Tue, 05 Nov 2024

Package sfsmisc updated to version 1.1-20 with previous version 1.1-19 dated 2024-08-19

Title: Utilities from 'Seminar fuer Statistik' ETH Zurich
Description: Useful utilities ['goodies'] from Seminar fuer Statistik ETH Zurich, some of which were ported from S-plus in the 1990s. For graphics, have pretty (Log-scale) axes eaxis(), an enhanced Tukey-Anscombe plot, combining histogram and boxplot, 2d-residual plots, a 'tachoPlot()', pretty arrows, etc. For robustness, have a robust F test and robust range(). For system support, notably on Linux, provides 'Sys.*()' functions with more access to system and CPU information. Finally, miscellaneous utilities such as simple efficient prime numbers, integer codes, Duplicated(), toLatex.numeric() and is.whole().
Author: Martin Maechler [aut, cre] , Werner Stahel [ctb] , f.robftest, last, p.scales, p.dnorm), Andreas Ruckstuhl [ctb] , p.profileTraces, p.res.2x), Christian Keller [ctb] , p.tachoPlot), Kjetil Halvorsen [ctb] , ecdf.ksCI), Alain Hauser [ctb] , is.whole, [...truncated...]
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

Diff between sfsmisc versions 1.1-19 dated 2024-08-19 and 1.1-20 dated 2024-11-05

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More information about sfsmisc at CRAN
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Package CausalQueries updated to version 1.2.1 with previous version 1.1.1 dated 2024-04-26

Title: Make, Update, and Query Binary Causal Models
Description: Users can declare causal models over binary nodes, update beliefs about causal types given data, and calculate arbitrary queries. Updating is implemented in 'stan'. See Humphreys and Jacobs, 2023, Integrated Inferences (<DOI: 10.1017/9781316718636>) and Pearl, 2009 Causality (<DOI:10.1017/CBO9780511803161>).
Author: Clara Bicalho [ctb], Jasper Cooper [ctb], Macartan Humphreys [aut] , Till Tietz [aut, cre] , Alan Jacobs [aut], Merlin Heidemanns [ctb], Lily Medina [aut] , Julio Solis [ctb], Georgiy Syunyaev [aut]
Maintainer: Till Tietz <ttietz2014@gmail.com>

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Package LMest updated to version 3.2.3 with previous version 3.2.2 dated 2024-09-15

Title: Generalized Latent Markov Models
Description: Latent Markov models for longitudinal continuous and categorical data. See Bartolucci, Pandolfi, Pennoni (2017)<doi:10.18637/jss.v081.i04>.
Author: Francesco Bartolucci [aut, cre], Silvia Pandolfi [aut], Fulvia Pennoni [aut], Alessio Farcomeni [ctb], Alessio Serafini [ctb]
Maintainer: Francesco Bartolucci <francesco.bartolucci@unipg.it>

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Package c212 updated to version 1.0.1 with previous version 0.98 dated 2020-09-08

Title: Methods for Detecting Safety Signals in Clinical Trials Using Body-Systems (System Organ Classes)
Description: Provides a self-contained set of methods to aid clinical trial safety investigators, statisticians and researchers, in the early detection of adverse events using groupings by body-system or system organ class. This work was supported by the Engineering and Physical Sciences Research Council (UK) (EPSRC) [award reference 1521741] and Frontier Science (Scotland) Ltd. The package title c212 is in reference to the original Engineering and Physical Sciences Research Council (UK) funded project which was named CASE 2/12.
Author: Raymond Carragher [aut, cre]
Maintainer: Raymond Carragher <rcarragh@gmail.com>

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Package manynet updated to version 1.3.2 with previous version 1.3.1 dated 2024-10-29

Title: Many Ways to Make, Modify, Map, Mark, and Measure Myriad Networks
Description: Many tools for making, modifying, mapping, marking, measuring, and motifs and memberships of many different types of networks. All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, and on one-mode, two-mode (bipartite), and sometimes three-mode networks. The package includes functions for importing and exporting, creating and generating networks, modifying networks and node and tie attributes, and describing and visualizing networks with sensible defaults.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb] , Christian Steglich [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

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Package vsp updated to version 0.1.2 with previous version 0.1.1 dated 2022-12-05

Title: Vintage Sparse PCA for Semi-Parametric Factor Analysis
Description: Provides fast spectral estimation of latent factors in random dot product graphs using the vsp estimator. Under mild assumptions, the vsp estimator is consistent for (degree-corrected) stochastic blockmodels, (degree-corrected) mixed-membership stochastic blockmodels, and degree-corrected overlapping stochastic blockmodels.
Author: Karl Rohe [aut], Muzhe Zeng [aut], Alex Hayes [aut, cre, cph] , Fan Chen [aut]
Maintainer: Alex Hayes <alexpghayes@gmail.com>

Diff between vsp versions 0.1.1 dated 2022-12-05 and 0.1.2 dated 2024-11-05

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Package fmeffects updated to version 0.1.4 with previous version 0.1.3 dated 2024-06-07

Title: Model-Agnostic Interpretations with Forward Marginal Effects
Description: Create local, regional, and global explanations for any machine learning model with forward marginal effects. You provide a model and data, and 'fmeffects' computes feature effects. The package is based on the theory in: C. A. Scholbeck, G. Casalicchio, C. Molnar, B. Bischl, and C. Heumann (2022) <doi:10.48550/arXiv.2201.08837>.
Author: Holger Loewe [cre, aut], Christian Scholbeck [aut], Christian Heumann [rev], Bernd Bischl [rev], Giuseppe Casalicchio [rev]
Maintainer: Holger Loewe <hbj.loewe@gmail.com>

