Fri, 02 Dec 2022

Package salso updated to version 0.3.27 with previous version 0.3.0 dated 2021-12-06

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], The authors of the dependency Rust crates [ctb]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

Diff between salso versions 0.3.0 dated 2021-12-06 and 0.3.27 dated 2022-12-02

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Package MACER updated to version 0.2.1 with previous version 0.2.0 dated 2022-10-04

Title: Molecular Acquisition, Cleaning, and Evaluation in R 'MACER'
Description: To assist biological researchers in assembling taxonomically and marker focused molecular sequence data sets. 'MACER' accepts a list of genera as a user input and uses NCBI-GenBank and BOLD as resources to download and assemble molecular sequence datasets. These datasets are then assembled by marker, aligned, trimmed, and cleaned. The use of this package allows the publication of specific parameters to ensure reproducibility. The 'MACER' package has four core functions and an example run through using all of these functions can be found in the associated repository <https://github.com/rgyoung6/MACER_example>.
Author: Robert G Young [aut, cre, cph] , Rekkab Gill [aut], Daniel Gillis [aut], Robert H Hanner [aut, cph]
Maintainer: Robert G Young <rgyoung6@gmail.com>

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Package soilDB updated to version 2.7.6 with previous version 2.7.5 dated 2022-10-18

Title: Soil Database Interface
Description: A collection of functions for reading data from USDA-NCSS soil databases.
Author: Dylan Beaudette [aut], Jay Skovlin [aut], Stephen Roecker [aut], Andrew Brown [aut, cre]
Maintainer: Andrew Brown <andrew.g.brown@usda.gov>

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Package optimizeR updated to version 0.2.0 with previous version 0.1.1 dated 2022-09-02

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

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Package statgenMPP updated to version 1.0.2 with previous version 1.0.1.1 dated 2022-08-24

Title: QTL Mapping for Multi Parent Populations
Description: For Multi Parent Populations (MPP) Identity By Descend (IBD) probabilities are computed using Hidden Markov Models. These probabilities are then used in a mixed model approach for QTL Mapping as described in Li et al. (<doi:10.1007/s00122-021-03919-7>).
Author: Wenhao Li [aut] , Martin Boer [aut] , Bart-Jan van Rossum [aut, cre] , Fred van Eeuwijk [ctb]
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>

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Package robustlmm updated to version 3.1-1 with previous version 3.0-4 dated 2022-09-17

Title: Robust Linear Mixed Effects Models
Description: Implements the Robust Scoring Equations estimator to fit linear mixed effects models robustly. Robustness is achieved by modification of the scoring equations combined with the Design Adaptive Scale approach.
Author: Manuel Koller
Maintainer: Manuel Koller <kollerma@proton.me>

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Package DecomposeR updated to version 1.0.5 with previous version 1.0.4 dated 2021-07-06

Title: Empirical Mode Decomposition for Cyclostratigraphy
Description: Tools to apply Ensemble Empirical Mode Decomposition (EEMD) for cyclostratigraphy purposes. Mainly: a new algorithm, extricate, that performs EEMD in seconds, a linear interpolation algorithm using the greatest rational common divisor of depth or time, different algorithms to compute instantaneous amplitude, frequency and ratios of frequencies, and functions to verify and visualise the outputs. The functions were developed during the CRASH project (Checking the Reproducibility of Astrochronology in the Hauterivian). When using for publication please cite Wouters, S., Da Silva, A.C. Crucifix, M., Sinnesael, M., Zivanovic, M., Boulvain, F., Devleeschouwer, X., 2019, "Litholog generation with the 'StratigrapheR' package and signal decomposition for cyclostratigraphic purposes". Geophysical Research Abstracts Vol. 21, EGU2019-5520, 2019, EGU General Assembly 2019. <http://hdl.handle.net/2268/234402>.
Author: Sebastien Wouters [aut, cre]
Maintainer: Sebastien Wouters <wouterseb@gmail.com>

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Package bizicount updated to version 1.3.0 with previous version 1.2.0 dated 2022-08-14

Title: Bivariate Zero-Inflated Count Models Using Copulas
Description: Maximum likelihood estimation of copula-based zero-inflated (and non-inflated) Poisson and negative binomial count models. Supports Frank and Gaussian copulas. Allows for mixed margins (e.g., one margin Poisson, the other zero-inflated negative binomial), and several marginal link functions. Built-in methods for publication-quality tables using 'texreg', post-estimation diagnostics using 'DHARMa', and testing for marginal zero-modification via <doi:10.1177/0962280217749991>. For information on copula regression for count data, see Genest and Nešlehová (2007) <doi:10.1017/S0515036100014963> as well as Nikoloulopoulos (2013) <doi:10.1007/978-3-642-35407-6_11>. For information on zero-inflated count regression generally, see Lambert (1992) <https:www.jstor.org/stable/1269547?origin=crossref>. The author acknowledges support by NSF DMS-1925119 and DMS-212324.
Author: John Niehaus [aut, cre]
Maintainer: John Niehaus <jniehaus2257@gmail.com>

Diff between bizicount versions 1.2.0 dated 2022-08-14 and 1.3.0 dated 2022-12-02

