Fri, 13 May 2022

Package egor updated to version 1.22.5 with previous version 1.22.1 dated 2022-01-14

Title: Import and Analyse Ego-Centered Network Data
Description: Tools for importing, analyzing and visualizing ego-centered network data. Supports several data formats, including the export formats of 'EgoNet', 'EgoWeb 2.0' and 'openeddi'. An interactive (shiny) app for the intuitive visualization of ego-centered networks is provided. Also included are procedures for creating and visualizing Clustered Graphs (Lerner 2008 <DOI:10.1109/PACIFICVIS.2008.4475458>).
Author: Till Krenz [aut, cre], Pavel N. Krivitsky [aut], Raffaele Vacca [aut], Michal Bojanowski [aut] , Markus Gamper [ctb], Andreas Herz [aut], Christopher McCarty [ctb]
Maintainer: Till Krenz <egor@tillt.net>

Diff between egor versions 1.22.1 dated 2022-01-14 and 1.22.5 dated 2022-05-13

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Package pscore updated to version 0.4.0 with previous version 0.1-2 dated 2015-06-24

Title: Standardizing Physiological Composite Risk Endpoints
Description: Provides a number of functions to simplify and automate the scoring, comparison, and evaluation of different ways of creating composites of data. It is particularly aimed at facilitating the creation of physiological composites of metabolic syndrome symptom score (MetSSS) and allostatic load (AL). Provides a wrapper to calculate the MetSSS on new data using the Healthy Hearts formula.
Author: Joshua F. Wiley [aut, cre]
Maintainer: Joshua F. Wiley <jwiley.psych@gmail.com>

Diff between pscore versions 0.1-2 dated 2015-06-24 and 0.4.0 dated 2022-05-13

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Package gap updated to version 1.2.3-6 with previous version 1.2.3-1 dated 2021-04-21

Title: Genetic Analysis Package
Description: As first reported [Zhao, J. H. 2007. "gap: Genetic Analysis Package". J Stat Soft 23(8):1-18. <doi:10.18637/jss.v023.i08>], it is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates. Over years, the package has been developed in-between many projects hence also in line with the name (gap).
Author: Jing Hua Zhao [aut, cre] , Kurt Hornik [ctb], Brian Ripley [ctb], Uwe Liggs [ctb]
Maintainer: Jing Hua Zhao <jinghuazhao@hotmail.com>

Diff between gap versions 1.2.3-1 dated 2021-04-21 and 1.2.3-6 dated 2022-05-13

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More information about gap at CRAN
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Package textometry updated to version 0.1.5 with previous version 0.1.4 dated 2015-01-09

Title: Textual Data Analysis Package Used by the TXM Software
Description: Statistical exploration of textual corpora using several methods from French 'Textometrie' (new name of 'Lexicometrie') and French 'Data Analysis' schools. It includes methods for exploring irregularity of distribution of lexicon features across text sets or parts of texts (Specificity analysis); multi-dimensional exploration (Factorial analysis), etc. Those methods are used in the TXM software.
Author: Sylvain Loiseau, Lise Vaudor, Matthieu Decorde, Serge Heiden
Maintainer: Matthieu Decorde <matthieu.decorde@ens-lyon.fr>

Diff between textometry versions 0.1.4 dated 2015-01-09 and 0.1.5 dated 2022-05-13

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New package PVplr with initial version 0.1.1
Package: PVplr
Title: Performance Loss Rate Analysis Pipeline
Version: 0.1.1
Description: The pipeline contained in this package provides tools used in the Solar Durability and Lifetime Extension Center (SDLE) for the analysis of Performance Loss Rates (PLR) in real world photovoltaic systems. Functions included allow for data cleaning, feature correction, power predictive modeling, PLR determination, and uncertainty bootstrapping through various methods <doi:10.1109/PVSC40753.2019.8980928>. The vignette "Pipeline Walkthrough" gives an explicit run through of typical package usage. This material is based upon work supported by the U.S Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy Technologies Office (SETO) Agreement Number DE-EE-0008172. This work made use of the High Performance Computing Resource in the Core Facility for Advanced Research Computing at Case Western Reserve University.
Depends: R (>= 2.10)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr (>= 0.7.8), magrittr (>= 1.5), broom (>= 0.5.1), ggplot2 (>= 3.1.0), stlplus (>= 0.5.1), cluster (>= 2.0.7-1), purrr (>= 0.3.3), tidyr (>= 1.1.1), minpack.lm (>= 1.2-1), rlang (>= 0.3.1), segmented, forecast, scales, zoo
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-04-25 19:24:55 UTC; wco3
Author: Alan Curran [aut] , Tyler Burleyson [aut] , William Oltjen [aut] , Sascha Lindig [aut] , David Moser [aut] , Roger French [aut, cre] , Solar Durability and Lifetime Extension research center [cph, fnd]
Maintainer: Roger French <roger.french@case.edu>
Repository: CRAN
Date/Publication: 2022-05-13 21:10:02 UTC

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Package PhageCocktail updated to version 1.0.3 with previous version 1.0.2 dated 2022-05-10

Title: Design of the Best Phage Cocktail
Description: There are 4 possible methods: "ExhaustiveSearch"; "ExhaustivePhi"; "ClusteringSearch"; and "ClusteringPhi". "ExhaustiveSearch"--> gives you the best phage cocktail from a phage-bacteria infection network. It checks different phage cocktail sizes from 1 to 7 and only stops before if it lyses all bacteria. Other option is when users have decided not to obtain a phage cocktail size higher than a limit value. "ExhaustivePhi"--> firstly, it finds Phi out. Phi is a formula indicating the necessary phage cocktail size. Phi needs nestedness temperature and fill, which are internally calculated. This function will only look for the best combination (phage cocktail) with a Phi size. "ClusteringSearch"--> firstly, an agglomerative hierarchical clustering using Ward's algorithm is calculated for phages. They will be clustered according to bacteria lysed by them. PhageCocktail() chooses how many clusters are needed in order to select 1 phage per cluster. Using the phages selected during the clustering, it checks different phage cocktail sizes from 1 to 7 and only stops before if it lyses all bacteria. Other option is when users have decided not to obtain a phage cocktail size higher than a limit value. "ClusteringPhi"--> firstly, an agglomerative hierarchical clustering using Ward's algorithm is calculated for phages. They will be clustered according to bacteria lysed by them. PhageCocktail() chooses how many clusters are needed in order to select 1 phage per cluster. Once the function has one phage per cluster, it calculates Phi. If the number of clusters is less than Phi number, it will be changed to obtain, as minimum, this quantity of candidates (phages). Then, it calculates the best combination of Phi phages using those selected during the clustering with Ward algorithm. If you use PhageCocktail, please cite it as: "PhageCocktail: An R Package to Design Phage Cocktails from Experimental Phage-Bacteria Infection Networks". María Victoria Díaz-Galián, Miguel A. Vega-Rodríguez, Felipe Molina. Computer Methods and Programs in Biomedicine, 221, 106865, Elsevier Ireland, Clare, Ireland, 2022, pp. 1-9, ISSN: 0169-2607. <doi:10.1016/j.cmpb.2022.106865>.
Author: Maria Victoria Diaz-Galian [aut, cre] , Miguel A. Vega-Rodriguez [aut] , Felipe Molina [aut]
Maintainer: Maria Victoria Diaz-Galian <mvdiazgalian@unex.es>