Diff between fmeffects versions 0.1.3 dated 2024-06-07 and 0.1.4 dated 2024-11-05

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Package rbcc updated to version 0.1.3 with previous version 0.1.2 dated 2024-10-17

Title: Risk-Based Control Charts
Description: Univariate and multivariate versions of risk-based control charts. Univariate versions of control charts, such as the risk-based version of X-bar, Moving Average (MA), Exponentially Weighted Moving Average Control Charts (EWMA), and Cumulative Sum Control Charts (CUSUM) charts. The risk-based version of the multivariate T2 control chart. Plot and summary functions. Kosztyan et. al. (2016) <doi:10.1016/j.eswa.2016.06.019>.
Author: Aamir Saghir [aut], Attila Imre Katona [aut], Zsolt Tibor Kosztyan [aut, cre]
Maintainer: Zsolt Tibor Kosztyan <kosztyan.zsolt@gtk.uni-pannon.hu>

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Package RaceID updated to version 0.3.8 with previous version 0.3.7 dated 2024-11-01

Title: Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data
Description: Application of 'RaceID' allows inference of cell types and prediction of lineage trees by the 'StemID2' algorithm (Herman, J.S., Sagar, Grun D. (2018) <DOI:10.1038/nmeth.4662>). 'VarID2' is part of this package and allows quantification of biological gene expression noise at single-cell resolution (Rosales-Alvarez, R.E., Rettkowski, J., Herman, J.S., Dumbovic, G., Cabezas-Wallscheid, N., Grun, D. (2023) <DOI:10.1186/s13059-023-02974-1>).
Author: Dominic Gruen [aut, cre]
Maintainer: Dominic Gruen <dominic.gruen@gmail.com>

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Package sf updated to version 1.0-19 with previous version 1.0-18 dated 2024-10-11

Title: Simple Features for R
Description: Support for simple features, a standardized way to encode spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations. Uses by default the 's2' package for spherical geometry operations on ellipsoidal (long/lat) coordinates.
Author: Edzer Pebesma [aut, cre] , Roger Bivand [ctb] , Etienne Racine [ctb], Michael Sumner [ctb], Ian Cook [ctb], Tim Keitt [ctb], Robin Lovelace [ctb], Hadley Wickham [ctb], Jeroen Ooms [ctb] , Kirill Mueller [ctb], Thomas Lin Pedersen [ctb], Dan Baston [c [...truncated...]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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Package MVar.pt updated to version 2.2.3 with previous version 2.2.2 dated 2024-06-21

Title: Analise multivariada (brazilian portuguese)
Description: Analise multivariada, tendo funcoes que executam analise de correspondencia simples (CA) e multipla (MCA), analise de componentes principais (PCA), analise de correlacao canonica (CCA), analise fatorial (FA), escalonamento multidimensional (MDS), analise discriminante linear (LDA) e quadratica (QDA), analise de cluster hierarquico e nao hierarquico, regressao linear simples e multipla, analise de multiplos fatores (MFA) para dados quantitativos, qualitativos, de frequencia (MFACT) e dados mistos, biplot, scatter plot, projection pursuit (PP), grant tour e outras funcoes uteis para a analise multivariada.
Author: Paulo Cesar Ossani [aut, cre] , Marcelo Angelo Cirillo [aut]
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>

Diff between MVar.pt versions 2.2.2 dated 2024-06-21 and 2.2.3 dated 2024-11-05

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Package MVar updated to version 2.2.3 with previous version 2.2.2 dated 2024-06-21

Title: Multivariate Analysis
Description: Multivariate analysis, having functions that perform simple correspondence analysis (CA) and multiple correspondence analysis (MCA), principal components analysis (PCA), canonical correlation analysis (CCA), factorial analysis (FA), multidimensional scaling (MDS), linear (LDA) and quadratic discriminant analysis (QDA), hierarchical and non-hierarchical cluster analysis, simple and multiple linear regression, multiple factor analysis (MFA) for quantitative, qualitative, frequency (MFACT) and mixed data, biplot, scatter plot, projection pursuit (PP), grant tour method and other useful functions for the multivariate analysis.
Author: Paulo Cesar Ossani [aut, cre] , Marcelo Angelo Cirillo [aut]
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>

Diff between MVar versions 2.2.2 dated 2024-06-21 and 2.2.3 dated 2024-11-05

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Package surveillance updated to version 1.24.1 with previous version 1.24.0 dated 2024-10-01

