Wed, 21 Dec 2022

Package WeMix updated to version 3.3.0 with previous version 3.2.4 dated 2022-10-05

Title: Weighted Mixed-Effects Models Using Multilevel Pseudo Maximum Likelihood Estimation
Description: Run mixed-effects models that include weights at every level. The WeMix package fits a weighted mixed model, also known as a multilevel, mixed, or hierarchical linear model (HLM). The weights could be inverse selection probabilities, such as those developed for an education survey where schools are sampled probabilistically, and then students inside of those schools are sampled probabilistically. Although mixed-effects models are already available in R, WeMix is unique in implementing methods for mixed models using weights at multiple levels. Both linear and logit models are supported. Models may have up to three levels.
Author: Emmanuel Sikali [pdr], Paul Bailey [aut, cre], Claire Kelley [aut], Trang Nguyen [aut], Huade Huo [aut], Eric Buehler [ctb], Christian Kjeldsen [ctb]
Maintainer: Paul Bailey <pbailey@air.org>

Diff between WeMix versions 3.2.4 dated 2022-10-05 and 3.3.0 dated 2022-12-21

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Package textrecipes updated to version 1.0.2 with previous version 1.0.1 dated 2022-10-05

Title: Extra 'Recipes' for Text Processing
Description: Converting text to numerical features requires specifically created procedures, which are implemented as steps according to the 'recipes' package. These steps allows for tokenization, filtering, counting (tf and tfidf) and feature hashing.
Author: Emil Hvitfeldt [aut, cre]
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>

Diff between textrecipes versions 1.0.1 dated 2022-10-05 and 1.0.2 dated 2022-12-21

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Package spOccupancy updated to version 0.5.2 with previous version 0.5.1 dated 2022-12-08

Title: Single-Species, Multi-Species, and Integrated Spatial Occupancy Models
Description: Fits single-species, multi-species, and integrated non-spatial and spatial occupancy models using Markov Chain Monte Carlo (MCMC). Models are fit using Polya-Gamma data augmentation detailed in Polson, Scott, and Windle (2013) <doi:10.1080/01621459.2013.829001>. Spatial models are fit using either Gaussian processes or Nearest Neighbor Gaussian Processes (NNGP) for large spatial datasets. Details on NNGP models are given in Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091> and Finley, Datta, and Banerjee (2020) <arXiv:2001.09111>. Provides functionality for data integration of multiple single-species occupancy data sets using a joint likelihood framework. Details on data integration are given in Miller, Pacifici, Sanderlin, and Reich (2019) <doi:10.1111/2041-210X.13110>. Details on single-species and multi-species models are found in MacKenzie, Nichols, Lachman, Droege, Royle, and Langtimm (2002) <doi:10.1890/0012-9658(2002)083[2 [...truncated...]
Author: Jeffrey Doser [aut, cre], Andrew Finley [aut], Marc Kery [ctb]
Maintainer: Jeffrey Doser <doserjef@msu.edu>

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Package rocbc updated to version 0.3.0 with previous version 0.2.0 dated 2022-11-15

Title: Statistical Inference for Box-Cox Based Receiver Operating Characteristic Curves
Description: Generation of Box-Cox based ROC curves and several aspects of inferences and hypothesis testing. Can be used when inferences for one biomarker (Bantis LE, Nakas CT, Reiser B. (2018) <doi:10.1002/bimj.201700107>) are of interest or when comparisons of two correlated biomarkers (Bantis LE, Nakas CT, Reiser B. (2021) <doi:10.1002/bimj.202000128>) are of interest. Provides inferences and comparisons around the AUC, the Youden index, the sensitivity at a given specificity level (and vice versa), the optimal operating point of the ROC curve (in the Youden sense), and the Youden based cutoff.
Author: Leonidas Bantis [aut], Benjamin Brewer [cre, ctb], Christos Nakas [ctb], Benjamin Reiser [ctb]
Maintainer: Benjamin Brewer <tennisbenj@gmail.com>

