Mon, 17 Apr 2023

Package penAFT updated to version 0.3.0 with previous version 0.2.0 dated 2022-01-25

Title: Fit the Regularized Gehan Estimator with Elastic Net and Sparse Group Lasso Penalties
Description: The semiparametric accelerated failure time (AFT) model is an attractive alternative to the Cox proportional hazards model. This package provides a suite of functions for fitting one popular estimator of the semiparametric AFT model, the regularized Gehan estimator. Specifically, we provide functions for cross-validation, prediction, coefficient extraction, and visualizing both trace plots and cross-validation curves. For further details, please see Suder, P. M. and Molstad, A. J., (2022+) Scalable algorithms for semiparametric accelerated failure time models in high dimensions, to appear in Statistics in Medicine <doi:10.1002/sim.9264>.
Author: Aaron J. Molstad [aut, cre] , Piotr M. Suder [aut]
Maintainer: Aaron J. Molstad <amolstad@ufl.edu>

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Package fastmatrix updated to version 0.5 with previous version 0.4-1245 dated 2022-10-07

Title: Fast Computation of some Matrices Useful in Statistics
Description: Small set of functions to fast computation of some matrices and operations useful in statistics and econometrics. Currently, there are functions for efficient computation of duplication, commutation and symmetrizer matrices with minimal storage requirements. Some commonly used matrix decompositions (LU and LDL), basic matrix operations (for instance, Hadamard, Kronecker products and the Sherman-Morrison formula) and iterative solvers for linear systems are also available. In addition, the package includes a number of common statistical procedures such as the sweep operator, weighted mean and covariance matrix using an online algorithm, linear regression (using Cholesky, QR, SVD, sweep operator and conjugate gradients methods), ridge regression (with optimal selection of the ridge parameter considering several procedures), functions to compute the multivariate skewness, kurtosis, Mahalanobis distance (checking the positive defineteness) and the Wilson-Hilferty transformation of chi squa [...truncated...]
Author: Felipe Osorio [aut, cre] , Alonso Ogueda [aut]
Maintainer: Felipe Osorio <felipe.osorios@usm.cl>

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Package TH.data updated to version 1.1-2 with previous version 1.1-1 dated 2022-04-26

Title: TH's Data Archive
Description: Contains data sets used in other packages Torsten Hothorn maintains.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package lablaster updated to version 1.0.1 with previous version 0.0.1 dated 2022-06-23

Title: Laser Ablation Blast Through Endpoint Detection
Description: Imports a data frame containing a single time resolved laser ablation mass spectrometry analysis of a foraminifera (or other carbonate shell), then detects when the laser has burnt through the foraminifera test as a function of change in signal over time.
Author: Alex Searle-Barnes [aut, cre]
Maintainer: Alex Searle-Barnes <c.j.a.searle-barnes@soton.ac.uk>

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Package ROI.models.netlib updated to version 1.1-2 with previous version 1.1-1 dated 2020-08-29

Title: 'ROI' Optimization Problems Based on 'NETLIB-LP'
Description: A collection of 'ROI' optimization problems based on the 'NETLIB-LP' collection. 'Netlib' is a software repository, which amongst many other software for scientific computing contains a collection of linear programming problems. The purpose of this package is to make this problems easily accessible from 'R' as 'ROI' optimization problems.
Author: Florian Schwendinger [aut, cre]
Maintainer: Florian Schwendinger <FlorianSchwendinger@gmx.at>

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Package pairwise updated to version 0.6.1-0 with previous version 0.6.0-0 dated 2022-08-25

Title: Rasch Model Parameters by Pairwise Algorithm
Description: Performs the explicit calculation -- not estimation! -- of the Rasch item parameters for dichotomous and polytomous item responses, using a pairwise comparison approach. Person parameters (WLE) are calculated according to Warm's weighted likelihood approach.
Author: Joerg-Henrik Heine <jhheine@googlemail.com>
Maintainer: Joerg-Henrik Heine <jhheine@googlemail.com>

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Package newsmd updated to version 0.5.1 with previous version 0.4.0 dated 2022-02-16

Title: Creation of NEWS.md File
Description: Adding updates (version or bullet points) to the NEWS.md file.
Author: Jakob Gepp [cre, aut]
Maintainer: Jakob Gepp <jakob.gepp@yahoo.de>

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Package CARRoT updated to version 3.0.0 with previous version 2.5.2 dated 2021-06-08

