahler <lfeuerstahler@fordham.edu>

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Package abglasso updated to version 0.1.1 with previous version 0.1.0 dated 2021-05-12

Title: Adaptive Bayesian Graphical Lasso
Description: Implements a Bayesian adaptive graphical lasso data-augmented block Gibbs sampler. The sampler simulates the posterior distribution of precision matrices of a Gaussian Graphical Model. This sampler was adapted from the original MATLAB routine proposed in Wang (2012) <doi:10.1214/12-BA729>.
Author: Jarod Smith [aut, cre] (<https://orcid.org/0000-0003-4235-6147>), Mohammad Arashi [aut] (<https://orcid.org/0000-0003-4793-5674>), Andriette Bekker [aut] (<https://orcid.org/0000-0002-5881-9241>)
Maintainer: Jarod Smith <jarodsmith706@gmail.com>

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Package rtables updated to version 0.3.8 with previous version 0.3.6 dated 2021-01-22

Title: Reporting Tables
Description: Reporting tables often have structure that goes beyond simple rectangular data. The 'rtables' package provides a framework for declaring complex multi-level tabulations and then applying them to data. This framework models both tabulation and the resulting tables as hierarchical, tree-like objects which support sibling sub-tables, arbitrary splitting or grouping of data in row and column dimensions, cells containing multiple values, and the concept of contextual summary computations. A convenient pipe-able interface is provided for declaring table layouts and the corresponding computations, and then applying them to data.
Author: Gabriel Becker [aut, cre], Adrian Waddell [aut], Daniel Sabanés Bové [ctb], Maximilian Mordig [ctb]
Maintainer: Gabriel Becker <gabembecker@gmail.com>

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Package RATest updated to version 0.1.9 with previous version 0.1.8 dated 2020-10-16

Title: Randomization Tests
Description: A collection of randomization tests, data sets and examples. The current version focuses on five testing problems and their implementation in empirical work. First, it facilitates the empirical researcher to test for particular hypotheses, such as comparisons of means, medians, and variances from k populations using robust permutation tests, which asymptotic validity holds under very weak assumptions, while retaining the exact rejection probability in finite samples when the underlying distributions are identical. Second, the description and implementation of a permutation test for testing the continuity assumption of the baseline covariates in the sharp regression discontinuity design (RDD) as in Canay and Kamat (2018) <https://goo.gl/UZFqt7>. More specifically, it allows the user to select a set of covariates and test the aforementioned hypothesis using a permutation test based on the Cramer-von Misses test statistic. Graphical inspection of the empirical CDF and histograms for the variables of interest is also supported in the package. Third, it provides the practitioner with an effortless implementation of a permutation test based on the martingale decomposition of the empirical process for testing for heterogeneous treatment effects in the presence of an estimated nuisance parameter as in Chung and Olivares (2021) <doi:10.1016/j.jeconom.2020.09.015>. Fourth, this version considers the two-sample goodness-of-fit testing problem under covariate adaptive randomization and implements a permutation test based on a prepivoted Kolmogorov-Smirnov test statistic. Lastly, it implements an asymptotically valid permutation test based on the quantile process for the hypothesis of constant quantile treatment effects in the presence of an estimated nuisance parameter.
Author: Mauricio Olivares [aut, cre], Ignacio Sarmiento-Barbieri [aut]
Maintainer: Mauricio Olivares <mau.olivarego@gmail.com>

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Package PDE updated to version 1.3.0 with previous version 1.2.1 dated 2021-04-01

Title: Extract Tables and Sentences from PDFs with User Interface
Description: The PDE (Pdf Data Extractor) allows the extraction of information and tables optionally based on search words from PDF (Portable Document Format) files and enables the visualization of the results, both by providing a convenient user-interface.
Author: Erik Stricker [aut, cre]
Maintainer: Erik Stricker <erik.stricker@gmx.com>

Diff between PDE versions 1.2.1 dated 2021-04-01 and 1.3.0 dated 2021-07-13

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 PDE-1.3.0/PDE/README.md                                                                                     |   52 
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 PDE-1.3.0/PDE/man/PDE_pdfs2table.Rd                                                                         |   16 
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Package lpme updated to version 1.1.2 with previous version 1.1.1 dated 2017-10-31

Title: Nonparametric Estimation of Measurement Error Models
Description: Provide nonparametric methods for mean regression model, modal regression and conditional density estimation in the presence/absence of measurement error. Bandwidth selection is also provided for each method. See Huang and Zhou (2017) <doi:10.1080/10485252.2017.1303060>, Zhou and Huang (2016) <doi:10.1214/16-EJS1210>, Huang and Zhou (2020) <doi:10.1214/20-EJS1688>, and Zhou and Huang (2019) <doi:10.1080/03610918.2017.1402044>.
Author: Haiming Zhou [aut, cre, cph], Xianzheng Huang [aut]
Maintainer: Haiming Zhou <zhouh@niu.edu>

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Package tidySEM updated to version 0.1.10 with previous version 0.1.9 dated 2021-04-20

Title: Tidy Structural Equation Modeling
Description: A tidy workflow for generating, estimating, reporting, and plotting structural equation models using 'lavaan', 'OpenMx', or 'Mplus'. Throughout this workflow, elements of syntax, results, and graphs are represented as 'tidy' data, making them easy to customize.
Author: Caspar J. van Lissa [aut, cre] (<https://orcid.org/0000-0002-0808-5024>)
Maintainer: Caspar J. van Lissa <c.j.vanlissa@uu.nl>

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Package collpcm updated to version 1.2 with previous version 1.1 dated 2019-10-24

Title: Collapsed Latent Position Cluster Model for Social Networks
Description: Markov chain Monte Carlo based inference routines for collapsed latent position cluster models or social networks, which includes searches over the model space (number of clusters in the latent position cluster model). The label switching algorithm used is that of Nobile and Fearnside (2007) <doi:10.1007/s11222-006-9014-7> which relies on the algorithm of Carpaneto and Toth (1980) <doi:10.1145/355873.355883>.
Author: Jason Wyse [aut, cre], Caitriona Ryan [aut], Nial Friel [ths]
Maintainer: Jason Wyse <wyseja@tcd.ie>

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 man/collpcm.control.Rd           |   16 +-
 man/collpcm.fit.Rd               |    4 
 man/collpcm.summaryplot.Rd       |    4 
 man/plot.collpcm.Rd              |    8 -
 man/print.collpcm.Rd             |    4 
 man/summary.collpcm.Rd           |    4 
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 19 files changed, 261 insertions(+), 384 deletions(-)

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Package tsrobprep updated to version 0.3.1 with previous version 0.3.0 dated 2021-06-30

Title: Robust Preprocessing of Time Series Data
Description: Methods for handling the missing values outliers are introduced in this package. The recognized missing values and outliers are replaced using a model-based approach. The model may consist of both autoregressive components and external regressors. The methods work robust and efficient, and they are fully tunable. The primary motivation for writing the package was preprocessing of the energy systems data, e.g. power plant production time series, but the package could be used with any time series data.
Author: Michał Narajewski [aut, cre] (<https://orcid.org/0000-0002-3115-0162>), Jens Kley-Holsteg [aut], Florian Ziel [aut] (<https://orcid.org/0000-0002-2974-2660>)
Maintainer: Michał Narajewski <michal.narajewski@uni-due.de>

Diff between tsrobprep versions 0.3.0 dated 2021-06-30 and 0.3.1 dated 2021-07-13

 DESCRIPTION            |    8 
 MD5                    |   10 
 R/auto_data_cleaning.R |    4 
 R/detect_outliers.R    |  134 ++++--
 R/model_missing_data.R |  950 ++++++++++++++++++++++++-------------------------
 man/detect_outliers.Rd |   40 +-
 6 files changed, 606 insertions(+), 540 deletions(-)

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Package Tplyr updated to version 0.4.1 with previous version 0.4.0 dated 2021-02-11

Title: A Grammar of Clinical Data Summary
Description: A tool created to simplify the data manipulation necessary to create clinical reports.
Author: Eli Miller [aut] (<https://orcid.org/0000-0002-2127-9456>), Mike Stackhouse [aut, cre] (<https://orcid.org/0000-0001-6030-723X>), Ashley Tarasiewicz [aut], Nathan Kosiba [aut] (<https://orcid.org/0000-0001-5359-4234>), Atorus Research LLC [cph]
Maintainer: Mike Stackhouse <mike.stackhouse@atorusresearch.com>

Diff between Tplyr versions 0.4.0 dated 2021-02-11 and 0.4.1 dated 2021-07-13

 DESCRIPTION                 |    7 +-
 MD5                         |   26 ++++-----
 NEWS.md                     |    7 ++
 R/prebuild.R                |   16 ++---
 R/riskdiff.R                |    5 -
 R/stats.R                   |    9 ---
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 inst/doc/desc.html          |    9 ++-
 inst/doc/options.html       |    9 ++-
 inst/doc/shift.html         |    9 ++-
 inst/doc/table.html         |    9 ++-
 tests/testthat/test-count.R |    5 +
 14 files changed, 154 insertions(+), 108 deletions(-)

