Tue, 29 Oct 2024

Package rice updated to version 0.4.0 with previous version 0.3.0 dated 2024-10-21

Title: Radiocarbon Equations
Description: Provides functions for the calibration of radiocarbon dates, as well as options to calculate different radiocarbon realms (C14 age, F14C, pMC, D14C) and estimating the effects of contamination or local reservoir offsets (Reimer and Reimer 2001 <doi:10.1017/S0033822200038339>). The methods follow long-established recommendations such as Stuiver and Polach (1977) <doi:10.1017/S0033822200003672> and Reimer et al. (2004) <doi:10.1017/S0033822200033154>. This package accompanies the data package 'rintcal'.
Author: Maarten Blaauw [aut, cre]
Maintainer: Maarten Blaauw <maarten.blaauw@qub.ac.uk>

Diff between rice versions 0.3.0 dated 2024-10-21 and 0.4.0 dated 2024-10-29

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Package refseqR updated to version 1.1.5 with previous version 1.1.4 dated 2024-08-18

Title: Common Computational Operations Working with RefSeq Entries (GenBank)
Description: Fetches NCBI data (RefSeq <https://www.ncbi.nlm.nih.gov/refseq/> database) and provides an environment to extract information at the level of gene, mRNA or protein accessions.
Author: Jose V. Die [aut, cre] , Lluis Revilla Sancho [ctb]
Maintainer: Jose V. Die <jose.die@uco.es>

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Package modEvA updated to version 3.20 with previous version 3.18.2 dated 2024-08-28

Title: Model Evaluation and Analysis
Description: Analyses species distribution models and evaluates their performance. It includes functions for variation partitioning, extracting variable importance, computing several metrics of model discrimination and calibration performance, optimizing prediction thresholds based on a number of criteria, performing multivariate environmental similarity surface (MESS) analysis, and displaying various analytical plots. Initially described in Barbosa et al. (2013) <doi:10.1111/ddi.12100>.
Author: A. Marcia Barbosa [aut, cre], Jennifer A. Brown [aut], Alberto Jimenez-Valverde [aut], Raimundo Real [aut], Oswald van Ginkel [ctb], Jurica Levatic [ctb], Victoria Formoso-Freire [ctb], Andres Baselga [ctb], Carola Gomez-Rodriguez [ctb], Jose Carlos [...truncated...]
Maintainer: A. Marcia Barbosa <ana.marcia.barbosa@gmail.com>

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Package elhmc updated to version 1.2.1 with previous version 1.2.0 dated 2024-08-25

Title: Sampling from a Empirical Likelihood Bayesian Posterior of Parameters Using Hamiltonian Monte Carlo
Description: A tool to draw samples from a Empirical Likelihood Bayesian posterior of parameters using Hamiltonian Monte Carlo.
Author: Dang Trung Kien [aut], Sanjay Chaudhuri [aut, cre], Neo Han Wei, [aut]
Maintainer: Sanjay Chaudhuri <schaudhuri2@unl.edu>

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Package rliger updated to version 2.1.0 with previous version 2.0.1 dated 2024-04-04

Title: Linked Inference of Genomic Experimental Relationships
Description: Uses an extension of nonnegative matrix factorization to identify shared and dataset-specific factors. See Welch J, Kozareva V, et al (2019) <doi:10.1016/j.cell.2019.05.006>, and Liu J, Gao C, Sodicoff J, et al (2020) <doi:10.1038/s41596-020-0391-8> for more details.
Author: Joshua Welch [aut], Yichen Wang [aut, cre], Chao Gao [aut], Jialin Liu [aut], Joshua Sodicoff [aut, ctb], Velina Kozareva [aut, ctb], Evan Macosko [aut, ctb], Paul Hoffman [ctb], Ilya Korsunsky [ctb], Robert Lee [ctb], Andrew Robbins [ctb]
Maintainer: Yichen Wang <wayichen@umich.edu>