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Package gimme updated to version 0.7-9 with previous version 0.7-8 dated 2022-08-09

Title: Group Iterative Multiple Model Estimation
Description: Data-driven approach for arriving at person-specific time series models. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. See Gates & Molenaar (2012) <doi:10.1016/j.neuroimage.2012.06.026>.
Author: Stephanie Lane [aut, trl], Kathleen Gates [aut, cre, ccp], Zachary Fisher [aut], Cara Arizmendi [aut], Peter Molenaar [aut, ccp], Michael Hallquist [ctb], Hallie Pike [ctb], Teague Henry [ctb], Kelly Duffy [ctb], Lan Luo [ctb], Adriene Beltz [csp], A [...truncated...]
Maintainer: Kathleen M Gates <gateskm@email.unc.edu>

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Package naijR updated to version 0.5.1 with previous version 0.5.0 dated 2022-09-30

Title: Operations to Ease Data Analyses Specific to Nigeria
Description: A set of convenience functions as well as geographical/political data about Nigeria, aimed at simplifying work with data and information that are specific to the country.
Author: Victor Ordu [aut, cre]
Maintainer: Victor Ordu <victorordu@outlook.com>

Diff between naijR versions 0.5.0 dated 2022-09-30 and 0.5.1 dated 2022-12-02

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Package unifir updated to version 0.2.3 with previous version 0.2.2 dated 2022-08-11

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

Diff between unifir versions 0.2.2 dated 2022-08-11 and 0.2.3 dated 2022-12-02

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Package scapGNN updated to version 0.1.3 with previous version 0.1.2 dated 2022-11-23

Title: Graph Neural Network-Based Framework for Single Cell Active Pathways and Gene Modules Analysis
Description: It is a single cell active pathway analysis tool based on the graph neural network (F. Scarselli (2009) <doi:10.1109/TNN.2008.2005605>; Thomas N. Kipf (2017) <arXiv:1609.02907v4>) to construct the gene-cell association network, infer pathway activity scores from different single cell modalities data, integrate multiple modality data on the same cells into one pathway activity score matrix, identify cell phenotype activated gene modules and parse association networks of gene modules under multiple cell phenotype. In addition, abundant visualization programs are provided to display the results.
Author: Xudong Han [aut, cre, cph], Xujiang Guo [fnd]
Maintainer: Xudong Han <hanxd1217@163.com>

Diff between scapGNN versions 0.1.2 dated 2022-11-23 and 0.1.3 dated 2022-12-02

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Package biogrowth updated to version 1.0.1 with previous version 1.0.0-3 dated 2022-08-28

Title: Modelling of Population Growth
Description: Modelling of population growth under static and dynamic environmental conditions. Includes functions for model fitting and making prediction under isothermal and dynamic conditions. The methods (algorithms & models) are based on predictive microbiology (See Perez-Rodriguez and Valero (2012, ISBN:978-1-4614-5519-6)).
Author: Alberto Garre [aut, cre] , Jeroen Koomen [aut], Heidy den Besten [aut], Marcel Zwietering [aut]
Maintainer: Alberto Garre <garre.alberto@gmail.com>

Diff between biogrowth versions 1.0.0-3 dated 2022-08-28 and 1.0.1 dated 2022-12-02

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New package POMADE with initial version 0.1.0
Package: POMADE
Title: Power for Meta-Analysis of Dependent Effects
Version: 0.1.0
BugReports: https://github.com/MikkelVembye/POMADE/issues
Description: Provides functions to compute and plot power levels, minimum detectable effect sizes, and minimum required sample sizes for the test of the overall average effect size in meta-analysis of dependent effect sizes.
Depends: R (>= 4.1.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: ggplot2, dplyr, magrittr, purrr, future, furrr, stats, stringr, utils, tidyr, tibble
Suggests: covr, roxygen2, testthat (>= 3.0.0)
Language: en-US
URL: https://mikkelvembye.github.io/POMADE/
NeedsCompilation: no
Packaged: 2022-12-01 18:16:09 UTC; B199526
Author: Mikkel H. Vembye [aut, cre] , James E. Pustejovsky [aut]
Maintainer: Mikkel H. Vembye <mikkel.vembye@gmail.com>
Repository: CRAN
Date/Publication: 2022-12-02 16:20:13 UTC

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New package PhaseType with initial version 0.2.0
Package: PhaseType
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.
URL: https://www.louisaslett.com/PhaseType/, https://github.com/louisaslett/PhaseType
BugReports: https://github.com/louisaslett/PhaseType/issues
Version: 0.2.0
Maintainer: Louis Aslett <louis.aslett@durham.ac.uk>
Copyright: The code in src/arms.c is slightly modified based on the research paper implementation written by Wally Gilks. All other code in all other files were written by the maintainer.
Imports: coda, ggplot2, reshape
Suggests: actuar
License: GPL-2 | GPL-3
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2022-12-01 16:29:39 UTC; louis
Author: Louis Aslett [aut, cre], Wally Gilks [ctb]
Repository: CRAN
Date/Publication: 2022-12-02 16:10:11 UTC