Title: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena
Description: Statistical methods for the modeling and monitoring of time series of counts, proportions and categorical data, as well as for the modeling of continuous-time point processes of epidemic phenomena. The monitoring methods focus on aberration detection in count data time series from public health surveillance of communicable diseases, but applications could just as well originate from environmetrics, reliability engineering, econometrics, or social sciences. The package implements many typical outbreak detection procedures such as the (improved) Farrington algorithm, or the negative binomial GLR-CUSUM method of Hoehle and Paul (2008) <doi:10.1016/j.csda.2008.02.015>. A novel CUSUM approach combining logistic and multinomial logistic modeling is also included. The package contains several real-world data sets, the ability to simulate outbreak data, and to visualize the results of the monitoring in a temporal, spatial or spatio-temporal fashion. A recent overview of the available mon [...truncated...]
Author: Michael Hoehle [aut, ths] , Sebastian Meyer [aut, cre] , Michaela Paul [aut], Leonhard Held [ctb, ths] , Howard Burkom [ctb], Thais Correa [ctb], Mathias Hofmann [ctb], Christian Lang [ctb], Juliane Manitz [ctb], Sophie Reichert [ctb], Andrea Riebler [...truncated...]
Maintainer: Sebastian Meyer <seb.meyer@fau.de>

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Package mtdesign updated to version 0.1.2 with previous version 0.1.0 dated 2022-10-27

Title: Mander and Thompson Designs
Description: Implements Mander & Thompson's (2010) <doi:10.1016/j.cct.2010.07.008> methods for two-stage designs optimal under the alternative hypothesis for phase II [cancer] trials. Also provides an implementation of Simon's (1989) <doi:10.1016/0197-2456(89)90015-9> original methodology and allows exploration of the operating characteristics of sub-optimal designs.
Author: John Kirkpatrick [aut, cre]
Maintainer: John Kirkpatrick <mtdesign@puzzledface.net>

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Package admix updated to version 2.3.2 with previous version 2.3.1 dated 2024-10-24

Title: Package Admix for Admixture (aka Contamination) Models
Description: Implements techniques to estimate the unknown quantities related to two-component admixture models, where the two components can belong to any distribution (note that in the case of multinomial mixtures, the two components must belong to the same family). Estimation methods depend on the assumptions made on the unknown component density; see Bordes and Vandekerkhove (2010) <doi:10.3103/S1066530710010023>, Patra and Sen (2016) <doi:10.1111/rssb.12148>, and Milhaud, Pommeret, Salhi, Vandekerkhove (2024) <doi:10.3150/23-BEJ1593>. In practice, one can estimate both the mixture weight and the unknown component density in a wide variety of frameworks. On top of that, hypothesis tests can be performed in one and two-sample contexts to test the unknown component density (see Milhaud, Pommeret, Salhi and Vandekerkhove (2022) <doi:10.1016/j.jspi.2021.05.010>, and Milhaud, Pommeret, Salhi, Vandekerkhove (2024) <doi:10.3150/23-BEJ1593>). Finally, clustering of unknown [...truncated...]
Author: Xavier Milhaud [aut, cre], Pierre Vandekerkhove [ctb], Denys Pommeret [ctb], Yahia Salhi [ctb]
Maintainer: Xavier Milhaud <xavier.milhaud.research@gmail.com>

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Package readODS updated to version 2.3.1 with previous version 2.3.0 dated 2024-05-26

Title: Read and Write ODS Files
Description: Read ODS (OpenDocument Spreadsheet) into R as data frame. Also support writing data frame into ODS file.
Author: Gerrit-Jan Schutten [aut], Chung-hong Chan [aut, cre] , Peter Brohan [aut], Detlef Steuer [aut] , Thomas J. Leeper [aut] , John Foster [ctb], Sergio Oller [ctb], Jim Hester [ctb] , Stephen Watts [ctb], Arthur Katossky [ctb], Stas Malavin [ctb], Dunca [...truncated...]
Maintainer: Chung-hong Chan <chainsawtiney@gmail.com>

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Package diceplot updated to version 0.1.3 with previous version 0.1.2 dated 2024-10-28

Title: High Dimensional Categorical Data Visualization
Description: Easy visualization for datasets with more than two categorical variables and additional continuous variables. 'diceplot' is particularly useful for exploring complex categorical data in the context of pathway analysis across multiple conditions. For a detailed documentation please visit <https://dice-and-domino-plot.readthedocs.io/en/latest/>.
Author: Matthias Flotho [aut, cre]
Maintainer: Matthias Flotho <matthias.flotho@ccb.uni-saarland.de>

Diff between diceplot versions 0.1.2 dated 2024-10-28 and 0.1.3 dated 2024-11-05

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Package curl updated to version 6.0.0 with previous version 5.2.3 dated 2024-09-20

Title: A Modern and Flexible Web Client for R
Description: Bindings to 'libcurl' <https://curl.se/libcurl/> for performing fully configurable HTTP/FTP requests where responses can be processed in memory, on disk, or streaming via the callback or connection interfaces. Some knowledge of 'libcurl' is recommended; for a more-user-friendly web client see the 'httr2' package which builds on this package with http specific tools and logic.
Author: Jeroen Ooms [aut, cre] , Hadley Wickham [ctb], Posit Software, PBC [cph]
Maintainer: Jeroen Ooms <jeroenooms@gmail.com>

Diff between curl versions 5.2.3 dated 2024-09-20 and 6.0.0 dated 2024-11-05

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Package resampledata updated to version 0.3.2 with previous version 0.3.1 dated 2019-08-30

Title: Data Sets for Mathematical Statistics with Resampling in R
Description: Package of data sets from "Mathematical Statistics with Resampling in R" (1st Ed. 2011, 2nd Ed. 2018) by Laura Chihara and Tim Hesterberg.
Author: Laura Chihara [aut], Tim Hesterberg [aut], Albert Y. Kim [aut, cre]
Maintainer: Albert Y. Kim <albert.ys.kim@gmail.com>

