Thu, 12 Dec 2024

Package slca updated to version 1.3.0 with previous version 1.2.0 dated 2024-11-01

Title: Structural Modeling for Multiple Latent Class Variables
Description: Provides comprehensive tools for the implementation of Structural Latent Class Models (SLCM), including Latent Transition Analysis (LTA; Linda M. Collins and Stephanie T. Lanza, 2009) <doi:10.1002/9780470567333>, Latent Class Profile Analysis (LCPA; Hwan Chung et al., 2010) <doi:10.1111/j.1467-985x.2010.00674.x>, and Joint Latent Class Analysis (JLCA; Saebom Jeon et al., 2017) <doi:10.1080/10705511.2017.1340844>, and any other extended models involving multiple latent class variables.
Author: Youngsun Kim [aut, cre] , Hwan Chung [aut]
Maintainer: Youngsun Kim <yskstat@gmail.com>

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Package economiccomplexity updated to version 2.0.0 with previous version 1.5.0 dated 2023-08-07

Title: Computational Methods for Economic Complexity
Description: A wrapper of different methods from Linear Algebra for the equations introduced in The Atlas of Economic Complexity and related literature. This package provides standard matrix and graph output that can be used seamlessly with other packages. See <doi:10.21105/joss.01866> for a summary of these methods and its evolution in literature.
Author: Mauricio Vargas Sepulveda [aut, cre, cph] , Carlo Bottai [ctb] , Diego Kozlowski [ctb] , Nico Pintar [rev] , The World Bank [dtc] , Open Trade Statistics [dtc]
Maintainer: Mauricio Vargas Sepulveda <m.sepulveda@mail.utoronto.ca>

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Package h3r updated to version 0.1.2 with previous version 0.1.1 dated 2024-03-12

Title: Hexagonal Hierarchical Geospatial Indexing System
Description: Provides access to Uber's 'H3' geospatial indexing system via 'h3lib' <https://CRAN.R-project.org/package=h3lib>. 'h3r' is designed to mimic the 'H3' Application Programming Interface (API) <https://h3geo.org/docs/api/indexing/>, so that any function in the API is also available in 'h3r'.
Author: David Cooley [aut, cre], Ray Shao [aut]
Maintainer: David Cooley <dcooley@symbolix.com.au>

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Package psc updated to version 1.1.0 with previous version 1.0.0 dated 2024-11-20

Title: Personalised Synthetic Controls
Description: Allows the comparison of data cohorts (DC) against a Counter Factual Model (CFM) and measures the difference in terms of an efficacy parameter. Allows the application of Personalised Synthetic Controls.
Author: Richard Jackson [cre, aut]
Maintainer: Richard Jackson <richJ23@liverpool.ac.uk>

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Package emmeans updated to version 1.10.6 with previous version 1.10.5 dated 2024-10-14

Title: Estimated Marginal Means, aka Least-Squares Means
Description: Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Author: Russell V. Lenth [aut, cre, cph], Balazs Banfai [ctb], Ben Bolker [ctb], Paul Buerkner [ctb], Iago Gine-Vazquez [ctb], Maxime Herve [ctb], Maarten Jung [ctb], Jonathon Love [ctb], Fernando Miguez [ctb], Julia Piaskowski [ctb], Hannes Riebl [ctb], Hen [...truncated...]
Maintainer: Russell V. Lenth <russell-lenth@uiowa.edu>

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Package enderecobr updated to version 0.3.0 with previous version 0.2.1 dated 2024-11-18

Title: Padronizador de Endereços Brasileiros (Brazilian Addresses Standardizer)
Description: Padroniza endereços brasileiros a partir de diferentes critérios. Os métodos de padronização incluem apenas manipulações básicas de strings, não oferecendo suporte a correspondências probabilísticas entre strings. (Standardizes brazilian addresses using different criteria. Standardization methods include only basic string manipulation, not supporting probabilistic matches between strings.)
Author: Daniel Herszenhut [aut, cre] , Rafael H. M. Pereira [aut] , Lucas Mation [aut]
Maintainer: Daniel Herszenhut <dhersz@gmail.com>

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Package options updated to version 0.3.0 with previous version 0.2.0 dated 2024-05-12

Title: Simple, Consistent Package Options
Description: Simple mechanisms for defining and interpreting package options. Provides helpers for interpreting environment variables, global options, defining default values and more.
Author: Doug Kelkhoff [aut, cre]
Maintainer: Doug Kelkhoff <doug.kelkhoff@gmail.com>