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New package netdiffuseR with initial version 1.22.5
Package: netdiffuseR
Title: Analysis of Diffusion and Contagion Processes on Networks
Version: 1.22.5
Description: Empirical statistical analysis, visualization and simulation of diffusion and contagion processes on networks. The package implements algorithms for calculating network diffusion statistics such as transmission rate, hazard rates, exposure models, network threshold levels, infectiousness (contagion), and susceptibility. The package is inspired by work published in Valente, et al., (2015) <DOI:10.1016/j.socscimed.2015.10.001>; Valente (1995) <ISBN: 9781881303213>, Myers (2000) <DOI:10.1086/303110>, Iyengar and others (2011) <DOI:10.1287/mksc.1100.0566>, Burt (1987) <DOI:10.1086/228667>; among others.
Depends: R (>= 3.1.1)
License: MIT + file LICENSE
LazyData: true
Imports: Rcpp (>= 0.12.1), sna, network, networkDynamic, Matrix, MASS, MatchIt, SparseM, methods, grDevices, graphics, stats, utils, boot, igraph, viridisLite
Suggests: covr, testthat, knitr, rmarkdown, ape, RSiena, survival
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
URL: https://github.com/USCCANA/netdiffuseR, https://USCCANA.github.io/netdiffuseR/
BugReports: https://github.com/USCCANA/netdiffuseR/issues
Classification/MSC: 90C35, 90B18, 91D30
NeedsCompilation: yes
Packaged: 2022-12-01 16:59:21 UTC; george
Author: George Vega Yon [aut, cre] , Thomas Valente [aut, cph] , Stephanie Dyal [ctb] , Timothy Hayes [ctb]
Maintainer: George Vega Yon <g.vegayon@gmail.com>
Repository: CRAN
Date/Publication: 2022-12-02 16:20:02 UTC

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Package mstDIF updated to version 0.1.7 with previous version 0.1.6 dated 2020-07-24

Title: A Collection of DIF Tests for Multistage Tests
Description: A collection of statistical tests for the detection of differential item functioning (DIF) in multistage tests. Methods entail logistic regression, an adaptation of the simultaneous item bias test (SIBTEST), and various score-based tests. The presented tests provide itemwise test for DIF along categorical, ordinal or metric covariates. Methods for uniform and non-uniform DIF effects are available depending on which method is used.
Author: Rudolf Debelak [aut, cre], Dries Debeer [aut], Sebastian Appelbaum [ctb], Mark J. Gierl [ctb]
Maintainer: Rudolf Debelak <rudolf.debelak@gmail.com>

Diff between mstDIF versions 0.1.6 dated 2020-07-24 and 0.1.7 dated 2022-12-02

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New package EDCimport with initial version 0.2.1
Package: EDCimport
Version: 0.2.1
Title: Import Data from EDC Software
Description: A convenient toolbox to import data exported from Electronic Data Capture (EDC) software 'TrialMaster' and 'Macro'.
License: GPL-3
URL: https://github.com/DanChaltiel/EDCimport
BugReports: https://github.com/DanChaltiel/EDCimport/issues
Depends: R (>= 3.1.0)
Imports: cli, dplyr, glue, forcats, haven, labelled, purrr, readr, rlang, stringr, tibble, tidyr
Suggests: callr, covr, crosstable, knitr, testthat (>= 3.0.0), withr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-12-01 15:45:34 UTC; Dan
Author: Dan Chaltiel [aut, cre]
Maintainer: Dan Chaltiel <dan.chaltiel@gmail.com>
Repository: CRAN
Date/Publication: 2022-12-02 16:10:14 UTC

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New package ddplot with initial version 0.0.1
Package: ddplot
Title: Create D3 Based SVG Graphics
Version: 0.0.1
Maintainer: Mohamed El Fodil Ihaddaden <ihaddaden.fodeil@gmail.com>
Description: Create 'D3' based 'SVG' ('Scalable Vector Graphics') graphics using a simple 'R' API. The package aims to simplify the creation of many 'SVG' plot types using a straightforward 'R' API. The package relies on the 'r2d3' 'R' package and the 'D3' 'JavaScript' library. See <https://rstudio.github.io/r2d3/> and <https://d3js.org/> respectively.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/feddelegrand7/ddplot
BugReports: https://github.com/feddelegrand7/ddplot/issues
Imports: r2d3
Suggests: knitr, rmarkdown, ggplot2, dplyr, tidyr, zoo, gapminder
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-12-01 15:15:20 UTC; Administrateur
Author: Mohamed El Fodil Ihaddaden [aut, cre], June Choe [ctb, cph], Mike Bostock [ctb, cph] , RStudio [ctb, cph]
Repository: CRAN
Date/Publication: 2022-12-02 16:10:08 UTC