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New package PosRatioDist with initial version 1.0.1
Package: PosRatioDist
Title: Quotient of Random Variables Conditioned to the Positive Quadrant
Version: 1.0.1
Authors@R: c(person(given = "Yuancheng", family = "Si", role = c("aut", "cre"), email = "siyuanchengman@gmail.com", comment = c(ORCID = "0000-0003-0944-0013")), person(given = "Saralees", family = "Nadarajah", role = "aut"), person(given = "Xiaodong", family = "Song", role = "ctb"))
Maintainer: Yuancheng Si <siyuanchengman@gmail.com>
Description: Computes the exact probability density function of X/Y conditioned on positive quadrant for series of bivariate distributions,for more details see Nadarajah,Song and Si (2019) <DOI:10.1080/03610926.2019.1576893>.
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
Imports: BMS, mvtnorm, stats, NORMT3
NeedsCompilation: no
Packaged: 2021-07-13 14:24:11 UTC; siyua
Author: Yuancheng Si [aut, cre] (<https://orcid.org/0000-0003-0944-0013>), Saralees Nadarajah [aut], Xiaodong Song [ctb]
Repository: CRAN
Date/Publication: 2021-07-13 16:30:05 UTC

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Package csv updated to version 0.6.1 with previous version 0.5.9 dated 2020-05-20

Title: Read and Write CSV Files with Selected Conventions
Description: Reads and writes CSV with selected conventions. Uses the same generic function for reading and writing to promote consistent formats.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

Diff between csv versions 0.5.9 dated 2020-05-20 and 0.6.1 dated 2021-07-13

 DESCRIPTION |    9 ++++-----
 MD5         |    4 ++--
 R/csv.R     |    4 ++--
 3 files changed, 8 insertions(+), 9 deletions(-)

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New package tRnslate with initial version 0.0.3
Package: tRnslate
Title: Translate R Code in Source Files
Version: 0.0.3
Date: 2021-07-13
Authors@R: c(person(given=c('Mario A.'), family='Martinez Araya', role=c('aut','cre', 'cph'), email='r@marioma.me', comment = c(ORCID = '0000-0002-4821-9314')))
Author: Mario A. Martinez Araya [aut, cre, cph] (<https://orcid.org/0000-0002-4821-9314>)
Maintainer: Mario A. Martinez Araya <r@marioma.me>
Description: Evaluate inline or chunks of R code in template files and replace with their output modifying the resulting template.
License: GPL (>= 2)
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown, markdown
URL: <https://marioma.me?i=soft>
BuildVignettes: yes
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-07-13 09:33:16 UTC; mma
Repository: CRAN
Date/Publication: 2021-07-13 15:40:02 UTC

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New package starter with initial version 0.1.4
Package: starter
Title: Starter Kit for New Projects
Version: 0.1.4
Authors@R: person(given = "Daniel D.", family = "Sjoberg", role = c("aut", "cre"), email = "danield.sjoberg@gmail.com", comment = c(ORCID = "0000-0003-0862-2018"))
Description: Get started with new projects by dropping a skeleton of a new project into a new or existing directory, initialise Git repositories, and create reproducible environments with the renv package. The package allows for dynamically named files, folders, file content, as well as the functionality to drop individual template files into existing projects.
License: AGPL (>= 3)
URL: https://github.com/ddsjoberg/starter, http://www.danieldsjoberg.com/starter/index.html
BugReports: https://github.com/ddsjoberg/starter/issues
Depends: R (>= 3.4)
Imports: dplyr (>= 1.0.6), fs (>= 1.5.0), gert (>= 1.3.0), glue (>= 1.4.2), here (>= 1.0.1), purrr (>= 0.3.4), R.utils (>= 2.10.1), readr (>= 1.4.0), renv (>= 0.13.2), rlang (>= 0.4.11), rstudioapi (>= 0.13), stringr (>= 1.4.0), tibble (>= 3.1.2), usethis (>= 2.0.1)
Suggests: covr (>= 3.5.1), knitr (>= 1.33), rmarkdown (>= 2.9), spelling (>= 2.2), testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2021-07-12 13:27:00 UTC; SjobergD
Author: Daniel D. Sjoberg [aut, cre] (<https://orcid.org/0000-0003-0862-2018>)
Maintainer: Daniel D. Sjoberg <danield.sjoberg@gmail.com>
Repository: CRAN
Date/Publication: 2021-07-13 15:20:02 UTC

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New package qpNCA with initial version 1.1.5
Package: qpNCA
Title: Noncompartmental Pharmacokinetic Analysis by qPharmetra
Version: 1.1.5
Authors@R: c(person("Jan", "Huisman", role = c("aut", "cre"), email = "jan.huisman@qpharmetra.com"), person("Koen", "Jolling", role = "ctb"), person("Krina", "Mehta", role = "ctb"), person("Tim", "Bergsma", role = "ctb"))
Author: Jan Huisman [aut, cre], Koen Jolling [ctb], Krina Mehta [ctb], Tim Bergsma [ctb]
Maintainer: Jan Huisman <jan.huisman@qpharmetra.com>
Description: Computes noncompartmental pharmacokinetic parameters for drug concentration profiles. For each profile, data imputations and adjustments are made as necessary and basic parameters are estimated. Supports single dose, multi-dose, and multi-subject data. Supports steady-state calculations and various routes of drug administration. See ?qpNCA and vignettes. Methodology follows Rowland and Tozer (2011, ISBN:978-0-683-07404-8), Gabrielsson and Weiner (1997, ISBN:978-91-9765-100-4), and Gibaldi and Perrier (1982, ISBN:978-0824710422).
License: GPL-3
Encoding: UTF-8
Suggests: rmarkdown, markdown, covr, testthat (>= 2.1.0)
Depends: R (>= 3.3.0)
Imports: dplyr(>= 0.7.0), tidyr (>= 0.8.2), magrittr, ggplot2, knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-07-12 13:00:26 UTC; rstudio
Repository: CRAN
Date/Publication: 2021-07-13 15:10:02 UTC

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New package posterior with initial version 1.0.0
Package: posterior
Title: Tools for Working with Posterior Distributions
Version: 1.0.0
Date: 2021-07-02
Authors@R: c(person("Paul-Christian", "Bürkner", email = "paul.buerkner@gmail.com", role = c("aut", "cre")), person("Jonah", "Gabry", email = "jsg2201@columbia.edu", role = c("aut")), person("Matthew", "Kay", email = "mjskay@umich.edu", role = c("aut")), person("Aki", "Vehtari", email = "Aki.Vehtari@aalto.fi", role = c("aut")), person("Måns", "Magnusson", role = c("ctb")), person("Rok", "Češnovar", role = c("ctb")), person("Ben", "Lambert", role = c("ctb")), person("Ozan", "Adıgüzel", role = c("ctb")), person("Jacob", "Socolar", role = c("ctb")))
Description: Provides useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to: (a) Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions. (b) Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws. (c) Provide various summaries of draws in convenient formats. (d) Provide lightweight implementations of state of the art posterior inference diagnostics. References: Vehtari et al. (2021) <doi:10.1214/20-BA1221>.
Depends: R (>= 3.2.0)
Imports: abind, checkmate, rlang (>= 0.4.7), stats, tibble (>= 3.0.0), vctrs, tensorA, pillar, distributional, parallel
Suggests: testthat (>= 2.1.0), caret (>= 6.0.84), gbm (>= 2.1.8), randomForest (>= 4.6.14), e1071 (>= 1.7.3), dplyr, tidyr, knitr, rmarkdown
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
LazyData: false
URL: https://mc-stan.org/posterior/, https://discourse.mc-stan.org/
BugReports: https://github.com/stan-dev/posterior/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-07-13 07:37:39 UTC; paulb
Author: Paul-Christian Bürkner [aut, cre], Jonah Gabry [aut], Matthew Kay [aut], Aki Vehtari [aut], Måns Magnusson [ctb], Rok Češnovar [ctb], Ben Lambert [ctb], Ozan Adıgüzel [ctb], Jacob Socolar [ctb]
Maintainer: Paul-Christian Bürkner <paul.buerkner@gmail.com>
Repository: CRAN
Date/Publication: 2021-07-13 15:40:04 UTC

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Package phangorn updated to version 2.7.1 with previous version 2.7.0 dated 2021-05-03

Title: Phylogenetic Reconstruction and Analysis
Description: Allows for estimation of phylogenetic trees and networks using Maximum Likelihood, Maximum Parsimony, distance methods and Hadamard conjugation. Offers methods for tree comparison, model selection and visualization of phylogenetic networks as described in Schliep et al. (2017) <doi:10.1111/2041-210X.12760>.
Author: Klaus Schliep [aut, cre] (<https://orcid.org/0000-0003-2941-0161>), Emmanuel Paradis [aut] (<https://orcid.org/0000-0003-3092-2199>), Leonardo de Oliveira Martins [aut] (<https://orcid.org/0000-0001-5247-1320>), Alastair Potts [aut], Tim W. White [aut], Cyrill Stachniss [ctb], Michelle Kendall [ctb], Keren Halabi [ctb], Richel Bilderbeek [ctb], Kristin Winchell [ctb], Liam Revell [ctb], Mike Gilchrist [ctb], Jeremy Beaulieu [ctb], Brian O'Meara [ctb], Long Qu [ctb]
Maintainer: Klaus Schliep <klaus.schliep@gmail.com>