Title: Predicting Categorical and Continuous Outcomes Using One in Ten Rule
Description: Predicts categorical or continuous outcomes while concentrating on a number of key points. These are Cross-validation, Accuracy, Regression and Rule of Ten or "one in ten rule" (CARRoT), and, in addition to it R-squared statistics, prior knowledge on the dataset etc. It performs the cross-validation specified number of times by partitioning the input into training and test set and fitting linear/multinomial/binary regression models to the training set. All regression models satisfying chosen constraints are fitted and the ones with the best predictive power are given as an output. Best predictive power is understood as highest accuracy in case of binary/multinomial outcomes, smallest absolute and relative errors in case of continuous outcomes. For binary case there is also an option of finding a regression model which gives the highest AUROC (Area Under Receiver Operating Curve) value. The option of parallel toolbox is also available. Methods are described in Peduzzi et al. (1996) < [...truncated...]
Author: Alina Bazarova [aut, cre], Marko Raseta [aut]
Maintainer: Alina Bazarova <al.bazarova@fz-juelich.de>

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Package afex updated to version 1.3-0 with previous version 1.2-1 dated 2023-01-09

Title: Analysis of Factorial Experiments
Description: Convenience functions for analyzing factorial experiments using ANOVA or mixed models. aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e., repeated-measures), or mixed (i.e., split-plot) ANOVAs for data in long format (i.e., one observation per row), automatically aggregating multiple observations per individual and cell of the design. mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed effects using either Kenward-Roger or Satterthwaite approximation for degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). afex_plot() provides a high-level interface for interaction or one-way plots using ggplot2, combining raw data and model estimates. afex uses type 3 sums of squares as default (imitating commercial statistical software).
Author: Henrik Singmann [aut, cre] , Ben Bolker [aut], Jake Westfall [aut], Frederik Aust [aut] , Mattan S. Ben-Shachar [aut], Soeren Hoejsgaard [ctb], John Fox [ctb], Michael A. Lawrence [ctb], Ulf Mertens [ctb], Jonathon Love [ctb], Russell Lenth [ctb], Rune [...truncated...]
Maintainer: Henrik Singmann <singmann@gmail.com>

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Package samplingR updated to version 0.1.3 with previous version 0.1.2 dated 2023-03-19

Title: Sampling and Estimation Methods
Description: Functions to take samples of data, sample size estimation and getting useful estimators such as total, mean, proportion about its population using simple random sampling and stratified sampling.
Author: Javier Estevez [aut, cre, cph]
Maintainer: Javier Estevez <javier.estase@gmail.com>

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Package RSC updated to version 2.0.4 with previous version 2.0.2 dated 2022-06-20

Title: Robust and Sparse Correlation Matrix
Description: Performs robust and sparse correlation matrix estimation. Robustness is achieved based on a simple robust pairwise correlation estimator, while sparsity is obtained based on thresholding. The optimal thresholding is tuned via cross-validation. See Serra, Coretto, Fratello and Tagliaferri (2018) <doi:10.1093/bioinformatics/btx642>.
Author: Luca Coraggio [cre, aut], Pietro Coretto [aut], Angela Serra [aut], Roberto Tagliaferri [ctb]
Maintainer: Luca Coraggio <luca.coraggio@unina.it>

Diff between RSC versions 2.0.2 dated 2022-06-20 and 2.0.4 dated 2023-04-17

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Package MazamaSpatialUtils updated to version 0.8.5 with previous version 0.8.1 dated 2022-11-09

Title: Spatial Data Download and Utility Functions
Description: A suite of conversion functions to create internally standardized spatial polygons data frames. Utility functions use these data sets to return values such as country, state, time zone, watershed, etc. associated with a set of longitude/latitude pairs. (They also make cool maps.)
Author: Jonathan Callahan [aut, cre], Rachel Carroll [aut], Eli Grosman [aut], Roger Andre [aut], Tom Bergamaschi [aut], Tina Chen [aut], Ruby Fore [aut], Will Leahy [aut], Helen Miller [aut], Henry Nguyen [aut], Robin Winstanley [aut], Alice Yang [aut]
Maintainer: Jonathan Callahan <jonathan.s.callahan@gmail.com>

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Package humanleague updated to version 2.2.0 with previous version 2.1.11 dated 2023-01-06

Title: Synthetic Population Generator
Description: Generates high-entropy integer synthetic populations from marginal and (optionally) seed data using quasirandom sampling, in arbitrary dimensionality (Smith, Lovelace and Birkin (2017) <doi:10.18564/jasss.3550>). The package also provides an implementation of the Iterative Proportional Fitting (IPF) algorithm (Zaloznik (2011) <doi:10.13140/2.1.2480.9923>).
Author: Andrew Smith [aut, cre], Steven Johnson [ctb] , Massachusetts Institute of Technology [cph] , John Burkhardt [ctb, cph] , G Bhattacharjee [ctb]
Maintainer: Andrew Smith <andrew@friarswood.net>