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New package dataset with initial version 0.1.9
Package: dataset
Title: Create Data Frames that are Easier to Exchange and Reuse
Date: 2022-12-01
Version: 0.1.9
Description: The aim of the 'dataset' package is to make tidy datasets easier to release, exchange and reuse. It organizes and formats data frame 'R' objects into well-referenced, well-described, interoperable datasets into release and reuse ready form. A subjective interpretation of the W3C DataSet recommendation and the datacube model <https://www.w3.org/TR/vocab-data-cube/>, which is also used in the global Statistical Data and Metadata eXchange standards, the application of the connected Dublin Core <https://www.dublincore.org/specifications/dublin-core/dcmi-terms/> and DataCite <https://support.datacite.org/docs/datacite-metadata-schema-44/> standards preferred by European open science repositories to improve the findability, accessibility, interoperability and reusability of the datasets.
License: GPL (>= 3)
URL: https://github.com/dataobservatory-eu/dataset
BugReports: https://github.com/dataobservatory-eu/dataset/issues
Encoding: UTF-8
Depends: R (>= 2.10)
Imports: assertthat, ISOcodes, utils
Suggests: covr, declared, dplyr, eurostat, here, kableExtra, knitr, rdflib, readxl, rmarkdown, spelling, statcodelists, testthat (>= 3.0.0), tidyr
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2022-12-01 20:20:58 UTC; antaldaniel
Author: Daniel Antal [aut, cre] , Marcelo Perlin [rev]
Maintainer: Daniel Antal <daniel.antal@dataobservatory.eu>
Repository: CRAN
Date/Publication: 2022-12-02 16:40:02 UTC

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New package appsflyeR with initial version 0.1.0
Package: appsflyeR
Title: Get Data from 'Appsflyer' via the 'Windsor.ai' API
Version: 0.1.0
Description: Collect your data on digital marketing campaigns from 'Appsflyer' using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.
License: GPL-3
URL: https://windsor.ai/
Depends: R (>= 3.5.0)
Imports: jsonlite (>= 1.7.2)
Suggests: knitr, rmarkdown, dplyr, ggplot2, tidyr, curl
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2022-12-01 18:29:37 UTC; pablo
Author: Pablo Sanchez [cre, aut], Windsor.ai [cph]
Maintainer: Pablo Sanchez <pablosama@outlook.es>
Repository: CRAN
Date/Publication: 2022-12-02 16:20:10 UTC

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Package qtl2 updated to version 0.30 with previous version 0.28 dated 2021-10-17

Title: Quantitative Trait Locus Mapping in Experimental Crosses
Description: Provides a set of tools to perform quantitative trait locus (QTL) analysis in experimental crosses. It is a reimplementation of the 'R/qtl' package to better handle high-dimensional data and complex cross designs. Broman et al. (2018) <doi:10.1534/genetics.118.301595>.
Author: Karl W Broman [aut, cre] , R Core Team [ctb]
Maintainer: Karl W Broman <broman@wisc.edu>

Diff between qtl2 versions 0.28 dated 2021-10-17 and 0.30 dated 2022-12-02

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Package oompaData updated to version 3.1.3 with previous version 3.1.2 dated 2022-05-03

Title: Data to Illustrate OOMPA Algorithms
Description: This is a data-only package to provide example data for other packages that are part of the "Object-Oriented Microrray and Proteomics Analysis" suite of packages. These are described in more detail at the package URL.
Author: Kevin R. Coombes
Maintainer: Kevin R. Coombes <krc@silicovore.com>

Diff between oompaData versions 3.1.2 dated 2022-05-03 and 3.1.3 dated 2022-12-02

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Package glm.predict updated to version 4.2-0 with previous version 4.1-0 dated 2021-08-16

Title: Predicted Values and Discrete Changes for GLM
Description: Functions to calculate predicted values and the difference between the two cases with confidence interval for lm() [linear model], glm() [generalised linear model], glm.nb() [negative binomial model], polr() [ordinal logistic model], multinom() [multinomial model] and tobit() [tobit model], svyglm() [survey-weighted generalised linear models], lmer() [linear multilevel models] using Monte Carlo simulations or bootstrap. Reference: Bennet A. Zelner (2009) <doi:10.1002/smj.783>.
Author: Benjamin Schlegel [aut,cre]
Maintainer: Benjamin Schlegel <kontakt@benjaminschlegel.ch>

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Package RBaseX updated to version 1.1.2 with previous version 1.1.1 dated 2022-03-10

Title: 'BaseX' Client
Description: 'BaseX' <https://basex.org> is a XML database engine and a compliant 'XQuery 3.1' processor with full support of 'W3C Update Facility'. This package is a full client-implementation of the client/server protocol for 'BaseX' and provides functionalities to create, manipulate and query on XML-data.
Author: Ben Engbers [aut, cre]
Maintainer: Ben Engbers <Ben.Engbers@Be-Logical.nl>

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Package prismjs updated to version 1.1.0 with previous version 1.0.0 dated 2022-11-21

Title: Server-Side Syntax Highlighting
Description: Prism <https://prismjs.com/> is a lightweight, extensible syntax highlighter, built with modern web standards in mind. This package provides server-side rendering in R using 'V8' such that no JavaScript library is required in the resulting HTML documents. Over 400 languages are supported.
Author: Jeroen Ooms [aut, cre] , Lea Verou [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package graphicalExtremes updated to version 0.2.0 with previous version 0.1.0 dated 2019-11-08