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New package exvatools with initial version 0.1.0
Package: exvatools
Title: Value Added in Exports with International Input-Output Table Tools
Version: 0.1.0
Description: Decomposition of value added in exports in an international input-output table framework using the methodologies of Borin and Mancini (2019) <https://openknowledge.worldbank.org/handle/10986/31533>, Miroudot and Ye (2021) <doi:10.1080/09535314.2020.1730308>, Wang et al. (2013) <https://econpapers.repec.org/paper/nbrnberwo/19677.htm> and Koopman et al. (2014) <doi:10.1257/aer.104.2.459>. Includes commands for easy data extraction, calculation of complex matrices and other useful tools for geographical and sector trade analysis.
License: GPL-3
Depends: R (>= 3.4.0)
Imports: cli, data.table, methods, openxlsx, reshape2, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2022-12-21 08:02:00 UTC; Enrique
Author: Enrique Feas [aut, cre]
Maintainer: Enrique Feas <efeas@runbox.com>
Repository: CRAN
Date/Publication: 2022-12-21 16:20:02 UTC

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New package dfdr with initial version 0.1.0
Package: dfdr
Title: Automatic Differentiation of Simple Functions
Version: 0.1.0
Description: Implementation of automatically computing derivatives of functions (see Mailund Thomas (2017) <doi:10.1007/978-1-4842-2881-4>). Moreover, calculating gradients, Hessian and Jacobian matrices is possible.
License: GPL-3
Encoding: UTF-8
Imports: methods, purrr, rlang, R6, pryr
Suggests: testthat
NeedsCompilation: no
Packaged: 2022-12-21 07:13:20 UTC; konrad
Author: Thomas Mailund [aut], Konrad Kraemer [aut, cre]
Maintainer: Konrad Kraemer <konrad_kraemer@yahoo.de>
Repository: CRAN
Date/Publication: 2022-12-21 16:20:05 UTC

More information about dfdr at CRAN
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New package colorRamp2 with initial version 0.1.0
Package: colorRamp2
Title: Generate Color Mapping Functions
Version: 0.1.0
Date: 2022-12-21
Description: A color mapping is generated according to the break values and corresponding colors. Other colors are generated by interpolating in a certain color space. The functions were part of the 'circlize' package <https://CRAN.R-project.org/package=circlize>.
Depends: R (> 3.0.0)
Imports: colorspace, grDevices, methods, stats
Suggests: knitr
VignetteBuilder: knitr
URL: https://github.com/jokergoo/colorRamp2
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2022-12-21 16:27:28 UTC; guz
Author: Zuguang Gu [aut, cre]
Maintainer: Zuguang Gu <z.gu@dkfz.de>
Repository: CRAN
Date/Publication: 2022-12-21 16:50:02 UTC

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Package scMappR (with last version 1.0.9) was removed from CRAN

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

2022-03-07 1.0.9
2021-10-16 1.0.7
2021-05-14 1.0.2
2021-03-29 1.0.1
2021-03-21 1.0.0
2020-11-30 0.1.5
2020-09-02 0.1.4
2020-07-20 0.1.3
2020-03-05 0.1.1
2020-03-04 0.1

Permanent link
Package DEET (with last version 1.0.7) was removed from CRAN

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

2022-12-14 1.0.7
2022-10-09 1.0.6
2022-07-19 1.0.5
2022-06-27 1.0.2

Permanent link
Package xfun updated to version 0.36 with previous version 0.35 dated 2022-11-16

Title: Supporting Functions for Packages Maintained by 'Yihui Xie'
Description: Miscellaneous functions commonly used in other packages maintained by 'Yihui Xie'.
Author: Yihui Xie [aut, cre, cph] , Wush Wu [ctb], Daijiang Li [ctb], Xianying Tan [ctb], Salim Brueggemann [ctb] , Christophe Dervieux [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package slickR updated to version 0.6.0 with previous version 0.5.0 dated 2020-12-18

Title: Create Interactive Carousels with the 'JavaScript' 'Slick' Library
Description: Create and customize interactive carousels using the 'Slick' 'JavaScript' library and the 'htmlwidgets' package. The carousels can contain plots produced in R, images, 'iframes', videos and other 'htmlwidgets'. These carousels can be created directly from the R console, and viewed in the 'RStudio' internal viewer, in 'Shiny' apps and R Markdown documents.
Author: Jonathan Sidi [aut, cre]
Maintainer: Jonathan Sidi <yonicd@gmail.com>

Diff between slickR versions 0.5.0 dated 2020-12-18 and 0.6.0 dated 2022-12-21

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Package DeCAFS updated to version 3.3.2 with previous version 3.3.1 dated 2022-01-05