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New package PublicWorksFinanceIT with initial version 0.3.0
Package: PublicWorksFinanceIT
Title: Soil Defense Investments in Italy: Data Retrieval, Analysis, Visualization
Version: 0.3.0
Description: Facilitates the retrieval and analysis of financial data related to public works in Italy, focusing on soil defense investments. It extracts data from 'OpenCoesione', 'OpenBDAP', and the 'ReNDiS' database, eliminating the need for direct access to these platforms. The package boasts a user-friendly design, featuring real time updates and a set of functions tailored for data retrieval and visualization. See the webpages for further information <http://www.rendis.isprambiente.it/rendisweb/>, <https://opencoesione.gov.it/en/>, and <https://bdap-opendata.rgs.mef.gov.it/>.
Encoding: UTF-8
Language: EN
LazyData: true
LazyDataCompression: xz
Imports: magrittr, dplyr, ggplot2, httr,leaflet,lubridate, rlang, rvest, scales, sf, tibble, tidyr, plotly, spdep, knitr
License: GPL (>= 3)
Author: Lorena Ricciotti [aut, cre] , Alessio Pollice [ths]
Maintainer: Lorena Ricciotti <lorena.ricciotti@uniba.it>
NeedsCompilation: no
Packaged: 2024-10-28 11:05:00 UTC; lori1
Repository: CRAN
Date/Publication: 2024-10-29 23:10:10 UTC

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Package gcbd updated to version 0.2.7 with previous version 0.2.6 dated 2016-09-28

Title: 'GPU'/CPU Benchmarking in Debian-Based Systems
Description: 'GPU'/CPU Benchmarking on Debian-package based systems This package benchmarks performance of a few standard linear algebra operations (such as a matrix product and QR, SVD and LU decompositions) across a number of different 'BLAS' libraries as well as a 'GPU' implementation. To do so, it takes advantage of the ability to 'plug and play' different 'BLAS' implementations easily on a Debian and/or Ubuntu system. The current version supports - 'Reference BLAS' ('refblas') which are un-accelerated as a baseline - Atlas which are tuned but typically configure single-threaded - Atlas39 which are tuned and configured for multi-threaded mode - 'Goto Blas' which are accelerated and multi-threaded - 'Intel MKL' which is a commercial accelerated and multithreaded version. As for 'GPU' computing, we use the CRAN package - 'gputools' For 'Goto Blas', the 'gotoblas2-helper' script from the ISM in Tokyo can be used. For 'Intel MKL' we use the Revolution R packages from Ubuntu 9.10.
Author: Dirk Eddelbuettel [aut, cre]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package dexisensitivity updated to version 1.0.1 with previous version 1.0.0 dated 2024-10-25

Title: 'DEXi' Decision Tree Analysis and Visualization
Description: Provides a versatile toolkit for analyzing and visualizing 'DEXi' (Decision EXpert for education) decision trees, facilitating multi-criteria decision analysis directly within R. Users can read .dxi files, manipulate decision trees, and evaluate various scenarios. It supports sensitivity analysis through Monte Carlo simulations, one-at-a-time approaches, and variance-based methods, helping to discern the impact of input variations. Additionally, it includes functionalities for generating sampling plans and an array of visualization options for decision trees and analysis results. A distinctive feature is the synoptic table plot, aiding in the efficient comparison of scenarios. Whether for in-depth decision modeling or sensitivity analysis, this package stands as a comprehensive solution. Definition of sensitivity analyses available in Carpani, Bergez and Monod (2012) <doi:10.1016/j.envsoft.2011.10.002> and detailed description of the package soon available in Alaphilippe, Allart, [...truncated...]
Author: Roland Allart [aut], Jacques-Eric Bergez [aut] , Marta Carpani [aut], Herve Monod [aut] , Aude Alaphilippe [ctb] , Nicolas Cavan [ctb, cre], INRAE [cph] )
Maintainer: Nicolas Cavan <nicolas.cavan@inrae.fr>

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Package bravo updated to version 3.2.2 with previous version 3.2.1 dated 2024-05-13

Title: Bayesian Screening and Variable Selection
Description: Performs Bayesian variable screening and selection for ultra-high dimensional linear regression models.
Author: Dongjin Li [aut, cre], Debarshi Chakraborty [aut], Somak Dutta [aut], Vivekananda Roy [ctb]
Maintainer: Dongjin Li <liyangxiaobei@gmail.com>

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Package bio3d updated to version 2.4-5 with previous version 2.4-4 dated 2022-10-26

