Tue, 17 Sep 2024

Package distributional updated to version 0.5.0 with previous version 0.4.0 dated 2024-02-07

Title: Vectorised Probability Distributions
Description: Vectorised distribution objects with tools for manipulating, visualising, and using probability distributions. Designed to allow model prediction outputs to return distributions rather than their parameters, allowing users to directly interact with predictive distributions in a data-oriented workflow. In addition to providing generic replacements for p/d/q/r functions, other useful statistics can be computed including means, variances, intervals, and highest density regions.
Author: Mitchell O'Hara-Wild [aut, cre] , Matthew Kay [aut] , Alex Hayes [aut] , Rob Hyndman [aut] , Earo Wang [ctb] , Vencislav Popov [ctb]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>

Diff between distributional versions 0.4.0 dated 2024-02-07 and 0.5.0 dated 2024-09-17

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Package bWGR updated to version 2.2.10 with previous version 2.2.9 dated 2024-05-20

Title: Bayesian Whole-Genome Regression
Description: Whole-genome regression methods on Bayesian framework fitted via EM or Gibbs sampling, single step (<doi:10.1534/g3.119.400728>), univariate and multivariate (<doi:10.1186/s12711-022-00730-w>), with optional kernel term and sampling techniques (<doi:10.1186/s12859-017-1582-3>).
Author: Alencar Xavier [aut, cre] , William Muir [aut], David Habier [aut], Kyle Kocak [aut], Shizhong Xu [aut], Katy Rainey [aut]
Maintainer: Alencar Xavier <alenxav@gmail.com>

Diff between bWGR versions 2.2.9 dated 2024-05-20 and 2.2.10 dated 2024-09-17

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Package feasts updated to version 0.4.0 with previous version 0.3.2 dated 2024-03-15

Title: Feature Extraction and Statistics for Time Series
Description: Provides a collection of features, decomposition methods, statistical summaries and graphics functions for the analysing tidy time series data. The package name 'feasts' is an acronym comprising of its key features: Feature Extraction And Statistics for Time Series.
Author: Mitchell O'Hara-Wild [aut, cre], Rob Hyndman [aut], Earo Wang [aut], Di Cook [ctb], Thiyanga Talagala [ctb] , Leanne Chhay [ctb]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>

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Package VGAMdata updated to version 1.1-12 with previous version 1.1-9 dated 2023-09-18

Title: Data Supporting the 'VGAM' Package
Description: Mainly data sets to accompany the VGAM package and the book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7>. These are used to illustrate vector generalized linear and additive models (VGLMs/VGAMs), and associated models (Reduced-Rank VGLMs, Quadratic RR-VGLMs, Row-Column Interaction Models, and constrained and unconstrained ordination models in ecology). This package now contains some old VGAM family functions which have been replaced by newer ones (often because they are now special cases).
Author: Thomas Yee [aut, cre, cph] , James Gray [dtc]
Maintainer: Thomas Yee <t.yee@auckland.ac.nz>

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Mon, 16 Sep 2024

Package trajmsm updated to version 0.1.2 with previous version 0.1.1 dated 2024-09-08

Title: Marginal Structural Models with Latent Class Growth Analysis of Treatment Trajectories
Description: Implements marginal structural models combined with a latent class growth analysis framework for assessing the causal effect of treatment trajectories. Based on the approach described in "Marginal Structural Models with Latent Class Growth Analysis of Treatment Trajectories" Diop, A., Sirois, C., Guertin, J.R., Schnitzer, M.E., Candas, B., Cossette, B., Poirier, P., Brophy, J., Mésidor, M., Blais, C. and Hamel, D., (2023) <doi:10.1177/09622802231202384>.
Author: Awa Diop [aut, cre], Denis Talbot [aut]
Maintainer: Awa Diop <awa.diop.2@ulaval.ca>

Diff between trajmsm versions 0.1.1 dated 2024-09-08 and 0.1.2 dated 2024-09-16

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Package LBI updated to version 0.1.4 with previous version 0.1.3 dated 2024-08-18

Title: Likelihood Based Inference
Description: Maximum likelihood estimation and likelihood ratio test are essential for modern statistics. This package supports in calculating likelihood based inference. Reference: Pawitan Y. (2001, ISBN:0-19-850765-8).
Author: Kyun-Seop Bae [aut, cre, cph]
Maintainer: Kyun-Seop Bae <k@acr.kr>

Diff between LBI versions 0.1.3 dated 2024-08-18 and 0.1.4 dated 2024-09-16

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Package BAS updated to version 1.7.2 with previous version 1.7.1 dated 2023-12-06

Title: Bayesian Variable Selection and Model Averaging using Bayesian Adaptive Sampling
Description: Package for Bayesian Variable Selection and Model Averaging in linear models and generalized linear models using stochastic or deterministic sampling without replacement from posterior distributions. Prior distributions on coefficients are from Zellner's g-prior or mixtures of g-priors corresponding to the Zellner-Siow Cauchy Priors or the mixture of g-priors from Liang et al (2008) <DOI:10.1198/016214507000001337> for linear models or mixtures of g-priors from Li and Clyde (2019) <DOI:10.1080/01621459.2018.1469992> in generalized linear models. Other model selection criteria include AIC, BIC and Empirical Bayes estimates of g. Sampling probabilities may be updated based on the sampled models using sampling w/out replacement or an efficient MCMC algorithm which samples models using a tree structure of the model space as an efficient hash table. See Clyde, Ghosh and Littman (2010) <DOI:10.1198/jcgs.2010.09049> for details on the sampling algorithms. Uniform prior [...truncated...]
Author: Merlise Clyde [aut, cre, cph] , Michael Littman [ctb], Joyee Ghosh [ctb], Yingbo Li [ctb], Betsy Bersson [ctb], Don van de Bergh [ctb], Quanli Wang [ctb]
Maintainer: Merlise Clyde <clyde@duke.edu>

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Package bartCause updated to version 1.0-9 with previous version 1.0-8 dated 2024-05-01

Title: Causal Inference using Bayesian Additive Regression Trees
Description: Contains a variety of methods to generate typical causal inference estimates using Bayesian Additive Regression Trees (BART) as the underlying regression model (Hill (2012) <doi:10.1198/jcgs.2010.08162>).
Author: Vincent Dorie [aut, cre] , Jennifer Hill [aut]
Maintainer: Vincent Dorie <vdorie@gmail.com>

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Package timeSeries updated to version 4041.110 with previous version 4032.109 dated 2024-01-14

Title: Financial Time Series Objects (Rmetrics)
Description: 'S4' classes and various tools for financial time series: Basic functions such as scaling and sorting, subsetting, mathematical operations and statistical functions.
Author: Diethelm Wuertz [aut] , Tobias Setz [aut], Yohan Chalabi [aut], Martin Maechler [ctb] , Georgi N. Boshnakov [cre, aut]
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

Diff between timeSeries versions 4032.109 dated 2024-01-14 and 4041.110 dated 2024-09-16

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Package tidyREDCap updated to version 1.1.2 with previous version 1.1.1 dated 2023-05-29

Title: Helper Functions for Working with 'REDCap' Data
Description: Helper functions for processing 'REDCap' data in R. 'REDCap' is a web-enabled application for building and managing surveys and databases developed at Vanderbilt University.
Author: Raymond Balise [aut, cre] , Gabriel Odom [aut] , Anna Calderon [aut] , Layla Bouzoubaa [aut] , Wayne DeFreitas [aut] , Lauren Nahodyl [ctb] , Kyle Grealis [aut]
Maintainer: Raymond Balise <balise@miami.edu>

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Package sbm updated to version 0.4.7 with previous version 0.4.6 dated 2024-01-31

Title: Stochastic Blockmodels
Description: A collection of tools and functions to adjust a variety of stochastic blockmodels (SBM). Supports at the moment Simple, Bipartite, 'Multipartite' and Multiplex SBM (undirected or directed with Bernoulli, Poisson or Gaussian emission laws on the edges, and possibly covariate for Simple and Bipartite SBM). See Léger (2016) <doi:10.48550/arXiv.1602.07587>, 'Barbillon et al.' (2020) <doi:10.1111/rssa.12193> and 'Bar-Hen et al.' (2020) <doi:10.48550/arXiv.1807.10138>.
Author: Julien Chiquet [aut, cre] , Sophie Donnet [aut] , grossBM team [ctb], Pierre Barbillon [aut]
Maintainer: Julien Chiquet <julien.chiquet@inrae.fr>

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Package rjson updated to version 0.2.23 with previous version 0.2.22 dated 2024-08-19

Title: JSON for R
Description: Converts R object into JSON objects and vice-versa.
Author: Alex Couture-Beil [aut, cre]
Maintainer: Alex Couture-Beil <rjson_pkg@mofo.ca>

Diff between rjson versions 0.2.22 dated 2024-08-19 and 0.2.23 dated 2024-09-16

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Package pedbp updated to version 2.0.1 with previous version 2.0.0 dated 2024-04-23

Title: Pediatric Blood Pressure
Description: Data and utilities for estimating pediatric blood pressure percentiles by sex, age, and optionally height (stature) as described in Martin et.al. (2022) <doi:10.1001/jamanetworkopen.2022.36918>. Blood pressure percentiles for children under one year of age come from Gemelli et.al. (1990) <doi:10.1007/BF02171556>. Estimates of blood pressure percentiles for children at least one year of age are informed by data from the National Heart, Lung, and Blood Institute (NHLBI) and the Centers for Disease Control and Prevention (CDC) <doi:10.1542/peds.2009-2107C> or from Lo et.al. (2013) <doi:10.1542/peds.2012-1292>. The flowchart for selecting the informing data source comes from Martin et.al. (2022) <doi:10.1542/hpeds.2021-005998>.
Author: Peter DeWitt [aut, cre] , Blake Martin [ctb] , David Albers [ctb] , Tell Bennett [ctb]
Maintainer: Peter DeWitt <peter.dewitt@cuanschutz.edu>

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Package pedalfast.data updated to version 1.0.2 with previous version 1.0.1 dated 2023-11-10

Title: PEDALFAST Data
Description: Data files and documentation for PEDiatric vALidation oF vAriableS in TBI (PEDALFAST). The data was used in "Functional Status Scale in Children With Traumatic Brain Injury: A Prospective Cohort Study" by Bennett, Dixon, et al (2016) <doi:10.1097/PCC.0000000000000934>.
Author: Peter DeWitt [aut, cre] , Tell Bennett [aut]
Maintainer: Peter DeWitt <peter.dewitt@cuanschutz.edu>

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Package jackstraw updated to version 1.3.17 with previous version 1.3.15 dated 2024-08-30

Title: Statistical Inference for Unsupervised Learning
Description: Test for association between the observed data and their estimated latent variables. The jackstraw package provides a resampling strategy and testing scheme to estimate statistical significance of association between the observed data and their latent variables. Depending on the data type and the analysis aim, the latent variables may be estimated by principal component analysis (PCA), factor analysis (FA), K-means clustering, and related unsupervised learning algorithms. The jackstraw methods learn over-fitting characteristics inherent in this circular analysis, where the observed data are used to estimate the latent variables and used again to test against that estimated latent variables. When latent variables are estimated by PCA, the jackstraw enables statistical testing for association between observed variables and latent variables, as estimated by low-dimensional principal components (PCs). This essentially leads to identifying variables that are significantly associated with PC [...truncated...]
Author: Neo Christopher Chung [aut, cre] , John D. Storey [aut] , Wei Hao [aut], Alejandro Ochoa [aut]
Maintainer: Neo Christopher Chung <nchchung@gmail.com>

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Package thor updated to version 1.1.6 with previous version 1.1.5 dated 2023-11-29

Title: Interface to 'LMDB'
Description: Key-value store, implemented as a wrapper around 'LMDB'; the "lightning memory-mapped database" <https://www.symas.com/lmdb>. 'LMDB' is a transactional key value store that uses a memory map for efficient access. This package wraps the entire 'LMDB' interface (except duplicated keys), and provides objects for transactions and cursors.
Author: Rich FitzJohn [aut, cre], Howard Chu [aut, cph], Symas Corporation [cph], Martin Hedenfalk [aut, cph], The OpenLDAP Foundation [cph]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>

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Package exvatools updated to version 0.9.0 with previous version 0.8.0 dated 2024-04-05

Title: Value Added in Exports and Other Input-Output Table Analysis Tools
Description: Analysis of trade in value added with international input-output tables. Includes commands for easy data extraction, matrix manipulation, decomposition of value added in gross exports and calculation of value added indicators, with full geographical and sector customization. Decomposition methods include Borin and Mancini (2023) <doi:10.1080/09535314.2022.2153221>, Miroudot and Ye (2021) <doi:10.1080/09535314.2020.1730308>, Wang et al. (2013) <https://econpapers.repec.org/paper/nbrnberwo/19677.htm> and Koopman et al. (2014) <doi:10.1257/aer.104.2.459>.
Author: Enrique Feas [aut, cre]
Maintainer: Enrique Feas <efeas@runbox.com>

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Package pks updated to version 0.6-1 with previous version 0.6-0 dated 2023-07-07

Title: Probabilistic Knowledge Structures
Description: Fitting and testing probabilistic knowledge structures, especially the basic local independence model (BLIM, Doignon & Flamagne, 1999) and the simple learning model (SLM), using the minimum discrepancy maximum likelihood (MDML) method (Heller & Wickelmaier, 2013 <doi:10.1016/j.endm.2013.05.145>).
Author: Florian Wickelmaier [aut, cre], Juergen Heller [aut], Julian Mollenhauer [aut], Pasquale Anselmi [ctb], Debora de Chiusole [ctb], Andrea Brancaccio [ctb], Luca Stefanutti [ctb]
Maintainer: Florian Wickelmaier <wickelmaier@web.de>

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Package distributions3 updated to version 0.2.2 with previous version 0.2.1 dated 2022-09-07

Title: Probability Distributions as S3 Objects
Description: Tools to create and manipulate probability distributions using S3. Generics pdf(), cdf(), quantile(), and random() provide replacements for base R's d/p/q/r style functions. Functions and arguments have been named carefully to minimize confusion for students in intro stats courses. The documentation for each distribution contains detailed mathematical notes.
Author: Alex Hayes [aut, cre] , Ralph Moller-Trane [aut], Emil Hvitfeldt [ctb] , Daniel Jordan [aut], Paul Northrop [aut], Moritz N. Lang [aut] , Achim Zeileis [aut] , Bruna Wundervald [ctb], Alessandro Gasparini [ctb]
Maintainer: Alex Hayes <alexpghayes@gmail.com>

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New package SEMdeep with initial version 0.1.0
Package: SEMdeep
Title: Structural Equation Modeling with Deep Neural Network and Machine Learning
Version: 0.1.0
Date: 2024-08-20
Description: Training and validation of a custom (or data-driven) Structural Equation Models using layer-wise Deep Neural Networks or node-wise Machine Learning algorithms, which extend the fitting procedures of the 'SEMgraph' R package <doi:10.32614/CRAN.package.SEMgraph>.
Depends: SEMgraph (>= 1.2.2), igraph (>= 2.0.0), R (>= 4.0)
Imports: cito, corpcor, lavaan, mgcv, NeuralNetTools, nnet, ranger, shapr, torch, xgboost
URL: https://github.com/BarbaraTarantino/SEMdeep
License: GPL (>= 3)
Encoding: UTF-8
NeedsCompilation: no
Author: Mario Grassi [aut], Barbara Tarantino [aut, cre]
Maintainer: Barbara Tarantino <barbara.tarantino01@universitadipavia.it>
Repository: CRAN
Packaged: 2024-09-16 07:19:37 UTC; mario
Date/Publication: 2024-09-16 15:30:02 UTC

More information about SEMdeep at CRAN
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New package rusquant with initial version 1.1.4
Package: rusquant
Title: Quantitative Trading Framework
Version: 1.1.4
Date: 2024-09-16
Depends: quantmod,data.table,jsonlite,httr,xts
Imports: XML,stringr,jose,stats,rvest,base64enc
Maintainer: Vyacheslav Arbuzov <arbuzov1989@gmail.com>
Description: Collection of functions to retrieve financial data from various sources, including brokerage and exchange platforms, financial websites, and data providers. Includes functions to retrieve account information, portfolio information, and place/cancel orders from different brokers. Additionally, allows users to download historical data such as earnings, dividends, stock splits.
LazyLoad: yes
License: GPL-3
Encoding: UTF-8
URL: https://rusquant.ru
BugReports: https://github.com/arbuzovv/rusquant/issues
NeedsCompilation: no
Packaged: 2024-09-16 11:46:38 UTC; vyacheslav
Author: Vyacheslav Arbuzov [cph, cre, aut], Sergey Edunov [aut]
Repository: CRAN
Date/Publication: 2024-09-16 15:10:02 UTC

More information about rusquant at CRAN
Permanent link

New package qs2 with initial version 0.1.1
Package: qs2
Title: Efficient Serialization of R Objects
Version: 0.1.1
Date: 2024-09-16
Maintainer: Travers Ching <traversc@gmail.com>
Description: Streamlines and accelerates the process of saving and loading R objects, improving speed and compression compared to other methods. The package provides two compression formats: the 'qs2' format, which uses R serialization via the C API while optimizing compression and disk I/O, and the 'qdata' format, featuring custom serialization for slightly faster performance and better compression. Additionally, the 'qs2' format can be directly converted to the standard 'RDS' format, ensuring long-term compatibility with future versions of R.
License: GPL-3
Biarch: true
Depends: R (>= 3.5.0)
Imports: Rcpp, stringfish (>= 0.15.1)
LinkingTo: Rcpp, stringfish, RcppParallel
Suggests: knitr, rmarkdown, dplyr, data.table, stringi
SystemRequirements: GNU make
Encoding: UTF-8
VignetteBuilder: knitr
Copyright: This package includes code from the 'zstd' library owned by Facebook, Inc. and created by Yann Collet; and code derived from the 'Blosc' library created and owned by Francesc Alted.
URL: https://github.com/traversc/qs2
BugReports: https://github.com/traversc/qs2/issues
NeedsCompilation: yes
Packaged: 2024-09-16 08:04:40 UTC; tching
Author: Travers Ching [aut, cre, cph], Yann Collet [ctb, cph] , Facebook, Inc. [cph] , Reichardt Tino [ctb, cph] , Skibinski Przemyslaw [ctb, cph] , Mori Yuta [ctb, cph] , Francesc Alted [ctb, cph]
Repository: CRAN
Date/Publication: 2024-09-16 15:10:06 UTC

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Package modelbpp updated to version 0.1.5 with previous version 0.1.3 dated 2024-02-20

Title: Model BIC Posterior Probability
Description: Fits the neighboring models of a fitted structural equation model and assesses the model uncertainty of the fitted model based on BIC posterior probabilities, using the method presented in Wu, Cheung, and Leung (2020) <doi:10.1080/00273171.2019.1574546>.
Author: Shu Fai Cheung [aut, cre] , Huiping Wu [aut], Shing On Leung [aut] , Ivan Jacob Agaloos Pesigan [ctb]
Maintainer: Shu Fai Cheung <shufai.cheung@gmail.com>

Diff between modelbpp versions 0.1.3 dated 2024-02-20 and 0.1.5 dated 2024-09-16

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Package mixAK updated to version 5.8 with previous version 5.7 dated 2023-12-14

Title: Multivariate Normal Mixture Models and Mixtures of Generalized Linear Mixed Models Including Model Based Clustering
Description: Contains a mixture of statistical methods including the MCMC methods to analyze normal mixtures. Additionally, model based clustering methods are implemented to perform classification based on (multivariate) longitudinal (or otherwise correlated) data. The basis for such clustering is a mixture of multivariate generalized linear mixed models. The package is primarily related to the publications Komárek (2009, Comp. Stat. and Data Anal.) <doi:10.1016/j.csda.2009.05.006> and Komárek and Komárková (2014, J. of Stat. Soft.) <doi:10.18637/jss.v059.i12>. It also implements methods published in Komárek and Komárková (2013, Ann. of Appl. Stat.) <doi:10.1214/12-AOAS580>, Hughes, Komárek, Bonnett, Czanner, García-Fiñana (2017, Stat. in Med.) <doi:10.1002/sim.7397>, Jaspers, Komárek, Aerts (2018, Biom. J.) <doi:10.1002/bimj.201600253> and Hughes, Komárek, Czanner, García-Fiñana (2018, Stat. Meth. in Med. Res) <doi:10.1177/0962280216674496>.
Author: Arnost Komarek [aut, cre]
Maintainer: Arnost Komarek <arnost.komarek@mff.cuni.cz>

Diff between mixAK versions 5.7 dated 2023-12-14 and 5.8 dated 2024-09-16

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 104 files changed, 1322 insertions(+), 1252 deletions(-)

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New package GISTools with initial version 1.0-0
Package: GISTools
Title: Further Capabilities in Geographic Information Science
Version: 1.0-0
Date: 2024-09-12
Maintainer: Binbin Lu <binbinlu@whu.edu.cn>
License: GPL (>= 2)
Repository: CRAN
Description: Mapping and spatial data manipulation tools - in particular drawing thematic maps with nice looking legends, and aggregation of point data to polygons.
Depends: R (>= 3.5.0),sf, sp
Imports: RColorBrewer, MASS,methods
NeedsCompilation: no
Packaged: 2024-09-16 08:30:19 UTC; Lenovo
Author: Chris Brunsdon [aut], Binbin Lu [aut, cre], Hongyan Chen [aut]
Date/Publication: 2024-09-16 15:10:16 UTC

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New package SVMD with initial version 0.1.0
Package: SVMD
Title: Spearman Variational Mode Decomposition
Version: 0.1.0
Author: Dr. Himadri Shekhar Roy [aut, cre], Dr. Ranjit Kumar Paul [aut], Dr. Chiranjit Mazumder [aut], Dr. Kamalika Nath [aut], Dr. Prakash Kumar [aut]
Maintainer: Dr. Himadri Shekhar Roy <himadriiasri@gmail.com>
Description: In practice, it is difficult to determine the number of decomposition modes, K, for Variational Mode Decomposition (VMD). To overcome this issue, this study offers Spearman Variational Mode Decomposition (SVMD), a method that uses the Spearman correlation coefficient to calculate the ideal mode number. Unlike the Pearson correlation coefficient, which only returns a perfect value when X and Y are linearly connected, the Spearman correlation can be calculated without knowing the probability distributions of X and Y. The Spearman correlation coefficient, also called Spearman's rank correlation coefficient, is a subset of a wider correlation coefficient. As VMD decomposes a signal, the Spearman correlation coefficient between the reconstructed and original sequences rises as the mode number K increases. Once the signal has been fully decomposed, subsequent increases in K cause the correlation to gradually level off. When the correlation reaches a specific level, VMD is said to have adequa [...truncated...]
License: GPL-3
Encoding: UTF-8
Imports: VMDecomp, stats
NeedsCompilation: no
Packaged: 2024-09-14 19:20:00 UTC; Admin
Repository: CRAN
Date/Publication: 2024-09-16 14:30:06 UTC

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New package ieegio with initial version 0.0.1
Package: ieegio
Title: File IO for Intracranial Electroencephalography
Version: 0.0.1
Language: en-US
Encoding: UTF-8
Description: Integrated toolbox supporting common file formats used for intracranial Electroencephalography (iEEG) and deep-brain stimulation (DBS) study.
URL: http://dipterix.org/ieegio/
BugReports: https://github.com/dipterix/ieegio/issues
License: MIT + file LICENSE
Imports: data.table (>= 1.16.0), digest, fastmap, filearray (>= 0.1.8), freesurferformats, fs, fst (>= 0.9.0), gifti (>= 0.8.0), grDevices, hdf5r, jsonlite, oro.nifti, R.matlab (>= 3.7.0), R6, readNSx (>= 0.0.5), rpyANTs (>= 0.0.3), stringr, utils, yaml
Suggests: reticulate, rgl, rpymat (>= 0.1.7), RNifti (>= 1.7.0), xml2, knitr, rmarkdown, tools
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-12 20:57:16 UTC; dipterix
Author: Zhengjia Wang [aut, cre]
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-16 14:20:02 UTC

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Package easybio updated to version 1.1.0 with previous version 1.0.1 dated 2024-09-08

Title: Comprehensive Single-Cell Annotation and Transcriptomic Analysis Toolkit
Description: Provides a comprehensive toolkit for single-cell annotation with the 'CellMarker2.0' database (see Xia Li, Peng Wang, Yunpeng Zhang (2023) <doi: 10.1093/nar/gkac947>). Streamlines biological label assignment in single-cell RNA-seq data and facilitates transcriptomic analysis, including preparation of TCGA<https://portal.gdc.cancer.gov/> and GEO<https://www.ncbi.nlm.nih.gov/geo/> datasets, differential expression analysis and visualization of enrichment analysis results. Additional utility functions support various bioinformatics workflows. See Wei Cui (2024) <doi: 10.1101/2024.09.14.609619> for more details.
Author: Wei Cui [aut, cre, cph]
Maintainer: Wei Cui <m2c.w@outlook.com>