Diff between phangorn versions 2.7.0 dated 2021-05-03 and 2.7.1 dated 2021-07-13

 DESCRIPTION                                |    6 
 MD5                                        |   48 ++---
 NEWS                                       |    7 
 R/ancestral_pml.R                          |    4 
 R/cladePar.R                               |    9 
 R/fitch64.R                                |    2 
 R/networx.R                                |    7 
 R/parsimony.R                              |   25 +-
 R/phyDat.R                                 |    2 
 R/phyDat2.R                                |    2 
 R/phylo.R                                  |    2 
 R/treeManipulation.R                       |   10 -
 R/treeRearrangement.R                      |    2 
 build/vignette.rds                         |binary
 inst/doc/AdvancedFeatures.html             |   29 +--
 inst/doc/Ancestral.html                    |   31 +--
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 inst/doc/Networx.html                      |   21 +-
 inst/doc/Trees.R                           |   29 ++-
 inst/doc/Trees.Rmd                         |   72 ++++++-
 inst/doc/Trees.html                        |  277 +++++++++++++++++------------
 man/cladePar.Rd                            |    2 
 src/RcppExports.cpp                        |    5 
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 25 files changed, 447 insertions(+), 229 deletions(-)

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Package patientProfilesVis updated to version 2.0.1 with previous version 2.0.0 dated 2021-06-14

Title: Visualization of Patient Profiles
Description: Creation of patient profile visualizations for exploration, diagnostic or monitoring purposes during a clinical trial. These static visualizations display a patient-specific overview of the evolution during the trial time frame of parameters of interest (as laboratory, ECG, vital signs), presence of adverse events, exposure to a treatment; associated with metadata patient information, as demography, concomitant medication. The visualizations can be tailored for specific domain(s) or endpoint(s) of interest. Visualizations are exported into patient profile report(s) or can be embedded in custom report(s).
Author: Laure Cougnaud [aut, cre], Open Analytics [cph]
Maintainer: Laure Cougnaud <laure.cougnaud@openanalytics.eu>

Diff between patientProfilesVis versions 2.0.0 dated 2021-06-14 and 2.0.1 dated 2021-07-13

 DESCRIPTION                                   |    8 -
 MD5                                           |   12 +-
 inst/NEWS                                     |    2 
 inst/doc/patientProfiles-template-SDTM.html   |   11 +-
 inst/doc/patientProfilesVis-introduction.Rmd  |  122 ++++++++++++--------------
 inst/doc/patientProfilesVis-introduction.html |   11 +-
 vignettes/patientProfilesVis-introduction.Rmd |  122 ++++++++++++--------------
 7 files changed, 146 insertions(+), 142 deletions(-)

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New package mutualinf with initial version 1.0.0
Package: mutualinf
Title: Calculation and Decomposition of the Mutual Information Index
Version: 1.0.0
Authors@R: c(person("Rafael", "Fuentealba-Chaura", email = "rfuentealba@inf.uct.cl", role = c("aut", "cre")), person("Ricardo", "Mora", email = "ricmora@eco.uc3m.es", role = "aut"), person("Julio", "Rojas-Mora", email = "jrojas@inf.uct.cl", role = "aut"))
Description: The Mutual Information Index (M) introduced to social science literature by Theil and Finizza (1971) <doi:10.1080/0022250X.1971.9989795> is a multigroup segregation measure that is highly decomposable and that according to Frankel and Volij (2011) <doi:10.1016/j.jet.2010.10.008> and Mora and Ruiz-Castillo (2011) <doi:10.1111/j.1467-9531.2011.01237.x> satisfies the Strong Unit Decomposability and Strong Group Decomposability properties. This package allows calculating and decomposing the total index value into its "between" and "within" terms. These last terms can also be decomposed into their contributions, either by group or unit characteristics. The factors that produce each "within" term can also be displayed at the user's request. The results can be calculated considering a variable or sets of variables that define separate clusters.
License: GPL-3
Imports: data.table, parallel, stats
Encoding: UTF-8
LazyData: true
URL: https://github.com/RafaelFuentealbaC/mutualinf
BugReports: https://github.com/RafaelFuentealbaC/mutualinf/issues
Depends: R (>= 2.10)
Collate: 'Data_Source.R' 'get_general_contribution.R' 'get_proportion.R' 'get_internal_data.R' 'M_within.R' 'mutual.R' 'get_contribution.R' 'M_value.R' 'M.R' 'globals.R' 'prepare_data.R'
NeedsCompilation: no
Packaged: 2021-07-12 23:21:39 UTC; rafael
Author: Rafael Fuentealba-Chaura [aut, cre], Ricardo Mora [aut], Julio Rojas-Mora [aut]
Maintainer: Rafael Fuentealba-Chaura <rfuentealba@inf.uct.cl>
Repository: CRAN
Date/Publication: 2021-07-13 15:20:05 UTC

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Package inTextSummaryTable updated to version 3.0.1 with previous version 3.0.0 dated 2021-06-10

Title: Creation of in-Text Summary Table
Description: Creation of tables of summary statistics or counts for clinical data (for 'TLFs'). These tables can be exported as in-text table (with the 'flextable' package) for a Clinical Study Report (Word format) or a 'topline' presentation (PowerPoint format), or as interactive table (with the 'DT' package) to an html document for clinical data review.
Author: Laure Cougnaud [aut, cre], Michela Pasetto [aut]
Maintainer: Laure Cougnaud <laure.cougnaud@openanalytics.eu>

Diff between inTextSummaryTable versions 3.0.0 dated 2021-06-10 and 3.0.1 dated 2021-07-13

 DESCRIPTION                                           |   10 
 MD5                                                   |   28 
 R/formatSummaryStatisticsTable.R                      |   20 
 inst/NEWS                                             |    3 
 inst/doc/inTextSummaryTable-advanced.html             |   31 
 inst/doc/inTextSummaryTable-aesthetics.html           |   51 -
 inst/doc/inTextSummaryTable-createTables.html         |  751 +++++++++---------
 inst/doc/inTextSummaryTable-exportTables.Rmd          |    4 
 inst/doc/inTextSummaryTable-exportTables.html         |  146 +--
 inst/doc/inTextSummaryTable-introduction.html         |   11 
 inst/doc/inTextSummaryTable-standardTables.html       |  131 +--
 inst/doc/inTextSummaryTable-visualization.html        |   11 
 tests/testthat/test_exportSummaryStatisticsTable-DT.R |   11 
 tests/testthat/test_exportSummaryStatisticsTable.R    |    6 
 vignettes/inTextSummaryTable-exportTables.Rmd         |    4 
 15 files changed, 635 insertions(+), 583 deletions(-)

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Package AtmChile updated to version 0.1.1 with previous version 0.1.0 dated 2021-05-04

Title: Download Air Quality and Meteorological Information of Chile
Description: Download air quality and meteorological information of Chile from the National Air Quality System (S.I.N.C.A.)<https://sinca.mma.gob.cl/> dependent on the Ministry of the Environment and the Meteorological Directorate of Chile (D.M.C.)<http://www.meteochile.gob.cl/> dependent on the Directorate General of Civil Aeronautics.
Author: Francisco Catalan Meyer [aut, cre] (<https://orcid.org/0000-0003-3506-5376>), Manuel Leiva [aut] (<https://orcid.org/0000-0001-8891-0399>), Richard Toro [aut]
Maintainer: Francisco Catalan Meyer <francisco.catalan@ug.uchile.cl>

Diff between AtmChile versions 0.1.0 dated 2021-05-04 and 0.1.1 dated 2021-07-13

 DESCRIPTION            |    6 -
 MD5                    |    8 -
 R/ChileAirQuality.R    |  269 ++++++++++++++++++++++++++++++++++++++++++++-----
 README.md              |    9 +
 man/ChileAirQuality.Rd |   17 ++-
 5 files changed, 273 insertions(+), 36 deletions(-)

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Package windAC updated to version 1.2.6 with previous version 1.2.4 dated 2020-11-23

Title: Area Correction Methods
Description: Post-construction fatality monitoring studies at wind facilities are based on data from searches for bird and bat carcasses in plots beneath turbines. Bird and bat carcasses can fall outside of the search plot. Bird and bat carcasses from wind turbines often fall outside of the searched area. To compensate, area correction (AC) estimations are calculated to estimate the percentage of fatalities that fall within the searched area versus those that fall outside of it. This package provides two likelihood based methods and one physics based method (Hull and Muir (2010) <doi:10.1080/14486563.2010.9725253>, Huso and Dalthorp (2014) <doi:10.1002/jwmg.663>) to estimate the carcass fall distribution. There are also functions for calculating the proportion of area searched within one unit annuli, log logistic distribution functions, and truncated distribution functions.
Author: Jared Studyvin [aut, cre], Paul Rabie [aut], Daniel Riser-Espinoza [aut], Trent McDonald [ctb]
Maintainer: Jared Studyvin <jared.studyvin@gmail.com>

Diff between windAC versions 1.2.4 dated 2020-11-23 and 1.2.6 dated 2021-07-13

 DESCRIPTION                              |   14 ++++++------
 MD5                                      |   34 +++++++++++++++----------------
 R/calcAC.R                               |    4 +--
 R/dllog.R                                |    2 -
 R/geometricRectanglePropSearchTable.R    |    4 +--
 R/geometricRoadPadPropSearchTable.R      |   11 ++++++----
 R/getProportionAreaSearched.R            |   27 ++++++++++++------------
 R/triangleProb.R                         |    4 +--
 R/weightFun.R                            |    6 ++---
 R/windAC.R                               |    2 -
 man/LogLogistic.Rd                       |    2 -
 man/calcAC.Rd                            |    4 +--
 man/geometricRectanglePropSearchTable.Rd |    4 +--
 man/geometricRoadPadPropSearchTable.Rd   |    2 -
 man/getProportionAreaSearched.Rd         |   17 ++++++++-------
 man/triangleProb.Rd                      |    4 +--
 man/weightFun.Rd                         |    6 ++---
 man/windAC.Rd                            |    2 -
 18 files changed, 77 insertions(+), 72 deletions(-)