Diff between resampledata versions 0.3.1 dated 2019-08-30 and 0.3.2 dated 2024-11-05

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Package rbin updated to version 0.2.1 with previous version 0.2.0 dated 2020-05-14

Title: Tools for Binning Data
Description: Manually bin data using weight of evidence and information value. Includes other binning methods such as equal length, quantile and winsorized. Options for combining levels of categorical data are also available. Dummy variables can be generated based on the bins created using any of the available binning methods. References: Siddiqi, N. (2006) <doi:10.1002/9781119201731.biblio>.
Author: Aravind Hebbali [aut, cre]
Maintainer: Aravind Hebbali <hebbali.aravind@gmail.com>

Diff between rbin versions 0.2.0 dated 2020-05-14 and 0.2.1 dated 2024-11-05

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New package subsampling with initial version 0.1.1
Package: subsampling
Title: Optimal Subsampling Methods for Statistical Models
Version: 0.1.1
Date: 2024-11-2
Maintainer: Qingkai Dong <qingkai.dong@uconn.edu>
Description: Balancing computational and statistical efficiency, subsampling techniques offer a practical solution for handling large-scale data analysis. Subsampling methods enhance statistical modeling for massive datasets by efficiently drawing representative subsamples from full dataset based on tailored sampling probabilities. These probabilities are optimized for specific goals, such as minimizing the variance of coefficient estimates or reducing prediction error.
License: GPL-3
URL: https://github.com/dqksnow/Subsampling
BugReports: https://github.com/dqksnow/Subsampling/issues
Imports: expm, nnet, quantreg, Rcpp (>= 1.0.12), stats, survey
Suggests: knitr, MASS, rmarkdown, tinytest
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2024-11-02 23:30:06 UTC; qingkaidong
Author: Qingkai Dong [aut, cre, cph], Yaqiong Yao [aut], Haiying Wang [aut], Qiang Zhang [ctb], Jun Yan [ctb]
Repository: CRAN
Date/Publication: 2024-11-05 10:20:02 UTC

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New package lubrilog with initial version 1.1.0
Package: lubrilog
Title: Get Insights on 'lubridate' Operations
Version: 1.1.0
Description: Provides a set of tools designed to enhance transparency and understanding of date-time manipulation functions from the 'lubridate' package. It provides detailed feedback about the operations performed by 'lubridate' functions, allowing users to better comprehend and debug their code. These insights serve as both a learning tool for newcomers and a debugging aid for programmers working with date-time data.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 2.10)
LazyData: true
Imports: cli, lubridate
Suggests: testthat (>= 3.0.0)
URL: https://github.com/arrismo/lubrilog
NeedsCompilation: no
Packaged: 2024-11-03 15:42:51 UTC; mmois
Author: Mikael Moise [aut, cre, cph]
Maintainer: Mikael Moise <mikaelmoise00@gmail.com>
Repository: CRAN
Date/Publication: 2024-11-05 10:30:02 UTC

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New package hdbcp with initial version 0.1.0
Package: hdbcp
Title: Bayesian Change Point Detection for High-Dimensional Data
Version: 0.1.0
Maintainer: JaeHoon Kim <jhkimstat@gmail.com>
Description: Functions implementing change point detection methods using the maximum pairwise Bayes factor approach. Additionally, the package includes tools for generating simulated datasets for comparing and evaluating change point detection techniques.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/JaeHoonKim98/hdbcp
BugReports: https://github.com/JaeHoonKim98/hdbcp/issues
Imports: Rcpp, stats, dplyr
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2024-11-03 13:24:49 UTC; jhkim
Author: JaeHoon Kim [aut, cre], KyoungJae Lee [aut, ths]
Repository: CRAN
Date/Publication: 2024-11-05 10:20:07 UTC

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New package dverse with initial version 0.0.1
Package: dverse
Title: Document a Universe of Packages
Version: 0.0.1
Description: Creates a data frame containing the metadata associated with the documentation of a collection of R packages. It allows for linking topic names to their corresponding documentation online. If you maintain a universe meta-package, it helps create a comprehensive reference for its website.
License: MIT + file LICENSE
URL: https://github.com/maurolepore/dverse, https://maurolepore.github.io/dverse/
BugReports: https://github.com/maurolepore/dverse/issues
Depends: R (>= 4.3)
Imports: cli, dplyr, glue, rlang, tibble, utils
Suggests: DT, knitr, testthat, withr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2024-11-03 19:42:44 UTC; rstudio
Author: Mauro Lepore [aut, cre, cph]
Maintainer: Mauro Lepore <maurolepore@gmail.com>
Repository: CRAN
Date/Publication: 2024-11-05 10:30:06 UTC

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Package coro updated to version 1.1.0 with previous version 1.0.5 dated 2024-10-15

Title: 'Coroutines' for R
Description: Provides 'coroutines' for R, a family of functions that can be suspended and resumed later on. This includes 'async' functions (which await) and generators (which yield). 'Async' functions are based on the concurrency framework of the 'promises' package. Generators are based on a dependency free iteration protocol defined in 'coro' and are compatible with iterators from the 'reticulate' package.
Author: Lionel Henry [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Lionel Henry <lionel@posit.co>