Title: Biological Structure Analysis
Description: Utilities to process, organize and explore protein structure, sequence and dynamics data. Features include the ability to read and write structure, sequence and dynamic trajectory data, perform sequence and structure database searches, data summaries, atom selection, alignment, superposition, rigid core identification, clustering, torsion analysis, distance matrix analysis, structure and sequence conservation analysis, normal mode analysis, principal component analysis of heterogeneous structure data, and correlation network analysis from normal mode and molecular dynamics data. In addition, various utility functions are provided to enable the statistical and graphical power of the R environment to work with biological sequence and structural data. Please refer to the URLs below for more information.
Author: Barry Grant [aut, cre], Xin-Qiu Yao [aut], Lars Skjaerven [aut], Julien Ide [aut]
Maintainer: Barry Grant <bjgrant@ucsd.edu>

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Package folda updated to version 0.2.0 with previous version 0.1.0 dated 2024-09-11

Title: Forward Stepwise Discriminant Analysis with Pillai's Trace
Description: A novel forward stepwise discriminant analysis framework that integrates Pillai's trace with Uncorrelated Linear Discriminant Analysis (ULDA), providing an improvement over traditional stepwise LDA methods that rely on Wilks' Lambda. A stand-alone ULDA implementation is also provided, offering a more general solution than the one available in the 'MASS' package. It automatically handles missing values and provides visualization tools. For more details, see Wang (2024) <doi:10.48550/arXiv.2409.03136>.
Author: Siyu Wang [aut, cre, cph]
Maintainer: Siyu Wang <iamwangsiyu@gmail.com>

Diff between folda versions 0.1.0 dated 2024-09-11 and 0.2.0 dated 2024-10-29

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New package redatamx with initial version 1.0.0
Package: redatamx
Title: R Interface to 'Redatam' Library
Version: 1.0.0
Date: 2024-11-01
Maintainer: Jaime Salvador <jaime.salvador@ideasybits.com>
Description: Provides an API to work with 'Redatam' (see <https://redatam.org>) databases in both formats: 'RXDB' (new format) and 'DICX' (old format) and running 'Redatam' programs written in 'SPC' language. It's a wrapper around 'Redatam' core and provides functions to open/close a database (redatam_open()/redatam_close()), list entities and variables from the database (redatam_entities(), redatam_variables()) and execute a 'SPC' program and gets the results as data frames (redatam_query(), redatam_run()).
License: GPL (>= 3)
Encoding: UTF-8
Language: en-US
NeedsCompilation: yes
LinkingTo: cpp11
SystemRequirements: 'Redatam' runtime engine (see https://redatam.org), The dynamic binary library is downloaded from <https://redatam-core.s3.us-west-2.amazonaws.com> during the build step. Currently supported platforms are Windows, Linux and macOS.
Copyright: See COPYRIGHTS for details.
Packaged: 2024-10-27 20:32:58 UTC; jsalvador2024
Author: Jaime Salvador [aut, cre] , CELADE [cph]
Repository: CRAN
Date/Publication: 2024-10-29 20:30:02 UTC

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Permanent link

New package mxcc with initial version 0.0.1
Package: mxcc
Title: Maxwell Control Charts
Version: 0.0.1
Maintainer: Zsolt T. Kosztyan <kosztyan.zsolt@gtk.uni-pannon.hu>
Description: Computes Control limits, coefficients of control limits, various performance metrics and depicts control charts for monitoring Maxwell-distributed quality characteristics.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
URL: https://github.com/kzst/mxcc
Depends: R (>= 4.00), chi, stats, shotGroups, graphics
NeedsCompilation: no
Packaged: 2024-10-27 11:56:20 UTC; kzst
Author: Zahid Khan [aut], Zsolt T. Kosztyan [aut, cre]
Repository: CRAN
Date/Publication: 2024-10-29 20:30:06 UTC

More information about mxcc at CRAN
Permanent link

Package manynet updated to version 1.3.1 with previous version 1.2.6 dated 2024-10-05

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>

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Package ordinalForest updated to version 2.4-4 with previous version 2.4-3 dated 2022-11-30