Diff between easybio versions 1.0.1 dated 2024-09-08 and 1.1.0 dated 2024-09-16

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New package dtreg with initial version 1.0.0
Package: dtreg
Title: Interact with Data Type Registries and Create Machine-Readable Data
Version: 1.0.0
Description: You can load a schema from a DTR (data type registry) as an R object. Use this schema to write your data in JSON-LD (JavaScript Object Notation for Linked Data) format to make it machine readable.
License: MIT + file LICENSE
URL: https://gitlab.com/TIBHannover/orkg/dtreg-r
BugReports: https://gitlab.com/TIBHannover/orkg/dtreg-r/-/issues
Imports: httr2, jsonlite, methods, R6, stringr
Suggests: knitr, rmarkdown, sets, stats, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-15 12:37:13 UTC; LezhninaO
Author: Olga Lezhnina [aut, cre] , Manuel Prinz [aut] , Markus Stocker [aut] , Open Research Knowledge Graph Project and Contributors [cph]
Maintainer: Olga Lezhnina <olga.lezhnina@tib.eu>
Repository: CRAN
Date/Publication: 2024-09-16 14:50:02 UTC

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Package diversityForest updated to version 0.5.0 with previous version 0.4.0 dated 2023-03-08

Title: Innovative Complex Split Procedures in Random Forests Through Candidate Split Sampling
Description: Implementations of three diversity forest (DF) (Hornung, 2022, <doi:10.1007/s42979-021-00920-1>) variants. The DF algorithm is a split-finding approach that allows complex split procedures to be realized in random forest variants. The three DF variants implemented are: 1. interaction forests (IFs) (Hornung & Boulesteix, 2022, <doi:10.1016/j.csda.2022.107460>): Model quantitative and qualitative interaction effects using bivariable splitting. Come with the Effect Importance Measure (EIM), which can be used to identify variable pairs that have well-interpretable quantitative and qualitative interaction effects with high predictive relevance. 2. multi forests (MuFs) (Hornung & Hapfelmeier, 2024, <doi:10.48550/arXiv.2409.08925>): Model multi-class outcomes using multi-way and binary splitting. Come with two variable importance measures (VIMs): The multi-class VIM measures the degree to which the variables are specifically associated with one or more outcome classe [...truncated...]
Author: Roman Hornung [aut, cre], Marvin N. Wright [ctb, cph]
Maintainer: Roman Hornung <hornung@ibe.med.uni-muenchen.de>

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Package crm12Comb updated to version 0.1.7 with previous version 0.1.6 dated 2024-06-07

Title: Phase I/II CRM Based Drug Combination Design
Description: Implements the adaptive designs for integrated phase I/II trials of drug combinations via continual reassessment method (CRM) to evaluate toxicity and efficacy simultaneously for each enrolled patient cohort based on Bayesian inference. It supports patients assignment guidance in a single trial using current enrolled data, as well as conducting extensive simulation studies to evaluate operating characteristics before the trial starts. It includes various link functions such as empiric, one-parameter logistic, two-parameter logistic, and hyperbolic tangent, as well as considering multiple prior distributions of the parameters like normal distribution, gamma distribution and exponential distribution to accommodate diverse clinical scenarios. Method using Bayesian framework with empiric link function is described in: Wages and Conaway (2014) <doi:10.1002/sim.6097>.
Author: Junying Wang [cre, aut], Song Wu [aut], Jie Yang [aut]
Maintainer: Junying Wang <junying.wang@stonybrook.edu>

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New package CAESAR.Suite with initial version 0.1.0
Package: CAESAR.Suite
Title: CAESAR: a Cross-Technology and Cross-Resolution Framework for Spatial Omics Annotation
Version: 0.1.0
Author: Xiao Zhang [aut, cre], Wei Liu [aut], Jin Liu [aut]
Maintainer: Xiao Zhang <zhangxiao1994@cuhk.edu.cn>
Description: Biotechnology in spatial omics has advanced rapidly over the past few years, enhancing both throughput and resolution. However, existing annotation pipelines in spatial omics predominantly rely on clustering methods, lacking the flexibility to integrate extensive annotated information from single-cell RNA sequencing (scRNA-seq) due to discrepancies in spatial resolutions, species, or modalities. Here we introduce the CAESAR suite, an open-source software package that provides image-based spatial co-embedding of locations and genomic features. It uniquely transfers labels from scRNA-seq reference, enabling the annotation of spatial omics datasets across different technologies, resolutions, species, and modalities, based on the conserved relationship between signature genes and cells/locations at an appropriate level of granularity. Notably, CAESAR enriches location-level pathways, allowing for the detection of gradual biological pathway activation within spatially defined domain types. [...truncated...]
License: GPL (>= 2)
Depends: R (>= 3.5.0)
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp (>= 1.0.10), Matrix, Seurat, DescTools, ProFAST, furrr, future, ggplot2, ggrepel, grDevices, irlba, pbapply, progress, scater, stats, ade4, methods
Repository: CRAN
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
VignetteBuilder: knitr, rmarkdown
Suggests: knitr, rmarkdown, cowplot, scales, tibble, dplyr, msigdbr
URL: https://github.com/XiaoZhangryy/CAESAR.Suite
BugReports: https://github.com/XiaoZhangryy/CAESAR.Suite/issues
NeedsCompilation: yes
Packaged: 2024-09-14 01:06:05 UTC; ZXiao
Date/Publication: 2024-09-16 14:20:06 UTC

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Package easyanova updated to version 11.0 with previous version 10.0 dated 2023-10-19

Title: Analysis of Variance and Other Important Complementary Analyses
Description: Perform analysis of variance and other important complementary analyses. The functions are easy to use. Performs analysis in various designs, with balanced and unbalanced data.
Author: Emmanuel Arnhold [aut, cre]
Maintainer: Emmanuel Arnhold <emmanuelarnhold@yahoo.com.br>

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Package cmahalanobis updated to version 0.4.0 with previous version 0.3.0 dated 2024-05-20

Title: Calculate Distance Measures for a Given List of Data Frames with Factors
Description: It provides functions that calculate Mahalanobis distance, Euclidean distance, Manhattan distance and Chebyshev distance between each pair of species in a list of data frames. These metrics are fundamental in various fields, such as cluster analysis, classification, and other applications of machine learning and data mining, where assessing similarity or dissimilarity between data is crucial. The package is designed to be flexible and easily integrated into data analysis workflows, providing reliable tools for evaluating distances in multidimensional contexts.
Author: Flavio Gioia [aut, cre]
Maintainer: Flavio Gioia <flaviogioia.fg@gmail.com>

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Package nanotime updated to version 0.3.10 with previous version 0.3.9 dated 2024-06-21

Title: Nanosecond-Resolution Time Support for R
Description: Full 64-bit resolution date and time functionality with nanosecond granularity is provided, with easy transition to and from the standard 'POSIXct' type. Three additional classes offer interval, period and duration functionality for nanosecond-resolution timestamps.
Author: Dirk Eddelbuettel [aut, cre] , Leonardo Silvestri [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package multinma updated to version 0.7.2 with previous version 0.7.1 dated 2024-06-11

Title: Bayesian Network Meta-Analysis of Individual and Aggregate Data
Description: Network meta-analysis and network meta-regression models for aggregate data, individual patient data, and mixtures of both individual and aggregate data using multilevel network meta-regression as described by Phillippo et al. (2020) <doi:10.1111/rssa.12579>. Models are estimated in a Bayesian framework using 'Stan'.
Author: David M. Phillippo [aut, cre]
Maintainer: David M. Phillippo <david.phillippo@bristol.ac.uk>

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Package bayesSurv updated to version 3.8 with previous version 3.7 dated 2023-12-18

Title: Bayesian Survival Regression with Flexible Error and Random Effects Distributions
Description: Contains Bayesian implementations of the Mixed-Effects Accelerated Failure Time (MEAFT) models for censored data. Those can be not only right-censored but also interval-censored, doubly-interval-censored or misclassified interval-censored. The methods implemented in the package have been published in Komárek and Lesaffre (2006, Stat. Modelling) <doi:10.1191/1471082X06st107oa>, Komárek, Lesaffre and Legrand (2007, Stat. in Medicine) <doi:10.1002/sim.3083>, Komárek and Lesaffre (2007, Stat. Sinica) <https://www3.stat.sinica.edu.tw/statistica/oldpdf/A17n27.pdf>, Komárek and Lesaffre (2008, JASA) <doi:10.1198/016214507000000563>, García-Zattera, Jara and Komárek (2016, Biometrics) <doi:10.1111/biom.12424>.
Author: Arnost Komarek [aut, cre]
Maintainer: Arnost Komarek <arnost.komarek@mff.cuni.cz>

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Package voi updated to version 1.0.3 with previous version 1.0.2 dated 2023-11-27

Title: Expected Value of Information
Description: Methods to calculate the expected value of information from a decision-analytic model. This includes the expected value of perfect information (EVPI), partial perfect information (EVPPI) and sample information (EVSI), and the expected net benefit of sampling (ENBS). A range of alternative computational methods are provided under the same user interface. See Heath et al. (2024) <doi:10.1201/9781003156109>, Jackson et al. (2022) <doi:10.1146/annurev-statistics-040120-010730>.
Author: Christopher Jackson [aut, cre], Anna Heath [aut], Gianluca Baio [ctb] , Mark Strong [ctb] , Kofi Placid Adragni [ctb] , Andrew Raim [ctb]
Maintainer: Christopher Jackson <chris.jackson@mrc-bsu.cam.ac.uk>

Diff between voi versions 1.0.2 dated 2023-11-27 and 1.0.3 dated 2024-09-16

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Package transport updated to version 0.15-4 with previous version 0.15-2 dated 2024-05-09

Title: Computation of Optimal Transport Plans and Wasserstein Distances
Description: Solve optimal transport problems. Compute Wasserstein distances (a.k.a. Kantorovitch, Fortet--Mourier, Mallows, Earth Mover's, or minimal L_p distances), return the corresponding transference plans, and display them graphically. Objects that can be compared include grey-scale images, (weighted) point patterns, and mass vectors.
Author: Dominic Schuhmacher [aut, cre], Bjoern Baehre [aut] , Nicolas Bonneel [aut] , Carsten Gottschlich [aut] , Valentin Hartmann [aut] , Florian Heinemann [aut] , Bernhard Schmitzer [aut] , Joern Schrieber [aut] , Timo Wilm [ctb]
Maintainer: Dominic Schuhmacher <dominic.schuhmacher@mathematik.uni-goettingen.de>

Diff between transport versions 0.15-2 dated 2024-05-09 and 0.15-4 dated 2024-09-16

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Package tcl updated to version 0.2.1 with previous version 0.2.0 dated 2023-05-02

Title: Testing in Conditional Likelihood Context
Description: An implementation of hypothesis testing in an extended Rasch modeling framework, including sample size planning procedures and power computations. Provides 4 statistical tests, i.e., gradient test (GR), likelihood ratio test (LR), Rao score or Lagrange multiplier test (RS), and Wald test, for testing a number of hypotheses referring to the Rasch model (RM), linear logistic test model (LLTM), rating scale model (RSM), and partial credit model (PCM). Three types of functions for power and sample size computations are provided. Firstly, functions to compute the sample size given a user-specified (predetermined) deviation from the hypothesis to be tested, the level alpha, and the power of the test. Secondly, functions to evaluate the power of the tests given a user-specified (predetermined) deviation from the hypothesis to be tested, the level alpha of the test, and the sample size. Thirdly, functions to evaluate the so-called post hoc power of the tests. This is the power of the tests giv [...truncated...]
Author: Clemens Draxler [aut, cre], Andreas Kurz [aut]
Maintainer: Clemens Draxler <clemens.draxler@umit-tirol.at>

Diff between tcl versions 0.2.0 dated 2023-05-02 and 0.2.1 dated 2024-09-16

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Package salso updated to version 0.3.42 with previous version 0.3.41 dated 2024-09-06

Title: Search Algorithms and Loss Functions for Bayesian Clustering
Description: The SALSO algorithm is an efficient randomized greedy search method to find a point estimate for a random partition based on a loss function and posterior Monte Carlo samples. The algorithm is implemented for many loss functions, including the Binder loss and a generalization of the variation of information loss, both of which allow for unequal weights on the two types of clustering mistakes. Efficient implementations are also provided for Monte Carlo estimation of the posterior expected loss of a given clustering estimate. See Dahl, Johnson, Müller (2022) <doi:10.1080/10618600.2022.2069779>.
Author: David B. Dahl [aut, cre] , Devin J. Johnson [aut] , Peter Mueller [aut], Alex Crichton [ctb] , Brendan Zabarauskas [ctb] , David B. Dahl [ctb] , David Tolnay [ctb] , Jim Turner [ctb] , Josh Stone [ctb] , R. Janis Goldschmidt [ctb] , Sean McArthur [ctb [...truncated...]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

Diff between salso versions 0.3.41 dated 2024-09-06 and 0.3.42 dated 2024-09-16

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New package ream with initial version 1.0-2
Package: ream
Title: Density, Distribution, and Sampling Functions for Evidence Accumulation Models
Version: 1.0-2
Description: Calculate the probability density functions (PDFs) for two threshold evidence accumulation models (EAMs). These are defined using the following Stochastic Differential Equation (SDE), dx(t) = v(x(t),t)*dt+D(x(t),t)*dW, where x(t) is the accumulated evidence at time t, v(x(t),t) is the drift rate, D(x(t),t) is the noise scale, and W is the standard Wiener process. The boundary conditions of this process are the upper and lower decision thresholds, represented by b_u(t) and b_l(t), respectively. Upper threshold b_u(t) > 0, while lower threshold b_l(t) < 0. The initial condition of this process x(0) = z where b_l(t) < z < b_u(t). We represent this as the relative start point w = z/(b_u(0)-b_l(0)), defined as a ratio of the initial threshold location. This package generates the PDF using the same approach as the 'python' package it is based upon, 'PyBEAM' by Murrow and Holmes (2023) <doi:10.3758/s13428-023-02162-w>. First, it converts the SDE model into the forwards Fokke [...truncated...]
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: GPL (>= 2)
Encoding: UTF-8
URL: https://github.com/RaphaelHartmann/ream
BugReports: https://github.com/RaphaelHartmann/ream/issues
NeedsCompilation: yes
Packaged: 2024-09-13 12:58:55 UTC; hartmann
Author: Raphael Hartmann [aut, cre] , Matthew Murrow [aut]
Maintainer: Raphael Hartmann <raphael.hartmann@protonmail.com>
Repository: CRAN
Date/Publication: 2024-09-16 11:50:02 UTC

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New package DMCfun with initial version 4.0.1
Package: DMCfun
Title: Diffusion Model of Conflict (DMC) in Reaction Time Tasks
Version: 4.0.1
Date: 2024-09-13
Description: DMC model simulation detailed in Ulrich, R., Schroeter, H., Leuthold, H., & Birngruber, T. (2015). Automatic and controlled stimulus processing in conflict tasks: Superimposed diffusion processes and delta functions. Cognitive Psychology, 78, 148-174. Ulrich et al. (2015) <doi:10.1016/j.cogpsych.2015.02.005>. Decision processes within choice reaction-time (CRT) tasks are often modelled using evidence accumulation models (EAMs), a variation of which is the Diffusion Decision Model (DDM, for a review, see Ratcliff & McKoon, 2008). Ulrich et al. (2015) introduced a Diffusion Model for Conflict tasks (DMC). The DMC model combines common features from within standard diffusion models with the addition of superimposed controlled and automatic activation. The DMC model is used to explain distributional reaction time (and error rate) patterns in common behavioural conflict-like tasks (e.g., Flanker task, Simon task). This R-package implements the DMC model and provides functional [...truncated...]
URL: https://github.com/igmmgi/DMCfun, https://CRAN.R-project.org/package=DMCfun, https://www.sciencedirect.com/science/article/pii/S259026012100031X
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: DEoptim, Rcpp (>= 0.12.16), dplyr (>= 1.0.0), methods, parallel, pbapply, tidyr
Suggests: ggplot2, scales, shiny, testthat
LinkingTo: Rcpp, BH
LazyData: true
NeedsCompilation: yes
Packaged: 2024-09-13 12:12:53 UTC; ian
Author: Ian G. Mackenzie [cre, aut], Carolin Dudschig [aut]
Maintainer: Ian G. Mackenzie <ian.mackenzie@uni-tuebingen.de>
Repository: CRAN
Date/Publication: 2024-09-16 11:50:10 UTC

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Package dietr updated to version 1.1.5-1 with previous version 1.1.4 dated 2023-02-25

Title: Diet Estimated Trophic Levels
Description: Estimates fractional trophic level from quantitative and qualitative diet data and calculates electivity indices in R. Borstein (2020) <doi:10.1007/s10750-020-04417-5>.
Author: Samuel R. Borstein [aut, cre]
Maintainer: Samuel R. Borstein <sam@borstein.com>

Diff between dietr versions 1.1.4 dated 2023-02-25 and 1.1.5-1 dated 2024-09-16

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Package box.lsp updated to version 0.1.2 with previous version 0.1.1 dated 2024-09-10

Title: Provides 'box' Compatibility for 'languageserver'
Description: A 'box' compatible custom language parser for the 'languageserver' package to provide completion and signature hints in code editors.
Author: Ricardo Rodrigo Basa [aut, cre], Pavel Demin [aut], Jakub Nowicki [aut], Appsilon Sp. z o.o. [cph]
Maintainer: Ricardo Rodrigo Basa <opensource+rodrigo@appsilon.com>

Diff between box.lsp versions 0.1.1 dated 2024-09-10 and 0.1.2 dated 2024-09-16

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Package vcd updated to version 1.4-13 with previous version 1.4-12 dated 2023-12-29

Title: Visualizing Categorical Data
Description: Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).
Author: David Meyer [aut, cre] , Achim Zeileis [aut] , Kurt Hornik [aut] , Florian Gerber [ctb], Michael Friendly [aut]
Maintainer: David Meyer <David.Meyer@R-project.org>

Diff between vcd versions 1.4-12 dated 2023-12-29 and 1.4-13 dated 2024-09-16

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Package HAC updated to version 1.1-1 with previous version 1.1-0 dated 2022-03-14

Title: Estimation, Simulation and Visualization of Hierarchical Archimedean Copulae (HAC)
Description: Package provides the estimation of the structure and the parameters, sampling methods and structural plots of Hierarchical Archimedean Copulae (HAC).
Author: Ostap Okhrin [aut], Alexander Ristig [aut], Gong Chen [cre]
Maintainer: Gong Chen <gong.chen1@tu-dresden.de>

Diff between HAC versions 1.1-0 dated 2022-03-14 and 1.1-1 dated 2024-09-16

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Package crch updated to version 1.2-1 with previous version 1.2-0 dated 2024-08-22

Title: Censored Regression with Conditional Heteroscedasticity
Description: Different approaches to censored or truncated regression with conditional heteroscedasticity are provided. First, continuous distributions can be used for the (right and/or left censored or truncated) response with separate linear predictors for the mean and variance. Second, cumulative link models for ordinal data (obtained by interval-censoring continuous data) can be employed for heteroscedastic extended logistic regression (HXLR). In the latter type of models, the intercepts depend on the thresholds that define the intervals. Infrastructure for working with censored or truncated normal, logistic, and Student-t distributions, i.e., d/p/q/r functions and distributions3 objects.
Author: Achim Zeileis [aut, cre] , Jakob W. Messner [aut] , Reto Stauffer [aut] , Ioannis Kosmidis [ctb] , Georg J. Mayr [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

Diff between crch versions 1.2-0 dated 2024-08-22 and 1.2-1 dated 2024-09-16

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Package BayesFBHborrow updated to version 2.0.2 with previous version 2.0.1 dated 2024-06-24

Title: Bayesian Dynamic Borrowing with Flexible Baseline Hazard Function
Description: Allows Bayesian borrowing from a historical dataset for time-to- event data. A flexible baseline hazard function is achieved via a piecewise exponential likelihood with time varying split points and smoothing prior on the historic baseline hazards. The method is described in Scott and Lewin (2024) <doi:10.48550/arXiv.2401.06082>, and the software paper is in Axillus et al. (2024) <doi:10.48550/arXiv.2408.04327>.
Author: Darren Scott [aut, cre], Sophia Axillus [aut]
Maintainer: Darren Scott <darren.scott@astrazeneca.com>

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Package patchwork updated to version 1.3.0 with previous version 1.2.0 dated 2024-01-08

Title: The Composer of Plots
Description: The 'ggplot2' package provides a strong API for sequentially building up a plot, but does not concern itself with composition of multiple plots. 'patchwork' is a package that expands the API to allow for arbitrarily complex composition of plots by, among others, providing mathematical operators for combining multiple plots. Other packages that try to address this need (but with a different approach) are 'gridExtra' and 'cowplot'.
Author: Thomas Lin Pedersen [cre, aut]
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>

Diff between patchwork versions 1.2.0 dated 2024-01-08 and 1.3.0 dated 2024-09-16

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 patchwork-1.3.0/patchwork/DESCRIPTION                                                                    |   12 
 patchwork-1.3.0/patchwork/MD5                                                                            |  129 +--
 patchwork-1.3.0/patchwork/NAMESPACE                                                                      |   16 
 patchwork-1.3.0/patchwork/NEWS.md                                                                        |   61 +
 patchwork-1.3.0/patchwork/R/aaa.R                                                                        |    2 
 patchwork-1.3.0/patchwork/R/add_plot.R                                                                   |   37 -
 patchwork-1.3.0/patchwork/R/arithmetic.R                                                                 |    3 
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 patchwork-1.3.0/patchwork/R/free.R                                                                       |   73 +-
 patchwork-1.3.0/patchwork/R/guides.R                                                                     |   86 +-
 patchwork-1.3.0/patchwork/R/inset_element.R                                                              |    6 
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 patchwork-1.3.0/patchwork/R/plot_patchwork.R                                                             |  359 ++++++++--
 patchwork-1.3.0/patchwork/R/wrap_elements.R                                                              |   12 
 patchwork-1.3.0/patchwork/R/wrap_ggplot_grob.R                                                           |   18 
 patchwork-1.3.0/patchwork/R/wrap_plots.R                                                                 |    6 
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 patchwork-1.3.0/patchwork/R/zzz.R                                                                        |   26 
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 patchwork-1.3.0/patchwork/man/free.Rd                                                                    |   53 +
 patchwork-1.3.0/patchwork/man/inset_element.Rd                                                           |    2 
 patchwork-1.3.0/patchwork/man/plot_annotation.Rd                                                         |   19 
 patchwork-1.3.0/patchwork/man/plot_arithmetic.Rd                                                         |    3 
 patchwork-1.3.0/patchwork/man/plot_layout.Rd                                                             |   21 
 patchwork-1.3.0/patchwork/man/wrap_elements.Rd                                                           |    4 
 patchwork-1.3.0/patchwork/man/wrap_plots.Rd                                                              |   16 
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Package fHMM updated to version 1.4.1 with previous version 1.4.0 dated 2024-08-26

Title: Fitting Hidden Markov Models to Financial Data
Description: Fitting (hierarchical) hidden Markov models to financial data via maximum likelihood estimation. See Oelschläger, L. and Adam, T. "Detecting Bearish and Bullish Markets in Financial Time Series Using Hierarchical Hidden Markov Models" (2021, Statistical Modelling) <doi:10.1177/1471082X211034048> for a reference on the method. A user guide is provided by the accompanying software paper "fHMM: Hidden Markov Models for Financial Time Series in R", Oelschläger, L., Adam, T., and Michels, R. (2024, Journal of Statistical Software) <doi:10.18637/jss.v109.i09>.
Author: Lennart Oelschlaeger [aut, cre] , Timo Adam [aut] , Rouven Michels [aut]
Maintainer: Lennart Oelschlaeger <oelschlaeger.lennart@gmail.com>

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Package e1071 updated to version 1.7-16 with previous version 1.7-14 dated 2023-12-06

Title: Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien
Description: Functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, generalized k-nearest neighbour ...
Author: David Meyer [aut, cre] , Evgenia Dimitriadou [aut, cph], Kurt Hornik [aut] , Andreas Weingessel [aut], Friedrich Leisch [aut], Chih-Chung Chang [ctb, cph] , Chih-Chen Lin [ctb, cph]
Maintainer: David Meyer <David.Meyer@R-project.org>

Diff between e1071 versions 1.7-14 dated 2023-12-06 and 1.7-16 dated 2024-09-16

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Package fmdates (with last version 0.1.4) was removed from CRAN