Diff between coro versions 1.0.5 dated 2024-10-15 and 1.1.0 dated 2024-11-05

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New package cocoon with initial version 0.1.0
Package: cocoon
Title: Extract, Format, and Print Statistical Output
Version: 0.1.0
Maintainer: Jeffrey R. Stevens <jeffrey.r.stevens@protonmail.com>
Description: Provides functions that format statistical output in a way that can be inserted into R Markdown documents. This is analogous to the apa_print() functions in the 'papaja' package but prints Markdown or LaTeX syntax.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: BayesFactor, correlation, knitr, rmarkdown, testthat (>= 3.0.0)
Imports: dplyr, lifecycle
URL: https://github.com/JeffreyRStevens/cocoon, https://jeffreyrstevens.github.io/cocoon/
BugReports: https://github.com/JeffreyRStevens/cocoon/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-11-02 20:30:27 UTC; jstevens
Author: Jeffrey R. Stevens [aut, cre, cph]
Repository: CRAN
Date/Publication: 2024-11-05 10:10:02 UTC

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Package WeightIt updated to version 1.3.2 with previous version 1.3.1 dated 2024-10-04

Title: Weighting for Covariate Balance in Observational Studies
Description: Generates balancing weights for causal effect estimation in observational studies with binary, multi-category, or continuous point or longitudinal treatments by easing and extending the functionality of several R packages and providing in-house estimation methods. Available methods include those that rely on parametric modeling, optimization, and machine learning. Also allows for assessment of weights and checking of covariate balance by interfacing directly with the 'cobalt' package. Methods for estimating weighted regression models that take into account uncertainty in the estimation of the weights via M-estimation or bootstrapping are available. See the vignette "Installing Supporting Packages" for instructions on how to install any package 'WeightIt' uses, including those that may not be on CRAN.
Author: Noah Greifer [aut, cre]
Maintainer: Noah Greifer <noah.greifer@gmail.com>

Diff between WeightIt versions 1.3.1 dated 2024-10-04 and 1.3.2 dated 2024-11-05

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Package SlaPMEG updated to version 1.0.2 with previous version 1.0.1 dated 2021-07-05

Title: Pathway Testing for Longitudinal Omics
Description: A self-contained hypothesis is tested for a given pathway of longitudinal omics. 'SlaPMEG' is a two-step procedure. First, a shared latent process mixed model is fitted over the longitudinal measures of omics in a pathway. This shared model allows deviation from the shared process at subject level (a random intercept, slope, or both per subject) and also at omic level (a random effect per omic). These random effects summarize the longitudinal trend of the observations which can be used to test for group differences using 'Globaltest' in the second step. If the pathway is large or the shared effect is small, the package fits a series of pairwise models and estimates the shared random effects based on them.
Author: Mitra Ebrahimpoor [aut, cre]
Maintainer: Mitra Ebrahimpoor <mitra.ebrahimpoor@gmail.com>

Diff between SlaPMEG versions 1.0.1 dated 2021-07-05 and 1.0.2 dated 2024-11-05

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Package finbif updated to version 0.9.9 with previous version 0.9.8 dated 2024-08-19

Title: Interface for the 'Finnish Biodiversity Information Facility' API
Description: A programmatic interface to the 'Finnish Biodiversity Information Facility' ('FinBIF') API (<https://api.laji.fi>). 'FinBIF' aggregates Finnish biodiversity data from multiple sources in a single open access portal for researchers, citizen scientists, industry and government. 'FinBIF' allows users of biodiversity information to find, access, combine and visualise data on Finnish plants, animals and microorganisms. The 'finbif' package makes the publicly available data in 'FinBIF' easily accessible to programmers. Biodiversity information is available on taxonomy and taxon occurrence. Occurrence data can be filtered by taxon, time, location and other variables. The data accessed are conveniently preformatted for subsequent analyses.
Author: Finnish Museum of Natural History - Luomus [cph], William K. Morris [aut, cre]
Maintainer: William K. Morris <willi@mmorris.email>

Diff between finbif versions 0.9.8 dated 2024-08-19 and 0.9.9 dated 2024-11-05

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Package COveR (with last version 1.0.4) was removed from CRAN

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

2024-10-21 1.0.4

Permanent link
New package minFactorial with initial version 0.1.0
Package: minFactorial
Title: All Possible Minimally Changed Factorial Run Orders
Version: 0.1.0
Maintainer: Bijoy Chanda <bijoychanda08@gmail.com>
Description: In many agricultural, engineering, industrial, post-harvest and processing experiments, the number of factor level changes and hence the total number of changes is of serious concern as such experiments may consists of hard-to-change factors where it is physically very difficult to change levels of some factors or sometime such experiments may require normalization time to obtain adequate operating condition. For this reason, run orders that offer the minimum number of factor level changes and at the same time minimize the possible influence of systematic trend effects on the experimentation have been sought. Factorial designs with minimum changes in factors level may be preferred for such situations as these minimally changed run orders will minimize the cost of the experiments. For method details see, Bhowmik, A.,Varghese, E., Jaggi, S. and Varghese, C. (2017)<doi:10.1080/03610926.2016.1152490>.This package used to construct all possible minimally changed factorial run orders [...truncated...]
Imports: FMC
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-11-02 15:39:11 UTC; ICAR-CAFRI
Author: Arpan Bhowmik [aut, ctb], Bijoy Chanda [aut, cre, ctb], Seema Jaggi [aut], Eldho Varghese [aut, ctb], Cini Varghese [aut], Anindita Datta [aut]
Repository: CRAN
Date/Publication: 2024-11-05 08:10:02 UTC

