Sat, 21 Dec 2024

Package learningtower updated to version 1.1.0 with previous version 1.0.1 dated 2023-02-18

Title: OECD PISA Datasets from 2000-2022 in an Easy-to-Use Format
Description: The Programme for International Student Assessment (PISA) is a global study conducted by the Organization for Economic Cooperation and Development (OECD) in member and non-member countries to assess educational systems by assessing 15-year-old school students academic performance in mathematics, science, and reading. This datasets contains information on their scores and other socioeconomic characteristics, information about their school and its infrastructure, as well as the countries that are taking part in the program.
Author: Kevin Wang [aut, cre], Paul Yacobellis [aut], Erika Siregar [aut], Sarah Romanes [aut], Kim Fitter [aut], Giulio Valentino Dalla Riva [aut], Dianne Cook [aut], Nick Tierney [aut], Priya Dingorkar [aut], Shabarish Sai Subramanian [aut], Guan Ru Chen [ [...truncated...]
Maintainer: Kevin Wang <kevinwangstats@gmail.com>

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Package SVEMnet updated to version 1.3.0 with previous version 1.2.1 dated 2024-12-07

Title: Self-Validated Ensemble Models with Elastic Net Regression
Description: Implements Self-Validated Ensemble Models (SVEM, Lemkus et al. (2021) <doi:10.1016/j.chemolab.2021.104439>) using Elastic Net regression via 'glmnet' (Friedman et al. <doi:10.18637/jss.v033.i01>). SVEM averages predictions from multiple models fitted to fractionally weighted bootstraps of the data, tuned with anti-correlated validation weights. Also implements the randomized permutation whole model test for SVEM (Karl (2024) <doi:10.1016/j.chemolab.2024.105122>). \\Code for the whole model test was taken from the supplementary material of Karl (2024). Development of this package was assisted by 'GPT o1-preview' for code structure and documentation.
Author: Andrew T. Karl [cre, aut]
Maintainer: Andrew T. Karl <akarl@asu.edu>

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Package vtable updated to version 1.4.8 with previous version 1.4.7 dated 2024-10-17

Title: Variable Table for Variable Documentation
Description: Automatically generates HTML variable documentation including variable names, labels, classes, value labels (if applicable), value ranges, and summary statistics. See the vignette "vtable" for a package overview.
Author: Nick Huntington-Klein [aut, cre]
Maintainer: Nick Huntington-Klein <nhuntington-klein@seattleu.edu>

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Package rstpm2 updated to version 1.6.6.1 with previous version 1.6.6 dated 2024-10-29

Title: Smooth Survival Models, Including Generalized Survival Models
Description: R implementation of generalized survival models (GSMs), smooth accelerated failure time (AFT) models and Markov multi-state models. For the GSMs, g(S(t|x))=eta(t,x) for a link function g, survival S at time t with covariates x and a linear predictor eta(t,x). The main assumption is that the time effect(s) are smooth <doi:10.1177/0962280216664760>. For fully parametric models with natural splines, this re-implements Stata's 'stpm2' function, which are flexible parametric survival models developed by Royston and colleagues. We have extended the parametric models to include any smooth parametric smoothers for time. We have also extended the model to include any smooth penalized smoothers from the 'mgcv' package, using penalized likelihood. These models include left truncation, right censoring, interval censoring, gamma frailties and normal random effects <doi:10.1002/sim.7451>, and copulas. For the smooth AFTs, S(t|x) = S_0(t*eta(t,x)), where the baseline survival function S_0 [...truncated...]
Author: Mark Clements [aut, cre], Xing-Rong Liu [aut], Benjamin Christoffersen [aut], Paul Lambert [ctb], Lasse Hjort Jakobsen [ctb], Alessandro Gasparini [ctb], Gordon Smyth [cph], Patrick Alken [cph], Simon Wood [cph], Rhys Ulerich [cph]
Maintainer: Mark Clements <mark.clements@ki.se>

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Package Rfast updated to version 2.1.2 with previous version 2.1.0 dated 2023-11-09

Title: A Collection of Efficient and Extremely Fast R Functions
Description: A collection of fast (utility) functions for data analysis. Column and row wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), are some of the many fast functions. References: a) Tsagris M., Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints 6:e26605v1 <doi:10.7287/peerj.preprints.26605v1>. b) Tsagris M. and Papadakis M. (2018). Forward regression in R: from the extreme slow to the extreme fast. Journal of Data Science, 16(4): 771--780. <doi:10.6339/JDS.201810_16(4).00006>. c) Chatzipantsiou C., Dimitriadis M., Papadakis M. and Tsagris M. (2020). Extremely Efficient Permutation and Bootstrap Hypothesis Tests Using Hypothesis Tests Using R. Journal of Modern Applied Statistical Methods, 18(2), eP2898. <doi:10.48550/arXiv.1806.10947>.
Author: Manos Papadakis [aut, cre, cph], Michail Tsagris [aut], Marios Dimitriadis [ctb], Stefanos Fafalios [aut], Ioannis Tsamardinos [ctb], Matteo Fasiolo [ctb], Giorgos Borboudakis [ctb], John Burkardt [ctb], Changliang Zou [ctb], Kleanthi Lakiotaki [ctb] [...truncated...]
Maintainer: Manos Papadakis <rfastofficial@gmail.com>