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

2018-01-04 0.1.4
2017-10-08 0.1.3
2017-02-11 0.1.2
2017-02-05 0.1.1
2017-01-08 0.1.0

Permanent link
Package fmbasics (with last version 0.3.0) was removed from CRAN

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

2018-01-05 0.3.0
2017-04-30 0.2.0
2017-02-12 0.1.0

Permanent link
New package shrinkTVPVAR with initial version 0.1.1
Package: shrinkTVPVAR
Title: Efficient Bayesian Inference for TVP-VAR-SV Models with Shrinkage
Version: 0.1.1
Maintainer: Peter Knaus <peter.knaus@wu.ac.at>
Description: Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter vector autoregressive models with shrinkage priors. Details on the algorithms used are provided in Cadonna et al. (2020) <doi:10.3390/econometrics8020020> and Knaus et al. (2021) <doi:10.18637/jss.v100.i13>.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.3.0)
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, shrinkTVP, stochvol
Imports: Rcpp, shrinkTVP, stochvol, coda, methods, grDevices, RColorBrewer, lattice, zoo
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2024-09-13 19:48:33 UTC; Peter
Author: Peter Knaus [aut, cre]
Repository: CRAN
Date/Publication: 2024-09-16 09:00:02 UTC

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New package regreplaceR with initial version 0.1.0
Package: regreplaceR
Title: Match and Replace Strings Based on Named Groups in Regular Expressions
Language: en-US
Version: 0.1.0
Date: 2024-09-05
Author: Gwang-Jin Kim [aut, cre]
Description: An R6 class "Replacer" provided by the package simplifies working with regex patterns containing named groups. It allows easy retrieval of matched portions and targeted replacements by group name, improving both code clarity and maintainability.
URL: https://github.com/gwangjinkim/regreplaceR
Suggests: rmarkdown, knitr
VignetteBuilder: knitr
License: MIT + file LICENSE
Encoding: UTF-8
Imports: R6
NeedsCompilation: no
Packaged: 2024-09-13 05:27:19 UTC; josephus
Maintainer: Gwang-Jin Kim <gwang.jin.kim.phd@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-16 08:20:02 UTC

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New package PredTest with initial version 0.1.0
Package: PredTest
Title: Preparing Data For, and Calculating the Prediction Test
Version: 0.1.0
Description: Global hypothesis tests combine information across multiple endpoints to test a single hypothesis. The prediction test is a recently proposed global hypothesis test with good performance for small sample sizes and many endpoints of interest. The test is also flexible in the types and combinations of expected results across the individual endpoints. This package provides functions for data processing and calculation of the prediction test.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: devtools, ggplot2, kableExtra, knitr, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 3.5.0)
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-13 21:00:53 UTC; richardvargas
Author: Richard Vargas [aut] , Neal Montgomery [aut, cre]
Maintainer: Neal Montgomery <rmontgomery@kumc.edu>
Repository: CRAN
Date/Publication: 2024-09-16 09:00:06 UTC

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Package bvhar updated to version 2.1.0 with previous version 2.0.1 dated 2024-03-01

Title: Bayesian Vector Heterogeneous Autoregressive Modeling
Description: Tools to model and forecast multivariate time series including Bayesian Vector heterogeneous autoregressive (VHAR) model by Kim & Baek (2023) (<doi:10.1080/00949655.2023.2281644>). 'bvhar' can model Vector Autoregressive (VAR), VHAR, Bayesian VAR (BVAR), and Bayesian VHAR (BVHAR) models.
Author: Young Geun Kim [aut, cre, cph] , Changryong Baek [ctb]
Maintainer: Young Geun Kim <ygeunkimstat@gmail.com>

Diff between bvhar versions 2.0.1 dated 2024-03-01 and 2.1.0 dated 2024-09-16

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New package solaR2 with initial version 0.10
Package: solaR2
Title: Radiation and Photovoltaic Systems
Version: 0.10
Encoding: UTF-8
Description: Provides tools for calculating solar geometry, solar radiation on horizontal and inclined planes, and simulating the performance of various photovoltaic (PV) systems. Supports daily and intradaily irradiation data, enabling detailed analysis of grid-connected and water-pumping PV systems, including shading effects and solar angle calculations.
URL: https://solarization.github.io/solaR2/
BugReports: https://github.com/solarization/solaR2/issues
License: GPL-3
LazyData: yes
Depends: R (>= 4.0.0), data.table, lattice, latticeExtra
Imports: RColorBrewer, graphics, grDevices, stats, methods, utils
Suggests: zoo, sp, raster, rasterVis, tdr, meteoForecast, httr2, jsonlite, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2024-09-13 11:09:05 UTC; Fran
Author: Oscar Perpinan-Lamigueiro [aut] , Francisco Delgado-Lopez [aut, cre]
Maintainer: Francisco Delgado-Lopez <f.delgadol@alumnos.upm.es>
Repository: CRAN
Date/Publication: 2024-09-16 07:50:02 UTC

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New package R4HCR with initial version 0.1
Package: R4HCR
Version: 0.1
Date: 2024-09-09
Title: R for Health Care Research
Description: A collection of datasets that accompany the forthcoming book "R for Health Care Research".
Depends: R (>= 4.4.0)
License: MIT + file LICENSE
LazyData: true
Encoding: UTF-8
Imports: irr, mada, meta, metafor, survival
NeedsCompilation: no
Packaged: 2024-09-13 12:10:33 UTC; okejx
Author: Jason L. Oke [aut, cre, cph]
Maintainer: Jason L. Oke <jasonoke98@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-16 07:50:07 UTC

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Package multiblock updated to version 0.8.8.2 with previous version 0.8.8.1 dated 2024-03-11

Title: Multiblock Data Fusion in Statistics and Machine Learning
Description: Functions and datasets to support Smilde, Næs and Liland (2021, ISBN: 978-1-119-60096-1) "Multiblock Data Fusion in Statistics and Machine Learning - Applications in the Natural and Life Sciences". This implements and imports a large collection of methods for multiblock data analysis with common interfaces, result- and plotting functions, several real data sets and six vignettes covering a range different applications.
Author: Kristian Hovde Liland [aut, cre] , Solve Saeboe [ctb], Stefan Schrunner [rev]
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>

Diff between multiblock versions 0.8.8.1 dated 2024-03-11 and 0.8.8.2 dated 2024-09-16

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New package MUVR2 with initial version 0.1.0
Package: MUVR2
Title: Multivariate Methods with Unbiased Variable Selection
Version: 0.1.0
Author: Carl Brunius [aut], Yingxiao Yan [aut, cre]
Maintainer: Yingxiao Yan <yingxiao@chalmers.se>
Description: Predictive multivariate modelling for metabolomics. Types: Classification and regression. Methods: Partial Least Squares, Random Forest ans Elastic Net Data structures: Paired and unpaired Validation: repeated double cross-validation (Westerhuis et al. (2008)<doi:10.1007/s11306-007-0099-6>, Filzmoser et al. (2009)<doi:10.1002/cem.1225>) Variable selection: Performed internally, through tuning in the inner cross-validation loop.
URL: https://github.com/MetaboComp/MUVR2
BugReports: https://github.com/MetaboComp/MUVR2/issues
Depends: R (>= 3.5.0)
Imports: stats, graphics, randomForest, ranger, pROC, doParallel, foreach, caret, glmnet, splines, dplyr, psych, magrittr, mgcv, grDevices, parallel
License: GPL-3
LazyData: true
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2024-09-13 11:07:32 UTC; yingxiao
Repository: CRAN
Date/Publication: 2024-09-16 07:50:11 UTC

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New package MSIMST with initial version 1.1
Package: MSIMST
Title: Bayesian Monotonic Single-Index Regression Model with the Skew-T Likelihood
Version: 1.1
Date: 2024-08-16
Description: Incorporates a Bayesian monotonic single-index mixed-effect model with a multivariate skew-t likelihood, specifically designed to handle survey weights adjustments. Features include a simulation program and an associated Gibbs sampler for model estimation. The single-index function is constrained to be monotonic increasing, utilizing a customized Gaussian process prior for precise estimation. The model assumes random effects follow a canonical skew-t distribution, while residuals are represented by a multivariate Student-t distribution. Offers robust Bayesian adjustments to integrate survey weight information effectively.
URL: https://github.com/rh8liuqy/MSIMST
License: GPL (>= 3)
Depends: R (>= 3.4.0)
Imports: MASS (>= 7.3-58.4), Rcpp (>= 1.0.12), mvtnorm (>= 1.2-4), fields (>= 15.2), parallel (>= 4.3.0), truncnorm (>= 1.0-9), Rdpack (>= 2.6)
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
Suggests: lattice (>= 0.21-8), HDInterval (>= 0.2.4), latex2exp (>= 0.9.6), posterior (>= 1.5.0)
NeedsCompilation: yes
Packaged: 2024-09-13 02:15:51 UTC; Kevin_Liu
Author: Qingyang Liu [aut, cre] , Debdeep Pati [aut], Dipankar Bandyopadhyay [aut]
Maintainer: Qingyang Liu <rh8liuqy@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-16 07:20:05 UTC

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New package microbiomeMQC with initial version 1.0.2
Package: microbiomeMQC
Title: Calculate 4 Key Reporting Measures
Version: 1.0.2
Maintainer: Jacob Dehinsilu <jacobdehinsilu@outlook.com>
Description: Perform calculations for the WHO International Reference Reagents for the microbiome. Using strain, species or genera abundance tables generated through analysis of 16S ribosomal RNA sequencing or shotgun sequencing which included a reference reagent. This package will calculate measures of sensitivity, False positive relative abundance, diversity, and similarity based on mean average abundances with respect to the reference reagent.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: readxl, vegan
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-13 00:02:10 UTC; Jacob
Author: Jacob Dehinsilu [aut, cre] , Ravneet Bhuller [aut]
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2024-09-16 07:20:02 UTC

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New package dtmapi with initial version 0.0.1
Package: dtmapi
Title: Fetching Data from the 'Displacement Tracking Matrix'
Version: 0.0.1
Description: Allows humanitarian community, academia, media, government, and non-governmental organizations to utilize the data collected by the `Displacement Tracking Matrix` (<https://dtm.iom.int>), a unit in the International Organization for Migration. This also provides non-sensitive Internally Displaced Person figures, aggregated at the country, Admin 1 (states, provinces, or equivalent), and Admin 2 (smaller administrative areas) levels.
URL: https://github.com/Displacement-Tracking-Matrix/dtmapi-R, https://displacement-tracking-matrix.github.io/dtmapi-R/
License: MIT + file LICENSE
Encoding: UTF-8
Imports: httr, jsonlite, config
Suggests: knitr, rmarkdown, testthat (>= 3.1.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-13 08:06:43 UTC; bangtranl
Author: Luong Bang Tran [aut, cre]
Maintainer: Luong Bang Tran <lutran@iom.int>
Repository: CRAN
Date/Publication: 2024-09-16 07:40:02 UTC

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Package dotwhisker (with last version 0.8.2) was removed from CRAN

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

2024-06-07 0.8.2

Permanent link
Package tidyfst updated to version 1.8.1 with previous version 1.8.0 dated 2024-08-30

Title: Tidy Verbs for Fast Data Manipulation
Description: A toolkit of tidy data manipulation verbs with 'data.table' as the backend. Combining the merits of syntax elegance from 'dplyr' and computing performance from 'data.table', 'tidyfst' intends to provide users with state-of-the-art data manipulation tools with least pain. This package is an extension of 'data.table'. While enjoying a tidy syntax, it also wraps combinations of efficient functions to facilitate frequently-used data operations.
Author: Tian-Yuan Huang [aut, cre]
Maintainer: Tian-Yuan Huang <huang.tian-yuan@qq.com>

Diff between tidyfst versions 1.8.0 dated 2024-08-30 and 1.8.1 dated 2024-09-16

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Sun, 15 Sep 2024

Package gdverse updated to version 1.0-1 with previous version 1.0.0 dated 2024-09-09

Title: Analysis of Spatial Stratified Heterogeneity
Description: Analyzing spatial factors and exploring spatial associations based on the concept of spatial stratified heterogeneity, and also takes into account local spatial dependencies, spatial interpretability, potential spatial interactions, and robust spatial stratification. Additionally, it supports geographical detector models established in academic literature.
Author: Wenbo Lv [aut, cre, cph] , Yangyang Lei [aut] , Yongze Song [aut] , Wufan Zhao [aut] , Jianwu Yan [aut]
Maintainer: Wenbo Lv <lyu.geosocial@gmail.com>

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Package glmm.hp updated to version 0.1-5 with previous version 0.1-4 dated 2024-08-24

Title: Hierarchical Partitioning of Marginal R2 for Generalized Mixed-Effect Models
Description: Conducts hierarchical partitioning to calculate individual contributions of each predictor (fixed effects) towards marginal R2 for generalized linear mixed-effect model (including lm, glm and glmm) 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 timeordered updated to version 1.0.1 with previous version 1.0.0 dated 2023-08-20

Title: Time-Ordered and Time-Aggregated Network Analyses
Description: Approaches for incorporating time into network analysis. Methods include: construction of time-ordered networks (temporal graphs); shortest-time and shortest-path-length analyses; resource spread calculations; data resampling and rarefaction for null model construction; reduction to time-aggregated networks with variable window sizes; application of common descriptive statistics to these networks; vector clock latencies; and plotting functionalities. The package supports <doi:10.1371/journal.pone.0020298>.
Author: Benjamin Wong Blonder [aut, cre]
Maintainer: Benjamin Wong Blonder <benjamin.blonder@berkeley.edu>

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Package RcppFastAD updated to version 0.0.3 with previous version 0.0.2 dated 2023-03-06

Title: 'Rcpp' Bindings to 'FastAD' Auto-Differentiation
Description: The header-only 'C++' template library 'FastAD' for automatic differentiation <https://github.com/JamesYang007/FastAD> is provided by this package, along with a few illustrative examples that can all be called from R.
Author: Dirk Eddelbuettel [aut, cre] , James Yang [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package LMest updated to version 3.2.2 with previous version 3.2.1 dated 2024-09-09

Title: Generalized Latent Markov Models
Description: Latent Markov models for longitudinal continuous and categorical data. See Bartolucci, Pandolfi, Pennoni (2017)<doi:10.18637/jss.v081.i04>.
Author: Francesco Bartolucci [aut, cre], Silvia Pandolfi [aut], Fulvia Pennoni [aut], Alessio Farcomeni [ctb], Alessio Serafini [ctb]
Maintainer: Francesco Bartolucci <francesco.bartolucci@unipg.it>

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Package epiR updated to version 2.0.76 with previous version 2.0.75 dated 2024-06-17

Title: Tools for the Analysis of Epidemiological Data
Description: Tools for the analysis of epidemiological and surveillance data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, computation of confidence intervals around incidence risk and incidence rate estimates and sample size calculations for cross-sectional, case-control and cohort studies. Surveillance tools include functions to calculate an appropriate sample size for 1- and 2-stage representative freedom surveys, functions to estimate surveillance system sensitivity and functions to support scenario tree modelling analyses.
Author: Mark Stevenson [aut, cre] , Evan Sergeant [aut], Cord Heuer [ctb], Telmo Nunes [ctb], Cord Heuer [ctb], Jonathon Marshall [ctb], Javier Sanchez [ctb], Ron Thornton [ctb], Jeno Reiczigel [ctb], Jim Robison-Cox [ctb], Paola Sebastiani [ctb], Peter Soly [...truncated...]
Maintainer: Mark Stevenson <mark.stevenson1@unimelb.edu.au>

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Package sandwich updated to version 3.1-1 with previous version 3.1-0 dated 2023-12-11

Title: Robust Covariance Matrix Estimators
Description: Object-oriented software for model-robust covariance matrix estimators. Starting out from the basic robust Eicker-Huber-White sandwich covariance methods include: heteroscedasticity-consistent (HC) covariances for cross-section data; heteroscedasticity- and autocorrelation-consistent (HAC) covariances for time series data (such as Andrews' kernel HAC, Newey-West, and WEAVE estimators); clustered covariances (one-way and multi-way); panel and panel-corrected covariances; outer-product-of-gradients covariances; and (clustered) bootstrap covariances. All methods are applicable to (generalized) linear model objects fitted by lm() and glm() but can also be adapted to other classes through S3 methods. Details can be found in Zeileis et al. (2020) <doi:10.18637/jss.v095.i01>, Zeileis (2004) <doi:10.18637/jss.v011.i10> and Zeileis (2006) <doi:10.18637/jss.v016.i09>.
Author: Achim Zeileis [aut, cre] , Thomas Lumley [aut] , Nathaniel Graham [ctb] , Susanne Koell [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

Diff between sandwich versions 3.1-0 dated 2023-12-11 and 3.1-1 dated 2024-09-15

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Package locuszoomr updated to version 0.3.5 with previous version 0.3.4 dated 2024-09-06

Title: Gene Locus Plot with Gene Annotations
Description: Publication-ready regional gene locus plots similar to those produced by the web interface 'LocusZoom' <https://my.locuszoom.org>, but running locally in R. Genetic or genomic data with gene annotation tracks are plotted via R base graphics, 'ggplot2' or 'plotly', allowing flexibility and easy customisation including laying out multiple locus plots on the same page. It uses the 'LDlink' API <https://ldlink.nih.gov/?tab=apiaccess> to query linkage disequilibrium data from the 1000 Genomes Project and can overlay this on plots.
Author: Myles Lewis [aut, cre]
Maintainer: Myles Lewis <myles.lewis@qmul.ac.uk>

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New package TLIC with initial version 0.1
Package: TLIC
Title: The LIC for T Distribution Regression Analysis
Version: 0.1
Date: 2024-08-30
Description: This comprehensive toolkit for T-distribution regression, known as the analysis of "TLIC" (T-distribution Linear regression Integrated Corrector), adopts ordinary least squares method and assumes that errors follow a T-distribution. This approach gives it an advantage when dealing with small samples or non-normal error distributions, and can provide more robust parameter estimation and hypothesis testing results.The philosophy of the package is described in Guo G. (2020) <doi:10.1080/02664763.2022.2053949>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats
NeedsCompilation: no
Packaged: 2024-09-11 01:32:24 UTC; A
Author: Guangbao Guo [aut, cre] , Guofu Jing [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>
Repository: CRAN
Date/Publication: 2024-09-15 20:10:02 UTC

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New package spectralAnomaly with initial version 0.1.1
Package: spectralAnomaly
Title: Detect Anomalies Using the Spectral Residual Algorithm
Version: 0.1.1
Description: Apply the spectral residual algorithm to data, such as a time series, to detect anomalies. Anomaly scores can be used to determine outliers based upon a threshold or fed into more sophisticated prediction models. Methods are based upon "Time-Series Anomaly Detection Service at Microsoft", Ren, H., Xu, B., Wang, Y., et al., (2019) <doi:10.48550/arXiv.1906.03821>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats, utils
Suggests: testthat (>= 3.0.0)
URL: https://al-obrien.github.io/spectralAnomaly/, https://github.com/al-obrien/spectralAnomaly
BugReports: https://github.com/al-obrien/spectralAnomaly/issues
NeedsCompilation: no
Packaged: 2024-09-12 21:32:26 UTC; allen
Author: Allen OBrien [aut, cre, cph]
Maintainer: Allen OBrien <allen.g.obrien@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-15 21:00:02 UTC

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New package RandomWalker with initial version 0.1.0
Package: RandomWalker
Title: Generate Random Walks Compatible with the 'tidyverse'
Version: 0.1.0
Description: Generates random walks of various types by providing a set of functions that are compatible with the 'tidyverse'. The functions provided in the package make it simple to create random walks with a variety of properties, such as how many simulations to run, how many steps to take, and the distribution of random walk itself.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://www.spsanderson.com/RandomWalker/, https://github.com/spsanderson/RandomWalker
BugReports: https://github.com/spsanderson/RandomWalker/issues
Depends: R (>= 4.1.0)
Imports: dplyr, tidyr, purrr, rlang, patchwork, NNS
Suggests: knitr, rmarkdown, stats, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-12 12:53:51 UTC; ssanders
Author: Steven Sanderson [aut, cre, cph] , Antti Rask [aut, cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-15 20:30:24 UTC

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New package PytrendsLongitudinalR with initial version 0.1.3
Package: PytrendsLongitudinalR
Title: Create Longitudinal Google Trends Data
Version: 0.1.3
Description: 'Google Trends' provides cross-sectional and time-series data on searches, but lacks readily available longitudinal data. Researchers, who want to create longitudinal 'Google Trends' on their own, face practical challenges, such as normalized counts that make it difficult to combine cross-sectional and time-series data and limitations in data formats and timelines that limit data granularity over extended time periods. This package addresses these issues and enables researchers to generate longitudinal 'Google Trends' data. This package is built on 'pytrends', a Python library that acts as the unofficial 'Google Trends API' to collect 'Google Trends' data. As long as the 'Google Trends API', 'pytrends' and all their dependencies are working, this package will work. During testing, we noticed that for the same input (keyword, topic, data_format, timeline), the output index can vary from time to time. Besides, if the keyword is not very popular, then the resulting dataset will contain a [...truncated...]
Encoding: UTF-8
Imports: lubridate, jsonlite, reticulate, utils
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2024-09-12 09:11:07 UTC; malika
Author: Taeyong Park [cre, cph, aut], Malika Dixit [aut]
Maintainer: Taeyong Park <taeyongp@andrew.cmu.edu>
Repository: CRAN
Date/Publication: 2024-09-15 20:10:05 UTC

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Package pls updated to version 2.8-5 with previous version 2.8-4 dated 2024-08-01

Title: Partial Least Squares and Principal Component Regression
Description: Multivariate regression methods Partial Least Squares Regression (PLSR), Principal Component Regression (PCR) and Canonical Powered Partial Least Squares (CPPLS).
Author: Kristian Hovde Liland [aut, cre], Bjoern-Helge Mevik [aut], Ron Wehrens [aut], Paul Hiemstra [ctb]
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>

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New package mvcor with initial version 1.0
Package: mvcor
Title: Correlation Coefficients for Multivariate Data
Version: 1.0
Date: 2024-09-12
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Rfast, stats
Description: Correlation coefficients for multivariate data, namely the squared correlation coefficient and the RV coefficient (multivariate generalization of the squared Pearson correlation coefficient). References include Mardia K.V., Kent J.T. and Bibby J.M. (1979). "Multivariate Analysis". ISBN: 978-0124712522. London: Academic Press.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2024-09-12 11:42:35 UTC; mtsag
Repository: CRAN
Date/Publication: 2024-09-15 20:30:07 UTC

More information about mvcor at CRAN
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New package ggalign with initial version 0.0.3
Package: ggalign
Title: Align Multiple 'ggplot' Objects
Version: 0.0.3
Description: A 'ggplot2' extension offers various tools for organizing and arranging plots. It is designed to consistently align a specific axis across multiple 'ggplot' objects, making it especially useful for plots requiring data order manipulation. A typical use case includes organizing combinations like a dendrogram and a heatmap.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: ggplot2
Imports: cli, ggh4x, grid, gtable, methods, rlang (>= 1.1.0), stats, tibble, tidyr
ByteCompile: true
URL: https://github.com/Yunuuuu/ggalign, https://yunuuuu.github.io/ggalign/
BugReports: https://github.com/Yunuuuu/ggalign/issues
Suggests: gridGraphics, knitr, patchwork, rmarkdown, scales, testthat (>= 3.0.0), vdiffr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-12 11:00:38 UTC; yun
Author: Yun Peng [aut, cre, cph]
Maintainer: Yun Peng <yunyunp96@163.com>
Repository: CRAN
Date/Publication: 2024-09-15 20:30:10 UTC

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New package gammi with initial version 0.1
Package: gammi
Title: Generalized Additive Mixed Model Interface
Version: 0.1
Date: 2024-09-12
Description: An interface for fitting generalized additive models (GAMs) and generalized additive mixed models (GAMMs) using the 'lme4' package as the computational engine, as described in Helwig (2024) <doi:10.3390/stats7010003>. Supports default and formula methods for model specification, additive and tensor product splines for capturing nonlinear effects, and automatic determination of spline type based on the class of each predictor. Includes an S3 plot method for visualizing the (nonlinear) model terms, an S3 predict method for forming predictions from a fit model, and an S3 summary method for conducting significance testing using the Bayesian interpretation of a smoothing spline.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: lme4, Matrix, methods
NeedsCompilation: no
Packaged: 2024-09-12 14:59:33 UTC; nate
Author: Nathaniel E. Helwig [aut, cre]
Maintainer: Nathaniel E. Helwig <helwig@umn.edu>
Repository: CRAN
Date/Publication: 2024-09-15 20:30:15 UTC

