Sun, 05 Mar 2023

Package rb3 updated to version 0.0.8 with previous version 0.0.7 dated 2022-12-14

Title: Download and Parse Public Data Released by B3 Exchange
Description: Download and parse public files released by B3 and convert them into useful formats and data structures common to data analysis practitioners.
Author: Wilson Freitas [aut, cre], Marcelo Perlin [aut]
Maintainer: Wilson Freitas <wilson.freitas@gmail.com>

Diff between rb3 versions 0.0.7 dated 2022-12-14 and 0.0.8 dated 2023-03-05

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Package RFCCA updated to version 1.0.10 with previous version 1.0.9 dated 2022-04-19

Title: Random Forest with Canonical Correlation Analysis
Description: Random Forest with Canonical Correlation Analysis (RFCCA) is a random forest method for estimating the canonical correlations between two sets of variables depending on the subject-related covariates. The trees are built with a splitting rule specifically designed to partition the data to maximize the canonical correlation heterogeneity between child nodes. The method is described in Alakus et al. (2021) <doi:10.1093/bioinformatics/btab158>. RFCCA uses 'randomForestSRC' package (Ishwaran and Kogalur, 2020) by freezing at the version 2.9.3. The custom splitting rule feature is utilised to apply the proposed splitting rule.
Author: Cansu Alakus [aut, cre], Denis Larocque [aut], Aurelie Labbe [aut], Hemant Ishwaran [ctb] , Udaya B. Kogalur [ctb]
Maintainer: Cansu Alakus <cansu.alakus@hec.ca>

Diff between RFCCA versions 1.0.9 dated 2022-04-19 and 1.0.10 dated 2023-03-05

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Package optimizeR updated to version 0.3.1 with previous version 0.3.0 dated 2023-01-22

Title: Unified Framework for Numerical Optimizers
Description: Provides a unified framework for numerical optimizers in R, particularly for their inputs and outputs.
Author: Lennart Oelschlaeger [aut, cre] , Marius Ötting [ctb]
Maintainer: Lennart Oelschlaeger <oelschlaeger.lennart@gmail.com>

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Package rosetta updated to version 0.3.12 with previous version 0.3.10 dated 2022-11-03

Title: Parallel Use of Statistical Packages in Teaching
Description: When teaching statistics, it can often be desirable to uncouple the content from specific software packages. To ease such efforts, the Rosetta Stats website (<https://rosettastats.com>) allows comparing analyses in different packages. This package is the companion to the Rosetta Stats website, aiming to provide functions that produce output that is similar to output from other statistical packages, thereby facilitating 'software-agnostic' teaching of statistics.
Author: Gjalt-Jorn Peters [aut, cre] , Peter Verboon [aut, ctb] , Ron Pat-El [ctb] , Melissa Gordon Wolf [ctb]
Maintainer: Gjalt-Jorn Peters <rosetta@opens.science>

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Package psyverse updated to version 0.2.6 with previous version 0.2.4 dated 2022-11-22

Title: Decentralized Unequivocality in Psychological Science
Description: The constructs used to study the human psychology have many definitions and corresponding instructions for eliciting and coding qualitative data pertaining to constructs' content and for measuring the constructs. This plethora of definitions and instructions necessitates unequivocal reference to specific definitions and instructions in empirical and secondary research. This package implements a human- and machine-readable standard for specifying construct definitions and instructions for measurement and qualitative research based on 'YAML'. This standard facilitates systematic unequivocal reference to specific construct definitions and corresponding instructions in a decentralized manner (i.e. without requiring central curation; Peters (2020) <doi:10.31234/osf.io/xebhn>).
Author: Gjalt-Jorn Peters [aut, cre, ctb] , Rik Crutzen [ctb]
Maintainer: Gjalt-Jorn Peters <psyverse@opens.science>

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Package preregr updated to version 0.2.8 with previous version 0.2.5 dated 2022-08-22