Diff between humanleague versions 2.1.11 dated 2023-01-06 and 2.2.0 dated 2023-04-17

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Package tableHTML updated to version 2.1.2 with previous version 2.1.1 dated 2022-12-07

Title: A Tool to Create HTML Tables
Description: A tool to create and style HTML tables with CSS. These can be exported and used in any application that accepts HTML (e.g. 'shiny', 'rmarkdown', 'PowerPoint'). It also provides functions to create CSS files (which also work with shiny).
Author: Theo Boutaris [aut, cre, cph], Clemens Zauchner [aut], Dana Jomar [aut]
Maintainer: Theo Boutaris <teoboot2007@hotmail.com>

Diff between tableHTML versions 2.1.1 dated 2022-12-07 and 2.1.2 dated 2023-04-17

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New package TukeyRegion with initial version 0.1.6.3
Package: TukeyRegion
Title: Tukey Region and Median
Version: 0.1.6.3
Date: 2023-04-17
Description: Tukey regions are polytopes in the Euclidean space, viz. upper-level sets of the Tukey depth function on given data. The bordering hyperplanes of a Tukey region are computed as well as its vertices, facets, centroid, and volume. In addition, the Tukey median set, which is the non-empty Tukey region having highest depth level, and its barycenter (= Tukey median) are calculated. Tukey regions are visualized in dimension two and three. For details see Liu, Mosler, and Mozharovskyi (2019, <doi:10.1080/10618600.2018.1546595>). See file LICENSE.note for additional license information.
License: GPL (>= 3)
Depends: rgl,ddalpha,MASS,bfp,Rglpk
Imports: Rcpp (>= 0.11.0)
LinkingTo: Rcpp,BH
NeedsCompilation: yes
Packaged: 2023-04-17 16:29:41 UTC; pavlomozharovskyi
Author: C.B. Barber [aut, cph] , The Geometry Center University of Minnesota [cph] , Pavlo Mozharovskyi [aut, cre]
Maintainer: Pavlo Mozharovskyi <pavlo.mozharovskyi@telecom-paris.fr>
Repository: CRAN
Date/Publication: 2023-04-17 18:30:10 UTC

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Package ppseq updated to version 0.2.2 with previous version 0.2.0 dated 2022-08-08

Title: Design Clinical Trials using Sequential Predictive Probability Monitoring
Description: Functions are available to calibrate designs over a range of posterior and predictive thresholds, to plot the various design options, and to obtain the operating characteristics of optimal accuracy and optimal efficiency designs.
Author: Emily C. Zabor [aut, cre] , Brian P. Hobbs [aut], Michael J. Kane [aut]
Maintainer: Emily C. Zabor <zabore2@ccf.org>

Diff between ppseq versions 0.2.0 dated 2022-08-08 and 0.2.2 dated 2023-04-17

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Package MSCMT updated to version 1.3.7 with previous version 1.3.6 dated 2023-03-09

Title: Multivariate Synthetic Control Method Using Time Series
Description: Three generalizations of the synthetic control method (which has already an implementation in package 'Synth') are implemented: first, 'MSCMT' allows for using multiple outcome variables, second, time series can be supplied as economic predictors, and third, a well-defined cross-validation approach can be used. Much effort has been taken to make the implementation as stable as possible (including edge cases) without losing computational efficiency. A detailed description of the main algorithms is given in Becker and Klößner (2018) <doi:10.1016/j.ecosta.2017.08.002>.
Author: Martin Becker [aut, cre] , Stefan Kloeßner [aut], Karline Soetaert [com], Jack Dongarra [cph], R.J. Hanson [cph], K.H. Haskell [cph], Cleve Moler [cph], LAPACK authors [cph]
Maintainer: Martin Becker <martin.becker@mx.uni-saarland.de>

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Package baizer updated to version 0.4.5 with previous version 0.4.0 dated 2023-04-11

Title: Useful Functions for Data Processing
Description: In ancient Chinese mythology, Bai Ze is a divine creature that knows the needs of everything. 'baizer' provides data processing functions frequently used by the author. Hope this package also knows what you want!
Author: William Song [aut, cre]
Maintainer: William Song <william_swl@163.com>

Diff between baizer versions 0.4.0 dated 2023-04-11 and 0.4.5 dated 2023-04-17

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Package kernscr updated to version 1.0.6 with previous version 1.0.5 dated 2019-08-20