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Package HQM updated to version 0.1.4 with previous version 0.1.2 dated 2024-12-04

Title: Superefficient Estimation of Future Conditional Hazards Based on Marker Information
Description: Provides a nonparametric smoothed kernel density estimator for the future conditional hazard when time-dependent covariates are present. It also provides pointwise and uniform confidence bands and a bandwidth selection.
Author: Dimitrios Bagkavos [aut, cre], Alex Isakson [ctb], Enno Mammen [ctb], Jens Nielsen [ctb], Cecile Proust-Lima [ctb]
Maintainer: Dimitrios Bagkavos <dimitrios.bagkavos@gmail.com>

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Package coursekata updated to version 0.18.1 with previous version 0.18.0 dated 2024-08-16

Title: Packages and Functions for 'CourseKata' Courses
Description: Easily install and load all packages and functions used in 'CourseKata' courses. Aid teaching with helper functions and augment generic functions to provide cohesion between the network of packages. Learn more about 'CourseKata' at <https://coursekata.org>.
Author: Adam Blake [cre, aut] , Ji Son [aut] , Jim Stigler [aut]
Maintainer: Adam Blake <adam@coursekata.org>

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Package PatientProfiles updated to version 1.2.3 with previous version 1.2.2 dated 2024-11-28

Title: Identify Characteristics of Patients in the OMOP Common Data Model
Description: Identify the characteristics of patients in data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model.
Author: Marti Catala [aut, cre] , Yuchen Guo [aut] , Mike Du [aut] , Kim Lopez-Guell [aut] , Edward Burn [aut] , Nuria Mercade-Besora [aut] , Xintong Li [ctb] , Xihang Chen [ctb]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>

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Package FPDclustering updated to version 2.3.2 with previous version 2.3.1 dated 2024-01-29

Title: PD-Clustering and Related Methods
Description: Probabilistic distance clustering (PD-clustering) is an iterative, distribution-free, probabilistic clustering method. PD-clustering assigns units to a cluster according to their probability of membership under the constraint that the product of the probability and the distance of each point to any cluster center is a constant. PD-clustering is a flexible method that can be used with elliptical clusters, outliers, or noisy data. PDQ is an extension of the algorithm for clusters of different sizes. GPDC and TPDC use a dissimilarity measure based on densities. Factor PD-clustering (FPDC) is a factor clustering method that involves a linear transformation of variables and a cluster optimizing the PD-clustering criterion. It works on high-dimensional data sets.
Author: Cristina Tortora [aut, cre, cph], Noe Vidales [aut], Francesco Palumbo [aut], Tina Kalra [aut], Paul D. McNicholas [fnd]
Maintainer: Cristina Tortora <grikris1@gmail.com>

Diff between FPDclustering versions 2.3.1 dated 2024-01-29 and 2.3.2 dated 2024-12-12

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New package pprof with initial version 1.0.1
Package: pprof
Title: Modeling, Standardization and Testing for Provider Profiling
Version: 1.0.1
Date: 2024-11-18
Description: Implements linear and generalized linear models for provider profiling, incorporating both fixed and random effects. For large-scale providers, the linear profiled-based method and the SerBIN method for binary data reduce the computational burden. Provides post-modeling features, such as indirect and direct standardization measures, hypothesis testing, confidence intervals, and post-estimation visualization. For more information, see Wu et al. (2022) <doi:10.1002/sim.9387>.
License: MIT + file LICENSE
LazyData: true
Imports: Rcpp, RcppParallel, stats, caret, olsrr, pROC, poibin, dplyr, ggplot2, Matrix, lme4, magrittr, scales, tibble, rlang
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Depends: R (>= 4.1.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/UM-KevinHe/pprof
Encoding: UTF-8
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2024-12-11 16:15:37 UTC; emily
Author: Xiaohan Liu [aut, cre], Lingfeng Luo [aut], Yubo Shao [aut], Xiangeng Fang [aut], Wenbo Wu [aut], Kevin He [aut]
Maintainer: Xiaohan Liu <xhliuu@umich.edu>
Repository: CRAN
Date/Publication: 2024-12-12 15:10:02 UTC

