Sun, 17 Dec 2023

Package stepp updated to version 3.2.6 with previous version 3.2.5 dated 2022-06-18

Title: Subpopulation Treatment Effect Pattern Plot (STEPP)
Description: A method to explore the treatment-covariate interactions in survival or generalized linear model (GLM) for continuous, binomial and count data arising from two or more treatment arms of a clinical trial. A permutation distribution approach to inference is implemented, based on permuting the covariate values within each treatment group.
Author: Wai-ki Yip [aut, cre], Ann Lazar [ctb], David Zahrieh [ctb], Chip Cole [ctb], Ann Lazar [ctb], Marco Bonetti [ctb], Victoria Wang [ctb], William Barcella [ctb], Sergio Venturini [aut] Richard Gelber [ctb]
Maintainer: Wai-ki Yip <yuser86@yahoo.com>

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Package Durga updated to version 2.0 with previous version 1.1.0 dated 2023-06-14

Title: Effect Size Estimation and Visualisation
Description: An easy-to-use yet powerful system for plotting grouped data effect sizes. Various types of effect size can be estimated, then plotted together with a representation of the original data. Select from many possible data representations (box plots, violin plots, raw data points etc.), and combine as desired. 'Durga' plots are implemented in base R, so are compatible with base R methods for combining plots, such as 'layout()'. See Khan & McLean (2023) <doi:10.1101/2023.02.06.526960>.
Author: Kawsar Khan [aut] , Jim McLean [aut, cre]
Maintainer: Jim McLean <jim_mclean@optusnet.com.au>

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Package migraph updated to version 1.2.1 with previous version 1.1.5 dated 2023-11-02

Title: Multimodal Network Analysis and More
Description: A set of tools for analysing multimodal networks. It includes functions for measuring centrality, centralization, cohesion, closure, constraint and diversity, as well as for network block-modelling, regression, and diffusion models. The package is released as a complement to 'Multimodal Political Networks' (2021, ISBN:9781108985000), and includes various datasets used in the book. Built on the 'manynet' package, 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.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb] , Jael Tan [ctb] , Bernhard Bieri [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

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Package littler updated to version 0.3.19 with previous version 0.3.18 dated 2023-03-26

Title: R at the Command-Line via 'r'
Description: A scripting and command-line front-end is provided by 'r' (aka 'littler') as a lightweight binary wrapper around the GNU R language and environment for statistical computing and graphics. While R can be used in batch mode, the r binary adds full support for both 'shebang'-style scripting (i.e. using a hash-mark-exclamation-path expression as the first line in scripts) as well as command-line use in standard Unix pipelines. In other words, r provides the R language without the environment.
Author: Dirk Eddelbuettel and Jeff Horner
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package radiant updated to version 1.6.1 with previous version 1.6.0 dated 2023-09-11

Title: Business Analytics using R and Shiny
Description: A platform-independent browser-based interface for business analytics in R, based on the shiny package. The application combines the functionality of 'radiant.data', 'radiant.design', 'radiant.basics', 'radiant.model', and 'radiant.multivariate'.
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>

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Package eodhd updated to version 1.0.3 with previous version 1.0.2 dated 2023-11-19

Title: Official 'eodhd' API R Financial Library
Description: Official 'eodhd' API R Library. It helps to get and work with financial data, historical data and etc. API reference available at <https://eodhd.com/financial-apis/>.
Author: Ivanchenko Gleb Developer [aut, cre], EODHD Maintainer [cph]
Maintainer: Ivanchenko Gleb Developer <kross_10@mail.ru>

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New package snpAIMeR with initial version 2.1.0
Package: snpAIMeR
Title: Assess the Diagnostic Power of Genomic Marker Combinations
Version: 2.1.0
Description: Population genetics package for designing diagnostic panels. Candidate markers, marker combinations, and different panel sizes are assessed for how well they can predict the source population of known samples. Requires a genotype file of candidate markers in STRUCTURE format. Methods for population cross-validation are described in Jombart (2008) <doi:10.1093/bioinformatics/btn129>.
License: MIT + file LICENSE
Contact: Kim Vertacnik <kim.vertacnik@mailbox.org> or Julian Dupuis <julian.dupuis@uky.edu>
URL: https://github.com/OksanaVe/snpAIMeR
Depends: R (>= 2.10)
Imports: adegenet, doParallel, dplyr, forcats, foreach, ggplot2, graphics, magrittr, parallel, readr, tidyr, utils, withr, yaml
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2023-12-15 22:10:45 UTC; kimvertacnik
Author: Kim Vertacnik [cre, aut] , Oksana Vernygora [aut] , Julian Dupuis [aut]
Maintainer: Kim Vertacnik <kim.vertacnik@mailbox.org>
Repository: CRAN
Date/Publication: 2023-12-17 08:00:02 UTC