Title: Kernel Machine Score Test for Semi-Competing Risks
Description: Kernel Machine Score Test for Pathway Analysis in the Presence of Semi-Competing Risks. Method is detailed in: Neykov, Hejblum & Sinnott (2018) <doi: 10.1177/0962280216653427>.
Author: Matey Neykov [aut], Boris P Hejblum [aut, cre], Jennifer A Sinnot [aut]
Maintainer: Boris P Hejblum <boris.hejblum@u-bordeaux.fr>

Diff between kernscr versions 1.0.5 dated 2019-08-20 and 1.0.6 dated 2023-04-17

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Package zip updated to version 2.3.0 with previous version 2.2.2 dated 2022-10-26

Title: Cross-Platform 'zip' Compression
Description: Cross-Platform 'zip' Compression Library. A replacement for the 'zip' function, that does not require any additional external tools on any platform.
Author: Gabor Csardi, Kuba Podgorski, Rich Geldreich
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between zip versions 2.2.2 dated 2022-10-26 and 2.3.0 dated 2023-04-17

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Package pomp updated to version 5.1 with previous version 4.7 dated 2023-03-02

Title: Statistical Inference for Partially Observed Markov Processes
Description: Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.
Author: Aaron A. King [aut, cre] , Edward L. Ionides [aut] , Carles Breto [aut] , Stephen P. Ellner [ctb] , Matthew J. Ferrari [ctb], Sebastian Funk [ctb] , Steven G. Johnson [ctb], Bruce E. Kendall [ctb] , Michael Lavine [ctb], Dao Nguyen [ctb] , Eamon B. O [...truncated...]
Maintainer: Aaron A. King <kingaa@umich.edu>

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Package LongDat updated to version 1.1.1 with previous version 1.1.0 dated 2022-07-14

Title: A Tool for 'Covariate'-Sensitive Longitudinal Analysis on 'omics' Data
Description: This tool takes longitudinal dataset as input and analyzes if there is significant change of the features over time (a proxy for treatments), while detects and controls for 'covariates' simultaneously. 'LongDat' is able to take in several data types as input, including count, proportion, binary, ordinal and continuous data. The output table contains p values, effect sizes and 'covariates' of each feature, making the downstream analysis easy.
Author: Chia-Yu Chen [aut, cre] , Sofia Forslund [ctb]
Maintainer: Chia-Yu Chen <Chia-Yu.Chen@mdc-berlin.de>

Diff between LongDat versions 1.1.0 dated 2022-07-14 and 1.1.1 dated 2023-04-17

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Package khroma updated to version 1.10.0 with previous version 1.9.0 dated 2022-06-18

Title: Colour Schemes for Scientific Data Visualization
Description: Colour schemes ready for each type of data (qualitative, diverging or sequential), with colours that are distinct for all people, including colour-blind readers. This package provides an implementation of Paul Tol (2018) and Fabio Crameri (2018) <doi:10.5194/gmd-11-2541-2018> colour schemes for use with 'graphics' or 'ggplot2'. It provides tools to simulate colour-blindness and to test how well the colours of any palette are identifiable. Several scientific thematic schemes (geologic timescale, land cover, FAO soils, etc.) are also implemented.
Author: Nicolas Frerebeau [aut, cre] , Brice Lebrun [ctb] , Vincent Arel-Bundock [ctb] , Ulrik Stervbo [ctb]
Maintainer: Nicolas Frerebeau <nicolas.frerebeau@u-bordeaux-montaigne.fr>

Diff between khroma versions 1.9.0 dated 2022-06-18 and 1.10.0 dated 2023-04-17

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Package CRE updated to version 0.2.2 with previous version 0.2.1 dated 2023-03-17

Title: Interpretable Subgroups Identification Through Ensemble Learning of Causal Rules
Description: Provides an interpretable identification of subgroups with heterogeneous causal effect. The heterogeneous subgroups are discovered through ensemble learning of causal rules. Causal rules are highly interpretable if-then statement that recursively partition the features space into heterogeneous subgroups. A small number of significant causal rules are selected through Stability Selection to control for family-wise error rate in the finite sample setting. It proposes various estimation methods for the conditional causal effects for each discovered causal rule. It is highly flexible and multiple causal estimands and imputation methods are implemented. Lee, K., Bargagli-Stoffi, F. J., & Dominici, F. (2020). Causal rule ensemble: Interpretable inference of heterogeneous treatment effects. arXiv preprint <arXiv:2009.09036>.
Author: Naeem Khoshnevis [aut, cre] , Daniela Maria Garcia [aut] , Riccardo Cadei [aut] , Kwonsang Lee [aut] , Falco Joannes Bargagli Stoffi [aut]
Maintainer: Naeem Khoshnevis <nkhoshnevis@g.harvard.edu>