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New package ugatsdb with initial version 0.1.7
Package: ugatsdb
Title: Uganda Time Series Database API
Version: 0.1.7
Date: 2021-07-11
Authors@R: person("Sebastian", "Krantz", role = c("aut", "cre"), email = "sebastian.krantz@graduateinstitute.ch")
Description: An R API providing easy access to a relational database with macroeconomic, financial and development related time series data for Uganda. Overall more than 5000 series at varying frequency (daily, monthly, quarterly, annual in fiscal or calendar years) can be accessed through the API. The data is provided by the Bank of Uganda, the Ugandan Ministry of Finance, Planning and Economic Development, the IMF and the World Bank. The database is being updated once a month.
URL: https://mepd.finance.go.ug/apps.html
License: GPL-3
Encoding: UTF-8
Imports: DBI, RMySQL, data.table, collapse, writexl
Suggests: magrittr, xts, dygraphs
NeedsCompilation: no
Packaged: 2021-07-11 10:28:26 UTC; Sebastian Krantz
Author: Sebastian Krantz [aut, cre]
Maintainer: Sebastian Krantz <sebastian.krantz@graduateinstitute.ch>
Repository: CRAN
Date/Publication: 2021-07-13 15:00:01 UTC

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Package rater updated to version 1.2.0 with previous version 1.1.0 dated 2021-03-14

Title: Statistical Models of Repeated Categorical Rating Data
Description: Fit statistical models based on the Dawid-Skene model - Dawid and Skene (1979) <doi:10.2307/2346806> - to repeated categorical rating data. Full Bayesian inference for these models is supported through the Stan modelling language. 'rater' also allows the user to extract and plot key parameters of these models.
Author: Jeffrey Pullin [aut, cre, cph] (<https://orcid.org/0000-0003-3651-5471>), Damjan Vukcevic [aut] (<https://orcid.org/0000-0001-7780-9586>), Lars Mølgaard Saxhaug [aut] (<https://orcid.org/0000-0001-5084-1578>)
Maintainer: Jeffrey Pullin <jeffrey.pullin@gmail.com>

Diff between rater versions 1.1.0 dated 2021-03-14 and 1.2.0 dated 2021-07-13

 DESCRIPTION                             |   57 ++++++++++++++++------------
 MD5                                     |   23 ++++++-----
 NAMESPACE                               |    3 +
 NEWS.md                                 |    8 ++++
 R/model_comparison.R                    |   63 ++++++++++++++++++++++++++++++++
 R/plotting.R                            |    4 +-
 R/posterior_predict.R                   |    2 -
 build/vignette.rds                      |binary
 inst/doc/data-formats.html              |    1 
 inst/doc/workflow.html                  |    9 ++--
 man/waic.rater_fit.Rd                   |only
 tests/testthat/test-model_comparison.R  |   24 ++++++++++++
 tests/testthat/test-posterior_predict.R |    5 ++
 13 files changed, 156 insertions(+), 43 deletions(-)

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New package PhotosynQ with initial version 0.2.3
Package: PhotosynQ
Title: Connect to PhotosynQ
Version: 0.2.3
Authors@R: person("Sebastian", "Kuhlgert", email = "sebastian.kuhlgert@gmail.com", role = c("aut", "cre"))
Description: Connect R to the PhotosynQ platform (<https://photosynq.org>). It allows to login and logout, as well as receive project information and project data. Further it transforms the received JSON objects into a data frame, which can be used for the final data analysis.
License: MIT + file LICENCE
Encoding: UTF-8
Language: en-US
URL: https://github.com/Photosynq/PhotosynQ-R
BugReports: https://github.com/Photosynq/PhotosynQ-R/issues
Depends: R (>= 3.2.4)
Imports: httr (>= 1.4.0), getPass (>= 0.2-2)
NeedsCompilation: no
Packaged: 2021-07-12 20:44:27 UTC; kuhlgert
Author: Sebastian Kuhlgert [aut, cre]
Maintainer: Sebastian Kuhlgert <sebastian.kuhlgert@gmail.com>
Repository: CRAN
Date/Publication: 2021-07-13 14:50:07 UTC

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New package natcpp with initial version 0.1.0
Package: natcpp
Title: Fast C++ Primitives for the 'NeuroAnatomy Toolbox'
Version: 0.1.0
Authors@R: person(given = "Gregory", family = "Jefferis", role = c("aut", "cre"), email = "jefferis@gmail.com", comment = c(ORCID = "0000-0002-0587-9355"))
Description: Fast functions implemented in C++ via 'Rcpp' to support the 'NeuroAnatomy Toolbox' ('nat') ecosystem. These functions provide large speed-ups for basic manipulation of neuronal skeletons over pure R functions found in the 'nat' package. The expectation is that end users will not use this package directly, but instead the 'nat' package will automatically use routines from this package when it is available to enable large performance gains.
License: GPL (>= 3)
URL: https://github.com/natverse/natcpp
BugReports: https://github.com/natverse/natcpp/issues
Imports: Rcpp (>= 1.0.6)
Suggests: spelling, testthat (>= 3.0.0)
LinkingTo: Rcpp
Encoding: UTF-8
Language: en-GB
NeedsCompilation: yes
Packaged: 2021-07-12 18:45:16 UTC; jefferis
Author: Gregory Jefferis [aut, cre] (<https://orcid.org/0000-0002-0587-9355>)
Maintainer: Gregory Jefferis <jefferis@gmail.com>
Repository: CRAN
Date/Publication: 2021-07-13 14:50:02 UTC

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New package kldtools with initial version 1.0
Package: kldtools
Title: Kullback-Leibler Divergence and Other Tools to Analyze Frequencies
Version: 1.0
Date: 2021-07-12
Authors@R: c(person("Alexey", "Shipunov", role=c("cre"), email="dactylorhiza@gmail.com"), person("Kateryna", "Krykoniuk", role="aut"), person("Jasjeet", "Sekhon", role="ctb"))
Description: Most importantly, calculates Kullback-Leibler Divergence (KLD), Turing's perspective estimator and their confidence intervals.
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2021-07-12 09:21:51 UTC; alexey
Author: Alexey Shipunov [cre], Kateryna Krykoniuk [aut], Jasjeet Sekhon [ctb]
Maintainer: Alexey Shipunov <dactylorhiza@gmail.com>
Repository: CRAN
Date/Publication: 2021-07-13 14:30:02 UTC

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Package ipmr updated to version 0.0.3 with previous version 0.0.2 dated 2021-05-22

Title: Integral Projection Models
Description: Flexibly implements Integral Projection Models using a mathematical(ish) syntax. This package will not help with the vital rate modeling process, but will help convert those regression models into an IPM. 'ipmr' handles density dependence and environmental stochasticity, with a couple of options for implementing the latter. In addition, provides functions to avoid unintentional eviction of individuals from models. Additionally, provides model diagnostic tools, plotting functionality, stochastic/deterministic simulations, and analysis tools. Integral projection models are described in depth by Easterling et al. (2000) <doi:10.1890/0012-9658(2000)081[0694:SSSAAN]2.0.CO;2>, Merow et al. (2013) <doi:10.1111/2041-210X.12146>, Rees et al. (2014) <doi:10.1111/1365-2656.12178>, and Metcalf et al. (2015) <doi:10.1111/2041-210X.12405>. Williams et al. (2012) <doi:10.1890/11-2147.1> discuss the problem of unintentional eviction.
Author: Sam Levin [aut, cre] (<https://orcid.org/0000-0002-3289-9925>), Aldo Compagnoni [aut], Dylan Childs [aut], Sanne Evers [aut], Roberto Salguero-Gomez [aut], Tiffany Knight [aut]
Maintainer: Sam Levin <levisc8@gmail.com>

Diff between ipmr versions 0.0.2 dated 2021-05-22 and 0.0.3 dated 2021-07-13

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New package geckor with initial version 0.1.1
Package: geckor
Title: R Client for the 'CoinGecko' API
Version: 0.1.1
Authors@R: c( person("Sergey", "Mastitsky", role = c("aut", "cre"), email = "sergey@nextgamesolutions.com"), person("Next Game Solutions", role = c("cph")) )
Description: Collect the current and historical cryptocurrency market data using the public 'CoinGecko' API (<https://www.coingecko.com/en/api>).
License: MIT + file LICENSE
URL: https://github.com/next-game-solutions/geckor
BugReports: https://github.com/next-game-solutions/geckor/issues
Depends: R (>= 4.0)
Encoding: UTF-8
Suggests: covr, markdown, readr, rmarkdown, spelling, testthat (>= 3.0.0)
Language: en-US
Imports: dplyr, jsonlite, httr, knitr, lifecycle, magrittr, rlang, tibble, tidyr, tidyselect
VignetteBuilder: knitr
RdMacros: lifecycle
NeedsCompilation: no
Packaged: 2021-07-12 12:40:21 UTC; masti
Author: Sergey Mastitsky [aut, cre], Next Game Solutions [cph]
Maintainer: Sergey Mastitsky <sergey@nextgamesolutions.com>
Repository: CRAN
Date/Publication: 2021-07-13 14:40:05 UTC