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New package equiBSPD with initial version 0.1.0
Package: equiBSPD
Title: Equivalent Estimation Balanced Split Plot Designs
Version: 0.1.0
Maintainer: Bijoy Chanda <bijoychanda08@gmail.com>
Description: In agricultural, post-harvest and processing, engineering and industrial experiments factors are often differentiated with ease with which they can change from experimental run to experimental run. This is due to the fact that one or more factors may be expensive or time consuming to change i.e. hard-to-change factors. These factors restrict the use of complete randomization as it may make the experiment expensive and time consuming. Split plot designs can be used for such situations. In general model estimation of split plot designs require the use of generalized least squares (GLS). However for some split-plot designs ordinary least squares (OLS) estimates are equivalent to generalized least squares (GLS) estimates. These types of designs are known in literature as equivalent-estimation split-plot design. For method details see, Macharia, H. and Goos, P.(2010) <doi:10.1080/00224065.2010.11917833>.Balanced split plot designs are designs which have an equal number of subplots wit [...truncated...]
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-12 14:10:22 UTC; ICAR-CAFRI
Author: Bijoy Chanda [aut, cre, ctb], Arpan Bhowmik [aut, ctb], Cini Varghese [aut], Seema Jaggi [aut, ctb], Eldho Varghese [aut, ctb], BN Mandal [ctb], Anindita Datta [ctb], Soumen Pal [ctb], Dibyendu Deb [ctb]
Repository: CRAN
Date/Publication: 2024-09-15 20:30:18 UTC

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New package CohortGenerator with initial version 0.11.1
Package: CohortGenerator
Title: Cohort Generation for the OMOP Common Data Model
Version: 0.11.1
Date: 2024-09-12
Maintainer: Anthony Sena <sena@ohdsi.org>
Description: Generate cohorts and subsets using an Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) Database. Cohorts are defined using 'CIRCE' (<https://github.com/ohdsi/circe-be>) or SQL compatible with 'SqlRender' (<https://github.com/OHDSI/SqlRender>).
Depends: DatabaseConnector (>= 5.0.0), R (>= 3.6.0), R6
Imports: checkmate, digest, dplyr, lubridate, methods, ParallelLogger (>= 3.0.0), readr (>= 2.1.0), rlang, RJSONIO, jsonlite, ResultModelManager, SqlRender (>= 1.11.1), stringi (>= 1.7.6), tibble
Suggests: CirceR (>= 1.1.1), Eunomia, knitr, rmarkdown, testthat, withr, zip
License: Apache License
VignetteBuilder: knitr
URL: https://ohdsi.github.io/CohortGenerator/, https://github.com/OHDSI/CohortGenerator
BugReports: https://github.com/OHDSI/CohortGenerator/issues
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2024-09-12 21:33:31 UTC; asena5
Author: Anthony Sena [aut, cre], Jamie Gilbert [aut], Gowtham Rao [aut], Martijn Schuemie [aut], Observational Health Data Science and Informatics [cph]
Repository: CRAN
Date/Publication: 2024-09-15 21:00:06 UTC

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New package aftsem with initial version 1.0
Package: aftsem
Title: Semiparametric Accelerated Failure Time Model
Version: 1.0
Date: 2024-09-01
Maintainer: Martin Benedikt <benedma2@cvut.cz>
Description: Implements several basic algorithms for estimating regression parameters for semiparametric accelerated failure time (AFT) model. The main methods are: Jin rank-based method (Jin (2003) <doi:10.1093/biomet/90.2.341>), Heller’s estimating method (Heller (2012) <doi:10.1198/016214506000001257>), Polynomial smoothed Gehan function method (Chung (2013) <doi:10.1007/s11222-012-9333-9>), Buckley-James method (Buckley (1979) <doi:10.2307/2335161>) and Jin`s improved least squares method (Jin (2006) <doi:10.1093/biomet/93.1.147>). This package can be used for modeling right-censored data and for comparing different estimation algorithms.
License: GPL (>= 3)
BugReports: https://github.com/benedma2/aftsem-package/issues
Imports: survival, Rcpp (>= 1.0.10), stats, quantreg, optimx
URL: https://github.com/benedma2/aftsem-package
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 4.2.0)
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2024-09-12 12:13:59 UTC; ivan
Author: Martin Benedikt [aut, cre]
Repository: CRAN
Date/Publication: 2024-09-15 20:30:21 UTC

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Package minic updated to version 1.0.1 with previous version 1.0 dated 2024-06-24

Title: Minimization Methods for Ill-Conditioned Problems
Description: Implementation of methods for minimizing ill-conditioned problems. Currently only includes regularized (quasi-)newton optimization (Kanzow and Steck et al. (2023), <doi:10.1007/s12532-023-00238-4>).
Author: Bert van der Veen [aut, cre]
Maintainer: Bert van der Veen <bert_van_der_veen@hotmail.com>

Diff between minic versions 1.0 dated 2024-06-24 and 1.0.1 dated 2024-09-15

 DESCRIPTION         |    8 ++++----
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New package lavaan.printer with initial version 0.1.0
Package: lavaan.printer
Title: Helper Functions for Printing 'lavaan' Outputs
Version: 0.1.0
Description: Helpers for customizing selected outputs from 'lavaan' by Rosseel (2012) <doi:10.18637/jss.v048.i02> and print them. The functions are intended to be used by package developers in their packages and so are not designed to be user-friendly. They are designed to be let developers customize the tables by other functions. Currently the parameter estimates tables of a fitted object are supported.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Imports: utils, methods, lavaan
Depends: R (>= 4.0.0)
URL: https://sfcheung.github.io/lavaan.printer/
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-12 00:11:33 UTC; shufa
Author: Shu Fai Cheung [aut, cre]
Maintainer: Shu Fai Cheung <shufai.cheung@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-15 20:00:02 UTC

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New package cancerR with initial version 0.1.0
Package: cancerR
Title: Classification of Cancer Using Administrative Data
Version: 0.1.0
Description: Classifies the type of cancer using routinely collected data commonly found in cancer registries from pathology reports. The package implements the International Classification of Diseases for Oncology, 3rd Edition site (topography), histology (morphology), and behaviour codes of neoplasms to classify cancer type <https://www.who.int/standards/classifications/other-classifications/international-classification-of-diseases-for-oncology>. Classification in children utilize the International Classification of Childhood Cancer by Steliarova-Foucher et al. (2005) <doi:10.1002/cncr.20910>. Adolescent and young adult cancer classification is based on Barr et al. (2020) <doi:10.1002/cncr.33041>.
License: GPL (>= 2)
URL: https://github.com/giancarlodigi/cancerR
BugReports: https://github.com/giancarlodigi/cancerR/issues
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-11 21:13:25 UTC; giancarlo
Author: Giancarlo Di Giuseppe [aut, cre, cph]
Maintainer: Giancarlo Di Giuseppe <digi.giancarlo@proton.me>
Repository: CRAN
Date/Publication: 2024-09-15 19:40:02 UTC

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Package CFtime updated to version 1.4.1 with previous version 1.4.0 dated 2024-06-05

Title: Using CF-Compliant Calendars with Climate Projection Data
Description: Support for all calendars as specified in the Climate and Forecast (CF) Metadata Conventions for climate and forecasting data. The CF Metadata Conventions is widely used for distributing files with climate observations or projections, including the Coupled Model Intercomparison Project (CMIP) data used by climate change scientists and the Intergovernmental Panel on Climate Change (IPCC). This package specifically allows the user to work with any of the CF-compliant calendars (many of which are not compliant with POSIXt). The CF time coordinate is formally defined in the CF Metadata Conventions document available at <https://cfconventions.org/Data/cf-conventions/cf-conventions-1.11/cf-conventions.html#time-coordinate>.
Author: Patrick Van Laake [aut, cre, cph]
Maintainer: Patrick Van Laake <patrick@vanlaake.net>

Diff between CFtime versions 1.4.0 dated 2024-06-05 and 1.4.1 dated 2024-09-15

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Package tinytex updated to version 0.53 with previous version 0.52 dated 2024-07-18

Title: Helper Functions to Install and Maintain TeX Live, and Compile LaTeX Documents
Description: Helper functions to install and maintain the 'LaTeX' distribution named 'TinyTeX' (<https://yihui.org/tinytex/>), a lightweight, cross-platform, portable, and easy-to-maintain version of 'TeX Live'. This package also contains helper functions to compile 'LaTeX' documents, and install missing 'LaTeX' packages automatically.
Author: Yihui Xie [aut, cre, cph] , Posit Software, PBC [cph, fnd], Christophe Dervieux [ctb] , Devon Ryan [ctb] , Ethan Heinzen [ctb], Fernando Cagua [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between tinytex versions 0.52 dated 2024-07-18 and 0.53 dated 2024-09-15

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Package mixhvg updated to version 1.0.1 with previous version 0.2.1 dated 2024-09-01

Title: Mixture of Multiple Highly Variable Feature Selection Methods
Description: Highly variable gene selection methods, including popular public available methods, and also the mixture of multiple highly variable gene selection methods, <https://github.com/RuzhangZhao/mixhvg>. Reference: <doi:10.1101/2024.08.25.608519>.
Author: Ruzhang Zhao [aut, cre] , Hongkai Ji [aut]
Maintainer: Ruzhang Zhao <ruzhangzhao@gmail.com>

Diff between mixhvg versions 0.2.1 dated 2024-09-01 and 1.0.1 dated 2024-09-15

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Package IsoplotR updated to version 6.3 with previous version 6.2 dated 2024-05-04

Title: Statistical Toolbox for Radiometric Geochronology
Description: Plots U-Pb data on Wetherill and Tera-Wasserburg concordia diagrams. Calculates concordia and discordia ages. Performs linear regression of measurements with correlated errors using 'York', 'Titterington', 'Ludwig' and Omnivariant Generalised Least-Squares ('OGLS') approaches. Generates Kernel Density Estimates (KDEs) and Cumulative Age Distributions (CADs). Produces Multidimensional Scaling (MDS) configurations and Shepard plots of multi-sample detrital datasets using the Kolmogorov-Smirnov distance as a dissimilarity measure. Calculates 40Ar/39Ar ages, isochrons, and age spectra. Computes weighted means accounting for overdispersion. Calculates U-Th-He (single grain and central) ages, logratio plots and ternary diagrams. Processes fission track data using the external detector method and LA-ICP-MS, calculates central ages and plots fission track and other data on radial (a.k.a. 'Galbraith') plots. Constructs total Pb-U, Pb-Pb, Th-Pb, K-Ca, Re-Os, Sm-Nd, Lu-Hf, Rb-Sr and 230Th-U isoch [...truncated...]
Author: Pieter Vermeesch [aut, cre]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

Diff between IsoplotR versions 6.2 dated 2024-05-04 and 6.3 dated 2024-09-15

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Package xaringanthemer updated to version 0.4.3 with previous version 0.4.2 dated 2022-08-20

Title: Custom 'xaringan' CSS Themes
Description: Create beautifully color-coordinated and customized themes for your 'xaringan' slides, without writing any CSS. Complete your slide theme with 'ggplot2' themes that match the font and colors used in your slides. Customized styles can be created directly in your slides' 'R Markdown' source file or in a separate external script.
Author: Garrick Aden-Buie [aut, cre]
Maintainer: Garrick Aden-Buie <garrick@adenbuie.com>

Diff between xaringanthemer versions 0.4.2 dated 2022-08-20 and 0.4.3 dated 2024-09-15

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 xaringanthemer-0.4.2/xaringanthemer/tests/manual                                                         |only
 xaringanthemer-0.4.3/xaringanthemer/DESCRIPTION                                                          |    8 
 xaringanthemer-0.4.3/xaringanthemer/MD5                                                                  |   79 +-
 xaringanthemer-0.4.3/xaringanthemer/NAMESPACE                                                            |    2 
 xaringanthemer-0.4.3/xaringanthemer/NEWS.md                                                              |   44 -
 xaringanthemer-0.4.3/xaringanthemer/R/ggplot2.R                                                          |    1 
 xaringanthemer-0.4.3/xaringanthemer/R/style_extra_css.R                                                  |    2 
 xaringanthemer-0.4.3/xaringanthemer/R/style_font_default.R                                               |    3 
 xaringanthemer-0.4.3/xaringanthemer/R/utils.R                                                            |    3 
 xaringanthemer-0.4.3/xaringanthemer/R/xaringanthemer-package.R                                           |   56 -
 xaringanthemer-0.4.3/xaringanthemer/README.md                                                            |    4 
 xaringanthemer-0.4.3/xaringanthemer/build/vignette.rds                                                   |binary
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 xaringanthemer-0.4.3/xaringanthemer/man/style_duo.Rd                                                     |    8 
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Package xgrove updated to version 0.1-12 with previous version 0.1-11 dated 2024-08-23

Title: Explanation Groves
Description: Compute surrogate explanation groves for predictive machine learning models and analyze complexity vs. explanatory power of an explanation according to Szepannek, G. and von Holt, B. (2023) <doi:10.1007/s41237-023-00205-2>.
Author: Gero Szepannek [aut, cre]
Maintainer: Gero Szepannek <gero.szepannek@web.de>

Diff between xgrove versions 0.1-11 dated 2024-08-23 and 0.1-12 dated 2024-09-15

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Package tidybayes updated to version 3.0.7 with previous version 3.0.6 dated 2023-08-12

Title: Tidy Data and 'Geoms' for Bayesian Models
Description: Compose data for and extract, manipulate, and visualize posterior draws from Bayesian models ('JAGS', 'Stan', 'rstanarm', 'brms', 'MCMCglmm', 'coda', ...) in a tidy data format. Functions are provided to help extract tidy data frames of draws from Bayesian models and that generate point summaries and intervals in a tidy format. In addition, 'ggplot2' 'geoms' and 'stats' are provided for common visualization primitives like points with multiple uncertainty intervals, eye plots (intervals plus densities), and fit curves with multiple, arbitrary uncertainty bands.
Author: Matthew Kay [aut, cre], Timothy Mastny [ctb]
Maintainer: Matthew Kay <mjskay@northwestern.edu>

Diff between tidybayes versions 3.0.6 dated 2023-08-12 and 3.0.7 dated 2024-09-15

 DESCRIPTION                                                                          |   18 
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 NAMESPACE                                                                            |  961 -
 NEWS.md                                                                              |  517 
 R/add_draws.R                                                                        |  198 
 R/compare_levels.R                                                                   |  442 
 R/compose_data.R                                                                     |  770 
 R/density_bins.R                                                                     |  194 
 R/deprecated.R                                                                       | 2164 +-
 R/emmeans_comparison.R                                                               |  162 
 R/epred_draws.R                                                                      |  164 
 R/epred_rvars.R                                                                      |  156 
 R/flip_aes.R                                                                         |  101 
 R/gather_draws.R                                                                     |   75 
 R/gather_emmeans_draws.R                                                             |  276 
 R/gather_pairs.R                                                                     |  290 
 R/gather_rvars.R                                                                     |   90 
 R/gather_variables.R                                                                 |  204 
 R/get_variables.R                                                                    |  106 
 R/ggdist-curve_interval.R                                                            |    6 
 R/ggdist-cut_cdf_qi.R                                                                |    6 
 R/ggdist-stat_pointinterval.R                                                        |   14 
 R/linpred_draws.R                                                                    |  216 
 R/linpred_rvars.R                                                                    |  156 
 R/nest_rvars.R                                                                       |  175 
 R/predict_curve.R                                                                    |  258 
 R/predicted_draws.R                                                                  |  800 -
 R/predicted_rvars.R                                                                  |  512 
 R/recover_types.R                                                                    |  364 
 R/residual_draws.R                                                                   |  128 
 R/sample_draws.R                                                                     |  132 
 R/spread_draws.R                                                                     | 1399 -
 R/spread_rvars.R                                                                     |  564 
 R/summarise_draws.R                                                                  |  152 
 R/testthat.R                                                                         |   39 
 R/tidy_draws.R                                                                       |  584 
 R/tidybayes-models.R                                                                 |  158 
 R/tidybayes-package.R                                                                |   73 
 R/ungather_draws.R                                                                   |  146 
 R/unspread_draws.R                                                                   |  230 
 R/util.R                                                                             |  358 
 R/x_at_y.R                                                                           |  174 
 build/partial.rdb                                                                    |binary
 build/vignette.rds                                                                   |binary
 inst/doc/tidy-brms.R                                                                 | 1228 -
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 inst/doc/tidy-brms.html                                                              | 5674 +++----
 inst/doc/tidy-posterior.R                                                            |  926 -
 inst/doc/tidy-posterior.Rmd                                                          | 1632 +-
 inst/doc/tidy-posterior.html                                                         | 2834 +--
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Package diathor (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:

2022-03-16 0.1.0

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Package TestFunctions updated to version 0.2.2 with previous version 0.2.1 dated 2024-01-21

Title: Test Functions for Simulation Experiments and Evaluating Optimization and Emulation Algorithms
Description: Test functions are often used to test computer code. They are used in optimization to test algorithms and in metamodeling to evaluate model predictions. This package provides test functions that can be used for any purpose.
Author: Collin Erickson [aut, cre]
Maintainer: Collin Erickson <collinberickson@gmail.com>

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Package sdsfun updated to version 0.2.0 with previous version 0.1.1 dated 2024-09-08

Title: Spatial Data Science Complementary Features
Description: Wrapping and supplementing commonly used functions in the R ecosystem related to spatial data science, while serving as a basis for other packages maintained by Wenbo Lv.
Author: Wenbo Lv [aut, cre, cph]
Maintainer: Wenbo Lv <lyu.geosocial@gmail.com>

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Package rvec updated to version 0.0.7 with previous version 0.0.6 dated 2023-11-08

Title: Vector Representing a Random Variable
Description: Random vectors, called rvecs. An rvec holds multiple draws, but tries to behave like a standard R vector, including working well in data frames. Rvecs are useful for working with output from a simulation or a Bayesian analysis.
Author: John Bryant [aut, cre], Bayesian Demography Limited [cph]
Maintainer: John Bryant <john@bayesiandemography.com>

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Sat, 14 Sep 2024

Package geosimilarity updated to version 3.3 with previous version 3.2 dated 2024-09-08

Title: Geographically Optimal Similarity
Description: Understanding spatial association is essential for spatial statistical inference, including factor exploration and spatial prediction. Geographically optimal similarity (GOS) model is an effective method for spatial prediction, as described in Yongze Song (2022) <doi:10.1007/s11004-022-10036-8>. GOS was developed based on the geographical similarity principle, as described in Axing Zhu (2018) <doi:10.1080/19475683.2018.1534890>. GOS has advantages in more accurate spatial prediction using fewer samples and critically reduced prediction uncertainty.
Author: Yongze Song [aut, cph] , Wenbo Lv [aut, cre]
Maintainer: Wenbo Lv <lyu.geosocial@gmail.com>

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Package TCIU updated to version 1.2.7 with previous version 1.2.6 dated 2024-05-17

Title: Spacekime Analytics, Time Complexity and Inferential Uncertainty
Description: Provide the core functionality to transform longitudinal data to complex-time (kime) data using analytic and numerical techniques, visualize the original time-series and reconstructed kime-surfaces, perform model based (e.g., tensor-linear regression) and model-free classification and clustering methods in the book Dinov, ID and Velev, MV. (2021) "Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics", De Gruyter STEM Series, ISBN 978-3-11-069780-3. <https://www.degruyter.com/view/title/576646>. The package includes 18 core functions which can be separated into three groups. 1) draw longitudinal data, such as Functional magnetic resonance imaging(fMRI) time-series, and forecast or transform the time-series data. 2) simulate real-valued time-series data, e.g., fMRI time-courses, detect the activated areas, report the corresponding p-values, and visualize the p-values in the 3D brain space. 3) Laplace transform and kimesurface reconstructions of the fMRI d [...truncated...]
Author: Yongkai Qiu [aut], Zhe Yin [aut], Jinwen Cao [aut], Yupeng Zhang [aut], Yuyao Liu [aut], Rongqian Zhang [aut], Yueyang Shen [aut, cre], Rouben Rostamian [ctb], Ranjan Maitra [ctb], Daniel Rowe [ctb], Daniel Adrian [ctb] , Yunjie Guo [aut], Ivo Dinov [...truncated...]
Maintainer: Yueyang Shen <petersyy@umich.edu>

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Package PRTree updated to version 0.1.1 with previous version 0.1.0 dated 2024-01-16

Title: Probabilistic Regression Trees
Description: Probabilistic Regression Trees (PRTree). Functions for fitting and predicting PRTree models with some adaptations to handle missing values. The main calculations are performed in 'FORTRAN', resulting in highly efficient algorithms. This package's implementation is based on the PRTree methodology described in Alkhoury, S.; Devijver, E.; Clausel, M.; Tami, M.; Gaussier, E.; Oppenheim, G. (2020) - "Smooth And Consistent Probabilistic Regression Trees" <https://proceedings.neurips.cc/paper_files/paper/2020/file/8289889263db4a40463e3f358bb7c7a1-Paper.pdf>.
Author: Alisson Silva Neimaier [aut, cre] , Taiane Schaedler Prass [aut, ths]
Maintainer: Alisson Silva Neimaier <alissonneimaier@hotmail.com>

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New package mixopt with initial version 0.1.3
Package: mixopt
Title: Mixed Variable Optimization
Version: 0.1.3
Maintainer: Collin Erickson <collinberickson@gmail.com>
Description: Mixed variable optimization for non-linear functions. Can optimize function whose inputs are a combination of continuous, ordered, and unordered variables.
Depends: dplyr, ggplot2, splitfngr
Suggests: ContourFunctions, gridExtra, lhs, testthat (>= 3.0.0)
License: LGPL (>= 3)
Encoding: UTF-8
URL: https://github.com/CollinErickson/mixopt
BugReports: https://github.com/CollinErickson/mixopt/issues
NeedsCompilation: no
Packaged: 2024-09-14 00:32:50 UTC; colli
Author: Collin Erickson [aut, cre]
Repository: CRAN
Date/Publication: 2024-09-15 00:20:02 UTC

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Package EntropyEstimation updated to version 1.2.1 with previous version 1.2 dated 2015-01-04

Title: Estimation of Entropy and Related Quantities
Description: Contains methods for the estimation of Shannon's entropy, variants of Renyi's entropy, mutual information, Kullback-Leibler divergence, and generalized Simpson's indices. The estimators used have a bias that decays exponentially fast.
Author: Lijuan Cao [aut], Michael Grabchak [aut, cre]
Maintainer: Michael Grabchak <mgrabcha@charlotte.edu>

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Package usefun updated to version 0.5.2 with previous version 0.5.0 dated 2023-09-17

Title: A Collection of Useful Functions by John
Description: A set of general functions that I have used in various projects and other R packages. Miscellaneous operations on data frames, matrices and vectors, ROC and PR statistics.
Author: John Zobolas [aut, cph, cre]
Maintainer: John Zobolas <bblodfon@gmail.com>

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Package forestmangr updated to version 0.9.7 with previous version 0.9.6 dated 2023-11-23

Title: Forest Mensuration and Management
Description: Processing forest inventory data with methods such as simple random sampling, stratified random sampling and systematic sampling. There are also functions for yield and growth predictions and model fitting, linear and nonlinear grouped data fitting, and statistical tests. References: Kershaw Jr., Ducey, Beers and Husch (2016). <doi:10.1002/9781118902028>.
Author: Sollano Rabelo Braga [aut, cre, cph], Marcio Leles Romarco de Oliveira [aut], Eric Bastos Gorgens [aut]
Maintainer: Sollano Rabelo Braga <sollanorb@gmail.com>

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Package emBayes updated to version 0.1.6 with previous version 0.1.5 dated 2024-03-29

Title: Robust Bayesian Variable Selection via Expectation-Maximization
Description: Variable selection methods have been extensively developed for analyzing highdimensional omics data within both the frequentist and Bayesian frameworks. This package provides implementations of the spike-and-slab quantile (group) LASSO which have been developed along the line of Bayesian hierarchical models but deeply rooted in frequentist regularization methods by utilizing Expectation–Maximization (EM) algorithm. The spike-and-slab quantile LASSO can handle data irregularity in terms of skewness and outliers in response variables, compared to its non-robust alternative, the spike-and-slab LASSO, which has also been implemented in the package. In addition, procedures for fitting the spike-and-slab quantile group LASSO and its non-robust counterpart have been implemented in the form of quantile/least-square varying coefficient mixed effect models for high-dimensional longitudinal data. The core module of this package is developed in 'C++'.
Author: Yuwen Liu [aut, cre], Cen Wu [aut]
Maintainer: Yuwen Liu <yuwenliu9@gmail.com>

Diff between emBayes versions 0.1.5 dated 2024-03-29 and 0.1.6 dated 2024-09-14

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Package charlesschwabapi updated to version 1.0.3 with previous version 1.0.2 dated 2024-07-17