Title: Specify (Pre)Registrations and Export Them Human- And Machine-Readably
Description: Preregistrations, or more generally, registrations, enable explicit timestamped and (often but not necessarily publicly) frozen documentation of plans and expectations as well as decisions and justifications. In research, preregistrations are commonly used to clearly document plans and facilitate justifications of deviations from those plans, as well as decreasing the effects of publication bias by enabling identification of research that was conducted but not published. Like reporting guidelines, (pre)registration forms often have specific structures that facilitate systematic reporting of important items. The 'preregr' package facilitates specifying (pre)registrations in R and exporting them to a human-readable format (using R Markdown partials or exporting to an 'HTML' file) as well as human-readable embedded data (using 'JSON'), as well as importing such exported (pre)registration specifications from such embedded 'JSON'.
Author: Gjalt-Jorn Peters [aut, cre] , Szilvia Zoergő [ctb] , Olmo den Akker [ctb] , Aleksandra Lazic [ctb] , Thomas Gueltzow [ctb]
Maintainer: Gjalt-Jorn Peters <preregr@opens.science>

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Package metan updated to version 1.18.0 with previous version 1.17.0 dated 2022-06-10

Title: Multi Environment Trials Analysis
Description: Performs stability analysis of multi-environment trial data using parametric and non-parametric methods. Parametric methods includes Additive Main Effects and Multiplicative Interaction (AMMI) analysis by Gauch (2013) <doi:10.2135/cropsci2013.04.0241>, Ecovalence by Wricke (1965), Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) <doi:10.1201/9781420040371>, geometric adaptability index by Mohammadi & Amri (2008) <doi:10.1007/s10681-007-9600-6>, joint regression analysis by Eberhart & Russel (1966) <doi:10.2135/cropsci1966.0011183X000600010011x>, genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method, power law residuals (POLAR) statistics by Doring et al. (2015) <doi:10.1016/j.fcr.2015.08.005>, scale-adjusted coefficient of variation by Doring & Reckling (2018) <doi:10.1016/j.eja.2018.06.007>, stability variance by Shukla (1972) <doi:10.1038/hdy.1972.87>, weighted ave [...truncated...]
Author: Tiago Olivoto [aut, cre, cph]
Maintainer: Tiago Olivoto <tiagoolivoto@gmail.com>

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Package errorist updated to version 0.1.1 with previous version 0.1.0 dated 2020-02-24

Title: Automatically Search Errors or Warnings
Description: Provides environment hooks that obtain errors and warnings which occur during the execution of code to automatically search for solutions.
Author: James Balamuta [aut, cre, cph]
Maintainer: James Balamuta <balamut2@illinois.edu>

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Package FactorCopula updated to version 0.9.3 with previous version 0.9.2 dated 2022-12-06

Title: Factor, Bi-Factor, Second-Order and Factor Tree Copula Models
Description: Estimation, model selection and goodness-of-fit of (1) factor copula models for mixed continuous and discrete data in Kadhem and Nikoloulopoulos (2021) <doi:10.1111/bmsp.12231>; (2) bi-factor and second-order copula models for item response data in Kadhem and Nikoloulopoulos (2023) <doi:10.1007/s11336-022-09894-2>; (3) factor tree copula models for item response data in Kadhem and Nikoloulopoulos (2022) <arXiv:2201.00339>.
Author: Sayed H. Kadhem [aut], Aristidis K. Nikoloulopoulos [aut, cre]
Maintainer: Aristidis K. Nikoloulopoulos <a.nikoloulopoulos@uea.ac.uk>

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Package shapviz updated to version 0.6.0 with previous version 0.5.0 dated 2023-02-03

Title: SHAP Visualizations
Description: Visualizations for SHAP (SHapley Additive exPlanations), such as waterfall plots, force plots, various types of importance plots, dependence plots, and interaction plots. These plots act on a 'shapviz' object created from a matrix of SHAP values and a corresponding feature dataset. Wrappers for the R packages 'xgboost', 'lightgbm', 'fastshap', 'shapr', 'h2o', 'treeshap', and 'kernelshap' are added for convenience. By separating visualization and computation, it is possible to display factor variables in graphs, even if the SHAP values are calculated by a model that requires numerical features. The plots are inspired by those provided by the 'shap' package in Python, but there is no dependency on it.
Author: Michael Mayer [aut, cre]
Maintainer: Michael Mayer <mayermichael79@gmail.com>