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New package orderanalyzer with initial version 1.0.0
Package: orderanalyzer
Title: Extracting Order Position Tables from PDF-Based Order Documents
Version: 1.0.0
Date: 2024-12-11
Maintainer: Michael Scholz <michael.scholz@th-deg.de>
Description: Functions for extracting text and tables from PDF-based order documents. It provides an n-gram-based approach for identifying the language of an order document. It furthermore uses R-package 'pdftools' to extract the text from an order document. In the case that the PDF document is only including an image (because it is scanned document), R package 'tesseract' is used for OCR. Furthermore, the package provides functionality for identifying and extracting order position tables in order documents based on a clustering approach.
License: GPL-3
SystemRequirements: Tesseract >= 5.0.0, libtesseract-dev (deb), tesseract-devel (rpm), libleptonica-dev (deb), leptonica-devel (rpm), tesseract-ocr-eng (deb), libpoppler-cpp-dev (deb), poppler-cpp-devel (rpm), poppler-data (rpm/deb), libxml2-dev (deb), libxml2-devel (rpm)
Depends: R(>= 4.3.0), tidyselect
Imports: data.table, dplyr, matrixcalc, quanteda, rlist, stringr, tibble, tidyr, utils, purrr, digest, lubridate
Suggests: pdftools, tesseract, xml2
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-12-11 16:46:01 UTC; mscholz
Author: Michael Scholz [cre, aut], Joerg Bauer [aut]
Repository: CRAN
Date/Publication: 2024-12-12 15:20:02 UTC

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New package moRphomenses with initial version 1.0.2
Package: moRphomenses
Title: Geometric Morphometric Tools to Align, Scale, and Compare "Shape" of Menstrual Cycle Hormones
Version: 1.0.2
Description: Mitteroecker & Gunz (2009) <doi:10.1007/s11692-009-9055-x> describe how geometric morphometric methods allow researchers to quantify the size and shape of physical biological structures. We provide tools to extend geometric morphometric principles to the study of non-physical structures, hormone profiles, as outlined in Ehrlich et al (2021) <doi:10.1002/ajpa.24514>. Easily transform daily measures into multivariate landmark-based data. Includes custom functions to apply multivariate methods for data exploration as well as hypothesis testing. Also includes 'shiny' web app to streamline data exploration. Developed to study menstrual cycle hormones but functions have been generalized and should be applicable to any biomarker over any time period.
License: GPL (>= 3.0)
URL: <https://github.com/ClancyLabUIUC/moRphomenses>
Depends: R (>= 2.10)
Imports: stats, graphics, grDevices, utils
Encoding: UTF-8
LazyData: true
Suggests: dendextend, geomorph, cluster, shiny
NeedsCompilation: no
Packaged: 2024-12-11 16:00:38 UTC; ehrli097
Author: Daniel Ehrlich [aut, cre]
Maintainer: Daniel Ehrlich <dan.ehrlich.e@gmail.com>
Repository: CRAN
Date/Publication: 2024-12-12 15:10:07 UTC

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New package ConjointChecks with initial version 0.2.0
Package: ConjointChecks
Title: Implementation of a Method to Check the Cancellation Axioms of Additive Conjoint Measurement
Version: 0.2.0
Date: 2024-12-02
Maintainer: Ben Domingue <ben.domingue@gmail.com>
Depends: R (>= 4.3), parallel, methods,
Suggests:
Description: Implementation of a procedure---Domingue (2012) <https://eric.ed.gov/?id=ED548657>, Domingue (2014) <doi:10.1007/s11336-013-9342-4>; see also Karabatsos (2001) <https://psycnet.apa.org/record/2002-01665-005> and Kyngdon (2011) <doi:10.1348/2044-8317.002004>---to test the single and double cancellation axioms of conjoint measure in data that is dichotomously coded and measured with error.
URL: https://github.com/ben-domingue/ConjointChecks
LazyData: Yes
Imports: Rcpp
LinkingTo: Rcpp
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2024-12-11 16:40:37 UTC; bdomingu
Author: Ben Domingue [aut, cre], Liam Fox [ctb], Vithor Franco [ctb]
Repository: CRAN
Date/Publication: 2024-12-12 15:20:06 UTC

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Package CompareTests updated to version 1.3 with previous version 1.2 dated 2017-02-06

Title: Correct for Verification Bias in Diagnostic Accuracy & Agreement
Description: A standard test is observed on all specimens. We treat the second test (or sampled test) as being conducted on only a stratified sample of specimens. Verification Bias is this situation when the specimens for doing the second (sampled) test is not under investigator control. We treat the total sample as stratified two-phase sampling and use inverse probability weighting. We estimate diagnostic accuracy (category-specific classification probabilities; for binary tests reduces to specificity and sensitivity, and also predictive values) and agreement statistics (percent agreement, percent agreement by category, Kappa (unweighted), Kappa (quadratic weighted) and symmetry tests (reduces to McNemar's test for binary tests)). See: Katki HA, Li Y, Edelstein DW, Castle PE. Estimating the agreement and diagnostic accuracy of two diagnostic tests when one test is conducted on only a subsample of specimens. Stat Med. 2012 Feb 28; 31(5) <doi:10.1002/sim.4422>.
Author: Hormuzd A. Katki [aut], David W. Edelstein [aut], Hormuzd Katki [cre]
Maintainer: Hormuzd Katki <katkih@mail.nih.gov>