Title: Detecting Changes in Autocorrelated and Fluctuating Signals
Description: Detect abrupt changes in time series with local fluctuations as a random walk process and autocorrelated noise as an AR(1) process. See Romano, G., Rigaill, G., Runge, V., Fearnhead, P. (2021) <doi:10.1080/01621459.2021.1909598>.
Author: Gaetano Romano [aut, cre], Guillem Rigaill [aut], Vincent Runge [aut], Paul Fearnhead [aut]
Maintainer: Gaetano Romano <g.romano@lancaster.ac.uk>

Diff between DeCAFS versions 3.3.1 dated 2022-01-05 and 3.3.2 dated 2022-12-21

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Package springer updated to version 0.1.6 with previous version 0.1.5 dated 2021-09-14

Title: Sparse Group Variable Selection for Gene-Environment Interactions in the Longitudinal Study
Description: Recently, regularized variable selection has emerged as a powerful tool to identify and dissect gene-environment interactions. Nevertheless, in longitudinal studies with high dimensional genetic factors, regularization methods for G×E interactions have not been systematically developed. In this package, we provide the implementation of sparse group variable selection, based on both the quadratic inference function (QIF) and generalized estimating equation (GEE), to accommodate the bi-level selection for longitudinal G×E studies with high dimensional genomic features. Alternative methods conducting only the group or individual level selection have also been included. The core modules of the package have been developed in C++.
Author: Fei Zhou, Yuwen Liu, Xi Lu, Jie Ren, Cen Wu
Maintainer: Fei Zhou <fei.zhou@outlook.com>

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Package norgeo updated to version 2.1.4 with previous version 2.1.3 dated 2022-12-13

Title: Tracking Geo Code Change of Regional Granularity in Norway
Description: Regional granularity levels in Norway which are depicted by different codes, have undergone several changes over the years. Identifying when codes have changed and how many changes have taken place can be troublesome. This package will help to identify these changes and when the changes have taken place. One of the limitation of this package is that it is heavily depending on the codes available from SSB website <https://data.ssb.no/api/klass/v1/api-guide.html>.
Author: Yusman Kamaleri [aut, cre]
Maintainer: Yusman Kamaleri <ybkamaleri@gmail.com>

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Package mlr3fselect updated to version 0.9.0 with previous version 0.8.1 dated 2022-11-27

Title: Feature Selection for 'mlr3'
Description: Feature selection package of the 'mlr3' ecosystem. It selects the optimal feature set for any 'mlr3' learner. The package works with several optimization algorithms e.g. Random Search, Recursive Feature Elimination, and Genetic Search. Moreover, it can automatically optimize learners and estimate the performance of optimized feature sets with nested resampling.
Author: Marc Becker [aut, cre] , Patrick Schratz [aut] , Michel Lang [aut] , Bernd Bischl [aut]
Maintainer: Marc Becker <marcbecker@posteo.de>

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Package diagmeta updated to version 0.5-1 with previous version 0.5-0 dated 2022-04-22

Title: Meta-Analysis of Diagnostic Accuracy Studies with Several Cutpoints
Description: Provides methods by Steinhauser et al. (2016) <DOI:10.1186/s12874-016-0196-1> for meta-analysis of diagnostic accuracy studies with several cutpoints.
Author: Gerta Ruecker [aut] , Susanne Steinhauser [aut], Srinath Kolampally [aut], Guido Schwarzer [aut, cre]
Maintainer: Guido Schwarzer <guido.schwarzer@uniklinik-freiburg.de>

Diff between diagmeta versions 0.5-0 dated 2022-04-22 and 0.5-1 dated 2022-12-21

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New package rworkflows with initial version 0.99.3
Package: rworkflows
Title: Test, Document, Containerise, and Deploy R Packages
Version: 0.99.3
Description: Continuous integration for R packages. Automates testing, documentation website building, and containerised deployment.
URL: https://github.com/neurogenomics/rworkflows
BugReports: https://github.com/neurogenomics/rworkflows/issues
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: here, yaml, utils, desc, badger
Suggests: markdown, rmarkdown, magick, remotes, knitr, BiocStyle, covr, testthat (>= 3.0.0), hexSticker, htmltools, rvest, UpSetR, githubinstall, BiocManager, data.table
VignetteBuilder: knitr
License: GPL-3
NeedsCompilation: no
Packaged: 2022-12-20 19:59:46 UTC; schilder
Author: Brian Schilder [aut, cre] , Alan Murphy [aut, ctb]
Maintainer: Brian Schilder <brian_schilder@alumni.brown.edu>
Repository: CRAN
Date/Publication: 2022-12-21 12:20:02 UTC