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Package fastcpd updated to version 0.14.6 with previous version 0.14.3 dated 2024-04-26

Title: Fast Change Point Detection via Sequential Gradient Descent
Description: Implements fast change point detection algorithm based on the paper "Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis" by Xianyang Zhang, Trisha Dawn <https://proceedings.mlr.press/v206/zhang23b.html>. The algorithm is based on dynamic programming with pruning and sequential gradient descent. It is able to detect change points a magnitude faster than the vanilla Pruned Exact Linear Time(PELT). The package includes examples of linear regression, logistic regression, Poisson regression, penalized linear regression data, and whole lot more examples with custom cost function in case the user wants to use their own cost function.
Author: Xingchi Li [aut, cre, cph] , Xianyang Zhang [aut, cph]
Maintainer: Xingchi Li <anthony.li@stat.tamu.edu>

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Package CollocInfer updated to version 1.0.5 with previous version 1.0.4 dated 2016-11-07

Title: Collocation Inference for Dynamic Systems
Description: These functions implement collocation-inference for continuous-time and discrete-time stochastic processes. They provide model-based smoothing, gradient-matching, generalized profiling and forwards prediction error methods.
Author: Giles Hooker [aut, cre], Luo Xiao [aut], James Ramsay [ctb]
Maintainer: Giles Hooker <ghooker@wharton.upenn.edu>

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Package cmhc updated to version 0.2.9 with previous version 0.2.8 dated 2024-07-12

Title: Access, Retrieve, and Work with CMHC Data
Description: Wrapper around the Canadian Mortgage and Housing Corporation (CMHC) web interface. It enables programmatic and reproducible access to a wide variety of housing data from CMHC.
Author: Jens von Bergmann [aut, cre]
Maintainer: Jens von Bergmann <jens@mountainmath.ca>

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Package animint2 updated to version 2024.11.2 with previous version 2024.1.24 dated 2024-01-24

Title: Animated Interactive Grammar of Graphics
Description: Functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, <doi:10.1080/10618600.2018.1513367> describes the concepts implemented.
Author: Toby Hocking [aut, cre] , Biplab Sutradhar [ctb] , Hadley Wickham [aut] , Winston Chang [aut] , RStudio [cph] , Nicholas Lewin-Koh [aut] , Martin Maechler [aut] , Randall Prium [aut] , Susan VanderPlas [aut] , Carson Sievert [aut] , Kevin Ferris [aut [...truncated...]
Maintainer: Toby Hocking <toby.hocking@r-project.org>

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New package tidywater with initial version 0.6.2
Package: tidywater
Title: Water Quality Models for Drinking Water Treatment Processes
Version: 0.6.2
URL: https://github.com/BrownandCaldwell-Public/tidywater
BugReports: https://github.com/BrownandCaldwell-Public/tidywater/issues
Description: Provides multiple water chemistry-based models and published empirical models in one standard format. Functions can be chained together to model a complete treatment process and are designed to work in a 'tidyverse' workflow. Models are primarily based on these sources: Benjamin, M. M. (2002, ISBN:147862308X), Crittenden, J. C., Trussell, R., Hand, D., Howe, J. K., & Tchobanoglous, G., Borchardt, J. H. (2012, ISBN:9781118131473), USEPA. (2001) <https://www.epa.gov/sites/default/files/2017-03/documents/wtp_model_v._2.0_manual_508.pdf>.
License: Apache License (>= 2) | MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, tidyr, knitr, ggplot2, ggrepel, magrittr, purrr, furrr, methods, rlang
Depends: R (>= 2.10)
Suggests: rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Date: 2024-11-01
NeedsCompilation: no
Packaged: 2024-11-01 16:31:08 UTC; SJohnson2
Author: Sierra Johnson [aut, cre], Libby McKenna [aut], Riley Mulhern [aut] , Chris Corwin [aut] , Rachel Merrifield [ctb], Mayuri Namasivayam [ctb], USEPA [cph] ), Brown and Caldwell [fnd, cph]
Maintainer: Sierra Johnson <sjohnson2@brwncald.com>
Repository: CRAN
Date/Publication: 2024-11-05 07:50:02 UTC

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New package speedyBBT with initial version 1.0
Package: speedyBBT
Title: Efficient Bayesian Inference for the Bradley--Terry Model
Version: 1.0
Description: A suite of functions that allow a full, fast, and efficient Bayesian treatment of the Bradley--Terry model. Prior assumptions about the model parameters can be encoded through a multivariate normal prior distribution. Inference is performed using a latent variable representation of the model.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: base, BayesLogit, Matrix, stats, utils
Suggests: expm, testthat (>= 3.0.0)
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2024-11-01 14:30:33 UTC; seymourg
Author: Rowland Seymour [aut, cre, cph]
Maintainer: Rowland Seymour <r.g.seymour@bham.ac.uk>
Repository: CRAN
Date/Publication: 2024-11-05 07:30:02 UTC