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Package tidyRSS updated to version 2.0.7 with previous version 2.0.6 dated 2022-08-25

Title: Tidy RSS for R
Description: With the objective of including data from RSS feeds into your analysis, 'tidyRSS' parses RSS, Atom and JSON feeds and returns a tidy data frame.
Author: Robert Myles McDonnell [aut, cre], Jonathan Carroll [ctb], Mike Smith [ctb], Joseph Stachelek [ctb], Andrew Frasier [ctb], Tom Broekel [ctb], Jeremy Gerdes [ctb], Chung-hong Chan [ctb]
Maintainer: Robert Myles McDonnell <robertmylesmcdonnell@gmail.com>

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Package ganDataModel updated to version 1.1.2 with previous version 1.1.1 dated 2022-12-19

Title: Build a Metric Subspaces Data Model for a Data Source
Description: Neural networks are applied to create a density value function which approximates density values for a data source. The trained neural network is analyzed for different levels. For each level metric subspaces with density values above a level are determined. The obtained set of metric subspaces and the trained neural network are assembled into a data model. A prerequisite is the definition of a data source, the generation of generative data and the calculation of density values. These tasks are executed using package 'ganGenerativeData' <https://cran.r-project.org/package=ganGenerativeData>.
Author: Werner Mueller
Maintainer: Werner Mueller <werner.mueller5@chello.at>

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Package glmm.hp updated to version 0.0-7 with previous version 0.0-6 dated 2022-12-16

Title: Hierarchical Partitioning of Marginal R2 for Generalized Mixed-Effect Models
Description: Conducts hierarchical partitioning to calculate individual contributions of each fixed effects towards marginal R2 for generalized mixed-effect model based on output of r.squaredGLMM() in 'MuMIn', applying the algorithm of Lai J.,Zou Y., Zhang S.,Zhang X.,Mao L.(2022)glmm.hp: an R package for computing individual effect of predictors in generalized linear mixed models.Journal of Plant Ecology,15(6)1302-1307<doi:10.1093/jpe/rtac096>.
Author: Jiangshan Lai [aut, cre] , Kim Nimon [aut]
Maintainer: Jiangshan Lai <lai@njfu.edu.cn>

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Package HostSwitch updated to version 0.1.3 with previous version 0.1.2 dated 2022-08-09

Title: Simulate the Extent of Host Switching by Consumers
Description: Using a simulation-based approach, the 'HostSwitch' package provides functions to investigate host switches by consumers. The individual-based model is based on the concept of ecological fitting. The mockup model is published by Araujo et al. 2015. Understanding Host-Switching by Ecological Fitting (<doi:10.1371/journal.pone.0139225>). The package provides an R-friendly and modified version of this model which can be applied to different consumer-resource scenarios.
Author: Valeria Trivellone [aut] , Sabrina B.L. Araujo [aut] , Bernd Panassiti [cre, aut]
Maintainer: Bernd Panassiti <bernd.panassiti@gmail.com>

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Package justifier updated to version 0.2.6 with previous version 0.2.4 dated 2022-06-09

Title: Human and Machine-Readable Justifications and Justified Decisions Based on 'YAML'
Description: Leverages the 'yum' package to implement a 'YAML' ('YAML Ain't Markup Language', a human friendly standard for data serialization; see <https:yaml.org>) standard for documenting justifications, such as for decisions taken during the planning, execution and analysis of a study or during the development of a behavior change intervention as illustrated by Marques & Peters (2019) <doi:10.17605/osf.io/ndxha>. These justifications are both human- and machine-readable, facilitating efficient extraction and organisation.
Author: Gjalt-Jorn Peters [aut, cre] , Szilvia Zorgo [ctb]
Maintainer: Gjalt-Jorn Peters <justifier@opens.science>