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New package jointVIP with initial version 0.1.0
Package: jointVIP
Title: Prioritize Variables with Joint Variable Importance Plot in Observational Study Design
Version: 0.1.0
Description: In the observational study design stage, matching/weighting methods are conducted. However, when many background variables are present, the decision as to which variables to prioritize for matching/weighting is not trivial. Thus, the joint treatment-outcome variable importance plots are created to guide variable selection. The joint variable importance plots enhance variable comparisons via bias curves, derived using the classical omitted variable bias framework. The joint variable importance plots translate variable importance into recommended values for tuning parameters in existing methods. Post-matching and/or weighting plots can also be used to visualize and assess the quality of the observational study design.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.3)
Suggests: causaldata, devtools (>= 2.4.5), knitr, MatchIt, WeightIt, optmatch, optweight (>= 0.2.4), rmarkdown (>= 2.18), testthat (>= 3.0.0)
Imports: ggrepel (>= 0.9.2), ggplot2 (>= 3.4.0)
VignetteBuilder: knitr
URL: https://github.com/ldliao/jointVIP
BugReports: https://github.com/ldliao/jointVIP/issues
NeedsCompilation: no
Packaged: 2022-12-21 00:05:11 UTC; ldliao
Author: Lauren D. Liao [aut, cre] , Samuel D. Pimentel [aut]
Maintainer: Lauren D. Liao <ldliao@berkeley.edu>
Repository: CRAN
Date/Publication: 2022-12-21 12:20:06 UTC

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Package kgp updated to version 1.1.1 with previous version 1.1.0 dated 2022-10-05

Title: 1000 Genomes Project Metadata
Description: Metadata about populations and data about samples from the 1000 Genomes Project, including the 2,504 samples sequenced for the Phase 3 release and the expanded collection of 3,202 samples with 602 additional trios. The data is described in Auton et al. (2015) <doi:10.1038/nature15393> and Byrska-Bishop et al. (2022) <doi:10.1016/j.cell.2022.08.004>, and raw data is available at <http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/>. See Turner (2022) <doi:10.48550/arXiv.2210.00539> for more details.
Author: Stephen Turner [aut, cre]
Maintainer: Stephen Turner <vustephen@gmail.com>

Diff between kgp versions 1.1.0 dated 2022-10-05 and 1.1.1 dated 2022-12-21

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Package Rforestry updated to version 0.9.0.152 with previous version 0.9.0.144 dated 2022-11-30

Title: Random Forests, Linear Trees, and Gradient Boosting for Inference and Interpretability
Description: Provides fast implementations of Honest Random Forests, Gradient Boosting, and Linear Random Forests, with an emphasis on inference and interpretability. Additionally contains methods for variable importance, out-of-bag prediction, regression monotonicity, and several methods for missing data imputation. Soren R. Kunzel, Theo F. Saarinen, Edward W. Liu, Jasjeet S. Sekhon (2019) <arXiv:1906.06463>.
Author: Soeren Kuenzel [aut], Theo Saarinen [aut, cre], Simon Walter [aut], Edward Liu [aut], Allen Tang [aut], Jasjeet Sekhon [aut]
Maintainer: Theo Saarinen <theo_s@berkeley.edu>

Diff between Rforestry versions 0.9.0.144 dated 2022-11-30 and 0.9.0.152 dated 2022-12-21

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Package PriceIndices updated to version 0.1.2 with previous version 0.1.1 dated 2022-09-16

Title: Calculating Bilateral and Multilateral Price Indexes
Description: Preparing a scanner data set for price dynamics calculations (data selecting, data classification, data matching, data filtering). Computing bilateral and multilateral indexes. For details on these methods see: Diewert and Fox (2020) <doi:10.1080/07350015.2020.1816176>, Białek (2019) <doi:10.2478/jos-2019-0014> or Białek (2020) <doi:10.2478/jos-2020-0037>.
Author: Jacek Bialek [aut, cre]
Maintainer: Jacek Bialek <jacek.bialek@uni.lodz.pl>