Diff between CompareTests versions 1.2 dated 2017-02-06 and 1.3 dated 2024-12-12

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Package clusterMI updated to version 1.3 with previous version 1.2.2 dated 2024-10-23

Title: Cluster Analysis with Missing Values by Multiple Imputation
Description: Allows clustering of incomplete observations by addressing missing values using multiple imputation. For achieving this goal, the methodology consists in three steps, following Audigier and Niang 2022 <doi:10.1007/s11634-022-00519-1>. I) Missing data imputation using dedicated models. Four multiple imputation methods are proposed, two are based on joint modelling and two are fully sequential methods, as discussed in Audigier et al. (2021) <doi:10.48550/arXiv.2106.04424>. II) cluster analysis of imputed data sets. Six clustering methods are available (distances-based or model-based), but custom methods can also be easily used. III) Partition pooling. The set of partitions is aggregated using Non-negative Matrix Factorization based method. An associated instability measure is computed by bootstrap (see Fang, Y. and Wang, J., 2012 <doi:10.1016/j.csda.2011.09.003>). Among applications, this instability measure can be used to choose a number of clusters with missing value [...truncated...]
Author: Vincent Audigier [aut, cre] , Hang Joon Kim [ctb]
Maintainer: Vincent Audigier <vincent.audigier@cnam.fr>

Diff between clusterMI versions 1.2.2 dated 2024-10-23 and 1.3 dated 2024-12-12

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New package TauStar with initial version 1.1.7
Package: TauStar
Title: Efficient Computation and Testing of the Bergsma-Dassios Sign Covariance
Version: 1.1.7
Date: 2024-12-11
Description: Computes the t* statistic corresponding to the tau* population coefficient introduced by Bergsma and Dassios (2014) <DOI:10.3150/13-BEJ514> and does so in O(n^2) time following the algorithm of Heller and Heller (2016) <DOI:10.48550/arXiv.1605.08732> building off of the work of Weihs, Drton, and Leung (2016) <DOI:10.1007/s00180-015-0639-x>. Also allows for independence testing using the asymptotic distribution of t* as described by Nandy, Weihs, and Drton (2016) <DOI:10.1214/16-EJS1166>.
License: GPL (>= 3)
Imports: Rcpp (>= 1.0.1)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2024-12-11 13:27:31 UTC; karch
Author: Luca Weihs [aut], Emin Martinian [ctb] , Julian D. Karch [cre]
Maintainer: Julian D. Karch <j.d.karch@fsw.leidenuniv.nl>
Repository: CRAN
Date/Publication: 2024-12-12 15:00:02 UTC

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Package PHEindicatormethods updated to version 2.1.0 with previous version 2.0.2 dated 2024-01-25

Title: Common Public Health Statistics and their Confidence Intervals
Description: Functions to calculate commonly used public health statistics and their confidence intervals using methods approved for use in the production of Public Health England indicators such as those presented via Fingertips (<https://fingertips.phe.org.uk/>). It provides functions for the generation of proportions, crude rates, means, directly standardised rates, indirectly standardised rates, standardised mortality ratios, slope and relative index of inequality and life expectancy. Statistical methods are referenced in the following publications. Breslow NE, Day NE (1987) <doi:10.1002/sim.4780080614>. Dobson et al (1991) <doi:10.1002/sim.4780100317>. Armitage P, Berry G (2002) <doi:10.1002/9780470773666>. Wilson EB. (1927) <doi:10.1080/01621459.1927.10502953>. Altman DG et al (2000, ISBN: 978-0-727-91375-3). Chiang CL. (1968, ISBN: 978-0-882-75200-6). Newell C. (1994, ISBN: 978-0-898-62451-9). Eayres DP, Williams ES (2004) <doi:10.1136/jech.2003.009654>. S [...truncated...]
Author: Georgina Anderson [aut, cre], Sebastian Fox [ctb], Matthew Francis [ctb], Paul Fryers [ctb], Emma Clegg [ctb], Annabel Westermann [ctb], Joshua Woolner [ctb], Charlotte Fellows [ctb], Olivia Box Power [ctb]
Maintainer: Georgina Anderson <georgina.anderson@dhsc.gov.uk>