Diff between PhageCocktail versions 1.0.2 dated 2022-05-10 and 1.0.3 dated 2022-05-13

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Permanent link

Package semtree updated to version 0.9.18 with previous version 0.9.17 dated 2021-07-30

Title: Recursive Partitioning for Structural Equation Models
Description: SEM Trees and SEM Forests -- an extension of model-based decision trees and forests to Structural Equation Models (SEM). SEM trees hierarchically split empirical data into homogeneous groups each sharing similar data patterns with respect to a SEM by recursively selecting optimal predictors of these differences. SEM forests are an extension of SEM trees. They are ensembles of SEM trees each built on a random sample of the original data. By aggregating over a forest, we obtain measures of variable importance that are more robust than measures from single trees. A description of the method was published by Brandmaier, von Oertzen, McArdle, & Lindenberger (2013) <doi:10.1037/a0030001> and Arnold, Voelkle, & Brandmaier (2020) <doi:10.3389/fpsyg.2020.564403>.
Author: Andreas M. Brandmaier [aut, cre], John J. Prindle [aut], Manuel Arnold [aut], Caspar J. Van Lissa [aut]
Maintainer: Andreas M. Brandmaier <andy@brandmaier.de>

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More information about semtree at CRAN
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Package scoringutils updated to version 1.0.0 with previous version 0.1.7.2 dated 2021-07-21

Title: Utilities for Scoring and Assessing Predictions
Description: Provides a collection of metrics and proper scoring rules (Tilmann Gneiting & Adrian E Raftery (2007) <doi:10.1198/016214506000001437>, Jordan, A., Krüger, F., & Lerch, S. (2019) <doi:10.18637/jss.v090.i12>) within a consistent framework for evaluation, comparison and visualisation of forecasts. In addition to proper scoring rules, functions are provided to assess bias, sharpness and calibration (Sebastian Funk, Anton Camacho, Adam J. Kucharski, Rachel Lowe, Rosalind M. Eggo, W. John Edmunds (2019) <doi:10.1371/journal.pcbi.1006785>) of forecasts. Several types of predictions (e.g. binary, discrete, continuous) which may come in different formats (e.g. forecasts represented by predictive samples or by quantiles of the predictive distribution) can be evaluated. Scoring metrics can be used either through a convenient data.frame format, or can be applied as individual functions in a vector / matrix format. All functionality has been implemented with a focus on performance and is robustly tested.
Author: Nikos Bosse [aut, cre] , Sam Abbott [aut] , Hugo Gruson [aut] , Johannes Bracher [ctb] , Sebastian Funk [ctb]
Maintainer: Nikos Bosse <nikosbosse@gmail.com>

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More information about scoringutils at CRAN
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Package optmatch updated to version 0.10.1 with previous version 0.10.0 dated 2022-03-15

Title: Functions for Optimal Matching
Description: Distance based bipartite matching using minimum cost flow, oriented to matching of treatment and control groups in observational studies (Hansen and Klopfer 2006 <doi:10.1198/106186006X137047>). Routines are provided to generate distances from generalised linear models (propensity score matching), formulas giving variables on which to limit matched distances, stratified or exact matching directives, or calipers, alone or in combination.
Author: Ben Hansen [aut], Mark Fredrickson [aut], Josh Errickson [cre, aut], Josh Buckner [aut], Adam Rauh [ctb]
Maintainer: Josh Errickson <jerrick@umich.edu>

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Package moveHMM updated to version 1.8 with previous version 1.7 dated 2019-05-19

Title: Animal Movement Modelling using Hidden Markov Models
Description: Provides tools for animal movement modelling using hidden Markov models. These include processing of tracking data, fitting hidden Markov models to movement data, visualization of data and fitted model, decoding of the state process...
Author: Theo Michelot, Roland Langrock, Toby Patterson, Brett McClintock, Eric Rexstad
Maintainer: Theo Michelot <tm75@st-andrews.ac.uk>

Diff between moveHMM versions 1.7 dated 2019-05-19 and 1.8 dated 2022-05-13

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Package LSDinterface updated to version 1.2.1 with previous version 1.2.0 dated 2022-02-27

Title: Interface Tools for LSD Simulation Results Files
Description: Interfaces R with LSD simulation models. Reads object-oriented data in results files (.res[.gz]) produced by LSD and creates appropriate multi-dimensional arrays in R. Supports multiple core parallel threads of multi-file data reading for increased performance. Also provides functions to extract basic information and statistics from data files. LSD (Laboratory for Simulation Development) is free software developed by Marco Valente and Marcelo C. Pereira (documentation and downloads available at <https://www.labsimdev.org/>).
Author: Marcelo C. Pereira [aut, cre]
Maintainer: Marcelo C. Pereira <mcper@unicamp.br>

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Package hlaR updated to version 0.1.3 with previous version 0.1.2 dated 2022-02-01

Title: Tools for HLA Data
Description: A streamlined tool for eplet analysis of donor and recipient HLA (human leukocyte antigen) mismatch. Messy, low-resolution HLA typing data is cleaned, and imputed to high-resolution using the NMDP (National Marrow Donor Program) haplotype reference database <https://haplostats.org/haplostats>. High resolution data is analyzed for overall or single antigen eplet mismatch using a reference table (currently supporting 'HLAMatchMaker' <http://www.epitopes.net> versions 2 and 3). Data can enter or exit the workflow at different points depending on the user's aims and initial data quality.
Author: Joan Zhang [aut, cre], Aileen Johnson [aut], Christian P Larsen [cph, aut]
Maintainer: Joan Zhang <joan.zhang@emory.edu>

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Package DanielBiostatistics10th updated to version 0.1.2 with previous version 0.1.1 dated 2022-05-06

Title: Functions for Wayne W. Daniel's Biostatistics, Tenth Edition
Description: Functions to accompany Wayne W. Daniel's Biostatistics: A Foundation for Analysis in the Health Sciences, Tenth Edition.
Author: Tingting Zhan [aut, cre, cph]
Maintainer: Tingting Zhan <tingtingzhan@gmail.com>

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Package bumbl updated to version 1.0.2 with previous version 1.0.1 dated 2021-08-25

Title: Tools for Modeling Bumblebee Colony Growth and Decline
Description: Bumblebee colonies grow during worker production, then decline after switching to production of reproductive individuals (drones and gynes). This package provides tools for modeling and visualizing this pattern by identifying a switchpoint with a growth rate before and a decline rate after the switchpoint. The mathematical models fit by bumbl are described in Crone and Williams (2016) <doi:10.1111/ele.12581>.
Author: Eric R. Scott [aut, cre]
Maintainer: Eric R. Scott <scottericr@gmail.com>