Title: Ordinal Forests: Prediction and Variable Ranking with Ordinal Target Variables
Description: The ordinal forest (OF) method allows ordinal regression with high-dimensional and low-dimensional data. After having constructed an OF prediction rule using a training dataset, it can be used to predict the values of the ordinal target variable for new observations. Moreover, by means of the (permutation-based) variable importance measure of OF, it is also possible to rank the covariates with respect to their importance in the prediction of the values of the ordinal target variable. OF is presented in Hornung (2020). NOTE: Starting with package version 2.4, it is also possible to obtain class probability predictions in addition to the class point predictions. Moreover, the variable importance values can also be based on the class probability predictions. Preliminary results indicate that this might lead to a better discrimination between influential and non-influential covariates. The main functions of the package are: ordfor() (construction of OF) and predict.ordfor() (prediction of [...truncated...]
Author: Roman Hornung [aut, cre]
Maintainer: Roman Hornung <hornung@ibe.med.uni-muenchen.de>

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Package nlmixr2extra updated to version 3.0.1 with previous version 3.0.0 dated 2024-09-18

Title: Nonlinear Mixed Effects Models in Population PK/PD, Extra Support Functions
Description: Fit and compare nonlinear mixed-effects models in differential equations with flexible dosing information commonly seen in pharmacokinetics and pharmacodynamics (Almquist, Leander, and Jirstrand 2015 <doi:10.1007/s10928-015-9409-1>). Differential equation solving is by compiled C code provided in the 'rxode2' package (Wang, Hallow, and James 2015 <doi:10.1002/psp4.12052>). This package is for support functions like preconditioned fits <doi:10.1208/s12248-016-9866-5>, boostrap and stepwise covariate selection.
Author: Matthew Fidler [aut, cre] , Vipul Mann [aut], Vishal Sarsani [aut] , Christian Bartels [ctb], Bill Denney [aut]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

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Package rqPen updated to version 4.1.2 with previous version 4.1.1 dated 2024-06-04

Title: Penalized Quantile Regression
Description: Performs penalized quantile regression with LASSO, elastic net, SCAD and MCP penalty functions including group penalties. In addition, offers a group penalty that provides consistent variable selection across quantiles. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC. Below URL provides a link to a work in progress vignette.
Author: Ben Sherwood [aut, cre], Shaobo Li [aut], Adam Maidman [aut]
Maintainer: Ben Sherwood <ben.sherwood@ku.edu>

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Package ggseqplot updated to version 0.8.5 with previous version 0.8.4 dated 2024-05-17

Title: Render Sequence Plots using 'ggplot2'
Description: A set of wrapper functions that mainly re-produces most of the sequence plots rendered with TraMineR::seqplot(). Whereas 'TraMineR' uses base R to produce the plots this library draws on 'ggplot2'. The plots are produced on the basis of a sequence object defined with TraMineR::seqdef(). The package automates the reshaping and plotting of sequence data. Resulting plots are of class 'ggplot', i.e. components can be added and tweaked using '+' and regular 'ggplot2' functions.
Author: Marcel Raab [aut, cre]
Maintainer: Marcel Raab <marcel.raab@gmail.com>

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Package MCARtest updated to version 1.2.2 with previous version 1.2.1 dated 2024-03-22

Title: Optimal Nonparametric Testing of Missing Completely at Random
Description: Provides functions for carrying out nonparametric hypothesis tests of the MCAR hypothesis based on the theory of Frechet classes and compatibility. Also gives functions for computing halfspace representations of the marginal polytope and related geometric objects.
Author: Thomas B. Berrett [aut, cre] , Alberto Bordino [aut], Danat Duisenbekov [aut], Sean Jaffe [aut], Richard J. Samworth [aut]
Maintainer: Thomas B. Berrett <tom.berrett@warwick.ac.uk>

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Package rstpm2 updated to version 1.6.6 with previous version 1.6.5 dated 2024-08-20

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

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Package reactable.extras updated to version 0.2.1 with previous version 0.2.0 dated 2023-11-23