Diff between PHEindicatormethods versions 2.0.2 dated 2024-01-25 and 2.1.0 dated 2024-12-12

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Package depCensoring updated to version 0.1.5 with previous version 0.1.4 dated 2024-12-04

Title: Statistical Methods for Survival Data with Dependent Censoring
Description: Several statistical methods for analyzing survival data under various forms of dependent censoring are implemented in the package. In addition to accounting for dependent censoring, it offers tools to adjust for unmeasured confounding factors. The implemented approaches allow users to estimate the dependency between survival time and dependent censoring time, based solely on observed survival data. For more details on the methods, refer to Deresa and Van Keilegom (2021) <doi:10.1093/biomet/asaa095>, Czado and Van Keilegom (2023) <doi:10.1093/biomet/asac067>, Crommen et al. (2024) <doi:10.1007/s11749-023-00903-9>, Deresa and Van Keilegom (2024) <doi:10.1080/01621459.2022.2161387> and Willems et al. (2024+) <doi:10.48550/arXiv.2403.11860> and Ding and Van Keilegom (2024).
Author: Ilias Willems [aut] , Gilles Crommen [aut] , Negera Wakgari Deresa [aut, cre] , Jie Ding [aut] , Claudia Czado [aut] , Ingrid Van Keilegom [aut]
Maintainer: Negera Wakgari Deresa <negera.deresa@gmail.com>

Diff between depCensoring versions 0.1.4 dated 2024-12-04 and 0.1.5 dated 2024-12-12

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Package cocons updated to version 0.1.4 with previous version 0.1.3 dated 2024-10-15

Title: Covariate-Based Covariance Functions for Nonstationary Spatial Modeling
Description: Estimation, prediction, and simulation of nonstationary Gaussian process with modular covariate-based covariance functions. Sources of nonstationarity, such as spatial mean, variance, geometric anisotropy, smoothness, and nugget, can be considered based on spatial characteristics. An induced compact-supported nonstationary covariance function is provided, enabling fast and memory-efficient computations when handling densely sampled domains.
Author: Federico Blasi [aut, cre] , Reinhard Furrer [ctb]
Maintainer: Federico Blasi <federico.blasi@gmail.com>

Diff between cocons versions 0.1.3 dated 2024-10-15 and 0.1.4 dated 2024-12-12

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Package RODBC updated to version 1.3-26 with previous version 1.3-25.1 dated 2024-12-11

Title: ODBC Database Access
Description: An ODBC database interface.
Author: Brian Ripley [aut, cre], Michael Lapsley [aut]
Maintainer: Brian Ripley <Brian.Ripley@R-project.org>

Diff between RODBC versions 1.3-25.1 dated 2024-12-11 and 1.3-26 dated 2024-12-12

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Package rms updated to version 6.9-0 with previous version 6.8-2 dated 2024-08-23

Title: Regression Modeling Strategies
Description: Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. 'rms' is a collection of functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models, ordinal models for continuous Y with a variety of distribution families, and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. 'rms' works with almost any regression model, but it was especially written to work with binary or ordinal regression models, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.
Author: Frank E Harrell Jr [aut, cre]
Maintainer: Frank E Harrell Jr <fh@fharrell.com>

Diff between rms versions 6.8-2 dated 2024-08-23 and 6.9-0 dated 2024-12-12

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Package PublicWorksFinanceIT updated to version 0.3.1 with previous version 0.3.0 dated 2024-10-29

Title: Soil Defense Investments in Italy: Data Retrieval, Analysis, Visualization
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/>.
Author: Lorena Ricciotti [aut, cre] , Alessio Pollice [ths]
Maintainer: Lorena Ricciotti <lorena.ricciotti@uniba.it>

Diff between PublicWorksFinanceIT versions 0.3.0 dated 2024-10-29 and 0.3.1 dated 2024-12-12

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Package ganGenerativeData updated to version 2.1.4 with previous version 2.1.3 dated 2024-10-07

Title: Generate Generative Data for a Data Source
Description: Generative Adversarial Networks are applied to generate generative data for a data source. A generative model consisting of a generator and a discriminator network is trained. During iterative training the distribution of generated data is converging to that of the data source. Direct applications of generative data are the created functions for data evaluation, missing data completion and data classification. A software service for accelerated training of generative models on graphics processing units is available. Reference: Goodfellow et al. (2014) <doi:10.48550/arXiv.1406.2661>.
Author: Werner Mueller [aut, cre]
Maintainer: Werner Mueller <werner.mueller5@chello.at>