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New package pepe with initial version 1.2.0
Package: pepe
Title: Data Manipulation
Version: 1.2.0
Author: Seyma Kalay
Maintainer: Seyma Kalay <seymakalay@hotmail.com>
Description: Is designed to make easier printing summary statistics (for continues and factor level) tables in Latex, and plotting by factor.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/seymakalay/pepe
BugReports: https://github.com/seymakalay/pepe/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 2.10)
Imports: dplyr, ggplot2, psych, tidyr, utils
NeedsCompilation: no
Packaged: 2022-05-12 14:26:14 UTC; Seyma
Repository: CRAN
Date/Publication: 2022-05-13 16:40:02 UTC

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Permanent link

New package NiLeDAM with initial version 0.2
Package: NiLeDAM
Title: Monazite Dating for the NiLeDAM Team
Version: 0.2
Date: 2022-05-12
Maintainer: Nathalie Vialaneix <nathalie.vialaneix@inrae.fr>
Description: Th-U-Pb electron microprobe age dating of monazite, as originally described in <doi:10.1016/0009-2541(96)00024-1>.
License: GPL (>= 2)
Depends: R (>= 2.4.0)
Imports: dplyr, ggplot2, magrittr, methods, nleqslv, rlang, scales, shiny, shinyjs, shinythemes, stats, thematic, tidyr
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Repository: CRAN
Language: en-US
NeedsCompilation: no
Packaged: 2022-05-12 10:29:00 UTC; nathalie
Author: Nathalie Vialaneix [aut, trl, cre], Aurelie Mercadie [aut], Jean-Marc Montel [aut], Anne-Magali Seydoux-Guillaume [ctb]
Date/Publication: 2022-05-13 16:10:02 UTC

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New package linelist with initial version 0.0.1
Package: linelist
Title: Tagging and Validating Epidemiological Data
Version: 0.0.1
Description: Provides tools to help storing and handling case line list data. The 'linelist' class adds a tagging system to classical 'data.frame' objects to identify key epidemiological data such as dates of symptom onset, epidemiological case definition, age, gender or disease outcome. Once tagged, these variables can be seamlessly used in downstream analyses, making data pipelines more robust and reliable.
License: MIT + file LICENSE
URL: https://github.com/epiverse-trace/linelist
BugReports: https://github.com/epiverse-trace/linelist/issues
Encoding: UTF-8
Imports: checkmate
Suggests: callr, covr, dplyr, knitr, magrittr, outbreaks, rmarkdown, testthat, tibble
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-05-12 13:17:06 UTC; thibaut
Author: Thibaut Jombart [aut, cre]
Maintainer: Thibaut Jombart <thibaut@data.org>
Repository: CRAN
Date/Publication: 2022-05-13 16:30:02 UTC

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New package jgsbook with initial version 1.0
Package: jgsbook
Title: Package of the German Book "Statistik mit R und RStudio" by Joerg grosse Schlarmann
Author: Joerg grosse Schlarmann
Maintainer: Joerg grosse Schlarmann <schlarmann@produnis.de>
Description: All datasets and functions used in the german book "Statistik mit R und RStudio" by Joerg grosse Schlarmann. You can read it online at <https://www.produnis.de/R/> .
Version: 1.0
Date: 2022-05-12
Language: de-de
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Encoding: UTF-8
Imports: statip
LazyData: true
NeedsCompilation: no
Packaged: 2022-05-12 10:09:42 UTC; produnis
Repository: CRAN
Date/Publication: 2022-05-13 16:00:02 UTC

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New package geomaroc with initial version 0.1.1
Package: geomaroc
Title: Easily Visualize Geographic Data of Morocco
Version: 0.1.1
Maintainer: Amine Andam <andamamine83@gmail.com>
Description: Tools to easily visualize geographic data of Morocco. This package interacts with data available through the 'geomarocdata' package, which is available in a 'drat' repository. The size of the 'geomarocdata' package is approximately 12 MB.
License: GPL
Imports: jsonlite , sf
Encoding: UTF-8
URL: https://github.com/AmineAndam04/R-geomaroc
Suggests: knitr, rmarkdown, testthat, geomarocdata
Additional_repositories: https://amineandam04.github.io/drat/
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-05-11 15:02:06 UTC; pc
Author: Amine Andam [aut, cre]
Repository: CRAN
Date/Publication: 2022-05-13 16:00:06 UTC

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Package vein updated to version 0.9.6 with previous version 0.9.5 dated 2022-02-06

Title: Vehicular Emissions Inventories
Description: Elaboration of vehicular emissions inventories, consisting in four stages, pre-processing activity data, preparing emissions factors, estimating the emissions and post-processing of emissions in maps and databases. More details in Ibarra-Espinosa et al (2018) <doi:10.5194/gmd-11-2209-2018>. Before using VEIN you need to know the vehicular composition of your study area, in other words, the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to start with the project to download a template to create a structure of directories and scripts.
Author: Sergio Ibarra-Espinosa [aut, cre] , Joao Bazzo [ctb]
Maintainer: Sergio Ibarra-Espinosa <zergioibarra@gmail.com>

Diff between vein versions 0.9.5 dated 2022-02-06 and 0.9.6 dated 2022-05-13

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Package unifir updated to version 0.2.1 with previous version 0.2.0 dated 2022-05-04

Title: A Unifying API for Calling the 'Unity' '3D' Video Game Engine
Description: Functions for the creation and manipulation of scenes and objects within the 'Unity' '3D' video game engine (<https://unity.com/>). Specific focuses include the creation and import of terrain data and 'GameObjects' as well as scene management.
Author: Michael Mahoney [aut, cre] , Will Jones [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/521>), Tan Tran [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/521>)
Maintainer: Michael Mahoney <mike.mahoney.218@gmail.com>

Diff between unifir versions 0.2.0 dated 2022-05-04 and 0.2.1 dated 2022-05-13

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Package squeezy updated to version 1.1-1 with previous version 1.1 dated 2022-03-22

Title: Group-Adaptive Elastic Net Penalised Generalised Linear Models
Description: Fit linear and logistic regression models penalised with group-adaptive elastic net penalties. The group penalties correspond to groups of covariates defined by a co-data group set. The method accommodates inclusion of unpenalised covariates and overlapping groups. See Van Nee et al. (2021) <arXiv:2101.03875>.
Author: Mirrelijn M. van Nee [aut, cre], Tim van de Brug [aut], Mark A. van de Wiel [aut]
Maintainer: Mirrelijn M. van Nee <m.vannee@amsterdamumc.nl>

Diff between squeezy versions 1.1 dated 2022-03-22 and 1.1-1 dated 2022-05-13

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Package mycobacrvR updated to version 1.1 with previous version 1.0 dated 2013-12-26