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New package plotthis with initial version 0.3.5
Package: plotthis
Title: High-Level Plotting Built Upon 'ggplot2' and Other Plotting Packages
Version: 0.3.5
Description: Provides high-level API and a wide range of options to create stunning, publication-quality plots effortlessly. It is built upon 'ggplot2' and other plotting packages, and is designed to be easy to use and to work seamlessly with 'ggplot2' objects. It is particularly useful for creating complex plots with multiple layers, facets, and annotations. It also provides a set of functions to create plots for specific types of data, such as Venn diagrams, alluvial diagrams, and phylogenetic trees. The package is designed to be flexible and customizable, and to work well with the 'ggplot2' ecosystem. The API can be found at <https://pwwang.github.io/plotthis/reference/index.html>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/pwwang/plotthis https://pwwang.github.io/plotthis/
BugReports: https://github.com/pwwang/plotthis/issues
Depends: R (>= 4.0.0)
Imports: circlize, ggplot2, rlang, dplyr, tidyr, glue, forcats, gtable, reshape2, stringr, scales, gridtext, methods, patchwork, ggrepel, ggnewscale, cowplot, zoo
Suggests: ComplexHeatmap, clustree, gglogger, ggwordcloud, ggalluvial, ggVennDiagram (>= 1.5.0), ggupset, ggpubr, ggforce, ggraph, ggridges, hexbin, igraph, iNEXT, scattermore, concaveman
LazyData: true
NeedsCompilation: no
Packaged: 2024-11-01 15:24:32 UTC; pwwang
Author: Panwen Wang [aut, cre]
Maintainer: Panwen Wang <pwwang@pwwang.com>
Repository: CRAN
Date/Publication: 2024-11-05 07:40:02 UTC

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New package mergedblocks with initial version 1.1.1
Package: mergedblocks
Title: Merged Block Randomization
Version: 1.1.1
Description: Package to carry out merged block randomization (Van der Pas (2019), <doi:10.1177/1740774519827957>), a restricted randomization method designed for small clinical trials (at most 100 subjects) or trials with small strata, for example in multicentre trials. It can be used for more than two groups or unequal randomization ratios.
Imports: randomizeR
License: GPL-3
Encoding: UTF-8
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-11-01 12:54:59 UTC; stephanie
Author: Stephanie van der Pas [aut, cre]
Maintainer: Stephanie van der Pas <s.l.vanderpas@amsterdamumc.nl>
Repository: CRAN
Date/Publication: 2024-11-05 07:30:06 UTC

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New package ggsem with initial version 0.1.0
Package: ggsem
Title: Interactively Visualize Structural Equation Modeling Diagrams
Version: 0.1.0
Maintainer: Seung Hyun Min <seung.min@mail.mcgill.ca>
Description: It allows users to perform interactive and reproducible visualizations of path diagrams for structural equation modeling (SEM) and small-to-medium sized networks using the 'ggplot2' engine. Its 'shiny' app provides an interface that allows extensive customization, and creates CSV outputs, which can then be used to recreate the figures either using the 'shiny' app or in a typical 'ggplot2' workflow.
License: GPL-2
Encoding: UTF-8
Depends: R (>= 3.4.0)
Imports: ggplot2, igraph, shiny, DT, colourpicker, grid, svglite, grDevices, stats, utils, lavaan
Suggests: semPlot
URL: https://smin95.github.io/ggsem/
BugReports: https://github.com/smin95/ggsem/issues/
NeedsCompilation: no
Packaged: 2024-11-01 05:11:51 UTC; sammi
Author: Seung Hyun Min [aut, cre]
Repository: CRAN
Date/Publication: 2024-11-05 07:30:10 UTC

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Package dfr (with last version 0.1.0) was removed from CRAN

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

2024-09-26 0.1.0

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Package faux (with last version 1.2.1) was removed from CRAN

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

2023-04-20 1.2.1

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Package sgs (with last version 0.3.0) was removed from CRAN

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

2024-09-18 0.3.0
2024-07-13 0.2.0
2023-08-22 0.1.1
2023-05-19 0.1.0

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Package infoelectoral (with last version 1.0.2) was removed from CRAN

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

2024-05-30 1.0.2
2024-05-21 1.0.1

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Package mgee2 updated to version 0.6 with previous version 0.5 dated 2023-12-02

Title: Marginal Analysis of Misclassified Longitudinal Ordinal Data
Description: Three estimating equation methods are provided in this package for marginal analysis of longitudinal ordinal data with misclassified responses and covariates. The naive analysis which is solely based on the observed data without adjustment may lead to bias. The corrected generalized estimating equations (GEE2) method which is unbiased requires the misclassification parameters to be known beforehand. The corrected generalized estimating equations (GEE2) with validation subsample method estimates the misclassification parameters based on a given validation set. This package is an implementation of Chen (2013) <doi:10.1002/bimj.201200195>.
Author: Yuliang Xu [aut, cre], Zhijian Chen [aut], Shuo Shuo Liu [aut], Grace Yi [aut]
Maintainer: Yuliang Xu <yuliangx@umich.edu>

Diff between mgee2 versions 0.5 dated 2023-12-02 and 0.6 dated 2024-11-05

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Package XNomial updated to version 1.0.4.1 with previous version 1.0.4 dated 2015-12-24