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Package radiant.data updated to version 1.6.3 with previous version 1.6.2 dated 2023-10-16

Title: Data Menu for Radiant: Business Analytics using R and Shiny
Description: The Radiant Data menu includes interfaces for loading, saving, viewing, visualizing, summarizing, transforming, and combining data. It also contains functionality to generate reproducible reports of the analyses conducted in the application.
Author: Vincent Nijs [aut, cre], Niklas von Hertzen [aut]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>

Diff between radiant.data versions 1.6.2 dated 2023-10-16 and 1.6.3 dated 2023-12-17

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Package PWEXP updated to version 0.4.3 with previous version 0.4.2 dated 2023-12-07

Title: Piecewise Exponential Distribution Prediction Model
Description: Build piecewise exponential survival model for study design (planning) and event/timeline prediction.
Author: Tianchen Xu [aut, cre]
Maintainer: Tianchen Xu <zjph602xutianchen@gmail.com>

Diff between PWEXP versions 0.4.2 dated 2023-12-07 and 0.4.3 dated 2023-12-17

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Package mRpostman updated to version 1.1.2 with previous version 1.1.0 dated 2022-10-27

Title: An IMAP Client for R
Description: An easy-to-use IMAP client that provides tools for message searching, selective fetching of message attributes, mailbox management, attachment extraction, and several other IMAP features, paving the way for e-mail data analysis in R.
Author: Allan Quadros [aut, cre] , Paul Smith [ctb], Kurt Hornik [ctb]
Maintainer: Allan Quadros <allanvcq@gmail.com>

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New package lorad with initial version 0.0.1.0
Package: lorad
Title: Lowest Radial Distance Method of Marginal Likelihood Estimation
Version: 0.0.1.0
Description: Estimates marginal likelihood from a posterior sample using the method described in Wang et al. (2023) <doi:10.1093/sysbio/syad007>, which does not require evaluation of any additional points and requires only the log of the unnormalized posterior density for each sampled parameter vector.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0), rstan (>= 2.32), bridgesampling (>= 1.1)
Imports: stats
Maintainer: Analisa Milkey <analisa.milkey@uconn.edu>
Author: Analisa Milkey [aut, cre] , Elena Korte [aut], Paul O. Lewis [aut]
VignetteBuilder: knitr, rmarkdown
Depends: R (>= 3.0)
LazyData: true
NeedsCompilation: no
Packaged: 2023-12-15 20:27:47 UTC; analisamilkey
Repository: CRAN
Date/Publication: 2023-12-17 08:00:05 UTC

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New package ggbiplot with initial version 0.6.1
Package: ggbiplot
Title: A Grammar of Graphics Implementation of Biplots
Version: 0.6.1
Date: 2023-12-12
Description: A 'ggplot2' based implementation of biplots, giving a representation of a dataset in a two dimensional space accounting for the greatest variance, together with variable vectors showing how the data variables relate to this space. It provides a replacement for stats::biplot(), but with many enhancements to control the analysis and graphical display. It implements biplot and scree plot methods which can be used with the results of prcomp(), princomp(), FactoMineR::PCA() or MASS::lda() and can be customized using 'ggplot2' techniques.
Depends: R (>= 3.5.0)
Imports: ggplot2, scales
Suggests: corrplot, dplyr, MASS
License: GPL-2
Encoding: UTF-8
Language: en-US
URL: https://github.com/friendly/ggbiplot
BugReports: https://github.com/friendly/ggbiplot/issues
LazyData: true
NeedsCompilation: no
Packaged: 2023-12-15 18:09:52 UTC; friendly
Author: Vincent Vu [aut], Michael Friendly [aut, cre] , Aghasi Tavadyan [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>
Repository: CRAN
Date/Publication: 2023-12-17 07:50:13 UTC