Title: Integrative Immunoinformatics for Mycobacterial Diseases in R Platform
Description: The mycobacrvR package contains utilities to provide detailed information for B cell and T cell epitopes for predicted adhesins from various servers such as ABCpred, Bcepred, Bimas, Propred, NetMHC and IEDB. Please refer the URL below to download data files (data_mycobacrvR.zip) used in functions of this package.
Author: Deepika Kulshreshtha, Rupanjali Chaudhuri, Surabhi Seth, S. Ramachandran
Maintainer: S. Ramachandran<ramu@igib.in>

Diff between mycobacrvR versions 1.0 dated 2013-12-26 and 1.1 dated 2022-05-13

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Package ecpc updated to version 3.1 with previous version 3.0 dated 2022-03-22

Title: Flexible Co-Data Learning for High-Dimensional Prediction
Description: Fit linear, logistic and Cox survival regression models penalised with adaptive multi-group ridge penalties. The multi-group penalties correspond to groups of covariates defined by (multiple) co-data sources. Group hyperparameters are estimated with an empirical Bayes method of moments, penalised with an extra level of hyper shrinkage. Various types of hyper shrinkage may be used for various co-data. Co-data may be continuous or categorical. The method accommodates inclusion of unpenalised covariates, posterior selection of covariates and multiple data types. The model fit is used to predict for new samples. The name 'ecpc' stands for Empirical Bayes, Co-data learnt, Prediction and Covariate selection. See Van Nee et al. (2020) <arXiv:2005.04010>.
Author: Mirrelijn M. van Nee [aut, cre], Lodewyk F.A. Wessels [aut], Mark A. van de Wiel [aut]
Maintainer: Mirrelijn M. van Nee <m.vannee@amsterdamumc.nl>

Diff between ecpc versions 3.0 dated 2022-03-22 and 3.1 dated 2022-05-13

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Package berryFunctions updated to version 1.21.14 with previous version 1.21.2 dated 2022-03-14

Title: Function Collection Related to Plotting and Hydrology
Description: Draw horizontal histograms, color scattered points by 3rd dimension, enhance date- and log-axis plots, zoom in X11 graphics, trace errors and warnings, use the unit hydrograph in a linear storage cascade, convert lists to data.frames and arrays, fit multiple functions.
Author: Berry Boessenkool
Maintainer: Berry Boessenkool <berry-b@gmx.de>

Diff between berryFunctions versions 1.21.2 dated 2022-03-14 and 1.21.14 dated 2022-05-13

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Package NMOF updated to version 2.5-1 with previous version 2.5-0 dated 2021-10-20

Title: Numerical Methods and Optimization in Finance
Description: Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments such as bonds and options, for portfolio selection and functions that help with stochastic simulations.
Author: Enrico Schumann [aut, cre]
Maintainer: Enrico Schumann <es@enricoschumann.net>

Diff between NMOF versions 2.5-0 dated 2021-10-20 and 2.5-1 dated 2022-05-13

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Package DDIwR updated to version 0.11 with previous version 0.10 dated 2022-04-20

Title: DDI with R
Description: Useful functions for various DDI (Data Documentation Initiative) related inputs and outputs. Converts data files to and from SPSS, Stata, SAS, R and Excel, including user declared missing values.
Author: Adrian Dusa [aut, cre, cph]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

Diff between DDIwR versions 0.10 dated 2022-04-20 and 0.11 dated 2022-05-13

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Package aRtsy updated to version 0.1.8 with previous version 0.1.7 dated 2022-04-10

Title: Generative Art with 'ggplot2'
Description: Provides algorithms for creating artworks in the 'ggplot2' language that incorporate some form of randomness.
Author: Koen Derks [aut, cre]
Maintainer: Koen Derks <koen-derks@hotmail.com>

Diff between aRtsy versions 0.1.7 dated 2022-04-10 and 0.1.8 dated 2022-05-13

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New package ycevo with initial version 0.1.0
Package: ycevo
Title: Nonparametric Estimation of the Yield Curve Evolution
Version: 0.1.0
Maintainer: Yangzhuoran Fin Yang <yangyangzhuoran@gmail.com>
Description: Nonparametric estimation of the discount rate and yield curve. Koo, B., La Vecchia, D., & Linton, O. B. (2021) <doi:10.1016/j.jeconom.2020.04.014> describe the application with the Center for Research in Security Prices (CRSP) Bond Data and document the methods of this package.
URL: https://github.com/bonsook/ycevo
BugReports: https://github.com/bonsook/ycevo/issues
License: GPL-3
Depends: R (>= 3.5.0)
Encoding: UTF-8
LazyData: true
Imports: dplyr, magrittr, Matrix, Rcpp (>= 0.12.18), rlang, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0), akima, knitr, plotly, rmarkdown, tidyverse
Language: en-AU
NeedsCompilation: yes
Packaged: 2022-05-12 06:36:07 UTC; fyan0012
Author: Bonsoo Koo [aut], Nathaniel Tomasetti [aut], Kai-Yang Goh [aut], Yangzhuoran Fin Yang [aut, cre]
Repository: CRAN
Date/Publication: 2022-05-13 09:10:01 UTC

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Package unmarked updated to version 1.2.5 with previous version 1.2.3 dated 2022-04-26

Title: Models for Data from Unmarked Animals
Description: Fits hierarchical models of animal abundance and occurrence to data collected using survey methods such as point counts, site occupancy sampling, distance sampling, removal sampling, and double observer sampling. Parameters governing the state and observation processes can be modeled as functions of covariates. Reference: Fiske and Chandler (2011) <doi:10.18637/jss.v043.i10>.
Author: Richard Chandler [aut], Ken Kellner [cre, aut], Ian Fiske [aut], David Miller [aut], Andy Royle [aut], Jeff Hostetler [aut], Rebecca Hutchinson [aut], Adam Smith [aut], Marc Kery [ctb], Mike Meredith [ctb], Auriel Fournier [ctb], Ariel Muldoon [ctb], [...truncated...]
Maintainer: Ken Kellner <contact@kenkellner.com>

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New package terminaldigits with initial version 0.1.0
Package: terminaldigits
Title: Tests of Uniformity and Independence for Terminal Digits
Version: 0.1.0
Description: Implements simulated tests for the hypothesis that terminal digits are uniformly distributed (chi-squared goodness-of-fit) and the hypothesis that terminal digits are independent from preceding digits (several tests of independence for r x c contingency tables). Also, for a number of distributions, implements Monte Carlo simulations for type I errors and power for the test of independence.
License: MIT + file LICENSE
Depends: R (>= 2.10)
Imports: discretefit, Rcpp
Suggests: dplyr, gt, ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
LinkingTo: Rcpp
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2022-05-12 06:54:28 UTC; Josh
Author: Josh McCormick [aut, cre]
Maintainer: Josh McCormick <josh.mccormick@aya.yale.edu>
Repository: CRAN
Date/Publication: 2022-05-13 09:10:12 UTC