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New package cubicBsplines with initial version 1.0.0
Package: cubicBsplines
Title: Computation of a Cubic B-Spline Basis and Its Derivatives
Date: 2021-07-11
Version: 1.0.0
Authors@R: person(given = "Philippe", family = "Lambert", role = c("aut", "cre"), email = "p.lambert@uliege.be", comment = "Université de Liège / Université catholique de Louvain (Belgium)")
Description: Computation of a cubic B-spline basis for arbitrary knots. It also provides the 1st and 2nd derivatives, as well as the integral of the basis elements. It is used by the author to fit penalized B-spline models, see e.g. Jullion, A. and Lambert, P. (2006) <doi:10.1016/j.csda.2006.09.027>, Lambert, P. and Eilers, P.H.C. (2009) <doi:10.1016/j.csda.2008.11.022> and, more recently, Lambert, P. (2021) <doi:10.1016/j.csda.2021.107250>. It is inspired by the algorithm developed by de Boor, C. (1977) <doi:10.1137/0714026>.
URL: http://www.statsoc.ulg.ac.be/
License: GPL-3
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2021-07-12 11:19:04 UTC; plambert
Author: Philippe Lambert [aut, cre] (Université de Liège / Université catholique de Louvain (Belgium))
Maintainer: Philippe Lambert <p.lambert@uliege.be>
Repository: CRAN
Date/Publication: 2021-07-13 14:30:04 UTC

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New package bcputility with initial version 0.1.0
Package: bcputility
Title: Wrapper for SQL Server bcp Utility
Version: 0.1.0
Authors@R: person("Thomas", "Roh", email = "thomas@roh.engineering", role = c("aut", "cre"))
Description: Provides functions to utilize a command line utility that does bulk inserts and exports from SQL Server databases.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: bcp Utility
Imports: data.table, DBI, odbc
NeedsCompilation: no
Packaged: 2021-07-12 19:28:24 UTC; troh
Author: Thomas Roh [aut, cre]
Maintainer: Thomas Roh <thomas@roh.engineering>
Repository: CRAN
Date/Publication: 2021-07-13 14:50:05 UTC

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Package holland updated to version 0.1.1-1 with previous version 0.1.0-6 dated 2021-06-22

Title: Statistics for Holland's Theory of Vocational Choice
Description: Offers a convenient way to compute parameters in the framework of the theory of vocational choice introduced by J.L. Holland, (1997). A comprehensive summary to this theory of vocational choice is given in Holland, J.L. (1997). Making vocational choices. A theory of vocational personalities and work environments. Lutz, FL: Psychological Assessment.
Author: Joerg-Henrik Heine [aut, cre, com], Florian Hartmann [rev, com], Bernhard Ertl [rev, com], Christian Tarnai [com, ths]
Maintainer: Joerg-Henrik Heine <jhheine@googlemail.com>

Diff between holland versions 0.1.0-6 dated 2021-06-22 and 0.1.1-1 dated 2021-07-13

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Package gtsummary updated to version 1.4.2 with previous version 1.4.1 dated 2021-05-19

Title: Presentation-Ready Data Summary and Analytic Result Tables
Description: Creates presentation-ready tables summarizing data sets, regression models, and more. The code to create the tables is concise and highly customizable. Data frames can be summarized with any function, e.g. mean(), median(), even user-written functions. Regression models are summarized and include the reference rows for categorical variables. Common regression models, such as logistic regression and Cox proportional hazards regression, are automatically identified and the tables are pre-filled with appropriate column headers.
Author: Daniel D. Sjoberg [aut, cre] (<https://orcid.org/0000-0003-0862-2018>), Michael Curry [aut] (<https://orcid.org/0000-0002-0261-4044>), Margie Hannum [aut] (<https://orcid.org/0000-0002-2953-0449>), Joseph Larmarange [aut] (<https://orcid.org/0000-0001-7097-700X>), Karissa Whiting [aut] (<https://orcid.org/0000-0002-4683-1868>), Emily C. Zabor [aut] (<https://orcid.org/0000-0002-1402-4498>), Esther Drill [ctb] (<https://orcid.org/0000-0002-3315-4538>), Jessica Flynn [ctb] (<https://orcid.org/0000-0001-8310-6684>), Jessica Lavery [ctb] (<https://orcid.org/0000-0002-2746-5647>), Stephanie Lobaugh [ctb], Gustavo Zapata Wainberg [ctb] (<https://orcid.org/0000-0002-2524-3637>)
Maintainer: Daniel D. Sjoberg <danield.sjoberg@gmail.com>

Diff between gtsummary versions 1.4.1 dated 2021-05-19 and 1.4.2 dated 2021-07-13

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Package TreeDist updated to version 2.1.1 with previous version 2.1.0 dated 2021-07-12

Title: Calculate and Map Distances Between Phylogenetic Trees
Description: Implements measures of tree similarity, including information-based generalized Robinson-Foulds distances (Phylogenetic Information Distance, Clustering Information Distance, Matching Split Information Distance; Smith, 2020) <doi:10.1093/bioinformatics/btaa614>; Jaccard-Robinson-Foulds distances (Bocker et al. 2013) <doi:10.1007/978-3-642-40453-5_13>, including the Nye et al. (2006) metric <doi:10.1093/bioinformatics/bti720>; the Matching Split Distance (Bogdanowicz & Giaro 2012) <doi:10.1109/TCBB.2011.48>; Maximum Agreement Subtree distances; the Kendall-Colijn (2016) distance <doi:10.1093/molbev/msw124>, and the Nearest Neighbour Interchange (NNI) distance, approximated per Li et al. (1996) <doi:10.1007/3-540-61332-3_168>. Includes tools for visualizing mappings of tree space, for calculating the median of sets of trees, and for computing the information content of trees and splits.
Author: Martin R. Smith [aut, cre, cph, prg] (<https://orcid.org/0000-0001-5660-1727>), Roy Jonker [prg, cph], Yong Yang [ctb, cph], Yi Cao [ctb, cph]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

Diff between TreeDist versions 2.1.0 dated 2021-07-12 and 2.1.1 dated 2021-07-13

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Package RcppCWB updated to version 0.4.2 with previous version 0.4.0 dated 2021-06-25

Title: 'Rcpp' Bindings for the 'Corpus Workbench' ('CWB')
Description: 'Rcpp' Bindings for the C code of the 'Corpus Workbench' ('CWB'), an indexing and query engine to efficiently analyze large corpora (<http://cwb.sourceforge.net>). 'RcppCWB' is licensed under the GNU GPL-3, in line with the GPL-3 license of the 'CWB' (<https://www.r-project.org/Licenses/GPL-3>). The 'CWB' relies on 'pcre' (BSD license, see <http://www.pcre.org/licence.txt>) and 'GLib' (LGPL license, see <https://www.gnu.org/licenses/lgpl-3.0.en.html>). See the file LICENSE.note for further information. The package includes modified code of the 'rcqp' package (GPL-2, see <https://cran.r-project.org/package=rcqp>). The original work of the authors of the 'rcqp' package is acknowledged with great respect, and they are listed as authors of this package. To achieve cross-platform portability (including Windows), using 'Rcpp' for wrapper code is the approach used by 'RcppCWB'.
Author: Andreas Blaette [aut, cre], Bernard Desgraupes [aut], Sylvain Loiseau [aut], Oliver Christ [ctb], Bruno Maximilian Schulze [ctb], Stefan Evert [ctb], Arne Fitschen [ctb], Jeroen Ooms [ctb], Marius Bertram [ctb]
Maintainer: Andreas Blaette <andreas.blaette@uni-due.de>

Diff between RcppCWB versions 0.4.0 dated 2021-06-25 and 0.4.2 dated 2021-07-13

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Package mombf updated to version 3.0.4 with previous version 3.0.3 dated 2021-06-01

Title: Bayesian Model Selection and Averaging for Non-Local and Local Priors
Description: Bayesian model selection and averaging for regression and mixtures for non-local and selected local priors.
Author: David Rossell, John D. Cook, Donatello Telesca, P. Roebuck, Oriol Abril
Maintainer: David Rossell <rosselldavid@gmail.com>

Diff between mombf versions 3.0.3 dated 2021-06-01 and 3.0.4 dated 2021-07-13

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Package MIIVsem updated to version 0.5.8 with previous version 0.5.7 dated 2021-07-07

Title: Model Implied Instrumental Variable (MIIV) Estimation of Structural Equation Models
Description: Functions for estimating structural equation models using instrumental variables.
Author: Zachary Fisher [aut, cre], Kenneth Bollen [aut], Kathleen Gates [aut], Mikko Rönkkö [aut]
Maintainer: Zachary Fisher <fish.zachary@gmail.com>

Diff between MIIVsem versions 0.5.7 dated 2021-07-07 and 0.5.8 dated 2021-07-13

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Package doBy updated to version 4.6.11 with previous version 4.6.10 dated 2021-04-29

Title: Groupwise Statistics, LSmeans, Linear Contrasts, Utilities
Description: Contains: 1) Facilities for working with grouped data: 'do' something to data stratified 'by' some variables. 2) LSmeans (least-squares means), general linear contrasts. 3) Miscellaneous other utilities.
Author: Søren Højsgaard <sorenh@math.aau.dk> and Ulrich Halekoh <uhalekoh@health.sdu.dk>
Maintainer: Søren Højsgaard <sorenh@math.aau.dk>