Title: Statistical Methodology for Graphical Extreme Value Models
Description: Statistical methodology for sparse multivariate extreme value models. Methods are provided for exact simulation and statistical inference for multivariate Pareto distributions on graphical structures as described in the paper 'Graphical Models for Extremes' by Engelke and Hitz (2020) <doi:10.1111/rssb.12355>.
Author: Sebastian Engelke [aut, cre], Adrien S. Hitz [aut], Nicola Gnecco [aut], Manuel Hentschel [aut]
Maintainer: Sebastian Engelke <sebastian.engelke@unige.ch>

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Package DriveML updated to version 0.1.5 with previous version 0.1.4 dated 2021-10-18

Title: Self-Drive Machine Learning Projects
Description: Implementing some of the pillars of an automated machine learning pipeline such as (i) Automated data preparation, (ii) Feature engineering, (iii) Model building in classification context that includes techniques such as (a) Regularised regression [1], (b) Logistic regression [2], (c) Random Forest [3], (d) Decision tree [4] and (e) Extreme Gradient Boosting (xgboost) [5], and finally, (iv) Model explanation (using lift chart and partial dependency plots). Accomplishes the above tasks by running the function instead of writing lengthy R codes. Also provides some additional features such as generating missing at random (MAR) variables and automated exploratory data analysis. Moreover, function exports the model results with the required plots in an HTML vignette report format that follows the best practices of the industry and the academia. [1] Gonzales G B and De Saeger (2018) <doi:10.1038/s41598-018-21851-7>, [2] Sperandei S (2014) <doi:10.11613/BM.2014.003>, [3] Breiman [...truncated...]
Author: Dayanand Ubrangala [aut, cre], Sayan Putatunda [aut, ctb], Kiran R [aut, ctb], Ravi Prasad Kondapalli [aut, ctb]
Maintainer: Dayanand Ubrangala <daya6489@gmail.com>

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Package terra updated to version 1.6-47 with previous version 1.6-41 dated 2022-11-18

Title: Spatial Data Analysis
Description: Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include standard operations such as intersect and buffer. Raster methods include global, local, zonal, and focal computations. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/terra/> to get started. 'terra' is a replacement for the 'raster' package ('terra' can do more, and it is faster and easier to use).
Author: Robert J. Hijmans [cre, aut] , Roger Bivand [ctb] , Edzer Pebesma [ctb] , Michael D. Sumner [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

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More information about terra at CRAN
Permanent link

Package stringr updated to version 1.5.0 with previous version 1.4.1 dated 2022-08-20

Title: Simple, Consistent Wrappers for Common String Operations
Description: A consistent, simple and easy to use set of wrappers around the fantastic 'stringi' package. All function and argument names (and positions) are consistent, all functions deal with "NA"'s and zero length vectors in the same way, and the output from one function is easy to feed into the input of another.
Author: Hadley Wickham [aut, cre, cph], RStudio [cph, fnd]
Maintainer: Hadley Wickham <hadley@rstudio.com>

Diff between stringr versions 1.4.1 dated 2022-08-20 and 1.5.0 dated 2022-12-02

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More information about stringr at CRAN
Permanent link

Package lemon updated to version 0.4.6 with previous version 0.4.5 dated 2020-06-08

Title: Freshing Up your 'ggplot2' Plots
Description: Functions for working with legends and axis lines of 'ggplot2', facets that repeat axis lines on all panels, and some 'knitr' extensions.
Author: Stefan McKinnon Edwards [aut, ctb, cre] , Baptiste Auguie [ctb] , Shaun Jackman [ctb] , Hadley Wickham [ctb] , Winston Chang [ctb]
Maintainer: Stefan McKinnon Edwards <sme@iysik.com>

Diff between lemon versions 0.4.5 dated 2020-06-08 and 0.4.6 dated 2022-12-02

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More information about lemon at CRAN
Permanent link

Package COMPoissonReg updated to version 0.8.0 with previous version 0.7.0 dated 2019-11-30

Title: Conway-Maxwell Poisson (COM-Poisson) Regression
Description: Fit Conway-Maxwell Poisson (COM-Poisson or CMP) regression models to count data (Sellers & Shmueli, 2010) <doi:10.1214/09-AOAS306>. The package provides functions for model estimation, dispersion testing, and diagnostics. Zero-inflated CMP regression (Sellers & Raim, 2016) <doi:10.1016/j.csda.2016.01.007> is also supported.
Author: Kimberly Sellers <kfs7@georgetown.edu> Thomas Lotze <thomas.lotze@thomaslotze.com> Andrew Raim <andrew.raim@gmail.com>
Maintainer: Andrew Raim <andrew.raim@gmail.com>

Diff between COMPoissonReg versions 0.7.0 dated 2019-11-30 and 0.8.0 dated 2022-12-02

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Package bayesm updated to version 3.1-5 with previous version 3.1-4 dated 2019-10-15