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Permanent link

Package Mestim updated to version 0.2.1 with previous version 0.2.0 dated 2022-12-18

Title: Computes the Variance-Covariance Matrix of Multidimensional Parameters Using M-Estimation
Description: Provides a flexible framework for estimating the variance-covariance matrix of estimated parameters. Estimation relies on unbiased estimating functions to compute the empirical sandwich variance. (i.e., M-estimation in the vein of Tsiatis et al. (2019) <doi:10.1201/9780429192692>.
Author: Francois Grolleau
Maintainer: Francois Grolleau <francois.grolleau@aphp.fr>

Diff between Mestim versions 0.2.0 dated 2022-12-18 and 0.2.1 dated 2022-12-21

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New package bRacatus with initial version 1.0.11
Package: bRacatus
Title: A Method to Estimate the Accuracy and Biogeographical Status of Georeferenced Biological Data
Version: 1.0.11
Language: en-GB
Description: Automated assessment of accuracy and geographical status of georeferenced biological data. The methods rely on reference regions, namely checklists and range maps. Includes functions to obtain data from the Global Biodiversity Information Facility <https://www.gbif.org/> and from the Global Inventory of Floras and Traits <https://gift.uni-goettingen.de/home>. Alternatively, the user can input their own data. Furthermore, provides easy visualisation of the data and the results through the plotting functions. Especially suited for large datasets. The reference for the methodology is: Arlé et al. (under review).
Depends: R (>= 3.5.0)
Imports: data.table, geojsonio, graphics, grDevices, jsonlite, maptools, methods, plotfunctions, raster, rgbif, rgdal, rgeos, rworldmap, sp, stats
License: GPL (>= 2)
Encoding: UTF-8
URL: https://github.com/EduardoArle/bRacatus
BugReports: https://github.com/EduardoArle/bRacatus/issues
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-12-21 09:09:58 UTC; carloseduardoaribeiro
Author: Eduardo Arle [aut, cre], Alexander Zizka [aut], Patrick Weigelt [ctb], Sam Levin [ctb], Carsten Meyer [ths]
Maintainer: Eduardo Arle <eduardoarle@tauex.tau.ac.il>
Repository: CRAN
Date/Publication: 2022-12-21 10:10:02 UTC

More information about bRacatus at CRAN
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Package multid updated to version 0.7.1 with previous version 0.7.0 dated 2022-08-18

Title: Multivariate Difference Between Two Groups
Description: Estimation of multivariate differences between two groups (e.g., multivariate sex differences) with regularized regression methods and predictive approach. See Lönnqvist & Ilmarinen (2021) <doi:10.1007/s11109-021-09681-2> and Ilmarinen et al. (2022) <doi:10.1177/08902070221088155>. Includes tools that help in understanding difference score reliability, predictions of difference score variables, conditional intra-class correlations, and heterogeneity of variance estimates. Package development was supported by the Academy of Finland research grant 338891.
Author: Ville-Juhani Ilmarinen [aut, cre]
Maintainer: Ville-Juhani Ilmarinen <vj.ilmarinen@gmail.com>

Diff between multid versions 0.7.0 dated 2022-08-18 and 0.7.1 dated 2022-12-21

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Package metasens updated to version 1.5-1 with previous version 1.5-0 dated 2022-07-11

Title: Statistical Methods for Sensitivity Analysis in Meta-Analysis
Description: The following methods are implemented to evaluate how sensitive the results of a meta-analysis are to potential bias in meta-analysis and to support Schwarzer et al. (2015) <DOI:10.1007/978-3-319-21416-0>, Chapter 5 'Small-Study Effects in Meta-Analysis': - Copas selection model described in Copas & Shi (2001) <DOI:10.1177/096228020101000402>; - limit meta-analysis by Rücker et al. (2011) <DOI:10.1093/biostatistics/kxq046>; - upper bound for outcome reporting bias by Copas & Jackson (2004) <DOI:10.1111/j.0006-341X.2004.00161.x>; - imputation methods for missing binary data by Gamble & Hollis (2005) <DOI:10.1016/j.jclinepi.2004.09.013> and Higgins et al. (2008) <DOI:10.1177/1740774508091600>; - LFK index test and Doi plot by Furuya-Kanamori et al. (2018) <DOI:10.1097/XEB.0000000000000141>.
Author: Guido Schwarzer [cre, aut] , James R. Carpenter [aut] , Gerta Ruecker [aut]
Maintainer: Guido Schwarzer <guido.schwarzer@uniklinik-freiburg.de>