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New package extBatchMarking with initial version 1.0
Package: extBatchMarking
Title: Extended Batch Marking Models
Version: 1.0
Date: 2023-12-08
Maintainer: Kehinde Olobatuyi <olobatuyikenny@uvic.ca>
Description: A system for batch-marking data analysis to estimate survival probabilities, capture probabilities, and enumerate the population abundance for both marked and unmarked individuals. The estimation of only marked individuals can be achieved through the batchMarkOptim() function. Similarly, the combined marked and unmarked can be achieved through the batchMarkUnmarkOptim() function. The algorithm was also implemented for the hidden Markov model encapsulated in batchMarkUnmarkOptim() to estimate the abundance of both marked and unmarked individuals in the population. The package is based on the paper: "Hidden Markov Models for Extended Batch Data" of Cowen et al. (2017) <doi:10.1111/biom.12701>.
License: AGPL (>= 3)
Encoding: UTF-8
LinkingTo: Rcpp, RcppArmadillo
Imports: doParallel, foreach, optimbase, Rcpp, parallel
Depends: R (>= 4.0)
LazyData: true
Suggests: testthat (>= 3.0.0), knitr
URL: https://github.com/Olobatuyi/extBatchMarking
BugReports: https://github.com/Olobatuyi/extBatchMarking/issues
NeedsCompilation: yes
Packaged: 2023-12-15 21:44:00 UTC; olobatuyikenny
Author: Kehinde Olobatuyi [aut, cre] , Simon Johns [aut], Matthew RP Parker [aut] , Steve Hof [aut], Laura LE Cowen [aut]
Repository: CRAN
Date/Publication: 2023-12-17 08:00:08 UTC

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New package EHRtemporalVariability with initial version 1.2.0
Package: EHRtemporalVariability
Title: Delineating Temporal Dataset Shifts in Electronic Health Records
Version: 1.2.0
Date: 2023-12-15
Encoding: UTF-8
Description: Functions to delineate temporal dataset shifts in Electronic Health Records through the projection and visualization of dissimilarities among data temporal batches. This is done through the estimation of data statistical distributions over time and their projection in non-parametric statistical manifolds, uncovering the patterns of the data latent temporal variability. 'EHRtemporalVariability' is particularly suitable for multi-modal data and categorical variables with a high number of values, common features of biomedical data where traditional statistical process control or time-series methods may not be appropriate. 'EHRtemporalVariability' allows you to explore and identify dataset shifts through visual analytics formats such as Data Temporal heatmaps and Information Geometric Temporal (IGT) plots. An additional 'EHRtemporalVariability' Shiny app can be used to load and explore the package results and even to allow the use of these functions to those users non-experienced in R codi [...truncated...]
Depends: R (>= 4.3.0), dplyr
License: Apache License 2.0 | file LICENSE
Imports: plotly, zoo, xts, lubridate, RColorBrewer, viridis, scales, methods, MASS
Suggests: knitr, rmarkdown, devtools, BiocStyle, dbscan, webshot, httr
VignetteBuilder: knitr
NeedsCompilation: no
Maintainer: Carlos Saez <carsaesi@upv.es>
URL: https://github.com/hms-dbmi/EHRtemporalVariability
Packaged: 2023-12-15 19:10:51 UTC; Carlos
Author: Carlos Saez [aut, cre], Alba Gutierrez-Sacristan [aut], Isaac Kohane [aut], Juan M Garcia-Gomez [aut], Paul Avillach [aut], Biomedical Data Science Lab, Universitat Politecnica de Valencia [cph], Department of Biomedical Informatics, Harvard Medical [...truncated...]
Repository: CRAN
Date/Publication: 2023-12-17 07:30:09 UTC

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Package bidask updated to version 2.0.2 with previous version 2.0.0 dated 2023-12-12

Title: Efficient Estimation of Bid-Ask Spreads from Open, High, Low, and Close Prices
Description: Implements an efficient estimator of bid-ask spreads from open, high, low, and close prices as described in Ardia, Guidotti, & Kroencke (2021) <https://www.ssrn.com/abstract=3892335>. It also provides an implementation of the estimators described in Roll (1984) <doi:10.1111/j.1540-6261.1984.tb03897.x>, Corwin & Schultz (2012) <doi:10.1111/j.1540-6261.2012.01729.x>, and Abdi & Ranaldo (2017) <doi:10.1093/rfs/hhx084>.
Author: Emanuele Guidotti [aut, cre] , David Ardia [ctb] , Tim Kroencke [ctb]
Maintainer: Emanuele Guidotti <emanuele.guidotti@usi.ch>

Diff between bidask versions 2.0.0 dated 2023-12-12 and 2.0.2 dated 2023-12-17

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