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Package esci updated to version 1.0.6 with previous version 1.0.5 dated 2024-09-23

Title: Estimation Statistics with Confidence Intervals
Description: A collection of functions and 'jamovi' module for the estimation approach to inferential statistics, the approach which emphasizes effect sizes, interval estimates, and meta-analysis. Nearly all functions are based on 'statpsych' and 'metafor'. This package is still under active development, and breaking changes are likely, especially with the plot and hypothesis test functions. Data sets are included for all examples from Cumming & Calin-Jageman (2024) <ISBN:9780367531508>.
Author: Robert Calin-Jageman [aut, cre, cph]
Maintainer: Robert Calin-Jageman <rcalinjageman@dom.edu>

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Package MultiTraits updated to version 0.2.0 with previous version 0.1.0 dated 2024-11-26

Title: Analyzing and Visualizing Multidimensional Plant Traits
Description: Implements analytical methods for multidimensional plant traits, including Competitors-Stress tolerators-Ruderals strategy analysis using leaf traits, Leaf-Height-Seed strategy analysis, Niche Periodicity Table analysis, and Trait Network analysis. Provides functions for data analysis, visualization, and network metrics calculation. Methods are based on Grime (1974) <doi:10.1038/250026a0>, Pierce et al. (2017) <doi:10.1111/1365-2435.12882>, Westoby (1998) <doi:10.1023/A:1004327224729>, Yang et al. (2022) <doi:10.1016/j.foreco.2022.120540>, Winemiller et al. (2015) <doi:10.1111/ele.12462>, He et al. (2020) <doi:10.1016/j.tree.2020.06.003>.
Author: Yan He [aut, cre]
Maintainer: Yan He <heyan@njfu.edu.cn>

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Package vcfppR updated to version 0.7.0 with previous version 0.6.0 dated 2024-09-29

Title: Rapid Manipulation of the Variant Call Format (VCF)
Description: The 'vcfpp.h' (<https://github.com/Zilong-Li/vcfpp>) provides an easy-to-use 'C++' 'API' of 'htslib', offering full functionality for manipulating Variant Call Format (VCF) files. The 'vcfppR' package serves as the R bindings of the 'vcfpp.h' library, enabling rapid processing of both compressed and uncompressed VCF files. Explore a range of powerful features for efficient VCF data manipulation.
Author: Zilong Li [aut, cre] , Bonfield, James K and Marshall, John and Danecek, Petr and Li, Heng and Ohan, Valeriu and Whitwham, Andrew and Keane, Thomas and Davies, Robert M [cph]
Maintainer: Zilong Li <zilong.dk@gmail.com>

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Package calendRio updated to version 0.2.1 with previous version 0.2.0 dated 2022-03-10

Title: 'calendR' Fork with Additional Features (Backwards Compatible)
Description: Fork of 'calendR' R package to generate ready to print calendars with 'ggplot2' (see <https://r-coder.com/calendar-plot-r/>) with additional features (backwards compatible). 'calendRio' provides a 'calendR()' function that serves as a drop-in replacement for the upstream version but allows for additional parameters unlocking extra functionality.
Author: Jose Carlos Soage Gonzalez [aut, cph], Natalia Perez Veiga [aut, cph], Marcel Schilling [aut, cph, cre]
Maintainer: Marcel Schilling <foss@mschilli.com>

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Package pqrBayes updated to version 1.0.3 with previous version 1.0.2 dated 2023-09-14

Title: Bayesian Penalized Quantile Regression
Description: The quantile varying coefficient model is robust to data heterogeneity, outliers and heavy-tailed distributions in the response variable. In addition, it can flexibly model dynamic patterns of regression coefficients through nonparametric varying coefficient functions. In this package, we have implemented the Gibbs samplers of the penalized Bayesian quantile varying coefficient model with spike-and-slab priors [Zhou et al.(2023)]<doi:10.1016/j.csda.2023.107808> for efficient Bayesian shrinkage estimation, variable selection and statistical inference. In particular, valid Bayesian inferences on sparse quantile varying coefficient functions can be validated on finite samples. The Markov Chain Monte Carlo (MCMC) algorithms of the proposed and alternative models can be efficiently performed by using the package.
Author: Cen Wu [aut, cre], Kun Fan [aut], Jie Ren [aut], Fei Zhou [aut]
Maintainer: Cen Wu <wucen@ksu.edu>

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Package loa updated to version 0.3.1.1 with previous version 0.3.0.1 dated 2024-12-13

Title: Lattice Options and Add-Ins
Description: Various plots and functions that make use of the lattice/trellis plotting framework. The plots, which include loaPlot(), loaMapPlot() and trianglePlot(), and use panelPal(), a function that extends 'lattice' and 'hexbin' package methods to automate plot subscript and panel-to-panel and panel-to-key synchronization/management.
Author: Karl Ropkins [aut, cre]
Maintainer: Karl Ropkins <karl.ropkins@gmail.com>

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