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New package linea with initial version 0.0.1
Package: linea
Title: Linear Regression Interface
Version: 0.0.1
Description: An interface to accelerate linear regression (Ordinary least squares) modelling, which allows users to build models quickly, while automatically generating interactive visualizations of the results. Non-linear models specification (e.g. y = b1*x1 + b2*log(x2)) can be easily constructed using user-defined transformations. Functions for testing wide ranges of model specifications (e.g. y = b*log(x,10) , y = b*log(x,20) , ...), all at once, are also available. Finally, models can be imported and exported as Excel files where all the information necessary for re-running the models is stored in separate sheets.
License: GPL-3
Encoding: UTF-8
Imports: anytime, dplyr , gtrendsR, lubridate , magrittr , methods , openxlsx , plotly , purrr , RColorBrewer , readr , readxl , reshape2 , rlist, sjmisc , stringr , tibble , tidyr , tidyverse , tis , zoo
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2022-05-12 05:47:12 UTC; 44751
Author: Claudio Paladini [aut, cre]
Maintainer: Claudio Paladini <clode.paladini@gmail.com>
Repository: CRAN
Date/Publication: 2022-05-13 09:10:15 UTC

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Package circularEV updated to version 0.1.1 with previous version 0.1.0 dated 2021-01-21

Title: Extreme Value Analysis for Circular Data
Description: General functions for performing extreme value analysis on a circular domain as part of the statistical methodology in the paper by Konzen, E., Neves, C., and Jonathan, P. (2021). Modeling nonstationary extremes of storm severity: Comparing parametric and semiparametric inference. Environmetrics, 32(4), e2667.
Author: Evandro Konzen
Maintainer: Evandro Konzen <circularev.r@gmail.com>

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Package tkImgR updated to version 0.0.5 with previous version 0.0.1 dated 2022-05-02

Title: Simple Image Viewer for R Using the 'tcltk' Package
Description: A 'Tcl/Tk' Graphical User Interface (GUI) to display images than can be zoomed and panned using the mouse and keyboard shortcuts. 'tkImgR' read and write different image formats (PPM/PGM, PNG and GIF) using the standard 'Tcl/Tk' distribution (>=8.6), but other formats (JPEG, TIFF, CR2) can be handled using the 'tkImg' package for 'Tcl/Tk'.
Author: Filipe Campelo [aut, cre]
Maintainer: Filipe Campelo <fcampelo@ci.uc.pt>

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Package RNeXML updated to version 2.4.7 with previous version 2.4.6 dated 2022-02-08

Title: Semantically Rich I/O for the 'NeXML' Format
Description: Provides access to phyloinformatic data in 'NeXML' format. The package should add new functionality to R such as the possibility to manipulate 'NeXML' objects in more various and refined way and compatibility with 'ape' objects.
Author: Carl Boettiger [cre, aut] , Scott Chamberlain [aut] , Hilmar Lapp [aut] , Kseniia Shumelchyk [aut], Rutger Vos [aut]
Maintainer: Carl Boettiger <cboettig@gmail.com>

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Package Renvlp updated to version 3.1 with previous version 3.0 dated 2021-09-11

Title: Computing Envelope Estimators
Description: Provides a general routine, envMU, which allows estimation of the M envelope of span(U) given root n consistent estimators of M and U. The routine envMU does not presume a model. This package implements response envelopes, partial response envelopes, envelopes in the predictor space, heteroscedastic envelopes, simultaneous envelopes, scaled response envelopes, scaled envelopes in the predictor space, groupwise envelopes, weighted envelopes, envelopes in logistic regression and envelopes in Poisson regression. For each of these model-based routines the package provides inference tools including bootstrap, cross validation, estimation and prediction, hypothesis testing on coefficients are included except for weighted envelopes. Tools for selection of dimension include AIC, BIC and likelihood ratio testing. Background is available at Cook, R. D., Forzani, L. and Su, Z. (2016) <doi:10.1016/j.jmva.2016.05.006>. Optimization is based on a clockwise coordinate descent algorithm.
Author: Minji Lee, Zhihua Su
Maintainer: Minji Lee <minjilee101@gmail.com>

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Package projpred updated to version 2.1.2 with previous version 2.1.1 dated 2022-04-03

Title: Projection Predictive Feature Selection
Description: Performs projection predictive feature selection for generalized linear models and generalized linear and additive multilevel models (see Piironen, Paasiniemi and Vehtari, 2020, <doi:10.1214/20-EJS1711>; Catalina, Bürkner and Vehtari, 2020, <arXiv:2010.06994>). The package is compatible with the 'rstanarm' and 'brms' packages, but other reference models can also be used. See the documentation as well as the package vignette for more information and examples.
Author: Juho Piironen [aut], Markus Paasiniemi [aut], Alejandro Catalina [aut], Frank Weber [cre, aut], Aki Vehtari [aut], Jonah Gabry [ctb], Marco Colombo [ctb], Paul-Christian Buerkner [ctb], Hamada S. Badr [ctb]
Maintainer: Frank Weber <fweber144@protonmail.com>

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Package oce updated to version 1.7-3 with previous version 1.7-2 dated 2022-03-22

Title: Analysis of Oceanographic Data
Description: Supports the analysis of Oceanographic data, including 'ADCP' measurements, measurements made with 'argo' floats, 'CTD' measurements, sectional data, sea-level time series, coastline and topographic data, etc. Provides specialized functions for calculating seawater properties such as potential temperature in either the 'UNESCO' or 'TEOS-10' equation of state. Produces graphical displays that conform to the conventions of the Oceanographic literature. This package is discussed extensively by Kelley (2018) "Oceanographic Analysis with R" <doi:10.1007/978-1-4939-8844-0>.
Author: Dan Kelley [aut, cre] , Clark Richards [aut] , Chantelle Layton [ctb] coauthor), British Geological Survey [ctb, cph]
Maintainer: Dan Kelley <Dan.Kelley@Dal.Ca>

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More information about oce at CRAN
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New package PALMO with initial version 0.1.0
Package: PALMO
Title: Identify Intra and Inter-Donor Variations in Bulk or Single Cell Longitudinal Dataset
Version: 0.1.0
Maintainer: Suhas Vasaikar <suhas.vasaikar@alleninstitute.org>
Description: It is a platform for analyzing longitudinal data from bulk as well as single cell datasets. It allows to identify variations in molecular features within and across donors over longitudinal time points. The analysis can be done on bulk expression dataset without known cell type information or single cell with cell type/user-defined groups. It allows to infer stable and variable features in given donor and each cell type (or user defined group). The outlier analysis can be performed to identify technical/biological perturbed samples in donor/participant. Further, differential analysis can be performed to decipher time-wise changes in gene expression in a cell type.
Depends: R (>= 4.0), methods, grid, graphics, stats, grDevices
Imports: Seurat (>= 3.9), ggrepel (>= 0.9), pbapply (>= 1.4), lme4 (>= 1.1), ggforce (>= 0.3), MAST (>= 1.14), factoextra (>= 1.0), Rtsne (>= 0.15), knitr(>= 1.30), dplyr, ggplot2, reshape2, ComplexHeatmap, circlize, cowplot, pheatmap, tidyverse, utils
Suggests: ggpubr, rmarkdown
URL: https://github.com/aifimmunology/PALMO
BugReports: https://github.com/aifimmunology/PALMO/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: false
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-05-11 16:21:00 UTC; suhas.vasaikar
Author: Suhas Vasaikar [aut, cre], Aarthi Talla [aut, ctb], Xiaojun Li [aut, ctb]
Repository: CRAN
Date/Publication: 2022-05-13 08:40:06 UTC