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Package iriR (with last version 0.2.2) was removed from CRAN

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

2021-04-22 0.2.2

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Package tramvs (with last version 0.0-3) was removed from CRAN

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

2022-11-11 0.0-3
2022-08-22 0.0-2

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Package spiR (with last version 0.2.1) was removed from CRAN

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

2021-03-05 0.2.1
2020-01-23 0.1.1

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Package SingleCaseES updated to version 0.7.1 with previous version 0.6.1 dated 2022-07-06

Title: A Calculator for Single-Case Effect Sizes
Description: Provides R functions for calculating basic effect size indices for single-case designs, including several non-overlap measures and parametric effect size measures, and for estimating the gradual effects model developed by Swan and Pustejovsky (2018) <DOI:10.1080/00273171.2018.1466681>. Standard errors and confidence intervals (based on the assumption that the outcome measurements are mutually independent) are provided for the subset of effect sizes indices with known sampling distributions.
Author: James E. Pustejovsky [aut, cre], Man Chen [aut], Daniel M. Swan [aut], Paulina Grekov [ctb]
Maintainer: James E. Pustejovsky <jepusto@gmail.com>

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Package RCzechia updated to version 1.11.1 with previous version 1.11 dated 2023-03-03

Title: Spatial Objects of the Czech Republic
Description: Administrative regions and other spatial objects of the Czech Republic.
Author: Jindra Lacko [aut, cre] , Nick Bearman [rev]
Maintainer: Jindra Lacko <jindra.lacko@gmail.com>

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Package ClustBlock updated to version 3.1.0 with previous version 3.0.0 dated 2022-09-07

Title: Clustering of Datasets
Description: Hierarchical and partitioning algorithms of blocks of variables. The partitioning algorithm includes an option called noise cluster to set aside atypical blocks of variables. The CLUSTATIS method (for quantitative blocks) (Llobell, Cariou, Vigneau, Labenne & Qannari (2020) <doi:10.1016/j.foodqual.2018.05.013>, Llobell, Vigneau & Qannari (2019) <doi:10.1016/j.foodqual.2019.02.017>) and the CLUSCATA method (for Check-All-That-Apply data) (Llobell, Cariou, Vigneau, Labenne & Qannari (2019) <doi:10.1016/j.foodqual.2018.09.006>, Llobell, Giacalone, Labenne & Qannari (2019) <doi:10.1016/j.foodqual.2019.05.017>) are the core of this package. The CATATIS methods allows to compute some indices and tests to control the quality of CATA data. Multivariate analysis and clustering of subjects for quantitative multiblock data, CATA, RATA, Free Sorting and JAR experiments are available.
Author: Fabien Llobell [aut, cre] , Evelyne Vigneau [ctb] , Veronique Cariou [ctb] , El Mostafa Qannari [ctb]
Maintainer: Fabien Llobell <fllobell@hotmail.fr>

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More information about ClustBlock at CRAN
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Package autostsm updated to version 3.1.0 with previous version 3.0.4 dated 2023-02-23

Title: Automatic Structural Time Series Models
Description: Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components, plus optionality for structural interpolation, using the Kalman filter. Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models" <doi:10.1093/oxfordhb/9780195398649.013.0006>. Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" <doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.
Author: Alex Hubbard [aut, cre]
Maintainer: Alex Hubbard <hubbard.alex@gmail.com>

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More information about autostsm at CRAN
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Package protr updated to version 1.6-3 with previous version 1.6-2 dated 2019-05-18

Title: Generating Various Numerical Representation Schemes for Protein Sequences
Description: Comprehensive toolkit for generating various numerical features of protein sequences described in Xiao et al. (2015) <DOI:10.1093/bioinformatics/btv042>. For full functionality, the software 'ncbi-blast+' is needed, see <https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocs&DOC_TYPE=Download> for more information.
Author: Nan Xiao [aut, cre] , Qing-Song Xu [aut], Dong-Sheng Cao [aut]
Maintainer: Nan Xiao <me@nanx.me>

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More information about protr at CRAN
Permanent link


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