Title: Bayesian Inference for Marketing/Micro-Econometrics
Description: Covers many important models used in marketing and micro-econometrics applications. The package includes: Bayes Regression (univariate or multivariate dep var), Bayes Seemingly Unrelated Regression (SUR), Binary and Ordinal Probit, Multinomial Logit (MNL) and Multinomial Probit (MNP), Multivariate Probit, Negative Binomial (Poisson) Regression, Multivariate Mixtures of Normals (including clustering), Dirichlet Process Prior Density Estimation with normal base, Hierarchical Linear Models with normal prior and covariates, Hierarchical Linear Models with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a Dirichlet Process prior and covariates, Hierarchical Negative Binomial Regression Models, Bayesian analysis of choice-based conjoint data, Bayesian treatment of linear instrumental variables models, Analysis of Multivariate Ordinal survey data with scale usage heterogeneity (as i [...truncated...]
Author: Peter Rossi <perossichi@gmail.com>
Maintainer: Peter Rossi <perossichi@gmail.com>

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Package activAnalyzer updated to version 1.1.0 with previous version 1.0.5 dated 2022-10-12

Title: A 'Shiny' App to Analyze Accelerometer-Measured Daily Physical Behavior Data
Description: A tool to analyse 'ActiGraph' accelerometer data and to implement the use of the PROactive Physical Activity in COPD (chronic obstructive pulmonary disease) instruments. Once analysis is completed, the app allows to export results to .csv files and to generate a report of the measurement. All the configured inputs relevant for interpreting the results are recorded in the report. In addition to the existing 'R' packages that are fully integrated with the app, the app uses some functions from the 'actigraph.sleepr' package developed by Petkova (2021) <https://github.com/dipetkov/actigraph.sleepr/>.
Author: Pierre-Yves de Muellenheim [cre, aut]
Maintainer: Pierre-Yves de Muellenheim <pydemull@uco.fr>

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Package weibullness updated to version 1.22.12 with previous version 1.19.8 dated 2019-08-19

Title: Goodness-of-Fit Test for Weibull Distribution (Weibullness)
Description: Performs a goodness-of-fit test of Weibull distribution (weibullness test) and provides the maximum likelihood estimates of the three-parameter Weibull distribution. Note that the threshold parameter is estimated based on the correlation from the Weibull plot. For more details, see Park (2018) <doi:10.1155/2018/6056975>. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1A2C1091319).
Author: Chanseok Park [aut, cre]
Maintainer: Chanseok Park <statpnu@gmail.com>

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Package tiledb updated to version 0.17.0 with previous version 0.16.0 dated 2022-10-21

Title: Universal Storage Engine for Sparse and Dense Multidimensional Arrays
Description: The universal storage engine 'TileDB' introduces a powerful on-disk format for multi-dimensional arrays. It supports dense and sparse arrays, dataframes and key-values stores, cloud storage ('S3', 'GCS', 'Azure'), chunked arrays, multiple compression, encryption and checksum filters, uses a fully multi-threaded implementation, supports parallel I/O, data versioning ('time travel'), metadata and groups. It is implemented as an embeddable cross-platform C++ library with APIs from several languages, and integrations.
Author: TileDB, Inc. [aut, cph], Dirk Eddelbuettel [cre]
Maintainer: Dirk Eddelbuettel <dirk@tiledb.com>

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Package SqlRender updated to version 1.11.0 with previous version 1.10.0 dated 2022-09-20

Title: Rendering Parameterized SQL and Translation to Dialects
Description: A rendering tool for parameterized SQL that also translates into different SQL dialects. These dialects include 'Microsoft SQL Server', 'Oracle', 'PostgreSql', 'Amazon RedShift', 'Apache Impala', 'IBM Netezza', 'Google BigQuery', 'Microsoft PDW', 'Snowflake', 'Azure Synapse Analytics Dedicated', 'Apache Spark', and 'SQLite'.
Author: Martijn Schuemie [aut, cre], Marc Suchard [aut]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

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Package sparrpowR updated to version 0.2.6 with previous version 0.2.5 dated 2022-02-04

Title: Power Analysis to Detect Spatial Relative Risk Clusters
Description: Calculate the statistical power to detect clusters using kernel-based spatial relative risk functions that are estimated using the 'sparr' package. Details about the 'sparr' package methods can be found in the tutorial: Davies et al. (2018) <doi:10.1002/sim.7577>. Details about kernel density estimation can be found in J. F. Bithell (1990) <doi:10.1002/sim.4780090616>. More information about relative risk functions using kernel density estimation can be found in J. F. Bithell (1991) <doi:10.1002/sim.4780101112>.
Author: Ian D. Buller [aut, cre, cph] , Derek W. Brown [aut, cph] , Mitchell J. Machiela [ctb] , Timothy A. Myers [ctb], NCI [cph, fnd]
Maintainer: Ian D. Buller <ian.buller@alumni.emory.edu>

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Package pdfCluster updated to version 1.0-4 with previous version 1.0-3 dated 2018-12-04

Title: Cluster Analysis via Nonparametric Density Estimation
Description: Cluster analysis via nonparametric density estimation is performed. Operationally, the kernel method is used throughout to estimate the density. Diagnostics methods for evaluating the quality of the clustering are available. The package includes also a routine to estimate the probability density function obtained by the kernel method, given a set of data with arbitrary dimensions.
Author: Menardi Giovanna [aut, cre], Azzalini Adelchi [aut], Rosolin Tiziana [ctb]
Maintainer: Menardi Giovanna <menardi@stat.unipd.it>