More information about PALMO at CRAN
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New package NovelDistns with initial version 0.1.0
Package: NovelDistns
Title: Computes PDF, CDF, Quantile, Random Numbers and Measures of Inference for 3 General Families of Distributions
Version: 0.1.0
Author: Mutua Kilai, Gichuhi Waititu, Wanjoya Kibira
Maintainer: Mutua Kilai <kilaimutua@gmail.com>
Description: Computes the probability density function, the cumulative density function, quantile function, random numbers and measures of inference for the following families exponentiated generalized gull alpha power family, exponentiated gull alpha powerfamily, gull alpha power family.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: AdequacyModel, gsl, rootSolve, stats
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2022-05-11 18:43:51 UTC; Mutua Sam
Repository: CRAN
Date/Publication: 2022-05-13 08:40:10 UTC

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Package insight updated to version 0.17.1 with previous version 0.17.0 dated 2022-03-29

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel Luedecke [aut, cre] , Dominique Makowski [aut, ctb] , Indrajeet Patil [aut, ctb] , Philip Waggoner [aut, ctb] , Mattan S. Ben-Shachar [aut, ctb] , Brenton M. Wiernik [aut] , Vincent Arel-Bundock [aut, ctb] , Alex Hayes [rev]
Maintainer: Daniel Luedecke <d.luedecke@uke.de>

Diff between insight versions 0.17.0 dated 2022-03-29 and 0.17.1 dated 2022-05-13

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 tests/testthat/test-zeroinfl.R                 |   20 +
 104 files changed, 3101 insertions(+), 1376 deletions(-)

More information about insight at CRAN
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Package hglasso updated to version 1.3 with previous version 1.2 dated 2014-08-09

Title: Learning Graphical Models with Hubs
Description: Implements the hub graphical lasso and hub covariance graph proposal by Tan, KM., London, P., Mohan, K., Lee, S-I., Fazel, M., and Witten, D. (2014). Learning graphical models with hubs. Journal of Machine Learning Research 15(Oct):3297-3331.
Author: Kean Ming Tan
Maintainer: Kean Ming Tan <keanming@umich.edu>

Diff between hglasso versions 1.2 dated 2014-08-09 and 1.3 dated 2022-05-13

 hglasso-1.2/hglasso/R/hglasso-internal.R   |only
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 hglasso-1.3/hglasso/NAMESPACE              |    7 +++++--
 hglasso-1.3/hglasso/R/Functions.R          |    2 +-
 hglasso-1.3/hglasso/man/hglasso-package.Rd |    2 +-
 hglasso-1.3/hglasso/man/summary.hglasso.Rd |    2 +-
 7 files changed, 20 insertions(+), 18 deletions(-)

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Package extlasso updated to version 0.3 with previous version 0.2 dated 2014-08-19

Title: Maximum Penalized Likelihood Estimation with Extended Lasso Penalty
Description: Estimates coefficients of extended LASSO penalized linear regression and generalized linear models. Currently lasso and elastic net penalized linear regression and generalized linear models are considered. This package currently utilizes an accurate approximation of L1 penalty and then a modified Jacobi algorithm to estimate the coefficients. There is provision for plotting of the solutions and predictions of coefficients at given values of lambda. This package also contains functions for cross validation to select a suitable lambda value given the data. Also provides a function for estimation in fused lasso penalized linear regression. For more details, see Mandal, B. N.(2014). Computational methods for L1 penalized GLM model fitting, unpublished report submitted to Macquarie University, NSW, Australia.
Author: B N Mandal <mandal.stat@gmail.com> and Jun Ma <jun.ma@mq.edu.au>
Maintainer: B N Mandal <mandal.stat@gmail.com>

Diff between extlasso versions 0.2 dated 2014-08-19 and 0.3 dated 2022-05-13

 DESCRIPTION |   14 +++++++-------
 MD5         |    4 ++--
 NAMESPACE   |    4 +++-
 3 files changed, 12 insertions(+), 10 deletions(-)

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Package ecospat updated to version 3.2.2 with previous version 3.2.1 dated 2022-01-07

Title: Spatial Ecology Miscellaneous Methods
Description: Collection of R functions and data sets for the support of spatial ecology analyses with a focus on pre, core and post modelling analyses of species distribution, niche quantification and community assembly. Written by current and former members and collaborators of the ecospat group of Antoine Guisan, Department of Ecology and Evolution (DEE) and Institute of Earth Surface Dynamics (IDYST), University of Lausanne, Switzerland. Read Di Cola et al. (2016) <doi:10.1111/ecog.02671> for details.
Author: Olivier Broennimann [cre, aut, ctb], Valeria Di Cola [aut, ctb], Blaise Petitpierre [ctb], Frank Breiner [ctb], Daniel Scherrer [ctb], Manuela D`Amen [ctb], Christophe Randin [ctb], Robin Engler [ctb], Wim Hordijk [ctb], Heidi Mod [ctb], Julien Potti [...truncated...]
Maintainer: Olivier Broennimann <olivier.broennimann@unil.ch>

Diff between ecospat versions 3.2.1 dated 2022-01-07 and 3.2.2 dated 2022-05-13

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More information about ecospat at CRAN
Permanent link

New package diceR with initial version 1.2.0
Package: diceR
Title: Diverse Cluster Ensemble in R
Version: 1.2.0
Description: Performs cluster analysis using an ensemble clustering framework, Chiu & Talhouk (2018) <doi:10.1186/s12859-017-1996-y>. Results from a diverse set of algorithms are pooled together using methods such as majority voting, K-Modes, LinkCluE, and CSPA. There are options to compare cluster assignments across algorithms using internal and external indices, visualizations such as heatmaps, and significance testing for the existence of clusters.
License: MIT + file LICENSE
URL: https://github.com/AlineTalhouk/diceR/, https://alinetalhouk.github.io/diceR/
BugReports: https://github.com/AlineTalhouk/diceR/issues
Depends: R (>= 3.5)
Imports: abind, assertthat, class, clue, clusterCrit, clValid, dplyr (>= 0.7.5), ggplot2, infotheo, klaR, magrittr, mclust, methods, NMF, purrr (>= 0.2.3), RankAggreg, Rcpp, stringr, tidyr, yardstick
Suggests: apcluster, blockcluster, cluster, covr, dbscan, e1071, kernlab, knitr, kohonen, pander, poLCA, progress, RColorBrewer, rlang, rmarkdown, Rtsne, sigclust, testthat
LinkingTo: Rcpp
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2022-05-11 19:21:18 UTC; derek
Author: Derek Chiu [aut, cre], Aline Talhouk [aut], Johnson Liu [ctb, com]
Maintainer: Derek Chiu <dchiu@bccrc.ca>
Repository: CRAN
Date/Publication: 2022-05-13 08:50:11 UTC