Title: Wrapper Functions Around 'Charles Schwab Individual Trader API'
Description: For those wishing to interact with the 'Charles Schwab Individual Trader API' (<https://developer.schwab.com/products/trader-api--individual>) with R in a simplified manner, this package offers wrapper functions around authentication and the available API calls to streamline the process.
Author: Nick Bultman [aut, cre, cph]
Maintainer: Nick Bultman <njbultman74@gmail.com>

Diff between charlesschwabapi versions 1.0.2 dated 2024-07-17 and 1.0.3 dated 2024-09-14

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Package BrazilCrime updated to version 0.2.1 with previous version 0.2 dated 2024-06-21

Title: Accesses Brazilian Public Security Data from SINESP Since 2015
Description: Allows access to data from the Brazilian Public Security Information System (SINESP) by state and municipality. <https://www.gov.br/mj/pt-br/assuntos/sua-seguranca/seguranca-publica/sinesp-1>.
Author: Giovanni Vargette [aut, cre] , Igor Laltuf [aut] , Marcelo Justus [aut]
Maintainer: Giovanni Vargette <g216978@dac.unicamp.br>

Diff between BrazilCrime versions 0.2 dated 2024-06-21 and 0.2.1 dated 2024-09-14

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Package stoppingrule updated to version 0.5.0 with previous version 0.4.0 dated 2024-03-17

Title: Create and Evaluate Stopping Rules for Safety Monitoring
Description: Provides functions for creating, displaying, and evaluating stopping rules for safety monitoring in clinical studies. Implements stopping rule methods described in Goldman (1987) <doi:10.1016/0197-2456(87)90153-X>; Geller et al. (2003, ISBN:9781135524388); Ivanova, Qaqish, and Schell (2005) <doi:10.1111/j.1541-0420.2005.00311.x>; Chen and Chaloner (2006) <doi:10.1002/sim.2429>; and Kulldorff et al. (2011) <doi:10.1080/07474946.2011.539924>.
Author: Michael J. Martens [aut, cre], Qinghua Lian [aut], Brent R. Logan [ctb]
Maintainer: Michael J. Martens <mmartens@mcw.edu>

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Package datanugget updated to version 1.3.1 with previous version 1.3.0 dated 2024-07-29

Title: Create, and Refine Data Nuggets
Description: Creating, and refining data nuggets. Data nuggets reduce a large dataset into a small collection of nuggets of data, each containing a center (location), weight (importance), and scale (variability) parameter. Data nugget centers are created by choosing observations in the dataset which are as equally spaced apart as possible. Data nugget weights are created by counting the number observations closest to a given data nugget center. We then say the data nugget 'contains' these observations and the data nugget center is recalculated as the mean of these observations. Data nugget scales are created by calculating the trace of the covariance matrix of the observations contained within a data nugget divided by the dimension of the dataset. Data nuggets are refined by 'splitting' data nuggets which have scales or shapes (defined as the ratio of the two largest eigenvalues of the covariance matrix of the observations contained within the data nugget) Reference paper: [1] Beavers, T. E., Cheng [...truncated...]
Author: Yajie Duan [cre, ctb], Traymon Beavers [aut], Javier Cabrera [aut], Ge Cheng [aut], Kunting Qi [aut], Mariusz Lubomirski [aut]
Maintainer: Yajie Duan <yajieritaduan@gmail.com>

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Package photobiologyInOut updated to version 0.4.28-1 with previous version 0.4.27 dated 2023-07-20

Title: Read Spectral and Logged Data from Foreign Files
Description: Functions for reading, and in some cases writing, foreign files containing spectral data from spectrometers and their associated software, output from daylight simulation models in common use, and some spectral data repositories. As well as functions for exchange of spectral data with other R packages. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre] , Titta K. Kotilainen [ctb] , Glenn Davis [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

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Package shapviz updated to version 0.9.5 with previous version 0.9.4 dated 2024-08-20

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', 'DALEX', 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], Adrian Stando [ctb]
Maintainer: Michael Mayer <mayermichael79@gmail.com>

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Package gvcR updated to version 0.3.0 with previous version 0.1.0 dated 2018-02-20

Title: Genotypic Variance Components
Description: Functionalities to compute model based genetic components i.e. genotypic variance, phenotypic variance and heritability for given traits of different genotypes from replicated data using methodology explained by Burton, G. W. & Devane, E. H. (1953) (<doi:10.2134/agronj1953.00021962004500100005x>) and Allard, R.W. (2010, ISBN:8126524154).
Author: Muhammad Yaseen [aut, cre], Sami Ullah [aut, ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>

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Package clusterSim updated to version 0.51-5 with previous version 0.51-4 dated 2024-06-26

Title: Searching for Optimal Clustering Procedure for a Data Set
Description: Distance measures (GDM1, GDM2, Sokal-Michener, Bray-Curtis, for symbolic interval-valued data), cluster quality indices (Calinski-Harabasz, Baker-Hubert, Hubert-Levine, Silhouette, Krzanowski-Lai, Hartigan, Gap, Davies-Bouldin), data normalization formulas (metric data, interval-valued symbolic data), data generation (typical and non-typical data), HINoV method, replication analysis, linear ordering methods, spectral clustering, agreement indices between two partitions, plot functions (for categorical and symbolic interval-valued data). (MILLIGAN, G.W., COOPER, M.C. (1985) <doi:10.1007/BF02294245>, HUBERT, L., ARABIE, P. (1985) <doi:10.1007%2FBF01908075>, RAND, W.M. (1971) <doi:10.1080/01621459.1971.10482356>, JAJUGA, K., WALESIAK, M. (2000) <doi:10.1007/978-3-642-57280-7_11>, MILLIGAN, G.W., COOPER, M.C. (1988) <doi:10.1007/BF01897163>, JAJUGA, K., WALESIAK, M., BAK, A. (2003) <doi:10.1007/978-3-642-55721-7_12>, DAVIES, D.L., BOULDIN, D.W. (1979) &l [...truncated...]
Author: Marek Walesiak [aut] , Andrzej Dudek [aut, cre]
Maintainer: Andrzej Dudek <andrzej.dudek@ue.wroc.pl>

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Package RMVL updated to version 1.1.0.1 with previous version 1.1.0.0 dated 2024-05-08

Title: Mappable Vector Library for Handling Large Datasets
Description: Mappable vector library provides convenient way to access large datasets. Use all of your data at once, with few limits. Memory mapped data can be shared between multiple R processes. Access speed depends on storage medium, so solid state drive is recommended, preferably with PCI Express (or M.2 nvme) interface or a fast network file system. The data is memory mapped into R and then accessed using usual R list and array subscription operators. Convenience functions are provided for merging, grouping and indexing large vectors and data.frames. The layout of underlying MVL files is optimized for large datasets. The vectors are stored to guarantee alignment for vector intrinsics after memory map. The package is built on top of libMVL, which can be used as a standalone C library. libMVL has simple C API making it easy to interchange datasets with outside programs. Large MVL datasets are distributed via Academic Torrents <https://academictorrents.com/collection/mvl-datasets>.
Author: Vladimir Dergachev [aut, cre]
Maintainer: Vladimir Dergachev <support@altumrete.com>

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Package reactR updated to version 0.6.1 with previous version 0.6.0 dated 2024-06-26

Title: React Helpers
Description: Make it easy to use 'React' in R with 'htmlwidget' scaffolds, helper dependency functions, an embedded 'Babel' 'transpiler', and examples.
Author: Facebook Inc [aut, cph] , Michel Weststrate [aut, cph] , Kent Russell [aut, cre] , Alan Dipert [aut] , Greg Lin [aut]
Maintainer: Kent Russell <kent.russell@timelyportfolio.com>

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Package PhaseType updated to version 0.3.0 with previous version 0.2.1 dated 2023-04-07

Title: Inference for Phase-Type Distributions
Description: Functions to perform Bayesian inference on absorption time data for Phase-type distributions. The methods of Bladt et al (2003) <doi:10.1080/03461230110106435> and Aslett (2012) <https://www.louisaslett.com/PhD_Thesis.pdf> are provided.
Author: Louis Aslett [aut, cre], Wally Gilks [ctb]
Maintainer: Louis Aslett <louis.aslett@durham.ac.uk>

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Package biplotEZ updated to version 2.1 with previous version 2.0 dated 2024-07-08

Title: EZ-to-Use Biplots
Description: Provides users with an EZ-to-use platform for representing data with biplots. Currently principal component analysis (PCA), canonical variate analysis (CVA) and simple correspondence analysis (CA) biplots are included. This is accompanied by various formatting options for the samples and axes. Alpha-bags and concentration ellipses are included for visual enhancements and interpretation. For an extensive discussion on the topic, see Gower, J.C., Lubbe, S. and le Roux, N.J. (2011, ISBN: 978-0-470-01255-0) Understanding Biplots. Wiley: Chichester.
Author: Sugnet Lubbe [aut, cre, cph] , Niel le Roux [aut] , Johane Nienkemper-Swanepoel [aut] , Raeesa Ganey [aut] , Ruan Buys [aut] , Zoe-Mae Adams [aut] , Peter Manefeldt [aut]
Maintainer: Sugnet Lubbe <muvisu@sun.ac.za>

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Package worcs updated to version 0.1.15 with previous version 0.1.14 dated 2023-10-25

Title: Workflow for Open Reproducible Code in Science
Description: Create reproducible and transparent research projects in 'R'. This package is based on the Workflow for Open Reproducible Code in Science (WORCS), a step-by-step procedure based on best practices for Open Science. It includes an 'RStudio' project template, several convenience functions, and all dependencies required to make your project reproducible and transparent. WORCS is explained in the tutorial paper by Van Lissa, Brandmaier, Brinkman, Lamprecht, Struiksma, & Vreede (2021). <doi:10.3233/DS-210031>.
Author: Caspar J. Van Lissa [aut, cre] , Aaron Peikert [aut] , Andreas M. Brandmaier [aut]
Maintainer: Caspar J. Van Lissa <c.j.vanlissa@tilburguniversity.edu>

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Package imf.data updated to version 0.1.7 with previous version 0.1.6 dated 2024-07-16

Title: An Interface to IMF (International Monetary Fund) Data JSON API
Description: A straightforward interface for accessing the IMF (International Monetary Fund) data JSON API, available at <https://data.imf.org/>. This package offers direct access to the primary API endpoints: Dataflow, DataStructure, and CompactData. And, it provides an intuitive interface for exploring available dimensions and attributes, as well as querying individual time-series datasets. Additionally, the package implements a rate limit on API calls to reduce the chances of exceeding service limits (limited to 10 calls every 5 seconds) and encountering response errors.
Author: Pedro Baltazar [aut, cre]
Maintainer: Pedro Baltazar <pedrobtz@gmail.com>

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Package iForecast updated to version 1.0.8 with previous version 1.0.7 dated 2023-07-01

Title: Machine Learning Time Series Forecasting
Description: Compute static, onestep and multistep time series forecasts for machine learning models.
Author: Ho Tsung-wu [aut, cre]
Maintainer: Ho Tsung-wu <tsungwu@ntnu.edu.tw>

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Package ream (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:

2024-09-10 1.0-1

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Package bayesCureRateModel updated to version 1.2 with previous version 1.1 dated 2024-07-24

Title: Bayesian Cure Rate Modeling for Time-to-Event Data
Description: A fully Bayesian approach in order to estimate a general family of cure rate models under the presence of covariates, see Papastamoulis and Milienos (2024) <doi:10.1007/s11749-024-00942-w>. The promotion time can be modelled (a) parametrically using typical distributional assumptions for time to event data (including the Weibull, Exponential, Gompertz, log-Logistic distributions), or (b) semiparametrically using finite mixtures of distributions. In both cases, user-defined families of distributions are allowed under some specific requirements. Posterior inference is carried out by constructing a Metropolis-coupled Markov chain Monte Carlo (MCMC) sampler, which combines Gibbs sampling for the latent cure indicators and Metropolis-Hastings steps with Langevin diffusion dynamics for parameter updates. The main MCMC algorithm is embedded within a parallel tempering scheme by considering heated versions of the target posterior distribution.
Author: Panagiotis Papastamoulis [aut, cre] , Fotios Milienos [aut]
Maintainer: Panagiotis Papastamoulis <papapast@yahoo.gr>

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Fri, 13 Sep 2024

Package PakPMICS2018 updated to version 1.1.0 with previous version 1.0.0 dated 2020-01-25

Title: Multiple Indicator Cluster Survey (MICS) 2017-18 Data for Punjab, Pakistan
Description: Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of SDG monitoring, as the survey produces information on 32 global SDG indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using Probability Proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5 [...truncated...]
Author: Muhammad Yaseen [aut, cre]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>

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Package poputils updated to version 0.3.3 with previous version 0.3.1 dated 2024-06-12

Title: Demographic Analysis and Data Manipulation
Description: Perform tasks commonly encountered when preparing and analysing demographic data. Some functions are intended for end users, and others for developers. Includes functions for working with life tables.
Author: John Bryant [aut, cre], Bayesian Demography Limited [cph]
Maintainer: John Bryant <john@bayesiandemography.com>

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Package OpenSpecy updated to version 1.2.0 with previous version 1.1.0 dated 2024-06-13

Title: Analyze, Process, Identify, and Share Raman and (FT)IR Spectra
Description: Raman and (FT)IR spectral analysis tool for plastic particles and other environmental samples (Cowger et al. 2021, <doi:10.1021/acs.analchem.1c00123>). With read_any(), Open Specy provides a single function for reading individual, batch, or map spectral data files like .asp, .csv, .jdx, .spc, .spa, .0, and .zip. process_spec() simplifies processing spectra, including smoothing, baseline correction, range restriction and flattening, intensity conversions, wavenumber alignment, and min-max normalization. Spectra can be identified in batch using an onboard reference library (Cowger et al. 2020, <doi:10.1177/0003702820929064>) using match_spec(). A Shiny app is available via run_app() or online at <https://openanalysis.org/openspecy/>.
Author: Win Cowger [cre, aut, dtc] , Zacharias Steinmetz [aut] , Nick Leong [aut] , Andrea Faltynkova [aut, dtc] , Hannah Sherrod [aut] , Andrew B Gray [ctb] , Hannah Hapich [ctb] , Jennifer Lynch [ctb, dtc] , Hannah De Frond [ctb, dtc] , Keenan Munno [ctb, [...truncated...]
Maintainer: Win Cowger <wincowger@gmail.com>

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Package httr2 updated to version 1.0.4 with previous version 1.0.3 dated 2024-08-21

Title: Perform HTTP Requests and Process the Responses
Description: Tools for creating and modifying HTTP requests, then performing them and processing the results. 'httr2' is a modern re-imagining of 'httr' that uses a pipe-based interface and solves more of the problems that API wrapping packages face.
Author: Hadley Wickham [aut, cre], Posit Software, PBC [cph, fnd], Maximilian Girlich [ctb]
Maintainer: Hadley Wickham <hadley@posit.co>

Diff between httr2 versions 1.0.3 dated 2024-08-21 and 1.0.4 dated 2024-09-13

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More information about httr2 at CRAN
Permanent link

Package eda4treeR updated to version 1.1.0 with previous version 0.6.0 dated 2023-05-01

Title: Experimental Design and Analysis for Tree Improvement
Description: Provides data sets and R Codes for E.R. Williams, C.E. Harwood and A.C. Matheson (2023). Experimental Design and Analysis for Tree Improvement, CSIRO Publishing.
Author: Muhammad Yaseen [aut, cre, cph] , Sami Ullah [aut, ctb], Kent Eskridge [aut, ctb], Emlyn Williams [aut, ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>

Diff between eda4treeR versions 0.6.0 dated 2023-05-01 and 1.1.0 dated 2024-09-13

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Package DiallelAnalysisR updated to version 0.6.0 with previous version 0.5.0 dated 2023-03-31

Title: Diallel Analysis with R
Description: Performs Diallel Analysis with R using Griffing's and Hayman's approaches. Four different Methods (1: Method-I (Parents + F1's + reciprocals); 2: Method-II (Parents and one set of F1's); 3: Method-III (One set of F1's and reciprocals); 4: Method-IV (One set of F1's only)) and two Models (1: Fixed Effects Model; 2: Random Effects Model) can be applied using Griffing's approach.
Author: Muhammad Yaseen [aut, cre, cph] , Kent Eskridge [ctb, aut], Pedro Barbosa [ctb, aut], Yuhang Guo [ctb, aut]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>

Diff between DiallelAnalysisR versions 0.5.0 dated 2023-03-31 and 0.6.0 dated 2024-09-13

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More information about DiallelAnalysisR at CRAN
Permanent link

Package rJavaEnv updated to version 0.2.2 with previous version 0.2.1 dated 2024-09-03

Title: 'Java' Environments for R Projects
Description: Quickly install 'Java Development Kit (JDK)' without administrative privileges and set environment variables in current R session or project to solve common issues with 'Java' environment management in 'R'. Recommended to users of 'Java'/'rJava'-dependent 'R' packages such as 'r5r', 'opentripplanner', 'xlsx', 'openNLP', 'rWeka', 'RJDBC', 'tabulapdf', and many more. 'rJavaEnv' prevents common problems like 'Java' not found, 'Java' version conflicts, missing 'Java' installations, and the inability to install 'Java' due to lack of administrative privileges. 'rJavaEnv' automates the download, installation, and setup of the 'Java' on a per-project basis by setting the relevant 'JAVA_HOME' in the current 'R' session or the current working directory (via '.Rprofile', with the user's consent). Similar to what 'renv' does for 'R' packages, 'rJavaEnv' allows different 'Java' versions to be used across different projects, but can also be configured to allow multiple versions within the same proj [...truncated...]
Author: Egor Kotov [aut, cre, cph] , Mauricio Vargas [ctb] , Hadley Wickham [ctb]
Maintainer: Egor Kotov <kotov.egor@gmail.com>

Diff between rJavaEnv versions 0.2.1 dated 2024-09-03 and 0.2.2 dated 2024-09-13

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Permanent link

Package ggspectra updated to version 0.3.13 with previous version 0.3.12 dated 2023-10-21

Title: Extensions to 'ggplot2' for Radiation Spectra
Description: Additional annotations, stats, geoms and scales for plotting "light" spectra with 'ggplot2', together with specializations of ggplot() and autoplot() methods for spectral data and waveband definitions stored in objects of classes defined in package 'photobiology'. Part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre] , Titta K. Kotilainen [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

Diff between ggspectra versions 0.3.12 dated 2023-10-21 and 0.3.13 dated 2024-09-13

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More information about ggspectra at CRAN
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Package BRcal updated to version 1.0.0 with previous version 0.0.4 dated 2024-06-25

Title: Boldness-Recalibration of Binary Events
Description: Boldness-recalibration maximally spreads out probability predictions while maintaining a user specified level of calibration, facilitated the brcal() function. Supporting functions to assess calibration via Bayesian and Frequentist approaches, Maximum Likelihood Estimator (MLE) recalibration, Linear in Log Odds (LLO)-adjust via any specified parameters, and visualize results are also provided. Methodological details can be found in Guthrie & Franck (2024) <doi:10.1080/00031305.2024.2339266>.
Author: Adeline P. Guthrie [aut, cre] , Christopher T. Franck [aut]
Maintainer: Adeline P. Guthrie <apguthrie47@gmail.com>

Diff between BRcal versions 0.0.4 dated 2024-06-25 and 1.0.0 dated 2024-09-13

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 BRcal-1.0.0/BRcal/DESCRIPTION                                                                          |   12 
 BRcal-1.0.0/BRcal/MD5                                                                                  |   57 +--
 BRcal-1.0.0/BRcal/NAMESPACE                                                                            |    2 
 BRcal-1.0.0/BRcal/R/boldness_recalib.R                                                                 |   42 --
 BRcal-1.0.0/BRcal/R/data.R                                                                             |   57 ++-
 BRcal-1.0.0/BRcal/R/plotting_functions.R                                                               |  161 ++++++----
 BRcal-1.0.0/BRcal/README.md                                                                            |    2 
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 BRcal-1.0.0/BRcal/data/foreclosure.rda                                                                 |only
 BRcal-1.0.0/BRcal/inst/doc/hockey_vignette.R                                                           |   27 +
 BRcal-1.0.0/BRcal/inst/doc/hockey_vignette.Rmd                                                         |   44 +-
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 BRcal-1.0.0/BRcal/man/foreclosure.Rd                                                                   |only
 BRcal-1.0.0/BRcal/man/lineplot.Rd                                                                      |   27 +
 BRcal-1.0.0/BRcal/man/plot_params.Rd                                                                   |   17 -
 BRcal-1.0.0/BRcal/vignettes/hockey_vignette.Rmd                                                        |   44 +-
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New package timeSeriesDataSets with initial version 0.1.0
Package: timeSeriesDataSets
Title: Time Series Data Sets
Version: 0.1.0
Maintainer: Renzo Caceres Rossi <arenzocaceresrossi@gmail.com>
Description: Provides a diverse collection of time series datasets spanning various fields such as economics, finance, energy, healthcare, and more. Designed to support time series analysis in R by offering datasets from multiple disciplines, making it a valuable resource for researchers and analysts.
License: GPL-3
URL: https://github.com/lightbluetitan/timeseriesdatasets_R
Encoding: UTF-8
LazyData: true
Suggests: ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-11 02:07:23 UTC; renzorossiv
Author: Renzo Caceres Rossi [aut, cre]
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2024-09-13 18:10:02 UTC

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New package power.transform with initial version 1.0.0
Package: power.transform
Title: Location and Scale Invariant Power Transformations
Version: 1.0.0
Description: Location- and scale-invariant Box-Cox and Yeo-Johnson power transformations allow for transforming variables with distributions distant from 0 to normality. Transformers are implemented as S4 objects. These allow for transforming new instances to normality after optimising fitting parameters on other data. A test for central normality allows for rejecting transformations that fail to produce a suitably normal distribution, independent of sample number.
URL: https://github.com/oncoray/power.transform
BugReports: https://github.com/oncoray/power.transform/issues
License: EUPL
Encoding: UTF-8
Imports: data.table, methods, rlang (>= 1.0.0), nloptr
Suggests: ggplot2 (>= 3.4.0), testthat (>= 3.0.0)
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2024-09-11 07:24:33 UTC; alexz
Author: Alex Zwanenburg [aut, cre] , Steffen Loeck [aut], German Cancer Research Center [cph]
Maintainer: Alex Zwanenburg <alexander.zwanenburg@nct-dresden.de>
Repository: CRAN
Date/Publication: 2024-09-13 18:20:02 UTC

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New package miniLNM with initial version 0.1.0
Package: miniLNM
Title: Miniature Logistic-Normal Multinomial Models
Version: 0.1.0
Description: Logistic-normal Multinomial (LNM) models are common in problems with multivariate count data. This package gives a simple implementation with a 30 line 'Stan' script. This lightweight implementation makes it an easy starting point for other projects, in particular for downstream tasks that require analysis of "compositional" data. It can be applied whenever a multinomial probability parameter is thought to depend linearly on inputs in a transformed, log ratio space. Additional utilities make it easy to inspect, create predictions, and draw samples using the fitted models. More about the LNM can be found in Xia et al. (2013) "A Logistic Normal Multinomial Regression Model for Microbiome Compositional Data Analysis" <doi:10.1111/biom.12079> and Sankaran and Holmes (2023) "Generative Models: An Interdisciplinary Perspective" <doi:10.1146/annurev-statistics-033121-110134>.
License: CC0
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), cli, dplyr, fansi, formula.tools, glue, methods, posterior, rstan (>= 2.18.1), rstantools (>= 2.4.0), tidyselect
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Biarch: true
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
SystemRequirements: GNU make
BugReports: https://github.com/krisrs1128/miniLNM/issues/
URL: https://github.com/krisrs1128/miniLNM/, https://krisrs1128.github.io/miniLNM/
NeedsCompilation: yes
Packaged: 2024-09-11 17:28:57 UTC; krissankaran
Author: Kris Sankaran [aut, cre]
Maintainer: Kris Sankaran <ksankaran@wisc.edu>
Repository: CRAN
Date/Publication: 2024-09-13 18:30:02 UTC

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New package healthatlas with initial version 0.1.0
Package: healthatlas
Title: Explore and Import 'Metopio' Health Atlas Data and Spatial Layers
Version: 0.1.0
Description: Allows for painless use of the 'Metopio' health atlas APIs <https://metopio.com/how-it-works/atlas/> to explore and import data. 'Metopio' health atlases store open public health data. See what topics (or indicators) are available among specific populations, periods, and geographic layers. Download relevant data along with geographic boundaries or point datasets. Spatial datasets are returned as 'sf' objects.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: curl, dplyr, httr2, purrr, sf, tibble, tidyr
Suggests: ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://ryanzomorrodi.github.io/healthatlas/, https://github.com/ryanzomorrodi/healthatlas
BugReports: https://github.com/ryanzomorrodi/healthatlas/issues
NeedsCompilation: no
Packaged: 2024-09-11 04:45:03 UTC; user
Author: Ryan Zomorrodi [aut, cre, cph]
Maintainer: Ryan Zomorrodi <rzomor2@uic.edu>
Repository: CRAN
Date/Publication: 2024-09-13 18:20:05 UTC