Title: Extra Features for 'reactable' Package
Description: Enhanced functionality for 'reactable' in 'shiny' applications, offering interactive and dynamic data table capabilities with ease. With 'reactable.extras', easily integrate a range of functions and components to enrich your 'shiny' apps and facilitate user-friendly data exploration.
Author: Recle Vibal [aut, cre], Ivan Hrychaniuk [aut], Andres Quintero [aut], Pedro Silva [aut], Eduardo Almeida [ctb], Appsilon Sp. z o.o. [cph]
Maintainer: Recle Vibal <opensource+recle@appsilon.com>

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Package RcmdrPlugin.DoE updated to version 0.12-6 with previous version 0.12-5 dated 2023-10-07

Title: R Commander Plugin for (Industrial) Design of Experiments
Description: Provides a platform-independent GUI for design of experiments. The package is implemented as a plugin to the R-Commander, which is a more general graphical user interface for statistics in R based on tcl/tk. DoE functionality can be accessed through the menu Design that is added to the R-Commander menus.
Author: Ulrike Groemping [aut, cre], Fox John [ctb]
Maintainer: Ulrike Groemping <ulrike.groemping@bht-berlin.de>

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Package microeco updated to version 1.10.0 with previous version 1.9.1 dated 2024-08-23

Title: Microbial Community Ecology Data Analysis
Description: A series of statistical and plotting approaches in microbial community ecology based on the R6 class. The classes are designed for data preprocessing, taxa abundance plotting, alpha diversity analysis, beta diversity analysis, differential abundance test, null model analysis, network analysis, machine learning, environmental data analysis and functional analysis.
Author: Chi Liu [aut, cre], Felipe R. P. Mansoldo [ctb], Minjie Yao [ctb], Xiangzhen Li [ctb]
Maintainer: Chi Liu <liuchi0426@126.com>

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Package biostat3 updated to version 0.2.2 with previous version 0.2.1 dated 2024-08-19

Title: Utility Functions, Datasets and Extended Examples for Survival Analysis
Description: Utility functions, datasets and extended examples for survival analysis. This extends a range of other packages, some simple wrappers for time-to-event analyses, datasets, and extensive examples in HTML with R scripts. The package also supports the course Biostatistics III entitled "Survival analysis for epidemiologists in R".
Author: Annika Tillander [ctb], Andreas Karlsson [aut], Johan Zetterqvist [ctb], Peter Strom [ctb], Benedicte Delcoigne [ctb], Mark Clements [aut, cre]
Maintainer: Mark Clements <mark.clements@ki.se>

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Package xplorerr updated to version 0.2.0 with previous version 0.1.2 dated 2021-05-21

Title: Tools for Interactive Data Exploration
Description: Tools for interactive data exploration built using 'shiny'. Includes apps for descriptive statistics, visualizing probability distributions, inferential statistics, linear regression, logistic regression and RFM analysis.
Author: Aravind Hebbali [aut, cre]
Maintainer: Aravind Hebbali <hebbali.aravind@gmail.com>

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Package rspm updated to version 0.6.1 with previous version 0.6.0 dated 2024-06-21

Title: 'RStudio' Package Manager
Description: Enables binary package installations on Linux distributions. Provides access to 'RStudio' public repositories at <https://packagemanager.posit.co>, and transparent management of system requirements without administrative privileges. Currently supported distributions are 'CentOS' / 'RHEL' 7-9, and several 'RHEL' derivatives ('Rocky Linux', 'AlmaLinux', 'Oracle Linux', and 'Amazon Linux'), 'openSUSE' / 'SLES' 15.4-5, 'Debian' 11-12, and 'Ubuntu' LTS 20-22.
Author: Inaki Ucar [aut, cph, cre] , R Core Team [aut, cph]
Maintainer: Inaki Ucar <iucar@fedoraproject.org>

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Package QuadratiK updated to version 1.1.2 with previous version 1.1.1 dated 2024-06-05