Diff between CRE versions 0.2.1 dated 2023-03-17 and 0.2.2 dated 2023-04-17

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New package gKRLS with initial version 1.0.1
Package: gKRLS
Title: Generalized Kernel Regularized Least Squares
Version: 1.0.1
Date: 2023-4-13
Encoding: UTF-8
License: GPL (>= 2)
Description: Kernel regularized least squares, also known as kernel ridge regression, is a flexible machine learning method. This package implements this method by providing a smooth term for use with 'mgcv' and uses random sketching to facilitate scalable estimation on large datasets. It provides additional functions for calculating marginal effects after estimation and for use with ensembles ('SuperLearning'), double/debiased machine learning ('DoubleML'), and robust/clustered standard errors ('sandwich'). Chang and Goplerud (2023) <arXiv:2209.14355> provide further details.
LinkingTo: Rcpp, RcppEigen
Imports: Rcpp (>= 1.0.6), Matrix, mlr3, R6
Depends: mgcv, sandwich (>= 2.4.0)
Suggests: SuperLearner, mlr3misc, DoubleML, testthat
SystemRequirements: GNU make
NeedsCompilation: yes
URL: https://github.com/mgoplerud/gKRLS
BugReports: https://github.com/mgoplerud/gKRLS/issues
Packaged: 2023-04-14 19:59:14 UTC; MHG23
Author: Qing Chang [aut], Max Goplerud [aut, cre]
Maintainer: Max Goplerud <mgoplerud@pitt.edu>
Repository: CRAN
Date/Publication: 2023-04-17 10:30:02 UTC

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New package fqadata with initial version 1.0.0
Package: fqadata
Title: Contains Regional Floristic Quality Assessment Databases
Version: 1.0.0
Description: Contains regional Floristic Quality Assessment databases that have been approved or approved with reservations by the U.S. Army Corps of Engineers (USACE). Paired with the 'fqacalc' R package, these data sets allow for Floristic Quality Assessment metrics to be calculated. For information on FQA see Spyreas (2019) <doi:10.1002/ecs2.2825>. Both packages were developed for the USACE by the U.S. Army Engineer Research and Development Center's Environmental Laboratory.
License: CC0
Depends: R (>= 2.10)
Suggests: dplyr, testthat (>= 3.0.0)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2023-04-14 21:29:42 UTC; irisfoxfoot
Author: Iris Foxfoot [aut, cre], U.S. Army Engineer Research and Development Center [cph, fnd]
Maintainer: Iris Foxfoot <iris.r.foxfoot@usace.army.mil>
Repository: CRAN
Date/Publication: 2023-04-17 10:40:02 UTC

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New package BayesQVGEL with initial version 0.1.0
Package: BayesQVGEL
Title: Bayesian Quantile Variable Selection for G - E in Longitudinal Studies
Version: 0.1.0
Date: 2023-04-03
Description: In longitudinal studies, the same subjects are measured repeatedly over time, leading to correlations among the repeated measurements. Properly accounting for the intra-cluster correlations in the presence of data heterogeneity and long tailed distributions of the disease phenotype is challenging, especially in the context of high dimensional regressions. Here, we aim at developing novel Bayesian regularized quantile mixed effect models to tackle these challenges. We have proposed a Bayesian variable selection in the mixed effect models for longitudinal genomics studies. To dissect important gene - environment interactions, our model can simultaneously identify important main and interaction effects on the individual and group level, which have been facilitated by imposing the spike- and -slab priors through Laplacian shrinkage in the Bayesian quantile hierarchical models. The within - subject dependence among data can be accommodated by incorporating the random effects. An efficient G [...truncated...]
Depends: R (>= 4.2.0)
License: GPL-2
Encoding: UTF-8
URL: https://github.com/kunfa/BayesQVGEL
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2023-04-14 20:20:03 UTC; grimf
Author: Kun Fan [aut, cre], Cen Wu [aut]
Maintainer: Kun Fan <kfan@ksu.edu>
Repository: CRAN
Date/Publication: 2023-04-17 10:40:08 UTC