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Package inlabru updated to version 2.7.0 with previous version 2.6.0 dated 2022-10-24

Title: Bayesian Latent Gaussian Modelling using INLA and Extensions
Description: Facilitates spatial and general latent Gaussian modeling using integrated nested Laplace approximation via the INLA package (<https://www.r-inla.org>). Additionally, extends the GAM-like model class to more general nonlinear predictor expressions, and implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. Model components are specified with general inputs and mapping methods to the latent variables, and the predictors are specified via general R expressions, with separate expressions for each observation likelihood model in multi-likelihood models. A prediction method based on fast Monte Carlo sampling allows posterior prediction of general expressions of the latent variables. Ecology-focused introduction in Bachl, Lindgren, Borchers, and Illian (2019) <doi:10.1111/2041-210X.13168>.
Author: Finn Lindgren [aut, cre, cph] , Fabian E. Bachl [aut, cph] , David L. Borchers [ctb, dtc, cph] , Daniel Simpson [ctb, cph] , Lindesay Scott-Howard [ctb, dtc, cph] , Seaton Andy [ctb] , Suen Man Ho [ctb, cph] , Roudier Pierre [ctb, cph] , Meehan Tim [ [...truncated...]
Maintainer: Finn Lindgren <finn.lindgren@gmail.com>

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Package helsinki updated to version 1.0.6 with previous version 1.0.5 dated 2021-09-29

Title: R Tools for Helsinki Open Data
Description: Tools for accessing various open data APIs in the Helsinki region in Finland. Current data sources include the Service Map API, Linked Events API, and Helsinki Region Infoshare statistics API.
Author: Juuso Parkkinen [aut, cre], Joona Lehtomaki [aut], Pyry Kantanen [aut] , Leo Lahti [aut]
Maintainer: Juuso Parkkinen <juuso.parkkinen@iki.fi>

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Package FuzzyResampling updated to version 0.5.0 with previous version 0.4.2 dated 2022-03-21

Title: Resampling Methods for Triangular and Trapezoidal Fuzzy Numbers
Description: The classical (i.e. Efron's, see Efron and Tibshirani (1994, ISBN:978-0412042317) "An Introduction to the Bootstrap") bootstrap is widely used for both the real (i.e. "crisp") and fuzzy data. The main aim of the algorithms implemented in this package is to overcome a problem with repetition of a few distinct values and to create fuzzy numbers, which are "similar" (but not the same) to values from the initial sample. To do this, different characteristics of triangular/trapezoidal numbers are kept (like the value, the ambiguity, etc., see Grzegorzewski et al. <doi:10.2991/eusflat-19.2019.68>, Grzegorzewski et al. (2020) <doi:10.2991/ijcis.d.201012.003>, Grzegorzewski et al. (2020) <doi:10.34768/amcs-2020-0022>, Grzegorzewski and Romaniuk (2022) <doi:10.1007/978-3-030-95929-6_3>, Romaniuk and Hryniewicz (2019) <doi:10.1007/s00500-018-3251-5>). Some additional procedures related to these resampling methods are also provided, like calculation of the Bertoluz [...truncated...]
Author: Maciej Romaniuk [cre], Przemyslaw Grzegorzewski [aut], Olgierd Hryniewicz [aut]
Maintainer: Maciej Romaniuk <mroman@ibspan.waw.pl>

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Package ASSISTant updated to version 1.4.3 with previous version 1.4.2 dated 2019-05-03

Title: Adaptive Subgroup Selection in Group Sequential Trials
Description: Clinical trial design for subgroup selection in three-stage group sequential trial as described in Lai, Lavori and Liao (2014, <doi:10.1016/j.cct.2014.09.001>). Includes facilities for design, exploration and analysis of such trials. An implementation of the initial DEFUSE-3 trial is also provided as a vignette.
Author: Tze Leung Lai [ctb], Philip Lavori [aut], Olivia Liao [aut], Balasubramanian Narasimhan [aut, cre], Ka Wai Tsang [aut]
Maintainer: Balasubramanian Narasimhan <naras@stat.Stanford.EDU>

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New package TSSVM with initial version 0.1.0
Package: TSSVM
Title: Time Series Forecasting using SVM Model
Version: 0.1.0
Depends: R (>= 2.3.1), e1071,forecast
Description: Implementation and forecasting univariate time series data using the Support Vector Machine model. Support Vector Machine is one of the prominent machine learning approach for non-linear time series forecasting. For method details see Kim, K. (2003) <doi:10.1016/S0925-2312(03)00372-2>.
Encoding: UTF-8
License: GPL-3
NeedsCompilation: no
Packaged: 2022-11-29 14:19:23 UTC; pc
Author: Mrinmoy Ray [aut, cre], Samir Barman [aut, ctb], Kanchan Sinha [aut, ctb], K. N. Singh [aut, ctb]
Maintainer: Mrinmoy Ray <mrinmoy4848@gmail.com>
Repository: CRAN
Date/Publication: 2022-12-02 08:10:02 UTC