More information about diceR at CRAN
Permanent link

New package CDM with initial version 8.1-12
Package: CDM
Title: Cognitive Diagnosis Modeling
Version: 8.1-12
Date: 2022-05-12 13:47:57
Author: Alexander Robitzsch [aut, cre], Thomas Kiefer [aut], Ann Cathrice George [aut], Ali Uenlue [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>
Description: Functions for cognitive diagnosis modeling and multidimensional item response modeling for dichotomous and polytomous item responses. This package enables the estimation of the DINA and DINO model (Junker & Sijtsma, 2001, <doi:10.1177/01466210122032064>), the multiple group (polytomous) GDINA model (de la Torre, 2011, <doi:10.1007/s11336-011-9207-7>), the multiple choice DINA model (de la Torre, 2009, <doi:10.1177/0146621608320523>), the general diagnostic model (GDM; von Davier, 2008, <doi:10.1348/000711007X193957>), the structured latent class model (SLCA; Formann, 1992, <doi:10.1080/01621459.1992.10475229>) and regularized latent class analysis (Chen, Li, Liu, & Ying, 2017, <doi:10.1007/s11336-016-9545-6>). See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) <doi:10.18637/jss.v074.i02> or Robitzsch and George (2019, <doi:10.1007/978-3-030-05584-4_26>) for further details on estimation and the package structure. For tutorials on how to use the CDM package see George and Robitzsch (2015, <doi:10.20982/tqmp.11.3.p189>) as well as Ravand and Robitzsch (2015).
Depends: R (>= 3.1), mvtnorm
Imports: graphics, grDevices, methods, polycor, Rcpp, stats, utils
Suggests: BIFIEsurvey, lattice, MASS, miceadds, ROI, sfsmisc
LinkingTo: Rcpp, RcppArmadillo
Enhances: dina, GDINA, mirt, rrum
LazyLoad: yes
LazyData: yes
URL: https://github.com/alexanderrobitzsch/CDM, https://sites.google.com/site/alexanderrobitzsch2/software
License: GPL (>= 2)
BugReports: https://github.com/alexanderrobitzsch/CDM/issues?state=open
NeedsCompilation: yes
Packaged: 2022-05-12 11:51:09 UTC; sunpn563
Repository: CRAN
Date/Publication: 2022-05-13 08:50:14 UTC

More information about CDM at CRAN
Permanent link

Package roxygen2 updated to version 7.2.0 with previous version 7.1.2 dated 2021-09-08

Title: In-Line Documentation for R
Description: Generate your Rd documentation, 'NAMESPACE' file, and collation field using specially formatted comments. Writing documentation in-line with code makes it easier to keep your documentation up-to-date as your requirements change. 'Roxygen2' is inspired by the 'Doxygen' system for C++.
Author: Hadley Wickham [aut, cre, cph] , Peter Danenberg [aut, cph], Gabor Csardi [aut], Manuel Eugster [aut, cph], RStudio [cph, fnd]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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More information about roxygen2 at CRAN
Permanent link

New package ParallelDSM with initial version 0.3.2
Package: ParallelDSM
Title: Parallel Digital Soil Mapping using Machine Learning
Version: 0.3.2
Description: Parallel computing, multi-core CPU is used to efficiently compute and process multi-dimensional soil data.This package includes the parallelized 'Quantile Regression Forests' algorithm for Digital Soil Mapping and is mainly dependent on the package 'quantregForest' and 'snowfall'. Detailed references to the R package and the web site are described in the methods, as detailed in the method documentation.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), snowfall, raster, sp
Imports: methods, pryr, utils, caret, gstat, quantregForest, randomForest, stringr, rgdal, stats,
NeedsCompilation: no
Packaged: 2022-05-13 06:24:01 UTC; tpc
Author: Xiaodong Song [aut], Peicong Tang [aut, cre], Gaoqiang Ge [aut], Jun Zhu [aut], Ganlin Zhang [aut]
Maintainer: Peicong Tang <peicongtang0409@163.com>
Repository: CRAN
Date/Publication: 2022-05-13 07:30:06 UTC

More information about ParallelDSM at CRAN
Permanent link

Package makepipe updated to version 0.2.0 with previous version 0.1.0 dated 2021-11-23

Title: Pipeline Tools Inspired by 'GNU Make'
Description: A suite of tools for transforming an existing workflow into a self-documenting pipeline with very minimal upfront costs. Segments of the pipeline are specified in much the same way a 'Make' rule is, by declaring an executable recipe (which might be an R script), along with the corresponding targets and dependencies. When the entire pipeline is run through, only those recipes that need to be executed will be. Meanwhile, execution metadata is captured behind the scenes for later inspection.
Author: Kinto Behr [aut, cre, cph]
Maintainer: Kinto Behr <kinto.behr@gmail.com>

Diff between makepipe versions 0.1.0 dated 2021-11-23 and 0.2.0 dated 2022-05-13

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Package iheiddown updated to version 0.9.3 with previous version 0.9.2 dated 2022-05-06

Title: For Writing Geneva Graduate Institute Documents
Description: A set of tools for writing documents according to Geneva Graduate Institute conventions and regulations. The most common use is for writing and compiling theses or thesis chapters, as drafts or for examination with correct preamble formatting. However, the package also offers users to create HTML presentation slides with 'xaringan', complete problem sets, format posters, and, for course instructors, prepare a syllabus. The package includes additional functions for institutional color palettes, an institutional 'ggplot' theme, a function for counting manuscript words, and a bibliographical analysis toolkit.
Author: James Hollway [aut, cre, cph] , Bernhard Bieri [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

Diff between iheiddown versions 0.9.2 dated 2022-05-06 and 0.9.3 dated 2022-05-13