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New package AHPtools with initial version 0.1.0
Package: AHPtools
Title: Consistency in the Analytic Hierarchy Process
Version: 0.1.0
URL: <https://CRAN.R-project.org/package=AHPtools>
Description: A set of three functions for 'AHP' users, namely CR() which evaluates the Consistency Ratio for a given 'PCM', improveCR() for any input 'PCM' suggests a matrix with preferences similar to the original preferences, having greater consistency than the input matrix and sensitivity() for an input 'PCM' returns the average rank correlation of the principal eigenvector of the input 'PCM' and of 500 sample matrices generated by random perturbations of elements of the input matrix to within the five nearest elements in the Fundamental Scale.
License: GPL-3
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2023-04-15 02:19:10 UTC; amarnath
Author: Amarnath Bose [aut, cre]
Maintainer: Amarnath Bose <amarnath.bose@gmail.com>
Repository: CRAN
Date/Publication: 2023-04-17 10:50:03 UTC

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New package swaprinc with initial version 1.0.1
Package: swaprinc
Title: Swap Principal Components into Regression Models
Version: 1.0.1
Description: Obtaining accurate and stable estimates of regression coefficients can be challenging when the suggested statistical model has issues related to multicollinearity, convergence, or overfitting. One solution is to use principal component analysis (PCA) results in the regression, as discussed in Chan and Park (2005) <doi:10.1080/01446190500039812>. The swaprinc() package streamlines comparisons between a raw regression model with the full set of raw independent variables and a principal component regression model where principal components are estimated on a subset of the independent variables, then swapped into the regression model in place of those variables. The swaprinc() function compares one raw regression model to one principal component regression model, while the compswap() function compares one raw regression model to many principal component regression models. Package functions include parameters to center, scale, and undo centering and scaling, as described by Harvey and [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/mncube/swaprinc
BugReports: https://github.com/mncube/swaprinc/issues
Imports: broom, broom.mixed, dplyr, Gifi, lme4, magrittr, rlang, tidyselect
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2023-04-14 15:47:08 UTC; Administrator
Author: Mackson Ncube [aut, cre, cph]
Maintainer: Mackson Ncube <macksonncube.stats@gmail.com>
Repository: CRAN
Date/Publication: 2023-04-17 10:00:02 UTC

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Package luz updated to version 0.4.0 with previous version 0.3.1 dated 2022-09-06

Title: Higher Level 'API' for 'torch'
Description: A high level interface for 'torch' providing utilities to reduce the the amount of code needed for common tasks, abstract away torch details and make the same code work on both the 'CPU' and 'GPU'. It's flexible enough to support expressing a large range of models. It's heavily inspired by 'fastai' by Howard et al. (2020) <arXiv:2002.04688>, 'Keras' by Chollet et al. (2015) and 'PyTorch Lightning' by Falcon et al. (2019) <doi:10.5281/zenodo.3828935>.
Author: Daniel Falbel [aut, cre, cph], RStudio [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>

Diff between luz versions 0.3.1 dated 2022-09-06 and 0.4.0 dated 2023-04-17

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New package intmap with initial version 1.0.0
Package: intmap
Title: Ordered Containers with Integer Keys
Version: 1.0.0
Author: Stephane Laurent
Maintainer: Stephane Laurent <laurent_step@outlook.fr>
Description: Provides a key-value store data structure. The keys are integers and the values can be any R object. This is like a list but indexed by a set of integers, not necessarily contiguous and possibly negative. The implementation uses a 'R6' class. These containers are not faster than lists but their usage can be more convenient for certain situations.
License: GPL-3
URL: https://github.com/stla/intmap
BugReports: https://github.com/stla/intmap/issues
Imports: maybe, methods, R6, Rcpp (>= 1.0.8)
LinkingTo: BH, Rcpp
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2023-04-14 15:27:47 UTC; stla
Repository: CRAN
Date/Publication: 2023-04-17 10:00:10 UTC

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New package iccTraj with initial version 1.0.2
Package: iccTraj
Title: Estimates the Intraclass Correlation Coefficient for Trajectory Data
Version: 1.0.2
Depends: R (>= 4.0)
Imports: doParallel, dplyr, magic, trajectories, sp, spacetime, purrr, utils, foreach
Description: Estimates the intraclass correlation coefficient for trajectory data using a matrix of distances between trajectories. The distances implemented are the extended Hausdorff distances (Min et al. 2007) <doi:10.1080/13658810601073315> and the discrete Fréchet distance (Magdy et al. 2015) <doi:10.1109/IntelCIS.2015.7397286>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2023-04-14 13:37:07 UTC; hexac
Author: Josep L. Carrasco [aut, cre]
Maintainer: Josep L. Carrasco <jlcarrasco@ub.edu>
Repository: CRAN
Date/Publication: 2023-04-17 09:50:02 UTC