Title: Collection of Methods Constructed using Kernel-Based Quadratic Distances
Description: It includes test for multivariate normality, test for uniformity on the d-dimensional Sphere, non-parametric two- and k-sample tests, random generation of points from the Poisson kernel-based density and clustering algorithm for spherical data. For more information see Saraceno G., Markatou M., Mukhopadhyay R. and Golzy M. (2024) <doi:10.48550/arXiv.2402.02290> Markatou, M. and Saraceno, G. (2024) <doi:10.48550/arXiv.2407.16374>, Ding, Y., Markatou, M. and Saraceno, G. (2023) <doi:10.5705/ss.202022.0347>, and Golzy, M. and Markatou, M. (2020) <doi:10.1080/10618600.2020.1740713>.
Author: Giovanni Saraceno [aut, cre] , Marianthi Markatou [aut], Raktim Mukhopadhyay [aut], Mojgan Golzy [aut]
Maintainer: Giovanni Saraceno <gsaracen@buffalo.edu>

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Package DisaggregateTS updated to version 3.0.0 with previous version 2.0.0 dated 2022-05-30

Title: High-Dimensional Temporal Disaggregation
Description: Provides tools for temporal disaggregation, including: (1) High-dimensional and low-dimensional series generation for simulation studies; (2) A toolkit for temporal disaggregation and benchmarking using low-dimensional indicator series as proposed by Dagum and Cholette (2006, ISBN:978-0-387-35439-2); (3) Novel techniques by Mosley, Gibberd, and Eckley (2022, <doi:10.1111/rssa.12952>) for disaggregating low-frequency series in the presence of high-dimensional indicator matrices.
Author: Kaveh Salehzadeh Nobari [aut, cre], Luke Mosley [aut]
Maintainer: Kaveh Salehzadeh Nobari <k.salehzadeh-nobari@imperial.ac.uk>

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New package TMTI with initial version 1.0.3
Package: TMTI
Title: Too Many, Too Improbable (TMTI) Test Procedures
Version: 1.0.3
Author: Phillip B. Mogensen [aut, cre]
Maintainer: Phillip B. Mogensen <pbm@math.ku.dk>
Description: Methods for computing joint tests, controlling the Familywise Error Rate (FWER) and getting lower bounds on the number of false hypotheses in a set. The methods implemented here are described in Mogensen and Markussen (2021) <doi:10.48550/arXiv.2108.04731>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats, Rcpp
Suggests: parallel
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2024-10-25 22:12:23 UTC; phillipbredahl
Repository: CRAN
Date/Publication: 2024-10-29 09:30:02 UTC

More information about TMTI at CRAN
Permanent link

Package FinNet updated to version 0.2 with previous version 0.1.2 dated 2023-08-10

Title: Quickly Build and Manipulate Financial Networks
Description: Providing classes, methods, and functions to deal with financial networks. Users can easily store information about both physical and legal persons by using pre-made classes that are studied for integration with scraping packages such as 'rvest' and 'RSelenium'. Moreover, the package assists in creating various types of financial networks depending on the type of relation between its units depending on the relation under scrutiny (ownership, board interlocks, etc.), the desired tie type (valued or binary), and renders them in the most common formats (adjacency matrix, incidence matrix, edge list, 'igraph', 'network'). There are also ad-hoc functions for the Fiedler value, global network efficiency, and cascade-failure analysis.
Author: Fabio Ashtar Telarico [aut, cre]
Maintainer: Fabio Ashtar Telarico <Fabio-Ashtar.Telarico@fdv.uni-lj.si>

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Package TDApplied updated to version 3.0.4 with previous version 3.0.3 dated 2024-03-12

Title: Machine Learning and Inference for Topological Data Analysis
Description: Topological data analysis is a powerful tool for finding non-linear global structure in whole datasets. The main tool of topological data analysis is persistent homology, which computes a topological shape descriptor of a dataset called a persistence diagram. 'TDApplied' provides useful and efficient methods for analyzing groups of persistence diagrams with machine learning and statistical inference, and these functions can also interface with other data science packages to form flexible and integrated topological data analysis pipelines.
Author: Shael Brown [aut, cre], Dr. Reza Farivar [aut, fnd]
Maintainer: Shael Brown <shaelebrown@gmail.com>

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Package sfaR updated to version 1.0.1 with previous version 1.0.0 dated 2023-07-04