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Package dttr2 updated to version 0.5.1 with previous version 0.5.0 dated 2023-11-14

Title: Manipulate Date, POSIXct and hms Vectors
Description: Manipulates date ('Date'), date time ('POSIXct') and time ('hms') vectors. Date/times are considered discrete and are floored whenever encountered. Times are wrapped and time zones are maintained unless explicitly altered by the user.
Author: Joe Thorley [aut] , Ayla Pearson [aut, cre] , Poisson Consulting [cph, fnd]
Maintainer: Ayla Pearson <ayla@poissonconsulting.ca>

Diff between dttr2 versions 0.5.0 dated 2023-11-14 and 0.5.1 dated 2024-09-13

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 27 files changed, 98 insertions(+), 69 deletions(-)

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New package dsld with initial version 0.2.2
Package: dsld
Version: 0.2.2
Title: Data Science Looks at Discrimination
Maintainer: Norm Matloff <nsmatloff@ucdavis.edu>
VignetteBuilder: knitr
Imports: Kendall, ranger, ggplot2, plotly, freqparcoord, fairness,sandwich
Depends: R (>= 3.5.0), fairml, gtools, regtools,qeML,rmarkdown
Suggests: knitr,bnlearn,Matching,randomForest
License: GPL (>= 2)
Description: Statistical and graphical tools for detecting and measuring discrimination and bias, be it racial, gender, age or other. Detection and remediation of bias in machine learning algorithms. 'Python' interfaces available.
URL: https://github.com/matloff/dsld
BugReports: https://github.com/matloff/dsld/issues
NeedsCompilation: no
Packaged: 2024-09-11 04:08:37 UTC; normanmatloff
Author: Norm Matloff [aut, cre] , Taha Abdullah [aut], Arjun Ashok [aut], Shubhada Martha [aut], Aditya Mittal [aut], Billy Ouattara [aut], Jonathan Tran [aut], Brandon Zarate Estrada [aut]
Repository: CRAN
Date/Publication: 2024-09-13 18:20:09 UTC

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New package douconca with initial version 1.2.0
Package: douconca
Title: Double Constrained Correspondence Analysis for Trait-Environment Analysis in Ecology
Version: 1.2.0
Date: 2024-08-29
Description: Double constrained correspondence analysis (dc-CA) analyzes (multi-)trait (multi-)environment ecological data by using the 'vegan' package and native R code. Throughout the two step algorithm of ter Braak et al. (2018) is used. This algorithm combines and extends community- (sample-) and species-level analyses, i.e. the usual community weighted means (CWM)-based regression analysis and the species-level analysis of species-niche centroids (SNC)-based regression analysis. The two steps use canonical correspondence analysis to regress the abundance data on to the traits and (weighted) redundancy analysis to regress the CWM of the orthonormalized traits on to the environmental predictors. The function dc_CA() has an option to divide the abundance data of a site by the site total, giving equal site weights. This division has the advantage that the multivariate analysis corresponds with an unweighted (multi-trait) community-level analysis, instead of being weighted. The first step of the al [...truncated...]
Depends: R (>= 3.6.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: ggplot2 (>= 3.5.1), ggrepel, gridExtra, permute, rlang, stats, vegan (>= 2.6-8)
NeedsCompilation: no
Suggests: rmarkdown, knitr, tinytest
VignetteBuilder: knitr
URL: https://github.com/CajoterBraak/douconca
BugReports: https://github.com/CajoterBraak/douconca/issues
Packaged: 2024-09-11 07:27:07 UTC; rossu027
Author: Cajo J.F ter Braak [aut] , Bart-Jan van Rossum [aut, cre]
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>
Repository: CRAN
Date/Publication: 2024-09-13 18:20:13 UTC

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New package DiscreteDists with initial version 1.0.0
Package: DiscreteDists
Title: Discrete Statistical Distributions
Version: 1.0.0
Description: Implementation of new discrete statistical distributions. Each distribution includes the traditional functions as well as an additional function called the family function, which can be used to estimate parameters within the 'gamlss' framework.
License: MIT + file LICENSE
Imports: gamlss, gamlss.dist, pracma, Rdpack, Rcpp
LinkingTo: Rcpp
Encoding: UTF-8
Suggests: knitr, rmarkdown
URL: https://github.com/fhernanb/DiscreteDists
BugReports: https://github.com/fhernanb/DiscreteDists/issues
NeedsCompilation: yes
Packaged: 2024-09-11 01:13:09 UTC; fhern
Author: Freddy Hernandez-Barajas [aut, cre] , Fernando Marmolejo-Ramos [aut] , Jamiu Olumoh [aut] , Osho Ajayi [aut] , Olga Usuga-Manco [aut]
Maintainer: Freddy Hernandez-Barajas <fhernanb@unal.edu.co>
Repository: CRAN
Date/Publication: 2024-09-13 18:10:06 UTC

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New package DEHOGT with initial version 0.99.0
Package: DEHOGT
Title: Differentially Expressed Heterogeneous Overdispersion Gene Test for Count Data
Version: 0.99.0
Description: Implements a generalized linear model approach for detecting differentially expressed genes across treatment groups in count data. The package supports both quasi-Poisson and negative binomial models to handle over-dispersion, ensuring robust identification of differential expression. It allows for the inclusion of treatment effects and gene-wise covariates, as well as normalization factors for accurate scaling across samples. Additionally, it incorporates statistical significance testing with options for p-value adjustment and log2 fold range thresholds, making it suitable for RNA-seq analysis as described in by Xu et al., (2024) <doi:10.1371/journal.pone.0300565>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: doParallel, foreach, MASS,
Suggests: knitr, rmarkdown, BiocStyle
VignetteBuilder: knitr
URL: https://github.com/ahshen26/DEHOGT
BugReports: https://github.com/ahshen26/DEHOGT/issues
NeedsCompilation: no
Packaged: 2024-09-11 15:00:01 UTC; arlinashen
Author: Qi Xu [aut], Arlina Shen [cre] , Yubai Yuan [ctb], Annie Qu [ctb]
Maintainer: Arlina Shen <ahshen24@berkeley.edu>
Repository: CRAN
Date/Publication: 2024-09-13 18:30:06 UTC

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New package stdReg2 with initial version 1.0.1
Package: stdReg2
Title: Regression Standardization for Causal Inference
Version: 1.0.1
URL: https://sachsmc.github.io/stdReg2/
BugReports: https://github.com/sachsmc/stdReg2/issues/
Date: 2024-09-10
Description: Contains more modern tools for causal inference using regression standardization. Four general classes of models are implemented; generalized linear models, conditional generalized estimating equation models, Cox proportional hazards models, and shared frailty gamma-Weibull models. Methodological details are described in Sjölander, A. (2016) <doi:10.1007/s10654-016-0157-3>. Also includes functionality for doubly robust estimation for generalized linear models in some special cases, and the ability to implement custom models.
License: AGPL (>= 3)
Encoding: UTF-8
Imports: data.table, drgee, generics, survival
Suggests: causaldata, AF, knitr, nnet, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2024-09-10 16:51:01 UTC; micsac
Author: Michael C Sachs [aut, cre], Arvid Sjoelander [aut], Erin E Gabriel [aut], Johan Sebastian Ohlendorff [aut], Adam Brand [aut]
Maintainer: Michael C Sachs <sachsmc@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-13 17:50:02 UTC

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New package sfcurve with initial version 1.0.0
Package: sfcurve
Title: 2x2, 3x3 and Nxn Space-Filling Curves
Version: 1.0.0
Date: 2024-09-10
Depends: R (>= 4.0.0)
Imports: grid, Rcpp, methods, colorRamp2
Suggests: rmarkdown, knitr, rgl, testthat, ComplexHeatmap, igraph, digest
VignetteBuilder: knitr
Description: Implementation of all possible forms of 2x2 and 3x3 space-filling curves, i.e., the generalized forms of the Hilbert curve <https://en.wikipedia.org/wiki/Hilbert_curve>, the Peano curve <https://en.wikipedia.org/wiki/Peano_curve> and the Peano curve in the meander type (Figure 5 in <https://eudml.org/doc/141086>). It can generates nxn curves expanded from any specific level-1 units. It also implements the H-curve and the three-dimensional Hilbert curve.
URL: https://github.com/jokergoo/sfcurve, https://jokergoo.github.io/sfcurve/
License: MIT + file LICENSE
LinkingTo: Rcpp
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2024-09-10 18:00:15 UTC; guz
Author: Zuguang Gu [aut, cre]
Maintainer: Zuguang Gu <z.gu@dkfz.de>
Repository: CRAN
Date/Publication: 2024-09-13 18:00:02 UTC

More information about sfcurve at CRAN
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Package epm updated to version 1.1.3 with previous version 1.1.2 dated 2023-12-19

Title: EcoPhyloMapper
Description: Facilitates the aggregation of species' geographic ranges from vector or raster spatial data, and that enables the calculation of various morphological and phylogenetic community metrics across geography. Citation: Title, PO, DL Swiderski and ML Zelditch (2022) <doi:10.1111/2041-210X.13914>.
Author: Pascal Title [aut, cre] , Donald Swiderski [aut], Miriam Zelditch [aut]
Maintainer: Pascal Title <pascal.title@stonybrook.edu>

Diff between epm versions 1.1.2 dated 2023-12-19 and 1.1.3 dated 2024-09-13

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New package distfromq with initial version 1.0.4
Package: distfromq
Title: Reconstruct a Distribution from a Collection of Quantiles
Version: 1.0.4
Description: Given a set of predictive quantiles from a distribution, estimate the distribution and create `d`, `p`, `q`, and `r` functions to evaluate its density function, distribution function, and quantile function, and generate random samples. On the interior of the provided quantiles, an interpolation method such as a monotonic cubic spline is used; the tails are approximated by a location-scale family.
License: GPL (>= 3)
URL: http://reichlab.io/distfromq/
Imports: checkmate, purrr, splines, stats, utils, zeallot
Suggests: dplyr, ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-10 21:02:16 UTC; lshandross
Author: Evan Ray [aut, cre], Aaron Gerding [aut], Li Shandross [ctb], Nick Reich [ctb]
Maintainer: Evan Ray <elray@umass.edu>
Repository: CRAN
Date/Publication: 2024-09-13 18:00:06 UTC

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New package anomo with initial version 0.5.2
Package: anomo
Title: Analysis of Moderation with the Monte Carlo Confidence Interval Method
Version: 0.5.2
Date: 2024-9-10
Description: Analysis of Moderation (anomo) uses the Monte Carlo confidence interval (MCCI) method to test the difference and equivalence of two effects with summary statistics from two studies.
Language: en-US
Depends: R (>= 4.0.0), graphics (>= 4.0.0), base(>= 4.0.0)
License: GPL-3
Encoding: UTF-8
Suggests: rmarkdown, knitr, markdown
VignetteBuilder: rmarkdown, knitr, markdown
NeedsCompilation: no
Packaged: 2024-09-10 15:26:14 UTC; zucha
Author: Zuchao Shen [aut, cre]
Maintainer: Zuchao Shen <zuchao.shen@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-13 17:40:01 UTC

More information about anomo at CRAN
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Package npboottprm updated to version 0.3.2 with previous version 0.3.1 dated 2024-07-16

Title: Nonparametric Bootstrap Test with Pooled Resampling
Description: Addressing crucial research questions often necessitates a small sample size due to factors such as distinctive target populations, rarity of the event under study, time and cost constraints, ethical concerns, or group-level unit of analysis. Many readily available analytic methods, however, do not accommodate small sample sizes, and the choice of the best method can be unclear. The 'npboottprm' package enables the execution of nonparametric bootstrap tests with pooled resampling to help fill this gap. Grounded in the statistical methods for small sample size studies detailed in Dwivedi, Mallawaarachchi, and Alvarado (2017) <doi:10.1002/sim.7263>, the package facilitates a range of statistical tests, encompassing independent t-tests, paired t-tests, and one-way Analysis of Variance (ANOVA) F-tests. The nonparboot() function undertakes essential computations, yielding detailed outputs which include test statistics, effect sizes, confidence intervals, and bootstrap distributions. F [...truncated...]
Author: Mackson Ncube [aut, cre], mightymetrika, LLC [cph, fnd]
Maintainer: Mackson Ncube <macksonncube.stats@gmail.com>

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Package digitalDLSorteR updated to version 1.1.0 with previous version 1.0.1 dated 2024-02-07

Title: Deconvolution of Bulk RNA-Seq Data Based on Deep Learning
Description: Deconvolution of bulk RNA-Seq data using context-specific deconvolution models based on Deep Neural Networks using scRNA-Seq data as input. These models are able to make accurate estimates of the cell composition of bulk RNA-Seq samples from the same context using the advances provided by Deep Learning and the meaningful information provided by scRNA-Seq data. See Torroja and Sanchez-Cabo (2019) <doi:10.3389/fgene.2019.00978> for more details.
Author: Diego Mananes [aut, cre] , Carlos Torroja [aut] , Fatima Sanchez-Cabo [aut]
Maintainer: Diego Mananes <dmananesc@cnic.es>

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Package tipsae updated to version 1.0.3 with previous version 1.0.2 dated 2024-07-30

Title: Tools for Handling Indices and Proportions in Small Area Estimation
Description: It allows for mapping proportions and indicators defined on the unit interval. It implements Beta-based small area methods comprising the classical Beta regression models, the Flexible Beta model and Zero and/or One Inflated extensions (Janicki 2020 <doi:10.1080/03610926.2019.1570266>). Such methods, developed within a Bayesian framework through Stan <https://mc-stan.org/>, come equipped with a set of diagnostics and complementary tools, visualizing and exporting functions. A Shiny application with a user-friendly interface can be launched to further simplify the process. For further details, refer to De Nicolò and Gardini (2024 <doi:10.18637/jss.v108.i01>).
Author: Silvia De Nicolo [aut, cre] , Aldo Gardini [aut]
Maintainer: Silvia De Nicolo <silvia.denicolo@unibo.it>

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Package spdep updated to version 1.3-6 with previous version 1.3-5 dated 2024-06-10

Title: Spatial Dependence: Weighting Schemes, Statistics
Description: A collection of functions to create spatial weights matrix objects from polygon 'contiguities', from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree; a collection of tests for spatial 'autocorrelation', including global 'Morans I' and 'Gearys C' proposed by 'Cliff' and 'Ord' (1973, ISBN: 0850860369) and (1981, ISBN: 0850860814), 'Hubert/Mantel' general cross product statistic, Empirical Bayes estimates and 'Assunção/Reis' (1999) <doi:10.1002/(SICI)1097-0258(19990830)18:16%3C2147::AID-SIM179%3E3.0.CO;2-I> Index, 'Getis/Ord' G ('Getis' and 'Ord' 1992) <doi:10.1111/j.1538-4632.1992.tb00261.x> and multicoloured join count statistics, 'APLE' ('Li 'et al.' ) <doi:10.1111/j.1538-4632.2007.00708.x>, local 'Moran's I', 'Gearys C' ('Anselin' 1995) <doi:10.1111/j.1538-4632.1995.tb00338.x> and 'Getis/Ord' G ('Ord' and 'Getis' 1995) < [...truncated...]
Author: Roger Bivand [cre, aut] , Micah Altman [ctb], Luc Anselin [ctb], Renato Assuncao [ctb], Anil Bera [ctb], Olaf Berke [ctb], F. Guillaume Blanchet [ctb], Marilia Carvalho [ctb], Bjarke Christensen [ctb], Yongwan Chun [ctb], Carsten Dormann [ctb], Steph [...truncated...]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

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Package cinterpolate updated to version 1.0.2 with previous version 1.0.1 dated 2023-11-29

Title: Interpolation From C
Description: Simple interpolation methods designed to be used from C code. Supports constant, linear and spline interpolation. An R wrapper is included but this package is primarily designed to be used from C code using 'LinkingTo'. The spline calculations are classical cubic interpolation, e.g., Forsythe, Malcolm and Moler (1977) <ISBN: 9780131653320>.
Author: Rich FitzJohn [aut, cre], Imperial College of Science, Technology and Medicine [cph]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>

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Package LiblineaR updated to version 2.10-24 with previous version 2.10-23 dated 2023-12-11

Title: Linear Predictive Models Based on the LIBLINEAR C/C++ Library
Description: A wrapper around the LIBLINEAR C/C++ library for machine learning (available at <https://www.csie.ntu.edu.tw/~cjlin/liblinear/>). LIBLINEAR is a simple library for solving large-scale regularized linear classification and regression. It currently supports L2-regularized classification (such as logistic regression, L2-loss linear SVM and L1-loss linear SVM) as well as L1-regularized classification (such as L2-loss linear SVM and logistic regression) and L2-regularized support vector regression (with L1- or L2-loss). The main features of LiblineaR include multi-class classification (one-vs-the rest, and Crammer & Singer method), cross validation for model selection, probability estimates (logistic regression only) or weights for unbalanced data. The estimation of the models is particularly fast as compared to other libraries.
Author: Thibault Helleputte [cre, aut, cph], Jerome Paul [aut], Pierre Gramme [aut]
Maintainer: Thibault Helleputte <thibault.helleputte@dnalytics.com>

Diff between LiblineaR versions 2.10-23 dated 2023-12-11 and 2.10-24 dated 2024-09-13

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Package compareGroups updated to version 4.9.0 with previous version 4.8.0 dated 2024-01-29

Title: Descriptive Analysis by Groups
Description: Create data summaries for quality control, extensive reports for exploring data, as well as publication-ready univariate or bivariate tables in several formats (plain text, HTML,LaTeX, PDF, Word or Excel. Create figures to quickly visualise the distribution of your data (boxplots, barplots, normality-plots, etc.). Display statistics (mean, median, frequencies, incidences, etc.). Perform the appropriate tests (t-test, Analysis of variance, Kruskal-Wallis, Fisher, log-rank, ...) depending on the nature of the described variable (normal, non-normal or qualitative). Summarize genetic data (Single Nucleotide Polymorphisms) data displaying Allele Frequencies and performing Hardy-Weinberg Equilibrium tests among other typical statistics and tests for these kind of data.
Author: Isaac Subirana [aut, cre] , Joan Salvador [ctb]
Maintainer: Isaac Subirana <isubirana@imim.es>

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Package sfdep updated to version 0.2.5 with previous version 0.2.4 dated 2024-02-20

Title: Spatial Dependence for Simple Features
Description: An interface to 'spdep' to integrate with 'sf' objects and the 'tidyverse'.
Author: Josiah Parry [aut] , Dexter Locke [aut, cre]
Maintainer: Dexter Locke <dexter.locke@gmail.com>

Diff between sfdep versions 0.2.4 dated 2024-02-20 and 0.2.5 dated 2024-09-13

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Package lsnstat updated to version 1.0.1 with previous version 1.0.0 dated 2023-04-22

Title: 'La Societe Nouvelle' API Access
Description: Tools facilitating access to the 'macro_data' service of the 'La Societe Nouvelle' API. It ensures an easy and fully-disclosed access to all macro-level data used in the 'La Societe Nouvelle' systems and the related metadata. Related API can be accessed from <https://api.lasocietenouvelle.org/>.
Author: Joris Blain [aut, cre]
Maintainer: Joris Blain <joris.blain@lasocietenouvelle.org>

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Package equateMultiple updated to version 1.0.0 with previous version 0.1.2 dated 2024-02-13

Title: Equating of Multiple Forms
Description: Equating of multiple forms using Item Response Theory (IRT) methods (Battauz M. (2017) <doi:10.1007/s11336-016-9517-x>, Battauz and 'Leoncio' (2023) <doi:10.1177/01466216231151702>, Haberman S. J. (2009) <doi:10.1002/j.2333-8504.2009.tb02197.x>).
Author: Michela Battauz [aut, cre], Waldir Leoncio [ctb]
Maintainer: Michela Battauz <michela.battauz@uniud.it>

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Package Deriv updated to version 4.1.6 with previous version 4.1.3 dated 2021-02-24

Title: Symbolic Differentiation
Description: R-based solution for symbolic differentiation. It admits user-defined function as well as function substitution in arguments of functions to be differentiated. Some symbolic simplification is part of the work.
Author: Andrew Clausen [aut], Serguei Sokol [aut, cre] , Andreas Rappold [ctb]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

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Package RJSDMX updated to version 3.4-0 with previous version 3.3-0 dated 2024-06-04

Title: R Interface to SDMX Web Services
Description: Provides functions to retrieve data and metadata from providers that disseminate data by means of SDMX web services. SDMX (Statistical Data and Metadata eXchange) is a standard that has been developed with the aim of simplifying the exchange of statistical information. More about the SDMX standard and the SDMX Web Services can be found at: <https://sdmx.org>.
Author: Attilio Mattiocco [aut, cre]
Maintainer: Attilio Mattiocco <attilio.mattiocco@bancaditalia.it>

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Package lfproQC updated to version 0.3.0 with previous version 0.2.0 dated 2024-09-06

Title: Quality Control for Label-Free Proteomics Expression Data
Description: Label-free bottom-up proteomics expression data is often affected by data heterogeneity and missing values. Normalization and missing value imputation are commonly used techniques to address these issues and make the dataset suitable for further downstream analysis. This package provides an optimal combination of normalization and imputation methods for the dataset. The package utilizes three normalization methods and three imputation methods.The statistical evaluation measures named pooled co-efficient of variance, pooled estimate of variance and pooled median absolute deviation are used for selecting the best combination of normalization and imputation method for the given dataset. The user can also visualize the results by using various plots available in this package. The user can also perform the differential expression analysis between two sample groups with the function included in this package. The chosen three normalization methods, three imputation methods and three evaluati [...truncated...]
Author: Kabilan S [aut, cre], Dr Shashi Bhushan Lal [aut, ths], Dr Sudhir Srivastava [aut, ths], Dr Krishna Kumar Chaturvedi [ths], Dr Yasin Jeshima K [ths], Dr Ramasubramanian V [ths], Dr Girish Kumar Jha [ctb]
Maintainer: Kabilan S <kabilan151414@gmail.com>

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Package LorMe updated to version 1.1.0 with previous version 1.0.0 dated 2024-08-29

Title: Lightening One-Code Resolving Microbial Ecology Solution
Description: Provides a robust collection of functions tailored for microbial ecology analysis, encompassing both data analysis and visualization. It introduces an encapsulation feature that streamlines the process into a summary object. With the initial configuration of this summary object, users can execute a wide range of analyses with a single line of code, requiring only two essential parameters for setup. The package delivers comprehensive outputs including analysis objects, statistical outcomes, and visualization-ready data, enhancing the efficiency of research workflows. Designed with user-friendliness in mind, it caters to both novices and seasoned researchers, offering an intuitive interface coupled with adaptable customization options to meet diverse analytical needs.
Author: Ningqi Wang [aut, cre, cph], Yaozhong Zhang [aut], Gaofei Jiang [aut]
Maintainer: Ningqi Wang <2434066068@qq.com>

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More information about LorMe at CRAN
Permanent link

New package hydflood with initial version 0.5.8
Package: hydflood
Title: Flood Extents and Duration along the Rivers Elbe and Rhine
Version: 0.5.8
Date: 2024-09-05
Description: Raster based flood modelling internally using 'hyd1d', an R package to interpolate 1d water level and gauging data. The package computes flood extent and duration through strategies originally developed for 'INFORM', an 'ArcGIS'-based hydro-ecological modelling framework. It does not provide a full, physical hydraulic modelling algorithm, but a simplified, near real time 'GIS' approach for flood extent and duration modelling. Computationally demanding annual flood durations have been computed already and data products were published by Weber (2022) <doi:10.1594/PANGAEA.948042>.
Depends: R (>= 4.0.0), sf, terra, raster, hyd1d
Imports: stats, Rdpack, grDevices, httr2, curl
Suggests: knitr, rmarkdown, devtools, pkgdown, roxygen2, testthat, plot3D, shiny, shinyjs, shiny.i18n, leaflet, leaflet.extras, leaflet.esri, pangaear, rgrass, stringr
License: GPL-2
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
BugReports: https://github.com/bafg-bund/hydflood/issues/
URL: https://hydflood.bafg.de, https://github.com/bafg-bund/hydflood
NeedsCompilation: no
Packaged: 2024-09-13 06:12:34 UTC; WeberA
Author: Arnd Weber [aut, cre] , Stephan Rosenzweig [ctb], Benjamin Eberhardt [ctb]
Maintainer: Arnd Weber <arnd.weber@bafg.de>
Repository: CRAN
Date/Publication: 2024-09-13 08:20:02 UTC