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Package meta updated to version 6.1-0 with previous version 6.0-0 dated 2022-09-17

Title: General Package for Meta-Analysis
Description: User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015): - common effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - three-level meta-analysis model; - generalised linear mixed model; - Hartung-Knapp method for random effects model; - Kenward-Roger method for random effects model; - prediction interval; - statistical tests for funnel plot asymmetry; - trim-and-fill method to evaluate bias in meta-analysis; - meta-regression; - cumulative meta-analysis and leave-one-out meta-analysis; - import data from 'RevMan 5'; - produce forest plot summarising several (subgroup) meta-analyses.
Author: Guido Schwarzer [cre, aut]
Maintainer: Guido Schwarzer <guido.schwarzer@uniklinik-freiburg.de>

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Package tidyfst updated to version 1.7.6 with previous version 1.7.5 dated 2022-10-27

Title: Tidy Verbs for Fast Data Manipulation
Description: A toolkit of tidy data manipulation verbs with 'data.table' as the backend. Combining the merits of syntax elegance from 'dplyr' and computing performance from 'data.table', 'tidyfst' intends to provide users with state-of-the-art data manipulation tools with least pain. This package is an extension of 'data.table'. While enjoying a tidy syntax, it also wraps combinations of efficient functions to facilitate frequently-used data operations.
Author: Tian-Yuan Huang [aut, cre]
Maintainer: Tian-Yuan Huang <huang.tian-yuan@qq.com>

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Package rvg updated to version 0.3.1 with previous version 0.3.0 dated 2022-12-08

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

Diff between rvg versions 0.3.0 dated 2022-12-08 and 0.3.1 dated 2022-12-21

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Package BiDAG updated to version 2.1.2 with previous version 2.1.1 dated 2022-08-05

Title: Bayesian Inference for Directed Acyclic Graphs
Description: Implementation of a collection of MCMC methods for Bayesian structure learning of directed acyclic graphs (DAGs), both from continuous and discrete data. For efficient inference on larger DAGs, the space of DAGs is pruned according to the data. To filter the search space, the algorithm employs a hybrid approach, combining constraint-based learning with search and score. A reduced search space is initially defined on the basis of a skeleton obtained by means of the PC-algorithm, and then iteratively improved with search and score. Search and score is then performed following two approaches: Order MCMC, or Partition MCMC. The BGe score is implemented for continuous data and the BDe score is implemented for binary data or categorical data. The algorithms may provide the maximum a posteriori (MAP) graph or a sample (a collection of DAGs) from the posterior distribution given the data. All algorithms are also applicable for structure learning and sampling for dynamic Bayesian networks. Refe [...truncated...]
Author: Polina Suter [aut, cre], Jack Kuipers [aut]
Maintainer: Polina Suter <polina.suter@gmail.com>

Diff between BiDAG versions 2.1.1 dated 2022-08-05 and 2.1.2 dated 2022-12-21

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Package AzureKusto updated to version 1.1.0 with previous version 1.0.7 dated 2022-08-26

Title: Interface to 'Kusto'/'Azure Data Explorer'
Description: An interface to 'Azure Data Explorer', also known as 'Kusto', a fast, highly scalable data exploration service from Microsoft: <https://azure.microsoft.com/en-us/products/data-explorer/>. Includes 'DBI' and 'dplyr' interfaces, with the latter modelled after the 'dbplyr' package, whereby queries are translated from R into the native 'KQL' query language and executed lazily. On the admin side, the package extends the object framework provided by 'AzureRMR' to support creation and deletion of databases, and management of database principals. Part of the 'AzureR' family of packages.
Author: Hong Ooi [aut], Alex Kyllo [aut, cre], dbplyr development team [cph] , Microsoft [cph]
Maintainer: Alex Kyllo <jekyllo@microsoft.com>

Diff between AzureKusto versions 1.0.7 dated 2022-08-26 and 1.1.0 dated 2022-12-21

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