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Package glmmrBase updated to version 0.11.2 with previous version 0.11.1 dated 2024-12-09

Title: Generalised Linear Mixed Models in R
Description: Specification, analysis, simulation, and fitting of generalised linear mixed models. Includes Markov Chain Monte Carlo Maximum likelihood and Laplace approximation model fitting for a range of models, non-linear fixed effect specifications, a wide range of flexible covariance functions that can be combined arbitrarily, robust and bias-corrected standard error estimation, power calculation, data simulation, and more. See <https://samuel-watson.github.io/glmmr-web/> for a detailed manual.
Author: Sam Watson [aut, cre]
Maintainer: Sam Watson <S.I.Watson@bham.ac.uk>

Diff between glmmrBase versions 0.11.1 dated 2024-12-09 and 0.11.2 dated 2024-12-12

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More information about glmmrBase at CRAN
Permanent link

Package RJDemetra updated to version 0.2.8 with previous version 0.2.7 dated 2024-10-01

Title: Interface to 'JDemetra+' Seasonal Adjustment Software
Description: Interface around 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System (ESS) and the European System of Central Banks. It offers full access to all options and outputs of 'JDemetra+', including the two leading seasonal adjustment methods TRAMO/SEATS+ and X-12ARIMA/X-13ARIMA-SEATS.
Author: Alain Quartier-la-Tente [aut, cre] , Anna Michalek [aut], Jean Palate [aut], Raf Baeyens [aut]
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>

Diff between RJDemetra versions 0.2.7 dated 2024-10-01 and 0.2.8 dated 2024-12-12

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Package pingr updated to version 2.0.5 with previous version 2.0.4 dated 2024-10-28

Title: Check if a Remote Computer is Up
Description: Check if a remote computer is up. It can either just call the system ping command, or check a specified TCP port.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between pingr versions 2.0.4 dated 2024-10-28 and 2.0.5 dated 2024-12-12

 DESCRIPTION               |    6 +++---
 MD5                       |    8 ++++----
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More information about pingr at CRAN
Permanent link

New package mtscr with initial version 1.0.2
Package: mtscr
Title: Multidimensional Top Scoring for Creativity Research
Version: 1.0.2
Description: Implementation of Multidimensional Top Scoring method for creativity assessment proposed in Boris Forthmann, Maciej Karwowski, Roger E. Beaty (2023) <doi:10.1037/aca0000571>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/jakub-jedrusiak/mtscr
BugReports: https://github.com/jakub-jedrusiak/mtscr/issues
Depends: R (>= 4.1.0)
Imports: broom.mixed, cli, dplyr (>= 1.1.0), glmmTMB, glue, lifecycle, methods, purrr, readr, rlang (>= 0.4.11), stringr, tibble
Suggests: shiny, covr, datamods, DT, roxygen2, shinyWidgets, testthat (>= 3.0.0), withr, writexl
NeedsCompilation: no
Packaged: 2024-12-12 10:01:29 UTC; jakub
Author: Jakub Jedrusiak [aut, cre, cph] , Boris Forthmann [aut, rev] , Roger E. Beaty [aut] , Maciej Karwowski [aut]
Maintainer: Jakub Jedrusiak <jakub.jedrusiak2@uwr.edu.pl>
Repository: CRAN
Date/Publication: 2024-12-12 10:20:02 UTC

More information about mtscr at CRAN
Permanent link

Package GPvam updated to version 3.2-0 with previous version 3.1-2 dated 2024-11-17

Title: Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling
Description: An EM algorithm, Karl et al. (2013) <doi:10.1016/j.csda.2012.10.004>, is used to estimate the generalized, variable, and complete persistence models, Mariano et al. (2010) <doi:10.3102/1076998609346967>. These are multiple-membership linear mixed models with teachers modeled as "G-side" effects and students modeled with either "G-side" or "R-side" effects.
Author: Andrew Karl [cre, aut] , Yan Yang [aut], Sharon Lohr [aut]
Maintainer: Andrew Karl <akarl@asu.edu>

Diff between GPvam versions 3.1-2 dated 2024-11-17 and 3.2-0 dated 2024-12-12

 DESCRIPTION             |    8 +++---
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Package terra updated to version 1.8-5 with previous version 1.7-83 dated 2024-10-14