Title: Stochastic Frontier Analysis Routines
Description: Maximum likelihood estimation for stochastic frontier analysis (SFA) of production (profit) and cost functions. The package includes the basic stochastic frontier for cross-sectional or pooled data with several distributions for the one-sided error term (i.e., Rayleigh, gamma, Weibull, lognormal, uniform, generalized exponential and truncated skewed Laplace), the latent class stochastic frontier model (LCM) as described in Dakpo et al. (2021) <doi:10.1111/1477-9552.12422>, for cross-sectional and pooled data, and the sample selection model as described in Greene (2010) <doi:10.1007/s11123-009-0159-1>, and applied in Dakpo et al. (2021) <doi:10.1111/agec.12683>. Several possibilities in terms of optimization algorithms are proposed.
Author: K Herve Dakpo [aut, cre], Yann Desjeux [aut], Arne Henningsen [aut], Laure Latruffe [aut]
Maintainer: K Herve Dakpo <k-herve.dakpo@inrae.fr>

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Package rminer updated to version 1.4.8 with previous version 1.4.7 dated 2024-10-23

Title: Data Mining Classification and Regression Methods
Description: Facilitates the use of data mining algorithms in classification and regression (including time series forecasting) tasks by presenting a short and coherent set of functions. Versions: 1.4.8 improved help, several warning and error code fixes (more stable version, all examples run correctly); 1.4.7 improved Importance function and examples, minor error fixes; 1.4.6 / 1.4.5 / 1.4.4 new automated machine learning (AutoML) and ensembles, via improved fit(), mining() and mparheuristic() functions, and new categorical preprocessing, via improved delevels() function; 1.4.3 new metrics (e.g., macro precision, explained variance), new "lssvm" model and improved mparheuristic() function; 1.4.2 new "NMAE" metric, "xgboost" and "cv.glmnet" models (16 classification and 18 regression models); 1.4.1 new tutorial and more robust version; 1.4 - new classification and regression models, with a total of 14 classification and 15 regression methods, including: Decision Trees, Neural Networks, Support Vect [...truncated...]
Author: Paulo Cortez [aut, cre]
Maintainer: Paulo Cortez <pcortez@dsi.uminho.pt>

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Package gtfsrouter updated to version 0.1.3 with previous version 0.1.2 dated 2023-09-23

Title: Routing with 'GTFS' (General Transit Feed Specification) Data
Description: Use 'GTFS' (General Transit Feed Specification) data for routing from nominated start and end stations, for extracting 'isochrones', and travel times from any nominated start station to all other stations.
Author: Mark Padgham [aut, cre], Marcin Stepniak [aut] , Alexandra Kapp [ctb]
Maintainer: Mark Padgham <mark.padgham@email.com>

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Package ECG updated to version 0.5.2 with previous version 0.5.1 dated 2024-10-22

Title: Center of Gravity Methods
Description: Implementation of the Centre of Gravity method and the Extrapolated Centre of Gravity method. It supports replicated observations. Cameron, D.G., et al (1982) <doi:10.1366/0003702824638610> JCGM (2008) <doi:10.59161/JCGM100-2008E>.
Author: Hugo Gasca-Aragon [aut, cre]
Maintainer: Hugo Gasca-Aragon <hugo_gasca_aragon@hotmail.com>

Diff between ECG versions 0.5.1 dated 2024-10-22 and 0.5.2 dated 2024-10-29

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Package Directional updated to version 6.9 with previous version 6.8 dated 2024-09-09