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New package asmbPLS with initial version 1.0.0
Package: asmbPLS
Title: Predicting and Classifying Patient Phenotypes with Multi-Omics Data
Version: 1.0.0
Date: 2023-04-13
Description: Adaptive Sparse Multi-block Partial Least Square, a supervised algorithm, is an extension of the Sparse Multi-block Partial Least Square, which allows different quantiles to be used in different blocks of different partial least square components to decide the proportion of features to be retained. The best combinations of quantiles can be chosen from a set of user-defined quantiles combinations by cross-validation. By doing this, it enables us to do the feature selection for different blocks, and the selected features can then be further used to predict the outcome. For example, in biomedical applications, clinical covariates plus different types of omics data such as microbiome, metabolome, mRNA data, methylation data, copy number variation data might be predictive for patients outcome such as survival time or response to therapy. Different types of data could be put in different blocks and along with survival time to fit the model. The fitted model can then be used to predict the su [...truncated...]
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.8), ggplot2, ggpubr, stats
LinkingTo: Rcpp, RcppArmadillo
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Author: Runzhi Zhang [aut, cre], Susmita Datta [aut, ths]
Maintainer: Runzhi Zhang <runzhi.zhang@ufl.edu>
NeedsCompilation: yes
Packaged: 2023-04-13 23:01:41 UTC; zhang
Repository: CRAN
Date/Publication: 2023-04-17 09:50:05 UTC

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Package SDLfilter updated to version 2.3.2 with previous version 2.3.1 dated 2023-01-16

Title: Filtering and Assessing the Sample Size of Tracking Data
Description: Functions to filter GPS/Argos locations, as well as assessing the sample size for the analysis of animal distributions. The filters remove temporal and spatial duplicates, fixes located at a given height from estimated high tide line, and locations with high error as described in Shimada et al. (2012) <doi:10.3354/meps09747> and Shimada et al. (2016) <doi:10.1007/s00227-015-2771-0>. Sample size for the analysis of animal distributions can be assessed by the conventional area-based approach or the alternative probability-based approach as described in Shimada et al. (2021) <doi:10.1111/2041-210X.13506>.
Author: Takahiro Shimada
Maintainer: Takahiro Shimada <taka.shimada@gmail.com>

Diff between SDLfilter versions 2.3.1 dated 2023-01-16 and 2.3.2 dated 2023-04-17

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Package MKinfer updated to version 1.1 with previous version 1.0 dated 2023-03-14

Title: Inferential Statistics
Description: Computation of various confidence intervals (Altman et al. (2000), ISBN:978-0-727-91375-3; Hedderich and Sachs (2018), ISBN:978-3-662-56657-2) including bootstrapped versions (Davison and Hinkley (1997), ISBN:978-0-511-80284-3) as well as Hsu (Hedderich and Sachs (2018), ISBN:978-3-662-56657-2), permutation (Janssen (1997), <doi:10.1016/S0167-7152(97)00043-6>), bootstrap (Davison and Hinkley (1997), ISBN:978-0-511-80284-3) and multiple imputation (Barnard and Rubin (1999), <doi:10.1093/biomet/86.4.948>) t-test and Wilcoxon tests. Graphical visualization by volcano and Bland-Altman plots (Bland and Altman (1986), <doi:10.1016/S0140-6736(86)90837-8>; Shieh (2018), <doi:10.1186/s12874-018-0505-y>).
Author: Matthias Kohl [aut, cre]
Maintainer: Matthias Kohl <Matthias.Kohl@stamats.de>

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Package mkin updated to version 1.2.3 with previous version 1.2.1 dated 2022-11-19

Title: Kinetic Evaluation of Chemical Degradation Data
Description: Calculation routines based on the FOCUS Kinetics Report (2006, 2014). Includes a function for conveniently defining differential equation models, model solution based on eigenvalues if possible or using numerical solvers. If a C compiler (on windows: 'Rtools') is installed, differential equation models are solved using automatically generated C functions. Heteroscedasticity can be taken into account using variance by variable or two-component error models as described by Ranke and Meinecke (2018) <doi:10.3390/environments6120124>. Hierarchical degradation models can be fitted using nonlinear mixed-effects model packages as a back end as described by Ranke et al. (2021) <doi:10.3390/environments8080071>. Please note that no warranty is implied for correctness of results or fitness for a particular purpose.
Author: Johannes Ranke [aut, cre, cph] , Katrin Lindenberger [ctb] ), Rene Lehmann [ctb] and invilr), Eurofins Regulatory AG [cph]
Maintainer: Johannes Ranke <johannes.ranke@jrwb.de>

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Package mirai updated to version 0.8.3 with previous version 0.8.2 dated 2023-04-03