Title: Spatial Data Analysis
Description: Methods for spatial data analysis with vector (points, lines, polygons) and raster (grid) data. Methods for vector data include geometric operations such as intersect and buffer. Raster methods include local, focal, global, zonal and geometric operations. 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/> to get started. 'terra' replaces the 'raster' package ('terra' can do more, and it is faster and easier to use).
Author: Robert J. Hijmans [cre, aut] , Roger Bivand [ctb] , Emanuele Cordano [ctb] , Krzysztof Dyba [ctb] , Edzer Pebesma [ctb] , Michael D. Sumner [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

Diff between terra versions 1.7-83 dated 2024-10-14 and 1.8-5 dated 2024-12-12

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Package phoenics updated to version 0.4 with previous version 0.3 dated 2024-07-22

Title: Pathways Longitudinal and Differential Analysis in Metabolomics
Description: Perform a differential analysis at pathway level based on metabolite quantifications and information on pathway metabolite composition. The method is based on a Principal Component Analysis step and on a linear mixed model. Automatic query of metabolic pathways is also implemented.
Author: Camille Guilmineau [aut, cre], Remi Servien [aut] , Nathalie Vialaneix [aut]
Maintainer: Camille Guilmineau <camille.guilmineau@inrae.fr>

Diff between phoenics versions 0.3 dated 2024-07-22 and 0.4 dated 2024-12-12

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Package WeightedTreemaps updated to version 0.1.4 with previous version 0.1.3 dated 2024-11-04

Title: Generate and Plot Voronoi or Sunburst Treemaps from Hierarchical Data
Description: Treemaps are a visually appealing graphical representation of numerical data using a space-filling approach. A plane or 'map' is subdivided into smaller areas called cells. The cells in the map are scaled according to an underlying metric which allows to grasp the hierarchical organization and relative importance of many objects at once. This package contains two different implementations of treemaps, Voronoi treemaps and Sunburst treemaps. The Voronoi treemap function subdivides the plot area in polygonal cells according to the highest hierarchical level, then continues to subdivide those parental cells on the next lower hierarchical level, and so on. The Sunburst treemap is a computationally less demanding treemap that does not require iterative refinement, but simply generates circle sectors that are sized according to predefined weights. The Voronoi tesselation is based on functions from Paul Murrell (2012) <https://www.stat.auckland.ac.nz/~paul/Reports/VoronoiTreemap/voronoi [...truncated...]
Author: Michael Jahn [aut, cre] , David Leslie [aut], Ahmadou Dicko [aut] , Dunipace Eric [aut] , Paul Murrell [aut, cph]
Maintainer: Michael Jahn <jahn@mpusp.mpg.de>

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Package RoBMA updated to version 3.2.0 with previous version 3.1.0 dated 2023-07-18

Title: Robust Bayesian Meta-Analyses
Description: A framework for estimating ensembles of meta-analytic models (assuming either presence or absence of the effect, heterogeneity, and publication bias). The RoBMA framework uses Bayesian model-averaging to combine the competing meta-analytic models into a model ensemble, weights the posterior parameter distributions based on posterior model probabilities and uses Bayes factors to test for the presence or absence of the individual components (e.g., effect vs. no effect; Bartoš et al., 2022, <doi:10.1002/jrsm.1594>; Maier, Bartoš & Wagenmakers, 2022, <doi:10.1037/met0000405>). Users can define a wide range of non-informative or informative prior distributions for the effect size, heterogeneity, and publication bias components (including selection models and PET-PEESE). The package provides convenient functions for summary, visualizations, and fit diagnostics.
Author: Frantisek Bartos [aut, cre] , Maximilian Maier [aut] , Eric-Jan Wagenmakers [ths] , Joris Goosen [ctb], Matthew Denwood [cph] , Martyn Plummer [cph]
Maintainer: Frantisek Bartos <f.bartos96@gmail.com>

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New package MDFS with initial version 1.5.5
Package: MDFS
Title: MultiDimensional Feature Selection
Version: 1.5.5
Date: 2024-12-11
URL: https://www.mdfs.it/
Description: Functions for MultiDimensional Feature Selection (MDFS): calculating multidimensional information gains, scoring variables, finding important variables, plotting selection results. This package includes an optional CUDA implementation that speeds up information gain calculation using NVIDIA GPGPUs. R. Piliszek et al. (2019) <doi:10.32614/RJ-2019-019>.
Depends: R (>= 3.4.0)
License: GPL-3
SystemRequirements: C++17
NeedsCompilation: yes
Encoding: UTF-8
LazyData: true
Packaged: 2024-12-11 19:31:00 UTC; radek
Author: Radoslaw Piliszek [aut, cre], Krzysztof Mnich [aut], Pawel Tabaszewski [aut], Szymon Migacz [aut], Andrzej Sulecki [aut], Witold Remigiusz Rudnicki [aut]
Maintainer: Radoslaw Piliszek <radek@piliszek.it>
Repository: CRAN
Date/Publication: 2024-12-12 08:30:12 UTC