Title: A Collection of Functions for Directional Data Analysis
Description: A collection of functions for directional data (including massive data, with millions of observations) analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). Other references include a) Phillip J. Paine, Simon P. Preston, Michail Tsagris and Andrew T. A. Wood (2018). "An elliptically symmetric angular Gaussian distribution". Statistics and Computing 28(3): 689-697. <doi:10.1007/s11222-017-9756-4>. b) Tsagris M. and Alenazi A. (2019). "Comparison of discriminant analysis methods on the sphere". Communications in Statistics: Case Studies, Data Analysis and Applications 5(4):467--491. <doi:10.1080/23737484.2019.1684854>. c) P. J. Paine, S. P. Preston, M. Tsagris and Andrew T. A. Wood (2020). "Spherical regression models with general covariates and anisotropic errors". Statistics and Computing 30(1): 153--165. < [...truncated...]
Author: Michail Tsagris [aut, cre], Giorgos Athineou [aut], Christos Adam [aut], Zehao Yu [aut], Anamul Sajib [ctb], Eli Amson [ctb], Micah J. Waldstein [ctb], Panagiotis Papastamoulis [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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New package dhis2r with initial version 0.2.0
Package: dhis2r
Title: Client for the 'DHIS2' Web API
Version: 0.2.0
Description: Connect and pull data from a 'DHIS2 (District Health Information Software 2)' instance into R.
License: MIT + file LICENSE
URL: https://github.com/amanyiraho/dhis2r
BugReports: https://github.com/amanyiraho/dhis2r/issues
Imports: attempt (>= 0.3.1), curl (>= 4.3.3), dplyr (>= 1.0.10), httr2 (>= 0.2.2), R6 (>= 2.5.1)
Suggests: covr, knitr, rmarkdown, testthat
Depends: R (>= 4.1.0)
Encoding: UTF-8
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2024-10-28 21:32:42 UTC; am
Author: Robinson Amanyiraho [cre, aut, cph]
Maintainer: Robinson Amanyiraho <amanyiraho@gmail.com>
Repository: CRAN
Date/Publication: 2024-10-29 08:20:02 UTC

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Package statgenMPP updated to version 1.0.3 with previous version 1.0.2 dated 2022-12-02

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: Martin Boer [aut] , Wenhao Li [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 TLIC updated to version 0.3 with previous version 0.2 dated 2024-09-25

Title: The LIC for T Distribution Regression Analysis
Description: This comprehensive toolkit for T-distributed regression is designated as "TLIC" (The LIC for T Distribution Regression Analysis) analysis. It is predicated on the assumption that the error term adheres to a T-distribution. The philosophy of the package is described in Guo G. (2020) <doi:10.1080/02664763.2022.2053949>.
Author: Guangbao Guo [aut, cre] , Guofu Jing [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>

Diff between TLIC versions 0.2 dated 2024-09-25 and 0.3 dated 2024-10-29

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Package progressr updated to version 0.15.0 with previous version 0.14.0 dated 2023-08-10

Title: An Inclusive, Unifying API for Progress Updates
Description: A minimal, unifying API for scripts and packages to report progress updates from anywhere including when using parallel processing. The package is designed such that the developer can to focus on what progress should be reported on without having to worry about how to present it. The end user has full control of how, where, and when to render these progress updates, e.g. in the terminal using utils::txtProgressBar(), cli::cli_progress_bar(), in a graphical user interface using utils::winProgressBar(), tcltk::tkProgressBar() or shiny::withProgress(), via the speakers using beepr::beep(), or on a file system via the size of a file. Anyone can add additional, customized, progression handlers. The 'progressr' package uses R's condition framework for signaling progress updated. Because of this, progress can be reported from almost anywhere in R, e.g. from classical for and while loops, from map-reduce API:s like the lapply() family of functions, 'purrr', 'plyr', and 'foreach'. It will als [...truncated...]
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between progressr versions 0.14.0 dated 2023-08-10 and 0.15.0 dated 2024-10-29

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Package dapper updated to version 1.0.1 with previous version 1.0.0 dated 2024-07-09

Title: Data Augmentation for Private Posterior Estimation
Description: A data augmentation based sampler for conducting privacy-aware Bayesian inference. The dapper_sample() function takes an existing sampler as input and automatically constructs a privacy-aware sampler. The process of constructing a sampler is simplified through the specification of four independent modules, allowing for easy comparison between different privacy mechanisms by only swapping out the relevant modules. Probability mass functions for the discrete Gaussian and discrete Laplacian are provided to facilitate analyses dealing with privatized count data. The output of dapper_sample() can be analyzed using many of the same tools from the 'rstan' ecosystem. For methodological details on the sampler see Ju et al. (2022) <doi:10.48550/arXiv.2206.00710>, and for details on the discrete Gaussian and discrete Laplacian distributions see Canonne et al. (2020) <doi:10.48550/arXiv.2004.00010>.
Author: Kevin Eng [aut, cre, cph]
Maintainer: Kevin Eng <kevine1221@gmail.com>

Diff between dapper versions 1.0.0 dated 2024-07-09 and 1.0.1 dated 2024-10-29

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