Title: Minimalist Async Evaluation Framework for R
Description: Lightweight parallel code execution and distributed computing. Designed for simplicity, a 'mirai' evaluates an R expression asynchronously, on local or network resources, resolving automatically upon completion. Features efficient task scheduling, scalability beyond R connection limits, and transports faster than TCP/IP for inter-process communications, courtesy of 'nanonext' and 'NNG' (Nanomsg Next Gen).
Author: Charlie Gao [aut, cre] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

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Package mgwrsar updated to version 1.0.4 with previous version 1.0 dated 2022-05-05

Title: GWR and MGWR with Spatial Autocorrelation
Description: Functions for computing (Mixed) Geographycally Weighted Regression with spatial autocorrelation, Geniaux and Martinetti (2017) <doi:10.1016/j.regsciurbeco.2017.04.001>.
Author: Ghislain Geniaux and Davide Martinetti
Maintainer: Ghislain Geniaux <ghislain.geniaux@inrae.fr>

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Package lmeInfo updated to version 0.3.2 with previous version 0.3.1 dated 2023-02-15

Title: Information Matrices for 'lmeStruct' and 'glsStruct' Objects
Description: Provides analytic derivatives and information matrices for fitted linear mixed effects (lme) models and generalized least squares (gls) models estimated using lme() (from package 'nlme') and gls() (from package 'nlme'), respectively. The package includes functions for estimating the sampling variance-covariance of variance component parameters using the inverse Fisher information. The variance components include the parameters of the random effects structure (for lme models), the variance structure, and the correlation structure. The expected and average forms of the Fisher information matrix are used in the calculations, and models estimated by full maximum likelihood or restricted maximum likelihood are supported. The package also includes a function for estimating standardized mean difference effect sizes (Pustejovsky, Hedges, and Shadish (2014) <DOI:10.3102/1076998614547577>) based on fitted lme or gls models.
Author: James Pustejovsky [aut] , Man Chen [aut, cre]
Maintainer: Man Chen <manchen9005@gmail.com>

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Package dittodb updated to version 0.1.6 with previous version 0.1.5 dated 2023-04-12

Title: A Test Environment for Database Requests
Description: Testing and documenting code that communicates with remote databases can be painful. Although the interaction with R is usually relatively simple (e.g. data(frames) passed to and from a database), because they rely on a separate service and the data there, testing them can be difficult to set up, unsustainable in a continuous integration environment, or impossible without replicating an entire production cluster. This package addresses that by allowing you to make recordings from your database interactions and then play them back while testing (or in other contexts) all without needing to spin up or have access to the database your code would typically connect to.
Author: Jonathan Keane [aut, cre] , Mauricio Vargas [aut] , Helen Miller [rev] , Etienne Racine [rev]
Maintainer: Jonathan Keane <jkeane@gmail.com>

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Package hightR updated to version 0.2.0 with previous version 0.1.0 dated 2023-04-10

Title: HIGHT Algorithm
Description: HIGHT(HIGh security and light weigHT) algorithm is a block cipher encryption algorithm developed to provide confidentiality in computing environments that demand low power consumption and lightweight, such as RFID(Radio-Frequency Identification) and USN(Ubiquitous Sensor Network), or in mobile environments that require low power consumption and lightweight, such as smartphones and smart cards. Additionally, it is designed with a simple structure that enables it to be used with basic arithmetic operations, XOR, and circular shifts in 8-bit units. This algorithm was designed to consider both safety and efficiency in a very simple structure suitable for limited environments, compared to the former 128-bit encryption algorithm SEED. In December 2010, it became an ISO(International Organization for Standardization) standard. The detailed procedure is described in Hong et al. (2006) <doi:10.1007/11894063_4>.
Author: Yongwoo Kim [aut, cre]
Maintainer: Yongwoo Kim <yw_kim@outlook.com>

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Package oncomsm updated to version 0.1.4 with previous version 0.1.3 dated 2023-03-11

Title: Bayesian Multi-State Models for Early Oncology
Description: Implements methods to fit a parametric Bayesian multi-state model to tumor response data. The model can be used to sample from the predictive distribution to impute missing data and calculate probability of success for custom decision criteria in early clinical trials during an ongoing trial. The inference is implemented using 'stan'.
Author: Kevin Kunzmann [aut, cre] , Karthik Ananthakrishnan [ctb], Boehringer Ingelheim Ltd. [cph, fnd]
Maintainer: Kevin Kunzmann <kevin.kunzmann@boehringer-ingelheim.com>

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Package tinyarray (with last version 2.2.9) was removed from CRAN

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

2023-03-04 2.2.9
2021-11-08 2.2.7
2021-09-14 2.2.6

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

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

2023-03-27 1.0.2
2023-01-17 1.0.0

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