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New package nieve with initial version 0.1.0
Package: nieve
Title: Miscellaneous Utilities for Extreme Value Analysis
Version: 0.1.0
Maintainer: Yves Deville <deville.yves@alpestat.com>
Description: Provides utility functions and objects for Extreme Value Analysis. These include probability functions with their exact derivatives w.r.t. the parameters that can be used for estimation and inference, even with censored observations. The transformations exchanging the two parameterizations of Peaks Over Threshold (POT) models: Poisson-GP and Point-Process are also provided with their derivatives.
License: GPL (>= 2)
Suggests: testthat, numDeriv, Renext, knitr, covr
Encoding: UTF-8
URL: https://github.com/yvesdeville/nieve/
BugReports: https://github.com/yvesdeville/nieve/issues/
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2022-11-30 13:51:57 UTC; yves
Author: Yves Deville [cre, aut]
Repository: CRAN
Date/Publication: 2022-12-02 08:20:02 UTC

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Package lslx updated to version 0.6.11 with previous version 0.6.10 dated 2020-04-27

Title: Semi-Confirmatory Structural Equation Modeling via Penalized Likelihood or Least Squares
Description: Fits semi-confirmatory structural equation modeling (SEM) via penalized likelihood (PL) or penalized least squares (PLS). For details, please see Huang (2020) <doi:10.18637/jss.v093.i07>.
Author: Po-Hsien Huang [cre, aut], Wen-Hsin Hu [aut]
Maintainer: Po-Hsien Huang <psyphh@gmail.com>

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New package jackknifeR with initial version 0.1.1
Package: jackknifeR
Title: Jackknife Linear Regression and Correlation
Version: 0.1.1
Description: This function creates jackknife samples from the data by sequentially removing d observations from the data, performs linear regression or correlation using the jackknife samples and estimates the jackknife coefficients bias standard error, standard error and confidence intervals based on the methodology discussed by Quenouille (1956) <doi:10.2307/2332914>, Tukey (1958) <doi:10.1214/aoms/1177706647> and Shi (1988) <doi:10.1016/0167-7152(88)90011-9>.
License: CC BY 4.0
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-11-30 09:26:04 UTC; Mohan
Author: S. Mohanasundaram [aut, cre]
Maintainer: S. Mohanasundaram <s.mohanasundaram@outlook.com>
Repository: CRAN
Date/Publication: 2022-12-02 08:20:09 UTC

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Package ClimProjDiags updated to version 0.2.1 with previous version 0.2.0 dated 2022-11-18

Title: Set of Tools to Compute Various Climate Indices
Description: Set of tools to compute metrics and indices for climate analysis. The package provides functions to compute extreme indices, evaluate the agreement between models and combine theses models into an ensemble. Multi-model time series of climate indices can be computed either after averaging the 2-D fields from different models provided they share a common grid or by combining time series computed on the model native grid. Indices can be assigned weights and/or combined to construct new indices.
Author: BSC-CNS [aut, cph], Nuria Perez-Zanon [aut] , An-Chi Ho [cre, ctb], Nicolau Manubens [ctb], Alasdair Hunter [aut], Louis-Philippe Caron [ctb], Eva Rifa [ctb]
Maintainer: An-Chi Ho <an.ho@bsc.es>

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Package mappoly updated to version 0.3.2 with previous version 0.3.1 dated 2022-07-06

Title: Genetic Linkage Maps in Autopolyploids
Description: Construction of genetic maps in autopolyploid full-sib populations. Uses pairwise recombination fraction estimation as the first source of information to sequentially position allelic variants in specific homologous chromosomes. For situations where pairwise analysis has limited power, the algorithm relies on the multilocus likelihood obtained through a hidden Markov model (HMM). For more detail, please see Mollinari and Garcia (2019) <doi:10.1534/g3.119.400378> and Mollinari et al. (2020) <doi:10.1534/g3.119.400620>.
Author: Marcelo Mollinari [aut, cre] , Gabriel Gesteira [aut] , Guilhereme Pereira [ctb] , Augusto Garcia [ctb] , Zhao-Bang Zeng [ctb] , Katharine Preedy [ctb, cph] , Robert Gentleman [cph] , Ross Ihaka [cph] , R Foundation [cph] , R-core [cph]
Maintainer: Marcelo Mollinari <mmollin@ncsu.edu>

Diff between mappoly versions 0.3.1 dated 2022-07-06 and 0.3.2 dated 2022-12-02

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Package apache.sedona updated to version 1.3.0 with previous version 1.2.1 dated 2022-08-31

Title: R Interface for Apache Sedona
Description: R interface for 'Apache Sedona' based on 'sparklyr' (<https://sedona.apache.org>).
Author: Apache Sedona [aut, cre], Jia Yu [ctb, cph], Yitao Li [aut, cph] , The Apache Software Foundation [cph], RStudio [cph]
Maintainer: Apache Sedona <private@sedona.apache.org>

Diff between apache.sedona versions 1.2.1 dated 2022-08-31 and 1.3.0 dated 2022-12-02

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