More information about hydflood at CRAN
Permanent link

Package charcuterie updated to version 0.0.4 with previous version 0.0.3 dated 2024-09-10

Title: Handle Strings as Vectors of Characters
Description: Creates a new chars class which looks like a string but is actually a vector of individual characters, making 'strings' iterable. This class enables vector operations on 'strings' such as reverse, sort, head, and set operations.
Author: Jonathan Carroll [aut, cre]
Maintainer: Jonathan Carroll <rpkg@jcarroll.com.au>

Diff between charcuterie versions 0.0.3 dated 2024-09-10 and 0.0.4 dated 2024-09-13

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Permanent link

Package posologyr updated to version 1.2.7 with previous version 1.2.6 dated 2024-08-27

Title: Individual Dose Optimization using Population Pharmacokinetics
Description: Optimize drug regimens through model-informed precision dosing, using individual pharmacokinetic (PK) and pharmacokinetic-pharmacodynamic (PK-PD) profiles. By integrating therapeutic drug monitoring (TDM) data with population models, 'posologyr' provides accurate posterior estimates and enables the calculation of personalized dosing regimens. The empirical Bayes estimates are computed following the method described by Kang et al. (2012) <doi:10.4196/kjpp.2012.16.2.97>.
Author: Cyril Leven [aut, cre, cph] , Matthew Fidler [ctb] , Emmanuelle Comets [ctb], Audrey Lavenu [ctb], Marc Lavielle [ctb]
Maintainer: Cyril Leven <cyril.leven@chu-brest.fr>

Diff between posologyr versions 1.2.6 dated 2024-08-27 and 1.2.7 dated 2024-09-13

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Permanent link

Package cassowaryr updated to version 2.0.2 with previous version 2.0.0 dated 2022-08-09

Title: Compute Scagnostics on Pairs of Numeric Variables in a Data Set
Description: Computes a range of scatterplot diagnostics (scagnostics) on pairs of numerical variables in a data set. A range of scagnostics, including graph and association-based scagnostics described by Leland Wilkinson and Graham Wills (2008) <doi:10.1198/106186008X320465> and association-based scagnostics described by Katrin Grimm (2016,ISBN:978-3-8439-3092-5) can be computed. Summary and plotting functions are provided.
Author: Harriet Mason [aut, cre] , Stuart Lee [aut] , Ursula Laa [aut] , Dianne Cook [aut]
Maintainer: Harriet Mason <harriet.m.mason@gmail.com>

Diff between cassowaryr versions 2.0.0 dated 2022-08-09 and 2.0.2 dated 2024-09-13

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Thu, 12 Sep 2024

Package garma updated to version 0.9.23 with previous version 0.9.22 dated 2024-09-05

Title: Fitting and Forecasting Gegenbauer ARMA Time Series Models
Description: Methods for estimating univariate long memory-seasonal/cyclical Gegenbauer time series processes. See for example (2022) <doi:10.1007/s00362-022-01290-3>. Refer to the vignette for details of fitting these processes.
Author: Richard Hunt [aut, cre]
Maintainer: Richard Hunt <maint@huntemail.id.au>

Diff between garma versions 0.9.22 dated 2024-09-05 and 0.9.23 dated 2024-09-12

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Package vDiveR updated to version 2.0.0 with previous version 1.2.1 dated 2024-01-09

Title: Visualization of Viral Protein Sequence Diversity Dynamics
Description: To ease the visualization of outputs from Diversity Motif Analyser ('DiMA'; <https://github.com/BVU-BILSAB/DiMA>). 'vDiveR' allows visualization of the diversity motifs (index and its variants – major, minor and unique) for elucidation of the underlying inherent dynamics. Please refer <https://vdiver-manual.readthedocs.io/en/latest/> for more information.
Author: Pendy Tok [aut, cre], Li Chuin Chong [aut], Evgenia Chikina [aut], Yin Cheng Chen [aut], Mohammad Asif Khan [aut]
Maintainer: Pendy Tok <pendytok0518@gmail.com>

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Package RSEIS updated to version 4.2-4 with previous version 4.2-0 dated 2024-02-25

Title: Seismic Time Series Analysis Tools
Description: Multiple interactive codes to view and analyze seismic data, via spectrum analysis, wavelet transforms, particle motion, hodograms. Includes general time-series tools, plotting, filtering, interactive display.
Author: Jonathan M. Lees [aut, cre], Jake Anderson [ctb], Leonard Lisapaly [ctb], Dave Harris [aut, cph]
Maintainer: Jonathan M. Lees <jonathan.lees@unc.edu>

Diff between RSEIS versions 4.2-0 dated 2024-02-25 and 4.2-4 dated 2024-09-12

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More information about RSEIS at CRAN
Permanent link

Package pomp updated to version 5.11 with previous version 5.10 dated 2024-07-01

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. [...truncated...]
Maintainer: Aaron A. King <kingaa@umich.edu>

Diff between pomp versions 5.10 dated 2024-07-01 and 5.11 dated 2024-09-12

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Permanent link

Package manynet updated to version 1.1.0 with previous version 1.0.5 dated 2024-08-30

Title: Many Ways to Make, Modify, Map, Mark, and Measure Myriad Networks
Description: Many tools for making, modifying, mapping, marking, measuring, and motifs and memberships of many different types of networks. All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, and on one-mode, two-mode (bipartite), and sometimes three-mode networks. The package includes functions for importing and exporting, creating and generating networks, modifying networks and node and tie attributes, and describing and visualizing networks with sensible defaults.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb] , Christian Steglich [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

Diff between manynet versions 1.0.5 dated 2024-08-30 and 1.1.0 dated 2024-09-12

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Package Luminescence updated to version 0.9.25 with previous version 0.9.24 dated 2024-06-07

Title: Comprehensive Luminescence Dating Data Analysis
Description: A collection of various R functions for the purpose of Luminescence dating data analysis. This includes, amongst others, data import, export, application of age models, curve deconvolution, sequence analysis and plotting of equivalent dose distributions.
Author: Sebastian Kreutzer [aut, trl, cre, dtc] , Christoph Burow [aut, trl, dtc] , Michael Dietze [aut] , Margret C. Fuchs [aut] , Christoph Schmidt [aut] , Manfred Fischer [aut, trl], Johannes Friedrich [aut] , Norbert Mercier [aut] , Rachel K. Smedley [ct [...truncated...]
Maintainer: Sebastian Kreutzer <maintainer_luminescence@r-luminescence.org>

Diff between Luminescence versions 0.9.24 dated 2024-06-07 and 0.9.25 dated 2024-09-12

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 Luminescence-0.9.25/Luminescence/man/calc_CentralDose.Rd                                 |    2 
 Luminescence-0.9.25/Luminescence/man/calc_CobbleDoseRate.Rd                              |    2 
 Luminescence-0.9.25/Luminescence/man/calc_CommonDose.Rd                                  |    2 
 Luminescence-0.9.25/Luminescence/man/calc_CosmicDoseRate.Rd                              |    2 
 Luminescence-0.9.25/Luminescence/man/calc_FadingCorr.Rd                                  |    2 
 Luminescence-0.9.25/Luminescence/man/calc_FastRatio.Rd                                   |   10 
 Luminescence-0.9.25/Luminescence/man/calc_FiniteMixture.Rd                               |    2 
 Luminescence-0.9.25/Luminescence/man/calc_FuchsLang2001.Rd                               |    4 
 Luminescence-0.9.25/Luminescence/man/calc_HomogeneityTest.Rd                             |    2 
 Luminescence-0.9.25/Luminescence/man/calc_Huntley2006.Rd                                 |    2 
 Luminescence-0.9.25/Luminescence/man/calc_IEU.Rd                                         |    2 
 Luminescence-0.9.25/Luminescence/man/calc_Kars2008.Rd                                    |    2 
 Luminescence-0.9.25/Luminescence/man/calc_Lamothe2003.Rd                                 |    4 
 Luminescence-0.9.25/Luminescence/man/calc_MaxDose.Rd                                     |    2 
 Luminescence-0.9.25/Luminescence/man/calc_MinDose.Rd                                     |   13 
 Luminescence-0.9.25/Luminescence/man/calc_OSLLxTxDecomposed.Rd                           |    2 
 Luminescence-0.9.25/Luminescence/man/calc_OSLLxTxRatio.Rd                                |    2 
 Luminescence-0.9.25/Luminescence/man/calc_SourceDoseRate.Rd                              |    2 
 Luminescence-0.9.25/Luminescence/man/calc_Statistics.Rd                                  |    2 
 Luminescence-0.9.25/Luminescence/man/calc_TLLxTxRatio.Rd                                 |    2 
 Luminescence-0.9.25/Luminescence/man/calc_ThermalLifetime.Rd                             |    2 
 Luminescence-0.9.25/Luminescence/man/calc_WodaFuchs2008.Rd                               |    8 
 Luminescence-0.9.25/Luminescence/man/calc_gSGC.Rd                                        |    4 
 Luminescence-0.9.25/Luminescence/man/calc_gSGC_feldspar.Rd                               |    2 
 Luminescence-0.9.25/Luminescence/man/combine_De_Dr.Rd                                    |    4 
 Luminescence-0.9.25/Luminescence/man/convert_Activity2Concentration.Rd                   |    2 
 Luminescence-0.9.25/Luminescence/man/convert_BIN2CSV.Rd                                  |    2 
 Luminescence-0.9.25/Luminescence/man/convert_Concentration2DoseRate.Rd                   |    2 
 Luminescence-0.9.25/Luminescence/man/convert_Daybreak2CSV.Rd                             |    4 
 Luminescence-0.9.25/Luminescence/man/convert_PSL2CSV.Rd                                  |    2 
 Luminescence-0.9.25/Luminescence/man/convert_RLum2Risoe.BINfileData.Rd                   |    2 
 Luminescence-0.9.25/Luminescence/man/convert_SG2MG.Rd                                    |    2 
 Luminescence-0.9.25/Luminescence/man/convert_Wavelength2Energy.Rd                        |    2 
 Luminescence-0.9.25/Luminescence/man/convert_XSYG2CSV.Rd                                 |    2 
 Luminescence-0.9.25/Luminescence/man/extract_IrradiationTimes.Rd                         |   12 
 Luminescence-0.9.25/Luminescence/man/extract_ROI.Rd                                      |    2 
 Luminescence-0.9.25/Luminescence/man/fit_CWCurve.Rd                                      |   15 
 Luminescence-0.9.25/Luminescence/man/fit_EmissionSpectra.Rd                              |    2 
 Luminescence-0.9.25/Luminescence/man/fit_LMCurve.Rd                                      |    2 
 Luminescence-0.9.25/Luminescence/man/fit_OSLLifeTimes.Rd                                 |    5 
 Luminescence-0.9.25/Luminescence/man/fit_SurfaceExposure.Rd                              |    2 
 Luminescence-0.9.25/Luminescence/man/fit_ThermalQuenching.Rd                             |    2 
 Luminescence-0.9.25/Luminescence/man/get_Layout.Rd                                       |    2 
 Luminescence-0.9.25/Luminescence/man/get_Quote.Rd                                        |    2 
 Luminescence-0.9.25/Luminescence/man/get_RLum.Rd                                         |    2 
 Luminescence-0.9.25/Luminescence/man/get_Risoe.BINfileData.Rd                            |    2 
 Luminescence-0.9.25/Luminescence/man/get_rightAnswer.Rd                                  |    2 
 Luminescence-0.9.25/Luminescence/man/import_Data.Rd                                      |    4 
 Luminescence-0.9.25/Luminescence/man/length_RLum.Rd                                      |    2 
 Luminescence-0.9.25/Luminescence/man/merge_RLum.Analysis.Rd                              |    6 
 Luminescence-0.9.25/Luminescence/man/merge_RLum.Data.Curve.Rd                            |    2 
 Luminescence-0.9.25/Luminescence/man/merge_RLum.Rd                                       |    6 
 Luminescence-0.9.25/Luminescence/man/merge_RLum.Results.Rd                               |    2 
 Luminescence-0.9.25/Luminescence/man/merge_Risoe.BINfileData.Rd                          |    2 
 Luminescence-0.9.25/Luminescence/man/methods_RLum.Rd                                     |    7 
 Luminescence-0.9.25/Luminescence/man/names_RLum.Rd                                       |    2 
 Luminescence-0.9.25/Luminescence/man/plot_AbanicoPlot.Rd                                 |   13 
 Luminescence-0.9.25/Luminescence/man/plot_DRCSummary.Rd                                  |    4 
 Luminescence-0.9.25/Luminescence/man/plot_DRTResults.Rd                                  |    2 
 Luminescence-0.9.25/Luminescence/man/plot_DetPlot.Rd                                     |    5 
 Luminescence-0.9.25/Luminescence/man/plot_FilterCombinations.Rd                          |    2 
 Luminescence-0.9.25/Luminescence/man/plot_GrowthCurve.Rd                                 |    9 
 Luminescence-0.9.25/Luminescence/man/plot_Histogram.Rd                                   |    2 
 Luminescence-0.9.25/Luminescence/man/plot_KDE.Rd                                         |    9 
 Luminescence-0.9.25/Luminescence/man/plot_NRt.Rd                                         |    6 
 Luminescence-0.9.25/Luminescence/man/plot_OSLAgeSummary.Rd                               |    2 
 Luminescence-0.9.25/Luminescence/man/plot_RLum.Analysis.Rd                               |    9 
 Luminescence-0.9.25/Luminescence/man/plot_RLum.Data.Curve.Rd                             |    8 
 Luminescence-0.9.25/Luminescence/man/plot_RLum.Data.Image.Rd                             |    2 
 Luminescence-0.9.25/Luminescence/man/plot_RLum.Data.Spectrum.Rd                          |    2 
 Luminescence-0.9.25/Luminescence/man/plot_RLum.Rd                                        |    2 
 Luminescence-0.9.25/Luminescence/man/plot_RLum.Results.Rd                                |    2 
 Luminescence-0.9.25/Luminescence/man/plot_ROI.Rd                                         |    2 
 Luminescence-0.9.25/Luminescence/man/plot_RadialPlot.Rd                                  |    7 
 Luminescence-0.9.25/Luminescence/man/plot_Risoe.BINfileData.Rd                           |    2 
 Luminescence-0.9.25/Luminescence/man/plot_ViolinPlot.Rd                                  |    9 
 Luminescence-0.9.25/Luminescence/man/read_BIN2R.Rd                                       |   10 
 Luminescence-0.9.25/Luminescence/man/read_Daybreak2R.Rd                                  |    2 
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 Luminescence-0.9.25/Luminescence/man/read_PSL2R.Rd                                       |   15 
 Luminescence-0.9.25/Luminescence/man/read_RF2R.Rd                                        |    2 
 Luminescence-0.9.25/Luminescence/man/read_SPE2R.Rd                                       |    8 
 Luminescence-0.9.25/Luminescence/man/read_TIFF2R.Rd                                      |    2 
 Luminescence-0.9.25/Luminescence/man/read_XSYG2R.Rd                                      |   12 
 Luminescence-0.9.25/Luminescence/man/replicate_RLum.Rd                                   |    2 
 Luminescence-0.9.25/Luminescence/man/report_RLum.Rd                                      |    2 
 Luminescence-0.9.25/Luminescence/man/sTeve.Rd                                            |    2 
 Luminescence-0.9.25/Luminescence/man/scale_GammaDose.Rd                                  |    6 
 Luminescence-0.9.25/Luminescence/man/set_RLum.Rd                                         |    2 
 Luminescence-0.9.25/Luminescence/man/set_Risoe.BINfileData.Rd                            |    2 
 Luminescence-0.9.25/Luminescence/man/smooth_RLum.Rd                                      |    2 
 Luminescence-0.9.25/Luminescence/man/structure_RLum.Rd                                   |    2 
 Luminescence-0.9.25/Luminescence/man/subset_SingleGrainData.Rd                           |    2 
 Luminescence-0.9.25/Luminescence/man/template_DRAC.Rd                                    |    2 
 Luminescence-0.9.25/Luminescence/man/trim_RLum.Data.Rd                                   |    2 
 Luminescence-0.9.25/Luminescence/man/tune_Data.Rd                                        |    2 
 Luminescence-0.9.25/Luminescence/man/use_DRAC.Rd                                         |    2 
 Luminescence-0.9.25/Luminescence/man/verify_SingleGrainData.Rd                           |   14 
 Luminescence-0.9.25/Luminescence/man/write_R2BIN.Rd                                      |   12 
 Luminescence-0.9.25/Luminescence/man/write_R2TIFF.Rd                                     |    2 
 Luminescence-0.9.25/Luminescence/man/write_RLum2CSV.Rd                                   |    2 
 Luminescence-0.9.25/Luminescence/tests/testthat/_data                                    |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_Analyse_SAROSLdata.R                |    5 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_CW2pX.R                             |    2 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_PSL2RisoeBINfiledata.R              |   17 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_RLum.Analysis-class.R               |  174 ++
 Luminescence-0.9.25/Luminescence/tests/testthat/test_RLum.Data.Curve.R                   |    1 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_RLum.Data.Image.R                   |    1 
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 Luminescence-0.9.25/Luminescence/tests/testthat/test_RisoeBINfileData-class.R            |   20 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_Second2Gray.R                       |   24 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_analyse_Al2O3C_CrossTalk.R          |   40 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_analyse_Al2O3C_ITC.R                |   54 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_analyse_Al2O3C_Measurement.R        |   84 -
 Luminescence-0.9.25/Luminescence/tests/testthat/test_analyse_FadingMeasurement.R         |   57 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_analyse_IRSAR.RF.R                  |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_analyse_SAR.CWOSL.R                 |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_analyse_SAR.TL.R                    |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_analyse_baSAR.R                     |  220 ++-
 Luminescence-0.9.25/Luminescence/tests/testthat/test_analyse_pIRIRSequence.R             |   59 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_analyse_portableOSL.R               |   72 -
 Luminescence-0.9.25/Luminescence/tests/testthat/test_apply_CosmicRayRemoval.R            |    8 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_apply_EfficiencyCorrection.R        |    7 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_as_latex_table.R                    |   37 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_bin_RLumData.R                      |    2 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_AliquotSize.R                  |   34 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_AverageDose.R                  |   32 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_CentralDose.R                  |   14 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_CobbleDoseRate.R               |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_CommonDose.R                   |   31 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_CosmicDoseRate.R               |   52 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_FadingCorr.R                   |   27 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_FastRatio.R                    |   67 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_FiniteMixture.R                |   30 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_FuchsLang2001.R                |   12 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_HomogeneityTest.R              |   14 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_Huntley2006.R                  |   78 -
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_IEU.R                          |   12 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_Lamothe2003.R                  |   59 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_MaxDose.R                      |    4 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_MinDose.R                      |   55 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_OSLLxTxDecomposed.R            |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_OSLLxTxRatio.R                 |    8 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_SourceDoseRate.R               |    3 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_Statistics.R                   |   19 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_TLLxTxRatio.R                  |    8 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_ThermalLifetime.R              |   26 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_WodaFuchs2008.R                |   50 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_gSGC.R                         |   85 -
 Luminescence-0.9.25/Luminescence/tests/testthat/test_calc_gSGC_feldspar.R                |   21 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_combine_De_Dr.R                     |   34 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_convert_Activity2Concentration.R    |   15 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_convert_Concentration2DoseRate.R    |    3 
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 Luminescence-0.9.25/Luminescence/tests/testthat/test_convert_PSL2CSV.R                   |    3 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_convert_RLum2Risoe.BINfileData.R    |   14 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_convert_SG2MG.R                     |   12 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_convert_Wavelength2Energy.R         |    8 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_convert_XSYG2CSV.R                  |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_extract_IrradiationTimes.R          |   50 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_extract_ROI.R                       |    2 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_fit_CWCurve.R                       |   67 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_fit_EmissionSpectra.R               |   42 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_fit_LMCurve.R                       |   83 -
 Luminescence-0.9.25/Luminescence/tests/testthat/test_fit_OSLLifeTimes.R                  |  102 +
 Luminescence-0.9.25/Luminescence/tests/testthat/test_fit_SurfaceExposure.R               |   74 -
 Luminescence-0.9.25/Luminescence/tests/testthat/test_fit_ThermalQuenching.R              |   13 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_get_Layout.R                        |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_get_RLum.R                          |   14 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_github.R                            |    5 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_import_Data.R                       |    8 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_internals.R                         |  121 +
 Luminescence-0.9.25/Luminescence/tests/testthat/test_merge_RLum.Analysis.R               |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_merge_RLum.Data.Curve.R             |only
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 Luminescence-0.9.25/Luminescence/tests/testthat/test_merge_Risoe.BINfileData.R           |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_methods_DRAC.R                      |   13 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_methods_S3.R                        |  158 +-
 Luminescence-0.9.25/Luminescence/tests/testthat/test_names_RLum.R                        |    1 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_AbanicoPlot.R                  |   89 +
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_DRCSummary.R                   |   57 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_DRTResults.R                   |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_DetPlot.R                      |   89 +
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_FilterCombinations.R           |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_Functions.R                    |   45 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_GrowthCurve.R                  |  147 +-
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_Histogram.R                    |only
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 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_OSLAgeSummary.R                |    5 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_RLum.Analysis.R                |   95 -
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_RLum.Data.Curve.R              |   11 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_RLum.Data.Image.R              |    7 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_RLum.Data.Spectrum.R           |   52 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_RLum.R                         |    1 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_RLum.Results.R                 |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_ROI.R                          |    1 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_RadialPlot.R                   |   95 +
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_Risoe.BINfileData.R            |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_plot_ViolinPlot.R                   |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_read_BIN2R.R                        |  211 +-
 Luminescence-0.9.25/Luminescence/tests/testthat/test_read_Daybreak2R.R                   |   75 -
 Luminescence-0.9.25/Luminescence/tests/testthat/test_read_HeliosOSL2R.R                  |only
 Luminescence-0.9.25/Luminescence/tests/testthat/test_read_PSL2R.R                        |   31 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_read_RF2R.R                         |   20 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_read_SPE2R.R                        |   69 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_read_TIFF2R.R                       |    1 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_read_XSYG2R.R                       |   76 -
 Luminescence-0.9.25/Luminescence/tests/testthat/test_replicate_RLum.R                    |    1 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_report_RLum.R                       |   17 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_scale_GammaDose.R                   |   12 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_smooth_RLum.R                       |    2 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_structure_RLum.R                    |    1 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_subset_RLum.R                       |   12 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_subset_SingleGrainData.R            |    1 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_template_DRAC.R                     |   20 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_trim_RLum.Data.R                    |   10 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_use_DRAC.R                          |   31 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_verify_SingleGrainData.R            |   49 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_write_R2BIN.R                       |   72 -
 Luminescence-0.9.25/Luminescence/tests/testthat/test_write_R2TIFF.R                      |    1 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_write_RLum2CSV.R                    |   27 
 Luminescence-0.9.25/Luminescence/tests/testthat/test_zzz.R                               |    7 
 375 files changed, 6085 insertions(+), 4646 deletions(-)

More information about Luminescence at CRAN
Permanent link

Package lares updated to version 5.2.9 with previous version 5.2.8 dated 2024-06-11

Title: Analytics & Machine Learning Sidekick
Description: Auxiliary package for better/faster analytics, visualization, data mining, and machine learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling, MMM, Exploratory, API, and Scrapper, it helps the analyst or data scientist to get quick and robust results, without the need of repetitive coding or advanced R programming skills.
Author: Bernardo Lares [aut, cre]
Maintainer: Bernardo Lares <laresbernardo@gmail.com>