Diff between doBy versions 4.6.10 dated 2021-04-29 and 4.6.11 dated 2021-07-13

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Package collapse updated to version 1.6.4 with previous version 1.6.2 dated 2021-07-04

Title: Advanced and Fast Data Transformation
Description: A C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, flexible and parsimonious to code with, class-agnostic and programmer friendly. It is well integrated with base R, 'dplyr' / (grouped) 'tibble', 'data.table', 'plm' (panel-series and data frames), 'sf' data frames, and non-destructively handles other matrix or data frame based classes (such as 'ts', 'xts' / 'zoo', 'timeSeries', 'tsibble', 'tibbletime' etc.) --- Key Features: --- (1) Advanced statistical programming: A full set of fast statistical functions supporting grouped and weighted computations on vectors, matrices and data frames. Fast and programmable grouping, ordering, unique values / rows, factor generation and interactions. Fast and flexible functions for data manipulation and data object conversions. (2) Advanced aggregation: Fast and easy multi-data-type, multi-function, weighted, parallelized and fully customized data aggregation. (3) Advanced transformations: Fast row / column arithmetic, (grouped) replacing and sweeping out of statistics, (grouped, weighted) scaling / standardizing, between (averaging) and (quasi-)within (centering / demeaning) transformations, higher-dimensional centering (i.e. multiple fixed effects transformations), linear prediction / partialling-out, linear model fitting and testing. (4) Advanced time-computations: Fast (sequences of) lags / leads, and (lagged / leaded, iterated, quasi-, log-) differences, (compounded) growth rates, and cumulative sums on (unordered, irregular) time series and panel data. Multivariate auto-, partial- and cross-correlation functions for panel data. Panel data to (ts-)array conversions. (5) List processing: (Recursive) list search / identification, splitting, extraction / subsetting, data-apply, and generalized recursive row-binding / unlisting in 2D. (6) Advanced data exploration: Fast (grouped, weighted, panel-decomposed) summary statistics for complex multilevel / panel data.
Author: Sebastian Krantz [aut, cre], Matt Dowle [ctb], Arun Srinivasan [ctb], Laurent Berge [ctb], Dirk Eddelbuettel [ctb], Josh Pasek [ctb], Kevin Tappe [ctb], R Core Team and contributors worldwide [ctb], Martyn Plummer [cph], 1999-2016 The R Core Team [cph]
Maintainer: Sebastian Krantz <sebastian.krantz@graduateinstitute.ch>

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Package mrbayes updated to version 0.4.0 with previous version 0.3.0 dated 2021-04-01

Title: Bayesian Summary Data Models for Mendelian Randomization Studies
Description: Bayesian estimation of inverse variance weighted (IVW), Burgess et al. (2013) <doi:10.1002/gepi.21758>, and MR-Egger, Bowden et al. (2015) <doi:10.1093/ije/dyv080>, summary data models for Mendelian randomization analyses.
Author: Okezie Uche-Ikonne [aut, cre] (<https://orcid.org/0000-0002-8461-8099>), Frank Dondelinger [aut] (<https://orcid.org/0000-0003-1816-6300>), Tom Palmer [aut] (<https://orcid.org/0000-0003-4655-4511>)
Maintainer: Okezie Uche-Ikonne <okezieikonne@gmail.com>

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Package MPTinR updated to version 1.14.1 with previous version 1.13.0 dated 2020-08-26

Title: Analyze Multinomial Processing Tree Models
Description: Provides a user-friendly way for the analysis of multinomial processing tree (MPT) models (e.g., Riefer, D. M., and Batchelder, W. H. [1988]. Multinomial modeling and the measurement of cognitive processes. Psychological Review, 95, 318-339) for single and multiple datasets. The main functions perform model fitting and model selection. Model selection can be done using AIC, BIC, or the Fisher Information Approximation (FIA) a measure based on the Minimum Description Length (MDL) framework. The model and restrictions can be specified in external files or within an R script in an intuitive syntax or using the context-free language for MPTs. The 'classical' .EQN file format for model files is also supported. Besides MPTs, this package can fit a wide variety of other cognitive models such as SDT models (see fit.model). It also supports multicore fitting and FIA calculation (using the snowfall package), can generate or bootstrap data for simulations, and plot predicted versus observed data.
Author: Henrik Singmann [aut, cre], David Kellen [aut], Quentin Gronau [aut], Christian Mueller [ctb], Akhil S Bhel [ctb]
Maintainer: Henrik Singmann <singmann@gmail.com>

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New package MatTransMix with initial version 0.1.14
Package: MatTransMix
Version: 0.1.14
Date: 2021-07-12
Title: Clustering with Matrix Gaussian and Matrix Transformation Mixture Models
Authors@R: c(person("Xuwen", "Zhu", role = c("aut", "cre"), email = "xzhu20@cba.ua.edu"), person("Volodymyr", "Melnykov", role = "aut"), person("Shuchismita", "Sarkar", role = "ctb"), person("Michael", "Hutt", role = c("ctb", "cph")), person("Stephen", "Moshier", role = c("ctb", "cph")), person("Rouben", "Rostamian", role = c("ctb", "cph")), person("Carl Edward", "Rasmussen", role = c("ctb", "cph")), person("Dianne", "Cook", role = c("ctb", "cph")))
Depends: R (>= 3.0.0)
LazyLoad: yes
LazyData: no
Description: Provides matrix Gaussian mixture models, matrix transformation mixture models and their model-based clustering results. The parsimonious models of the mean matrices and variance covariance matrices are implemented with a total of 196 variations.
License: GPL (>= 2)
Imports: mvtnorm
Packaged: 2021-07-12 21:21:48 UTC; root
Author: Xuwen Zhu [aut, cre], Volodymyr Melnykov [aut], Shuchismita Sarkar [ctb], Michael Hutt [ctb, cph], Stephen Moshier [ctb, cph], Rouben Rostamian [ctb, cph], Carl Edward Rasmussen [ctb, cph], Dianne Cook [ctb, cph]
Maintainer: Xuwen Zhu <xzhu20@cba.ua.edu>
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2021-07-13 12:00:16 UTC

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Package grpsel updated to version 1.1.1 with previous version 1.1.0 dated 2021-06-29

Title: Group Subset Selection
Description: Provides tools for sparse regression modelling with grouped predictors using the group subset selection penalty. Uses coordinate descent and local search algorithms to rapidly deliver near optimal estimates. The group subset penalty can be combined with a group lasso or ridge penalty for added shrinkage. Linear and logistic regression are supported, as are overlapping groups.
Author: Ryan Thompson [aut, cre] (<https://orcid.org/0000-0002-9002-0448>)
Maintainer: Ryan Thompson <ryan.thompson@monash.edu>

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Package gdalcubes updated to version 0.4.0 with previous version 0.3.1 dated 2020-08-27

Title: Earth Observation Data Cubes from Satellite Image Collections
Description: Processing collections of Earth observation images as on-demand multispectral, multitemporal raster data cubes. Users define cubes by spatiotemporal extent, resolution, and spatial reference system and let 'gdalcubes' automatically apply cropping, reprojection, and resampling using the 'Geospatial Data Abstraction Library' ('GDAL'). Implemented functions on data cubes include reduction over space and time, applying arithmetic expressions on pixel band values, moving window aggregates over time, filtering by space, time, bands, and predicates on pixel values, exporting data cubes as 'netCDF' or 'GeoTIFF' files, and plotting. The package implements lazy evaluation and multithreading. All computational parts are implemented in C++, linking to the 'GDAL', 'netCDF', 'CURL', and 'SQLite' libraries. See Appel and Pebesma (2019) <doi:10.3390/data4030092> for further details.
Author: Marius Appel [aut, cre] (<https://orcid.org/0000-0001-5281-3896>), Edzer Pebesma [ctb] (<https://orcid.org/0000-0001-8049-7069>), Roger Bivand [ctb], Lewis Van Winkle [cph], Ole Christian Eidheim [cph], Howard Hinnant [cph], Adrian Colomitchi [cph], Florian Dang [cph], Paul Thompson [cph], Tomasz Kamiński [cph], Dropbox, Inc. [cph]
Maintainer: Marius Appel <marius.appel@uni-muenster.de>

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Package emayili updated to version 0.4.12 with previous version 0.4.11 dated 2021-06-25

Title: Send Email Messages
Description: A light, simple tool for sending emails with minimal dependencies.
Author: Andrew B. Collier [aut, cre], Matt Dennis [ctb], Gerard Walsh [ctb], Antoine Bichat [ctb] (<https://orcid.org/0000-0001-6599-7081>), Daniel Fahey [ctb], Johann R. Kleinbub [ctb], Panagiotis Moulos [ctb]
Maintainer: Andrew B. Collier <andrew.b.collier@gmail.com>

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Package BayesTools updated to version 0.1.1 with previous version 0.1.0 dated 2021-07-02

Title: Tools for Bayesian Analyses
Description: Provides tools for conducting Bayesian analyses. The package contains functions for creating a wide range of prior distribution objects, mixing posterior samples from 'JAGS' and 'Stan' models, plotting posterior distributions, and etc... The tools for working with prior distribution span from visualization, generating 'JAGS' and 'bridgesampling' syntax to basic functions such as rng, quantile, and distribution functions.
Author: František Bartoš [aut, cre] (<https://orcid.org/0000-0002-0018-5573>)
Maintainer: František Bartoš <f.bartos96@gmail.com>