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New package GLDreg with initial version 1.1.0
Package: GLDreg
Title: Fit GLD Regression/Quantile/AFT Model to Data
Version: 1.1.0
Date: 2022-05-04
Maintainer: Steve Su <allegro.su@gmail.com>
Depends: GLDEX (>= 2.0.0.5), ddst, grDevices, graphics, stats
Suggests: MASS, quantreg, mlr3proba
Description: Owing to the rich shapes of Generalised Lambda Distributions (GLDs), GLD standard/quantile/Accelerated Failure Time (AFT) regression is a competitive flexible model compared to standard/quantile/AFT regression. The proposed method has some major advantages: 1) it provides a reference line which is very robust to outliers with the attractive property of zero mean residuals and 2) it gives a unified, elegant quantile regression model from the reference line with smooth regression coefficients across different quantiles. For AFT model, it also eliminates the needs to try several different AFT models, owing to the flexible shapes of GLD. The goodness of fit of the proposed model can be assessed via QQ plots and Kolmogorov-Smirnov tests and data driven smooth test, to ensure the appropriateness of the statistical inference under consideration. Statistical distributions of coefficients of the GLD regression line are obtained using simulation, and interval estimates are obtained directly from simulated data. References include the following: Su (2015) "Flexible Parametric Quantile Regression Model" <doi:10.1007/s11222-014-9457-1>, Su (2021) "Flexible parametric accelerated failure time model"<doi:10.1080/10543406.2021.1934854>.
License: GPL (>= 3)
NeedsCompilation: no
Packaged: 2022-05-09 12:45:20 UTC; Allegro
Author: Steve Su [aut, cre, cph] , R Core Team [aut]
Repository: CRAN
Date/Publication: 2022-05-13 07:30:09 UTC

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Package survivoR updated to version 1.0 with previous version 0.9.12 dated 2022-02-12

Title: Data from all Seasons of Survivor (US) TV Series in Tidy Format
Description: Several datasets which detail the results and events of each season of Survivor. This includes details on the cast, voting history, immunity and reward challenges, jury votes and viewers. This data is useful for practicing data wrangling, graph analytics and analysing how each season of Survivor played out. Includes 'ggplot2' scales and colour palettes for visualisation.
Author: Daniel Oehm [aut, cre], Carly Levitz [ctb]
Maintainer: Daniel Oehm <danieloehm@gmail.com>

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Package RCT updated to version 1.1.2 with previous version 1.1.1 dated 2021-08-02

Title: Assign Treatments, Power Calculations, Balances, Impact Evaluation of Experiments
Description: Assists in the whole process of designing and evaluating Randomized Control Trials. Robust treatment assignment by strata/blocks, that handles misfits; Power calculations of the minimum detectable treatment effect or minimum populations; Balance tables of T-test of covariates; Balance Regression: (treatment ~ all x variables) with F-test of null model; Impact_evaluation: Impact evaluation regressions. This function gives you the option to include control_vars, fixed effect variables, cluster variables (for robust SE), multiple endogenous variables and multiple heterogeneous variables (to test treatment effect heterogeneity) summary_statistics: Function that creates a summary statistics table with statistics rank observations in n groups: Creates a factor variable with n groups. Each group has a min and max label attach to each category. Athey, Susan, and Guido W. Imbens (2017) <arXiv:1607.00698>.
Author: Isidoro Garcia-Urquieta [aut, cre]
Maintainer: Isidoro Garcia-Urquieta <isidoro.gu@gmail.com>

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Package matlab2r updated to version 1.1.1 with previous version 1.1.0 dated 2022-04-13

Title: Translation Layer from MATLAB to R
Description: Allows users familiar with MATLAB to use MATLAB-named functions in R. Several basic MATLAB functions are written in this package to mimic the behavior of their original counterparts, with more to come as this package grows.
Author: Waldir Leoncio [aut, cre]
Maintainer: Waldir Leoncio <w.l.netto@medisin.uio.no>

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Package ahaz updated to version 1.15 with previous version 1.14 dated 2013-06-03

Title: Regularization for Semiparametric Additive Hazards Regression
Description: Computationally efficient procedures for regularized estimation with the semiparametric additive hazards regression model.
Author: Anders Gorst-Rasmussen <agorstras@gmail.com>
Maintainer: Anders Gorst-Rasmussen <agorstras@gmail.com>

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Package wwntests (with last version 1.0.1) was removed from CRAN

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

2020-05-18 1.0.1
2019-06-19 1.0.0

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Package rfinance (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:

2021-10-26 0.1.0

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Package waccR (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:

2017-07-08 0.1.0

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Package moderndive updated to version 0.5.4 with previous version 0.5.3 dated 2022-01-20

Title: Tidyverse-Friendly Introductory Linear Regression
Description: Datasets and wrapper functions for tidyverse-friendly introductory linear regression, used in "Statistical Inference via Data Science: A ModernDive into R and the Tidyverse" available at <https://moderndive.com/>.
Author: Albert Y. Kim [aut, cre] , Chester Ismay [aut] , Andrew Bray [ctb] , Delaney Moran [ctb], Evgeni Chasnovski [ctb] , Will Hopper [ctb] , Benjamin S. Baumer [ctb] , Marium Tapal [ctb] , Wayne Ndlovu [ctb], Catherine Peppers [ctb], Annah Mutaya [ctb], A [...truncated...]
Maintainer: Albert Y. Kim <albert.ys.kim@gmail.com>

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New package metaplus with initial version 1.0-4
Package: metaplus
Title: Robust Meta-Analysis and Meta-Regression
Version: 1.0-4
Date: 2022-05-11
Maintainer: Ken Beath <ken@kjbeath.com.au>
Contact: Ken Beath <ken@kjbeath.com.au>
Author: Ken Beath [aut, cre], Ben Bolker [aut], R Development Core Team [aut]
Description: Performs meta-analysis and meta-regression using standard and robust methods with confidence intervals based on the profile likelihood. Robust methods are based on alternative distributions for the random effect, either the t-distribution (Lee and Thompson, 2008 <doi:10.1002/sim.2897> or Baker and Jackson, 2008 <doi:10.1007/s10729-007-9041-8>) or mixtures of normals (Beath, 2014 <doi:10.1002/jrsm.1114>).
Depends: R(>= 3.2.0)
Suggests: R.rsp
VignetteBuilder: R.rsp
Imports: bbmle, metafor, boot, methods, numDeriv, MASS, graphics, stats, fastGHQuad, lme4, Rfast, parallel, doParallel, foreach, doRNG
LazyData: yes
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2022-05-11 09:07:31 UTC; kjbeath1
Repository: CRAN
Date/Publication: 2022-05-13 05:40:02 UTC

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New package CausCor with initial version 0.1.1
Package: CausCor
Title: Calculate Correlations and Estimate Causality
Version: 0.1.1
Description: This tool performs pairwise correlation analysis and estimate causality. Particularly, it is useful for detecting the metabolites that would be altered by the gut bacteria.
URL: https://github.com/sugym/CausCor
License: MIT + file LICENSE
Language: en-US
Encoding: UTF-8
Imports: cowplot, dplyr, ggplot2, grDevices, magrittr, stats, WriteXLS
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2022-05-12 02:22:05 UTC; sugiyamatomomi
Author: Tomomi Sugiyama [aut, cre]
Maintainer: Tomomi Sugiyama <sugiyama.t.am@m.titech.ac.jp>
Repository: CRAN
Date/Publication: 2022-05-13 05:40:05 UTC

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