Diff between lares versions 5.2.8 dated 2024-06-11 and 5.2.9 dated 2024-09-12

 DESCRIPTION                |   16 
 MD5                        |  514 +++----
 NAMESPACE                  | 1077 ++++++++--------
 R/apis.R                   |   68 -
 R/audio.R                  |  359 ++---
 R/cache.R                  |  326 ++--
 R/chatgpt.R                |  938 ++++++-------
 R/checks.R                 |  304 ++--
 R/clusters.R               |  694 +++++-----
 R/colour_palettes.R        |  394 ++---
 R/confidence.R             |  172 +-
 R/correlations.R           | 1116 ++++++++--------
 R/cran.R                   |  176 +-
 R/credentials.R            |  196 +-
 R/crosstab.R               |  202 +--
 R/currency.R               |  146 +-
 R/dalex_explainers.R       |  441 +++---
 R/dataframe_str.R          |  462 +++---
 R/datasets.R               |  160 +-
 R/dim_reduction.R          |  336 ++---
 R/distribution.R           |  950 +++++++-------
 R/dropbox.R                |  246 +--
 R/encoding.R               |   44 
 R/facebook.R               | 1528 +++++++++++-----------
 R/forecasting.R            |  710 +++++-----
 R/frequencies.R            | 1724 ++++++++++++-------------
 R/gemini.R                 |  166 +-
 R/geodata.R                |  524 +++----
 R/google_analytics.R       |  130 -
 R/google_sheets.R          |  258 +--
 R/google_trends.R          |  380 ++---
 R/hubspot.R                |  398 ++---
 R/hubspot_f1.R             |  502 +++----
 R/lares.R                  |  300 ++--
 R/lasso.R                  |  262 +--
 R/linkedin.R               |  114 -
 R/logo.R                   |   98 -
 R/mails.R                  |  190 +-
 R/maze.R                   |  669 ++++-----
 R/missings.R               |  260 +--
 R/model_functions.R        | 1954 ++++++++++++++---------------
 R/model_metrics.R          | 1232 +++++++++---------
 R/model_plots.R            | 2928 +++++++++++++++++++++----------------------
 R/model_predict.R          |  326 ++--
 R/model_preprocessing.R    |  490 +++----
 R/numble.R                 |   54 
 R/object_detection.R       |  120 -
 R/onehotencoding.R         | 1050 +++++++--------
 R/other_functions.R        | 2264 ++++++++++++++++-----------------
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More information about lares at CRAN
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Package gam updated to version 1.22-5 with previous version 1.22-4 dated 2024-07-18

Title: Generalized Additive Models
Description: Functions for fitting and working with generalized additive models, as described in chapter 7 of "Statistical Models in S" (Chambers and Hastie (eds), 1991), and "Generalized Additive Models" (Hastie and Tibshirani, 1990).
Author: Trevor Hastie [aut, cre], Balasubramanian Narasimhan [ctb]
Maintainer: Trevor Hastie <hastie@stanford.edu>

Diff between gam versions 1.22-4 dated 2024-07-18 and 1.22-5 dated 2024-09-12

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Package eAnalytics updated to version 0.3.1 with previous version 0.3 dated 2023-06-26

Title: Dynamic Web-Based Analytics for the Energy Industry
Description: A 'Shiny' web application for energy industry analytics. Take an overview of the industry, measure Key Performance Indicators, identify changes in the industry over time, and discover new relationships in the data.
Author: Paul Govan [aut, cre, cph]
Maintainer: Paul Govan <paul.govan2@gmail.com>

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Package BAMMtools updated to version 2.1.12 with previous version 2.1.11 dated 2023-12-19

Title: Analysis and Visualization of Macroevolutionary Dynamics on Phylogenetic Trees
Description: Provides functions for analyzing and visualizing complex macroevolutionary dynamics on phylogenetic trees. It is a companion package to the command line program BAMM (Bayesian Analysis of Macroevolutionary Mixtures) and is entirely oriented towards the analysis, interpretation, and visualization of evolutionary rates. Functionality includes visualization of rate shifts on phylogenies, estimating evolutionary rates through time, comparing posterior distributions of evolutionary rates across clades, comparing diversification models using Bayes factors, and more.
Author: Dan Rabosky [aut], Michael Grundler [aut], Pascal Title [aut, cre] , Carlos Anderson [aut], Jeff Shi [aut], Joseph Brown [aut], Huateng Huang [aut], Jon Mitchell [aut]
Maintainer: Pascal Title <ptitle@umich.edu>

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Permanent link

Package ecorest updated to version 2.0.0 with previous version 1.0.0 dated 2020-06-26

Title: Conducts Analyses Informing Ecosystem Restoration Decisions
Description: Three sets of data and functions for informing ecosystem restoration decisions, particularly in the context of the U.S. Army Corps of Engineers. First, model parameters are compiled as a data set and associated metadata for over 300 habitat suitability models developed by the U.S. Fish and Wildlife Service (USFWS 1980, <https://www.fws.gov/policy-library/870fw1>). Second, functions for conducting habitat suitability analyses both for the models described above as well as generic user-specified model parameterizations. Third, a suite of decision support tools for conducting cost-effectiveness and incremental cost analyses (Robinson et al. 1995, IWR Report 95-R-1, U.S. Army Corps of Engineers).
Author: S. Kyle McKay [aut, cre] , Darixa D. Hernandez-Abrams [aut], Kiara C. Cushway [aut]
Maintainer: S. Kyle McKay <kyle.mckay@usace.army.mil>

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Package csranks updated to version 1.2.3 with previous version 1.2.2 dated 2024-01-24

Title: Statistical Tools for Ranks
Description: Account for uncertainty when working with ranks. Estimate standard errors consistently in linear regression with ranked variables. Construct confidence sets of various kinds for positions of populations in a ranking based on values of a certain feature and their estimation errors. Theory based on Mogstad, Romano, Shaikh, and Wilhelm (2023)<doi:10.1093/restud/rdad006> and Chetverikov and Wilhelm (2023) <doi:10.48550/arXiv.2310.15512>.
Author: Daniel Wilhelm [aut, cre], Pawel Morgen [aut]
Maintainer: Daniel Wilhelm <d.wilhelm@lmu.de>

Diff between csranks versions 1.2.2 dated 2024-01-24 and 1.2.3 dated 2024-09-12

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More information about csranks at CRAN
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Package Colossus updated to version 1.1.3.1 with previous version 1.1.3 dated 2024-09-06

Title: "Risk Model Regression and Analysis with Complex Non-Linear Models"
Description: Performs survival analysis using general non-linear models. Risk models can be the sum or product of terms. Each term is the product of exponential/linear functions of covariates. Additionally sub-terms can be defined as a sum of exponential, linear threshold, and step functions. Cox Proportional hazards <https://en.wikipedia.org/wiki/Proportional_hazards_model>, Poisson <https://en.wikipedia.org/wiki/Poisson_regression>, and Fine-Grey competing risks <https://www.publichealth.columbia.edu/research/population-health-methods/competing-risk-analysis> regression are supported. This work was sponsored by NASA Grant 80NSSC19M0161 through a subcontract from the National Council on Radiation Protection and Measurements (NCRP). The computing for this project was performed on the Beocat Research Cluster at Kansas State University, which is funded in part by NSF grants CNS-1006860, EPS-1006860, EPS-0919443, ACI-1440548, CHE-1726332, and NIH P20GM113109.
Author: Eric Giunta [aut, cre] , Amir Bahadori [ctb] , Dan Andresen [ctb], Linda Walsh [ctb] , Benjamin French [ctb] , Lawrence Dauer [ctb], John Boice Jr [ctb] , Kansas State University [cph], NASA [fnd], NCRP [fnd], NRC [fnd]
Maintainer: Eric Giunta <egiunta@ksu.edu>

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Package caretEnsemble updated to version 4.0.1 with previous version 4.0.0 dated 2024-08-17

Title: Ensembles of Caret Models
Description: Functions for creating ensembles of caret models: caretList() and caretStack(). caretList() is a convenience function for fitting multiple caret::train() models to the same dataset. caretStack() will make linear or non-linear combinations of these models, using a caret::train() model as a meta-model.
Author: Zachary A. Deane-Mayer [aut, cre, cph], Jared E. Knowles [ctb], Anton Lopez [ctb]
Maintainer: Zachary A. Deane-Mayer <zach.mayer@gmail.com>

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Package maldipickr updated to version 1.3.1 with previous version 1.3.0 dated 2023-12-14

Title: Dereplicate and Cherry-Pick Mass Spectrometry Spectra
Description: Convenient wrapper functions for the analysis of matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) spectra data in order to select only representative spectra (also called cherry-pick). The package covers the preprocessing and dereplication steps (based on Strejcek, Smrhova, Junkova and Uhlik (2018) <doi:10.3389/fmicb.2018.01294>) needed to cluster MALDI-TOF spectra before the final cherry-picking step. It enables the easy exclusion of spectra and/or clusters to accommodate complex cherry-picking strategies. Alternatively, cherry-picking using taxonomic identification MALDI-TOF data is made easy with functions to import inconsistently formatted reports.
Author: Charlie Pauvert [aut, cre, cph] , David Wylensek [ctb] , Selina Nuechtern [ctb], Thomas Clavel [ctb, fnd, cph]
Maintainer: Charlie Pauvert <cpauvert@ukaachen.de>

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New package wither with initial version 0.1.0
Package: wither
Title: Temporarily Change Project Root
Version: 0.1.0
Description: Lets you temporarily execute an expression or a local block with a different here() root in the 'here' package. This is useful for sourcing code in other projects which expect the root directory of here() to be the project directory of those projects. This may be the case with git submodules for example.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: devtools, testthat (>= 3.0.0)
Imports: fs, here, withr
URL: https://github.com/torbjorn/wither
BugReports: https://github.com/torbjorn/wither/issues
NeedsCompilation: no
Packaged: 2024-09-10 10:33:15 UTC; tlindahl
Author: Torbjoern Lindahl [aut, cre, cph] , Anja Minsaas [aut]
Maintainer: Torbjoern Lindahl <torbjorn.lindahl@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-12 17:40:02 UTC

More information about wither at CRAN
Permanent link

New package wdi2 with initial version 0.1.0
Package: wdi2
Title: Download World Development Indicators from the World Bank Indicators API
Version: 0.1.0
Description: A modern, flexible interface for accessing the World Bank’s World Development Indicators (WDI) API <https://datahelpdesk.worldbank.org/knowledgebase/articles/889392-about-the-indicators-api-documentation>. Similar to the existing 'WDI' package, 'wdi2' allows users to download, process, and analyze indicator data for multiple countries and years. However, 'wdi2' differs by relying on 'httr2' for multi-page request and error handling, providing support for downloading multiple indicators with a single function call, using progress bars to keep users informed about the data processing, and returning the processed data in a tidy data format in line with Wickham (2014) <doi:10.18637/jss.v059.i10>.
License: MIT + file LICENSE
URL: https://github.com/tidy-intelligence/r-wdi2
BugReports: https://github.com/tidy-intelligence/r-wdi2/issues
Depends: R (>= 4.1)
Imports: cli, dplyr (>= 1.0.0), httr2 (>= 1.0.0), purrr (>= 1.0.0), tibble, tidyr (>= 1.0.0)
Suggests: knitr, rmarkdown, testthat (>= 3.2.0)
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-10 11:44:55 UTC; krise
Author: Christoph Scheuch [aut, cre]
Maintainer: Christoph Scheuch <christoph.scheuch@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-12 17:50:02 UTC

More information about wdi2 at CRAN
Permanent link

Package vglmer updated to version 1.0.5 with previous version 1.0.3 dated 2022-10-27

Title: Variational Inference for Hierarchical Generalized Linear Models
Description: Estimates hierarchical models using mean-field variational Bayes. At present, it can estimate logistic, linear, and negative binomial models. It can accommodate models with an arbitrary number of random effects and requires no integration to estimate. It also provides the ability to improve the quality of the approximation using marginal augmentation. Goplerud (2022) <doi:10.1214/21-BA1266> and Goplerud (2024) <doi:10.1017/S0003055423000035> provide details on the variational algorithms.
Author: Max Goplerud [aut, cre]
Maintainer: Max Goplerud <mgoplerud@austin.utexas.edu>

Diff between vglmer versions 1.0.3 dated 2022-10-27 and 1.0.5 dated 2024-09-12

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Package trekcolors updated to version 0.2.0 with previous version 0.1.3 dated 2021-06-01

Title: Star Trek Color Palettes
Description: Provides a dataset of predefined color palettes based on the Star Trek science fiction series, associated color palette functions, and additional functions for generating customized palettes that are on theme. The package also offers functions for applying the palettes to plots made using the 'ggplot2' package.
Author: Matthew Leonawicz [aut, cre]
Maintainer: Matthew Leonawicz <rpkgs@pm.me>

Diff between trekcolors versions 0.1.3 dated 2021-06-01 and 0.2.0 dated 2024-09-12

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Package naaccr updated to version 3.0.1 with previous version 2.0.2 dated 2022-11-23

Title: Read Cancer Records in the NAACCR Format
Description: Functions for reading cancer record files which follow a format defined by the North American Association of Central Cancer Registries (NAACCR).
Author: Nathan Werth [aut, cre], Pennsylvania Department of Health [cph], North American Association of Cancer Registries [cph], World Health Organization [cph], United States Centers for Disease Control and Prevention [cph], United States Bureau of the Cens [...truncated...]
Maintainer: Nathan Werth <nwerth@pa.gov>

Diff between naaccr versions 2.0.2 dated 2022-11-23 and 3.0.1 dated 2024-09-12

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Package biostats101 updated to version 0.1.1 with previous version 0.1.0 dated 2024-09-04

Title: Practical Functions for Biostatistics Beginners
Description: A set of user-friendly functions designed to fill gaps in existing introductory biostatistics R tools, making it easier for newcomers to perform basic biostatistical analyses without needing advanced programming skills. The methods implemented in this package are based on the works: Connor (1987) <doi:10.2307/2531961> Fleiss, Levin, & Paik (2013, ISBN:978-1-118-62561-3) Levin & Chen (1999) <doi:10.1080/00031305.1999.10474431> McNemar (1947) <doi:10.1007/BF02295996>.
Author: Marina Mautner Wizentier [aut, cre] , Melody S. Goodman [aut] , Jemar R. Bather [aut]
Maintainer: Marina Mautner Wizentier <mm12025@nyu.edu>

Diff between biostats101 versions 0.1.0 dated 2024-09-04 and 0.1.1 dated 2024-09-12

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New package tidycountries with initial version 0.0.1
Package: tidycountries
Title: Access and Manipulate Comprehensive Country Level Data in Tidy Format
Version: 0.0.1
Description: A comprehensive and user-friendly interface for accessing, manipulating, and analyzing country-level data from around the world. It allows users to retrieve detailed information on countries, including names, regions, continents, populations, currencies, calling codes, and more, all in a tidy data format. The package is designed to work seamlessly within the 'tidyverse' ecosystem, making it easy to filter, arrange, and visualize country-level data in R.
License: MIT + file LICENSE
URL: https://github.com/denironyx/tidycountries
BugReports: https://github.com/denironyx/tidycountries/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: dplyr, stringr
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2024-09-10 07:00:16 UTC; Dee
Author: Dennis Irorere [aut, cre, cph]
Maintainer: Dennis Irorere <denironyx@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-12 17:30:02 UTC

More information about tidycountries at CRAN
Permanent link

New package surreal with initial version 0.0.1
Package: surreal
Title: Create Datasets with Hidden Images in Residual Plots
Version: 0.0.1
Description: Implements the "Residual (Sur)Realism" algorithm described by Stefanski (2007) <doi:10.1198/000313007X190079> to generate datasets that reveal hidden images or messages in their residual plots. It offers both predefined datasets and tools to embed custom text or images into residual structures. Allowing users to create intriguing visual demonstrations for teaching model diagnostics.
License: GPL (>= 3)
Depends: R (>= 4.3.0)
Encoding: UTF-8
URL: https://github.com/coatless-rpkg/surreal, https://r-pkg.thecoatlessprofessor.com/surreal/
BugReports: https://github.com/coatless-rpkg/surreal/issues
LazyData: true
Imports: png
NeedsCompilation: no
Packaged: 2024-09-10 04:29:43 UTC; ronin
Author: James Joseph Balamuta [aut, cre, cph]
Maintainer: James Joseph Balamuta <james.balamuta@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-12 17:20:02 UTC

More information about surreal at CRAN
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Package SSplots updated to version 0.1.2 with previous version 0.1.1 dated 2023-05-08

Title: Stock Status Plots (SSPs)
Description: Pauly et al. (2008) <http://legacy.seaaroundus.s3.amazonaws.com/doc/Researcher+Publications/dpauly/PDF/2008/Books%26Chapters/FisheriesInLargeMarineEcosystems.pdf> created (and coined the name) 'Stock Status Plots' for a UNEP compendium on Large Marine Ecosystems(LMEs, Sherman and Hempel (2009)<https://marineinfo.org/imis?module=ref&refid=142061&printversion=1&dropIMIStitle=1>). Stock status plots are bivariate graphs summarizing the status (e.g., developing, fully exploited, overexploited, etc.), through time, of the multispecies fisheries of a fished area or ecosystem. This package contains three functions to generate stock status plots viz., SSplots_pauly() (as per the criteria proposed by Pauly et al.,2008), SSplots_kleisner() (as per the criteria proposed by Kleisner and Pauly (2011) <http://www.ecomarres.com/downloads/regional.pdf> and Kleisner et al. (2013) <doi:10.1111/j.1467-2979.2012.00469.x>)and SSplots_EPI() (as per the criteria proposed b [...truncated...]
Author: Eldho Varghese [aut, cre], J Jayasankar [aut], Sreepriya V [aut], Reshma Gills [ctb], Ashutosh Dalal [ctb]
Maintainer: Eldho Varghese <eldhoiasri@gmail.com>

Diff between SSplots versions 0.1.1 dated 2023-05-08 and 0.1.2 dated 2024-09-12

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New package splusTimeDate with initial version 2.5.8
Package: splusTimeDate
Version: 2.5.8
Title: Times and Dates from 'S-PLUS'
Depends: R (>= 2.12.0), methods, stats
Description: A collection of classes and methods for working with times and dates. The code was originally available in 'S-PLUS'.
License: BSD_3_clause + file LICENSE
URL: https://github.com/spkaluzny/splusTimeDate
BugReports: https://github.com/spkaluzny/splusTimeDate/issues
NeedsCompilation: yes
Packaged: 2024-09-09 23:30:48 UTC; spk
Author: Stephen Kaluzny [aut, cre], TIBCO Software Inc. [aut, cph]
Maintainer: Stephen Kaluzny <spkaluzny@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-12 17:20:05 UTC

More information about splusTimeDate at CRAN
Permanent link

Package ps updated to version 1.8.0 with previous version 1.7.7 dated 2024-07-02

Title: List, Query, Manipulate System Processes
Description: List, query and manipulate all system processes, on 'Windows', 'Linux' and 'macOS'.
Author: Jay Loden [aut], Dave Daeschler [aut], Giampaolo Rodola' [aut], Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package pkgdepends updated to version 0.8.0 with previous version 0.7.2 dated 2024-03-17

Title: Package Dependency Resolution and Downloads
Description: Find recursive dependencies of 'R' packages from various sources. Solve the dependencies to obtain a consistent set of packages to install. Download packages, and install them. It supports packages on 'CRAN', 'Bioconductor' and other 'CRAN-like' repositories, 'GitHub', package 'URLs', and local package trees and files. It caches metadata and package files via the 'pkgcache' package, and performs all 'HTTP' requests, downloads, builds and installations in parallel. 'pkgdepends' is the workhorse of the 'pak' package.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package pkgcache updated to version 2.2.3 with previous version 2.2.2 dated 2024-04-04

Title: Cache 'CRAN'-Like Metadata and R Packages
Description: Metadata and package cache for CRAN-like repositories. This is a utility package to be used by package management tools that want to take advantage of caching.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between pkgcache versions 2.2.2 dated 2024-04-04 and 2.2.3 dated 2024-09-12

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Package pcalg updated to version 2.7-12 with previous version 2.7-11 dated 2024-02-12

Title: Methods for Graphical Models and Causal Inference
Description: Functions for causal structure learning and causal inference using graphical models. The main algorithms for causal structure learning are PC (for observational data without hidden variables), FCI and RFCI (for observational data with hidden variables), and GIES (for a mix of data from observational studies (i.e. observational data) and data from experiments involving interventions (i.e. interventional data) without hidden variables). For causal inference the IDA algorithm, the Generalized Backdoor Criterion (GBC), the Generalized Adjustment Criterion (GAC) and some related functions are implemented. Functions for incorporating background knowledge are provided.
Author: Markus Kalisch [aut, cre], Alain Hauser [aut], Martin Maechler [aut], Diego Colombo [ctb], Doris Entner [ctb], Patrik Hoyer [ctb], Antti Hyttinen [ctb], Jonas Peters [ctb], Nicoletta Andri [ctb], Emilija Perkovic [ctb], Preetam Nandy [ctb], Philipp R [...truncated...]
Maintainer: Markus Kalisch <kalisch@stat.math.ethz.ch>

Diff between pcalg versions 2.7-11 dated 2024-02-12 and 2.7-12 dated 2024-09-12

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New package noegletalR with initial version 0.2.1
Package: noegletalR
Title: Tidy Tibbles of Noegletal
Version: 0.2.1
Description: Work with data from <https://noegletal.dk> in a tidy manner. Tidy up previously downloaded data or retrieve new data directly from the comfort of R. You can also browse an up-to-date list of available data, including thorough variable descriptions.
License: MIT + file LICENSE
Imports: dplyr, httr, readr, rlang, rvest, stringr, tibble, tidyr
Encoding: UTF-8
URL: https://github.com/FrLars21/noegletalR
BugReports: https://github.com/FrLars21/noegletalR/issues
NeedsCompilation: no
Packaged: 2024-09-10 09:25:03 UTC; frederik
Author: Frederik Larsen [aut, cre, cph]
Maintainer: Frederik Larsen <frlars21@student.aau.dk>
Repository: CRAN
Date/Publication: 2024-09-12 17:40:34 UTC

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New package MRG with initial version 0.2.14
Package: MRG
Title: Create Non-Confidential Multi-Resolution Grids
Version: 0.2.14
Maintainer: Jon Olav Skoien <jon.skoien@gmail.com>
Imports: magrittr, parallel, terra, sf, stars, plyr, dplyr, rlang, sjmisc, vardpoor, purrr, tidyr, tidyselect, methods
Suggests: ggplot2, patchwork, viridis, knitr, rmarkdown, giscoR, bookdown, units, ggforce, kableExtra
Description: Functionality for creating gridded data, respecting the confidentiality rules, such as a minimum number of units and dominance by one or more units in the grid cell. The functions also include the possibility for contextual suppression of data.
License: GPL (>= 3)
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Depends: R (>= 3.5.0)
LazyData: true
Packaged: 2024-09-10 07:39:55 UTC; skoiejo
Author: Jon Olav Skoien [aut, cre], Nicolas Lampach [aut]
Repository: CRAN
Date/Publication: 2024-09-12 17:40:59 UTC

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Package lpSolve updated to version 5.6.21 with previous version 5.6.20 dated 2023-12-10

Title: Interface to 'Lp_solve' v. 5.5 to Solve Linear/Integer Programs
Description: Lp_solve is freely available (under LGPL 2) software for solving linear, integer and mixed integer programs. In this implementation we supply a "wrapper" function in C and some R functions that solve general linear/integer problems, assignment problems, and transportation problems. This version calls lp_solve version 5.5.
Author: Gabor Csardi [cre], Michel Berkelaar [aut]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between lpSolve versions 5.6.20 dated 2023-12-10 and 5.6.21 dated 2024-09-12

 DESCRIPTION     |   15 ++++++++++-----
 MD5             |    7 ++++---
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New package LPDynR with initial version 1.0.5
Package: LPDynR
Title: Land Productivity Dynamics Indicator
Version: 1.0.5
Description: It uses 'phenological' and productivity-related variables derived from time series of vegetation indexes, such as the Normalized Difference Vegetation Index, to assess ecosystem dynamics and change, which eventually might drive to land degradation. The final result of the Land Productivity Dynamics indicator is a categorical map with 5 classes of land productivity dynamics, ranging from declining to increasing productivity. See www.sciencedirect.com/science/article/pii/S1470160X21010517/ for a description of the methods used in the package to calculate the indicator.
Depends: R (>= 3.6.0)
Imports: stats, dplyr, data.table, virtualspecies, magrittr, terra
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/xavi-rp/LPDynR
BugReports: https://github.com/xavi-rp/LPDynR/issues
NeedsCompilation: no
Packaged: 2024-09-10 10:36:06 UTC; xavi_rp
Author: Xavier Rotllan-Puig [aut, cre], Eva Ivits [aut], Michael Cherlet [aut]
Maintainer: Xavier Rotllan-Puig <xavier.rotllan.puig@aster-projects.cat>
Repository: CRAN
Date/Publication: 2024-09-12 17:41:07 UTC

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Package LocalCop updated to version 0.0.2 with previous version 0.0.1 dated 2024-03-21

Title: Local Likelihood Inference for Conditional Copula Models
Description: Implements a local likelihood estimator for the dependence parameter in bivariate conditional copula models. Copula family and local likelihood bandwidth parameters are selected by leave-one-out cross-validation. The models are implemented in 'TMB', meaning that the local score function is efficiently calculated via automated differentiation (AD), such that quasi-Newton algorithms may be used for parameter estimation.
Author: Elif Fidan Acar [aut], Martin Lysy [aut, cre], Alan Kuchinsky [ctb]
Maintainer: Martin Lysy <mlysy@uwaterloo.ca>

Diff between LocalCop versions 0.0.1 dated 2024-03-21 and 0.0.2 dated 2024-09-12

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