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New package blockcluster with initial version 4.5.0
Package: blockcluster
Title: Co-Clustering Package for Binary, Categorical, Contingency and Continuous Data-Sets
Version: 4.5.0
Encoding: UTF-8
Date: 2021-07-07
Authors@R: c( person("Serge", "Iovleff", role = c("aut","cre"), email = "Serge.Iovleff@stkpp.org") , person("Parmeet", "Singh Bhatia", role = "aut", email = "bhatia.parmeet@gmail.com") , person("Josselin", "Demont", role = "ctb") , person("Vincent", "Brault", role = "ctb", email = "vincent.brault@imag.fr") , person("Vincent", "Kubicki", role = "ctb", email = "vincent.kubicki@laposte.net") , person("Gerard", "Goavert", role = "ctb") , person("Christophe", "Biernacki", role = "ctb") , person("Gilles", "Celeux", role = "ctb"))
Copyright: Inria
Description: Simultaneous clustering of rows and columns, usually designated by biclustering, co-clustering or block clustering, is an important technique in two way data analysis. It consists of estimating a mixture model which takes into account the block clustering problem on both the individual and variables sets. The 'blockcluster' package provides a bridge between the C++ core library build on top of the 'STK++' library, and the R statistical computing environment. This package allows to co-cluster binary <doi:10.1016/j.csda.2007.09.007>, contingency <doi:10.1080/03610920903140197>, continuous <doi:10.1007/s11634-013-0161-3> and categorical data-sets <doi:10.1007/s11222-014-9472-2>. It also provides utility functions to visualize the results. This package may be useful for various applications in fields of Data mining, Information retrieval, Biology, computer vision and many more. More information about the project and comprehensive tutorial can be found on the link mentioned in URL.
License: GPL (>= 3)
URL: https://gforge.inria.fr/projects/cocluster/
BugReports: https://gforge.inria.fr/forum/forum.php?forum_id=11190&group_id=3679
LazyLoad: yes
Depends: R (>= 3.0.2), rtkore (>= 1.5.5)
Imports: methods
LinkingTo: Rcpp
SystemRequirements: GNU make
Collate: 'coclusterStrategy.R' 'RCocluster.R' 'optionclasses.R' 'cocluster.R' 'coclusterBinary.R' 'coclusterCategorical.R' 'coclusterContingency.R' 'coclusterContinuous.R' 'onattach.R'
NeedsCompilation: yes
Packaged: 2021-07-10 19:29:51 UTC; iovleff
Author: Serge Iovleff [aut, cre], Parmeet Singh Bhatia [aut], Josselin Demont [ctb], Vincent Brault [ctb], Vincent Kubicki [ctb], Gerard Goavert [ctb], Christophe Biernacki [ctb], Gilles Celeux [ctb]
Maintainer: Serge Iovleff <Serge.Iovleff@stkpp.org>
Repository: CRAN
Date/Publication: 2021-07-13 12:00:12 UTC

More information about blockcluster at CRAN
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New package BayesPPD with initial version 1.0.1
Package: BayesPPD
Title: Bayesian Power Prior Design
Version: 1.0.1
Authors@R: c( person(given = "Yueqi", family = "Shen", role = c("cre"), email = "ys137@live.unc.edu"), person(given = "Matthew A.", family = "Psioda", role = c("aut"), email = "matt_psioda@unc.edu"), person(given = "Joseph G.", family = "Ibrahim", role = c("aut"), email = "ibrahim@bios.unc.edu"))
Description: Bayesian power/type I error calculation and model fitting using the power prior and the normalized power prior for generalized linear models. The Bayesian clinical trial design methodology is described in Chen et al. (2011) <doi:10.1111/j.1541-0420.2011.01561.x>, and Psioda and Ibrahim (2019) <doi:10.1093/biostatistics/kxy009>. The normalized power prior is described in Duan et al. (2006) <doi:10.1002/env.752> and Ibrahim et al. (2015) <doi:10.1002/sim.6728>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: Rcpp, RcppNumerical
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, RcppNumerical
NeedsCompilation: yes
Packaged: 2021-07-02 04:44:25 UTC; angie
Author: Yueqi Shen [cre], Matthew A. Psioda [aut], Joseph G. Ibrahim [aut]
Maintainer: Yueqi Shen <ys137@live.unc.edu>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2021-07-13 12:00:23 UTC

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Package wrProteo updated to version 1.4.3 with previous version 1.4.2 dated 2021-07-05

Title: Proteomics Data Analysis Functions
Description: Data analysis of proteomics experiments by mass spectrometry is supported by this collection of functions mostly dedicated to the analysis of (bottom-up) quantitative (XIC) data. Fasta-formatted proteomes (eg from UniProt Consortium <doi:10.1093/nar/gky1049>) can be read with automatic parsing and multiple annotation types (like species origin, abbreviated gene names, etc) extracted. Quantitative proteomics measurements frequently contain multiple NA values, due to physical absence of given peptides in some samples, limitations in sensitivity or other reasons. The functions provided here help to inspect graphically the data to investigate the nature of NA-values via their respective replicate measurements and to help/confirm the choice of NA-replacement by low random values. Dedicated filtering and statistical testing using the framework of package 'limma' <doi:10.18129/B9.bioc.limma> can be run, enhanced by multiple rounds of NA-replacements to provide robustness towards rare stochastic events. Multi-species samples, as frequently used in benchmark-tests (eg Navarro et al 2016 <doi:10.1038/nbt.3685>, Ramus et al 2016 <doi:10.1016/j.jprot.2015.11.011>), can be run with special options separating the data into sub-groups during normalization and testing. As example the data-set from Ramus et al 2016 <doi:10.1016/j.jprot.2015.11.011>) is provided quantified by MaxQuant (Tyanova et al 2016 <doi:10.1038/nprot.2016.136>), ProteomeDiscoverer, OpenMS (<doi:10.1038/nmeth.3959>) and Proline (Bouyssie et al 2020 <doi:10.1093/bioinformatics/btaa118>). Subsequently, ROC curves (Hand and Till 2001 <doi:10.1023/A:1010920819831>) can be constructed to compare multiple analysis approaches.
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@gmail.com>

Diff between wrProteo versions 1.4.2 dated 2021-07-05 and 1.4.3 dated 2021-07-13

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Package scholar updated to version 0.2.2 with previous version 0.2.1 dated 2021-04-28

Title: Analyse Citation Data from Google Scholar
Description: Provides functions to extract citation data from Google Scholar. Convenience functions are also provided for comparing multiple scholars and predicting future h-index values.
Author: Guangchuang Yu [aut, cre] (<https://orcid.org/0000-0002-6485-8781>), James Keirstead [aut], Gregory Jefferis [ctb], Gordon Getzinger [ctb], Jorge Cimentada [ctb], Max Czapanskiy [ctb], Dominique Makowski [ctb]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package pullword updated to version 0.3 with previous version 0.2 dated 2016-07-22

Title: R Interface to Pullword Service
Description: R Interface to Pullword Service for natural language processing in Chinese. It enables users to extract valuable words from text by deep learning models. For more details please visit the official site (in Chinese) <http://www.pullword.com/>.
Author: Tong He <hetong007@gmail.com>
Maintainer: Tong He <hetong007@gmail.com>

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Package modelStudio updated to version 3.0.0 with previous version 2.1.2 dated 2021-04-20

Title: Interactive Studio for Explanatory Model Analysis
Description: Automate the explanatory analysis of machine learning predictive models. Generate advanced interactive model explanations in the form of a serverless HTML site with only one line of code. This tool is model-agnostic, therefore compatible with most of the black-box predictive models and frameworks. The main function computes various (instance and model-level) explanations and produces a customisable dashboard, which consists of multiple panels for plots with their short descriptions. Easily save the dashboard and share it with others. Tools for Explanatory Model Analysis unite with tools for Exploratory Data Analysis to give a broad overview of the model behavior.
Author: Hubert Baniecki [aut, cre] (<https://orcid.org/0000-0001-6661-5364>), Przemyslaw Biecek [aut] (<https://orcid.org/0000-0001-8423-1823>), Piotr Piatyszek [ctb]
Maintainer: Hubert Baniecki <hbaniecki@gmail.com>

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Package taxa updated to version 0.4.0 with previous version 0.3.4 dated 2020-04-29

Title: Classes for Storing and Manipulating Taxonomic Data
Description: Provides classes for storing and manipulating taxonomic data. Most of the classes can be treated like base R vectors (e.g. can be used in tables as columns and can be named). Vectorized classes can store taxon names and authorities, taxon IDs from databases, taxon ranks, and other types of information. More complex classes are provided to store taxonomic trees and user-defined data associated with them.
Author: Scott Chamberlain [aut] (<https://orcid.org/0000-0003-1444-9135>), Zachary Foster [aut, cre] (<https://orcid.org/0000-0002-5075-0948>)
Maintainer: Zachary Foster <zacharyfoster1989@gmail.com>

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Package gfoRmula updated to version 0.3.2 with previous version 0.3.1 dated 2020-03-23