Title: Exact Goodness-of-Fit Test for Multinomial Data with Fixed Probabilities
Description: Tests whether a set of counts fit a given expected ratio. For example, a genetic cross might be expected to produce four types in the relative frequencies of 9:3:3:1. To see whether a set of observed counts fits this expectation, one can examine all possible outcomes with xmulti() or a random sample of them with xmonte() and find the probability of an observation deviating from the expectation by at least as much as the observed. As a measure of deviation from the expected, one can use the log-likelihood ratio, the multinomial probability, or the classic chi-square statistic. A histogram of the test statistic can also be plotted and compared with the asymptotic curve.
Author: Bill Engels [aut, cre]
Maintainer: Bill Engels <wrengels@wisc.edu>

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Package TrialSize updated to version 1.4.1 with previous version 1.4 dated 2020-07-06

Title: R Functions for Chapter 3,4,6,7,9,10,11,12,14,15 of Sample Size Calculation in Clinical Research
Description: Functions and Examples in Sample Size Calculation in Clinical Research.
Author: Ed Zhang ; Vicky Qian Wu ; Shein-Chung Chow ; Harry G.Zhang <ed.zhang.jr@gmail.com>
Maintainer: Vicky Qian Wu <wuqian7@gmail.com>

Diff between TrialSize versions 1.4 dated 2020-07-06 and 1.4.1 dated 2024-11-05

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Package mRMRe updated to version 2.1.2.2 with previous version 2.1.2.1 dated 2023-04-25

Title: Parallelized Minimum Redundancy, Maximum Relevance (mRMR)
Description: Computes mutual information matrices from continuous, categorical and survival variables, as well as feature selection with minimum redundancy, maximum relevance (mRMR) and a new ensemble mRMR technique. Published in De Jay et al. (2013) <doi:10.1093/bioinformatics/btt383>.
Author: Nicolas De Jay [aut], Simon Papillon-Cavanagh [aut], Catharina Olsen [aut], Gianluca Bontempi [aut], Bo Li [aut], Christopher Eeles [ctb], Benjamin Haibe-Kains [aut, cre]
Maintainer: Benjamin Haibe-Kains <benjamin.haibe.kains@utoronto.ca>

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Package KODAMA updated to version 2.4.1 with previous version 2.4 dated 2023-01-12

Title: Knowledge Discovery by Accuracy Maximization
Description: An unsupervised and semi-supervised learning algorithm that performs feature extraction from noisy and high-dimensional data. It facilitates identification of patterns representing underlying groups on all samples in a data set. Based on Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA. (2017) Bioinformatics <doi:10.1093/bioinformatics/btw705> and Cacciatore S, Luchinat C, Tenori L. (2014) Proc Natl Acad Sci USA <doi:10.1073/pnas.1220873111>.
Author: Stefano Cacciatore [aut, trl, cre] , Leonardo Tenori [aut]
Maintainer: Stefano Cacciatore <tkcaccia@gmail.com>

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Package ergm.multi updated to version 0.2.1.1 with previous version 0.2.1 dated 2024-02-20

Title: Fit, Simulate and Diagnose Exponential-Family Models for Multiple or Multilayer Networks
Description: A set of extensions for the 'ergm' package to fit multilayer/multiplex/multirelational networks and samples of multiple networks. 'ergm.multi' is a part of the Statnet suite of packages for network analysis. See Krivitsky, Koehly, and Marcum (2020) <doi:10.1007/s11336-020-09720-7> and Krivitsky, Coletti, and Hens (2023) <doi:10.1080/01621459.2023.2242627>.
Author: Pavel N. Krivitsky [aut, cre] , Mark S. Handcock [ctb], David R. Hunter [ctb], Chad Klumb [ctb], Pietro Coletti [ctb], Joyce Cheng [ctb]
Maintainer: Pavel N. Krivitsky <pavel@statnet.org>

Diff between ergm.multi versions 0.2.1 dated 2024-02-20 and 0.2.1.1 dated 2024-11-05

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Package RAFS (with last version 0.2.4) was removed from CRAN

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

2024-05-11 0.2.4
2023-07-10 0.2.3
2023-05-30 0.2.2

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Package Corbi (with last version 0.6-2) was removed from CRAN

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

2022-05-30 0.6-2
2020-12-10 0.6-1
2020-06-13 0.6-0
2019-11-22 0.5-0
2019-03-04 0.4-4
2018-12-18 0.4-3
2017-05-03 0.4-2
2016-09-20 0.4-1
2016-07-22 0.4-0
2016-06-28 0.3-5
2016-06-06 0.3-4

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Package CRF (with last version 0.4-3) was removed from CRAN

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

2019-12-01 0.4-3
2019-03-04 0.4-2
2018-12-27 0.4-1
2018-12-18 0.4-0
2018-05-07 0.3-16
2018-05-06 0.3-15
2017-02-01 0.3-14
2016-09-20 0.3-12
2016-08-28 0.3-11
2016-06-04 0.3-10
2016-05-30 0.3-9
2014-07-30 0.3-8
2014-05-06 0.3-7
2014-02-17 0.3-6

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Package MDFS (with last version 1.5.3) was removed from CRAN

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

2023-05-09 1.5.3
2023-04-11 1.5.1
2023-03-14 1.5.0
2023-01-31 1.4.0
2022-04-19 1.3.0
2021-02-09 1.2.0
2021-01-21 1.1.1
2021-01-06 1.1.0
2019-11-10 1.0.5
2019-10-27 1.0.4
2018-11-08 1.0.3
2018-10-31 1.0.2
2018-06-26 1.0.1
2018-06-15 1.0.0

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