Title: Parametric G-Formula
Description: Implements the parametric g-formula algorithm of Robins (1986) <doi:10.1016/0270-0255(86)90088-6>. The g-formula can be used to estimate the causal effects of hypothetical time-varying treatment interventions on the mean or risk of an outcome from longitudinal data with time-varying confounding. This package allows: 1) binary or continuous/multi-level time-varying treatments; 2) different types of outcomes (survival or continuous/binary end of follow-up); 3) data with competing events or truncation by death and loss to follow-up and other types of censoring events; 4) different options for handling competing events in the case of survival outcomes; 5) a random measurement/visit process; 6) joint interventions on multiple treatments; and 7) general incorporation of a priori knowledge of the data structure.
Author: Victoria Lin [aut] (V. Lin and S. McGrath made equal contributions), Sean McGrath [aut, cre] (<https://orcid.org/0000-0002-7281-3516>, V. Lin and S. McGrath made equal contributions), Zilu Zhang [aut], Roger W. Logan [aut], Lucia C. Petito [aut], Jessica G. Young [aut] (<https://orcid.org/0000-0002-2758-6932>, M.A. Hernán and J.G. Young made equal contributions), Miguel A. Hernán [aut] (M.A. Hernán and J.G. Young made equal contributions), 2019 The President and Fellows of Harvard College [cph]
Maintainer: Sean McGrath <sean_mcgrath@g.harvard.edu>

Diff between gfoRmula versions 0.3.1 dated 2020-03-23 and 0.3.2 dated 2021-07-13

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Package ndtv (with last version 0.13.0) was removed from CRAN

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

2019-05-22 0.13.0
2018-10-08 0.12.3
2018-05-13 0.12.2
2016-05-06 0.10.0
2016-02-23 0.9.0
2015-12-02 0.8.0
2015-10-15 0.7.0
2015-04-30 0.6.1
2014-01-31 0.5.1
2013-12-04 0.4.0
2013-10-25 0.3
2013-06-01 0.2

Permanent link
Package mauricer (with last version 2.3) was removed from CRAN

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

2020-10-31 2.3
2020-08-10 2.1

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Package beastier (with last version 2.4.2) was removed from CRAN

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

2021-06-05 2.4.2
2021-05-23 2.4
2020-10-30 2.2.1
2020-10-16 2.2
2020-08-07 2.1.3

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Package mcbette (with last version 1.13) was removed from CRAN

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

2020-12-05 1.13
2020-11-16 1.12

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Package beautier (with last version 2.6) was removed from CRAN

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

2021-05-23 2.6
2021-05-22 2.5.2
2020-10-16 2.4
2020-08-05 2.3.7

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Package babette (with last version 2.2) was removed from CRAN

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

2020-11-06 2.2
2020-08-11 2.1.4

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Package esDesign updated to version 1.0.3 with previous version 1.0.2 dated 2018-11-23

Title: Adaptive Enrichment Designs with Sample Size Re-Estimation
Description: Software of 'esDesign' is developed to implement the adaptive enrichment designs with sample size re-estimation presented in Lin et al. (2021) <doi: 10.1016/j.cct.2020.106216>. In details, three-proposed trial designs are provided, including the AED1-SSR (or ES1-SSR), AED2-SSR (or ES2-SSR) and AED3-SSR (or ES3-SSR). In addition, this package also contains several widely used adaptive designs, such as the Marker Sequential Test (MaST) design proposed Freidlin et al. (2014) <doi:10.1177/1740774513503739>, the adaptive enrichment designs without early stopping (AED or ES), the sample size re-estimation procedure (SSR) based on the conditional power proposed by Proschan and Hunsberger (1995), and some useful functions. In details, we can calculate the futility and/or efficacy stopping boundaries, the sample size required, calibrate the value of the threshold of the difference between subgroup-specific test statistics, conduct the simulation studies in AED, SSR, AED1-SSR, AED2-SSR and AED3-SSR.
Author: Zhao Yang, Ruitao Lin, Guosheng Yin and Ying Yuan
Maintainer: Zhao Yang <yangz98@connect.hku.hk>

Diff between esDesign versions 1.0.2 dated 2018-11-23 and 1.0.3 dated 2021-07-13

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Package wk updated to version 0.5.0 with previous version 0.4.1 dated 2021-03-16

Title: Lightweight Well-Known Geometry Parsing
Description: Provides a minimal R and C++ API for parsing well-known binary and well-known text representation of geometries to and from R-native formats. Well-known binary is compact and fast to parse; well-known text is human-readable and is useful for writing tests. These formats are only useful in R if the information they contain can be accessed in R, for which high-performance functions are provided here.
Author: Dewey Dunnington [aut, cre] (<https://orcid.org/0000-0002-9415-4582>), Edzer Pebesma [aut] (<https://orcid.org/0000-0001-8049-7069>)
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

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Package styler updated to version 1.5.1 with previous version 1.4.1 dated 2021-03-30

Title: Non-Invasive Pretty Printing of R Code
Description: Pretty-prints R code without changing the user's formatting intent.
Author: Kirill Müller [aut], Lorenz Walthert [cre, aut]
Maintainer: Lorenz Walthert <lorenz.walthert@icloud.com>

Diff between styler versions 1.4.1 dated 2021-03-30 and 1.5.1 dated 2021-07-13

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Package rdrobust updated to version 1.0.4 with previous version 1.0.3 dated 2021-07-05

Title: Robust Data-Driven Statistical Inference in Regression-Discontinuity Designs
Description: Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust() to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection for the different procedures implemented, and rdplot() to conduct exploratory data analysis (RD plots).
Author: Sebastian Calonico <sebastian.calonico@columbia.edu>, Matias D. Cattaneo <cattaneo@princeton.edu>, Max H. Farrell <max.farrell@chicagobooth.edu>, Rocio Titiunik <titiunik@princeton.edu>
Maintainer: Sebastian Calonico <sebastian.calonico@columbia.edu>

Diff between rdrobust versions 1.0.3 dated 2021-07-05 and 1.0.4 dated 2021-07-13

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Package poismf updated to version 0.3.1 with previous version 0.3.0-1 dated 2021-05-08

Title: Factorization of Sparse Counts Matrices Through Poisson Likelihood
Description: Creates a low-rank factorization of a sparse counts matrix by maximizing Poisson likelihood with l1/l2 regularization with all non-negative latent factors (e.g. for recommender systems or topic modeling) (Cortes, (2018) <arXiv:1811.01908>). Similar to hierarchical Poisson factorization, but follows an optimization-based approach with regularization instead of a hierarchical structure, and is fit through gradient-based methods instead of variational inference.
Author: David Cortes [aut, cre, cph], Jean-Sebastien Roy [cph], Stephen Nash [cph]
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

Diff between poismf versions 0.3.0-1 dated 2021-05-08 and 0.3.1 dated 2021-07-13

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Package Numero updated to version 1.8.1 with previous version 1.8.0 dated 2021-02-11

Title: Statistical Framework to Define Subgroups in Complex Datasets
Description: High-dimensional datasets that do not exhibit a clear intrinsic clustered structure pose a challenge to conventional clustering algorithms. For this reason, we developed an unsupervised framework that helps scientists to better subgroup their datasets based on visual cues, please see Gao S, Mutter S, Casey A, Makinen V-P (2019) Numero: a statistical framework to define multivariable subgroups in complex population-based datasets, Int J Epidemiology, 48:369-37, <doi:10.1093/ije/dyy113>. The framework includes the necessary functions to construct a self-organizing map of the data, to evaluate the statistical significance of the observed data patterns, and to visualize the results.
Author: Song Gao [aut], Stefan Mutter [aut], Aaron E. Casey [aut], Ville-Petteri Makinen [aut, cre]
Maintainer: Ville-Petteri Makinen <vpmakine@gmail.com>

Diff between Numero versions 1.8.0 dated 2021-02-11 and 1.8.1 dated 2021-07-13

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Package isoband updated to version 0.2.5 with previous version 0.2.4 dated 2021-03-03

Title: Generate Isolines and Isobands from Regularly Spaced Elevation Grids
Description: A fast C++ implementation to generate contour lines (isolines) and contour polygons (isobands) from regularly spaced grids containing elevation data.
Author: Claus O. Wilke [aut, cre] (<https://orcid.org/0000-0002-7470-9261>), Thomas Lin Pedersen [aut] (<https://orcid.org/0000-0002-5147-4711>), testthat and Catch authors [ctb] (testthat C++ testing code)
Maintainer: Claus O. Wilke <wilke@austin.utexas.edu>

Diff between isoband versions 0.2.4 dated 2021-03-03 and 0.2.5 dated 2021-07-13

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Package iNZightTools updated to version 1.11.2 with previous version 1.11.1 dated 2021-06-30

Title: Tools for 'iNZight'
Description: Provides a collection of wrapper functions for common variable and dataset manipulation workflows primarily used by 'iNZight', a graphical user interface providing easy exploration and visualisation of data for students of statistics, available in both desktop and online versions. Additionally, many of the functions return the 'tidyverse' code used to obtain the result in an effort to bridge the gap between GUI and coding.
Author: Tom Elliott [aut, cre] (<https://orcid.org/0000-0002-7815-6318>), Christoph Knopf [ctb], Akshay Gupta [ctb], Owen Jin [aut] (Tidyverse variable/data manipulation functions), Lushi Cai [ctb], Yiwen He [aut] (Dates/times and dataset manipulation), Daniel Barnett [aut] (Data validation)
Maintainer: Tom Elliott <tom.elliott@auckland.ac.nz>

Diff between iNZightTools versions 1.11.1 dated 2021-06-30 and 1.11.2 dated 2021-07-13

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