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Package hexfont updated to version 0.5.1 with previous version 0.4.0 dated 2023-12-18

Title: 'GNU Unifont' Hex Fonts
Description: Contains most of the hex font files from the 'GNU Unifont Project' <https://unifoundry.com/unifont/> compressed by 'xz'. 'GNU Unifont' is a duospaced bitmap font that attempts to cover all the official Unicode glyphs plus several of the artificial scripts in the '(Under-)ConScript Unicode Registry' <https://www.kreativekorp.com/ucsur/>. Provides a convenience function for loading in several of them at the same time as a 'bittermelon' bitmap font object for easy rendering of the glyphs in an 'R' terminal or graphics device.
Author: Trevor L. Davis [aut, cre] , GNU Unifont authors [cph]
Maintainer: Trevor L. Davis <trevor.l.davis@gmail.com>

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Package ExtremalDep updated to version 0.0.4-3 with previous version 0.0.4-2 dated 2024-10-06

Title: Extremal Dependence Models
Description: A set of procedures for parametric and non-parametric modelling of the dependence structure of multivariate extreme-values is provided. The statistical inference is performed with non-parametric estimators, likelihood-based estimators and Bayesian techniques. It adapts the methodologies of Beranger and Padoan (2015) <doi:10.48550/arXiv.1508.05561>, Marcon et al. (2016) <doi:10.1214/16-EJS1162>, Marcon et al. (2017) <doi:10.1002/sta4.145>, Marcon et al. (2017) <doi:10.1016/j.jspi.2016.10.004> and Beranger et al. (2021) <doi:10.1007/s10687-019-00364-0>. This package also allows for the modelling of spatial extremes using flexible max-stable processes. It provides simulation algorithms and fitting procedures relying on the Stephenson-Tawn likelihood as per Beranger at al. (2021) <doi:10.1007/s10687-020-00376-1>.
Author: Boris Beranger [aut], Simone Padoan [cre, aut], Giulia Marcon [aut], Steven G. Johnson [ctb] , Rudolf Schuerer [ctb] , Brian Gough [ctb] , Alec G. Stephenson [ctb], Anne Sabourin [ctb] , Philippe Naveau [ctb]
Maintainer: Simone Padoan <simone.padoan@unibocconi.it>

Diff between ExtremalDep versions 0.0.4-2 dated 2024-10-06 and 0.0.4-3 dated 2024-12-12

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Package VertexWiseR updated to version 1.2.0 with previous version 1.1.0 dated 2024-10-09

Title: Simplified Vertex-Wise Analyses of Whole-Brain and Hippocampal Surface
Description: Provides functions to run statistical analyses on surface-based neuroimaging data, computing measures including cortical thickness and surface area of the whole-brain and of the hippocampi. It can make use of 'FreeSurfer', 'fMRIprep' and 'HCP' preprocessed datasets and 'HippUnfold' hippocampal segmentation outputs for a given sample by restructuring the data values into a single file. The single file can then be used by the package for analyses independently from its base dataset and without need for its access.
Author: Junhong Yu [aut] , Charly Billaud [aut, cre]
Maintainer: Charly Billaud <charly.billaud@ntu.edu.sg>

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Package erfe (with last version 0.0.1) was removed from CRAN

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

2022-12-16 0.0.1

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Package PSGD (with last version 1.0.3) was removed from CRAN

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

2023-04-24 1.0.3
2022-11-22 1.0.2
2022-07-01 1.0.1
2022-03-09 1.0.0

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Package stepSplitReg (with last version 1.0.3) was removed from CRAN

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

2022-11-22 1.0.3
2022-06-26 1.0.2
2022-03-16 1.0.1
2022-03-07 1.0.0

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Package reproducible updated to version 2.1.2 with previous version 2.1.0 dated 2024-05-29

Title: Enhance Reproducibility of R Code
Description: A collection of high-level, machine- and OS-independent tools for making reproducible and reusable content in R. The two workhorse functions are Cache() and prepInputs(). Cache() allows for nested caching, is robust to environments and objects with environments (like functions), and deals with some classes of file-backed R objects e.g., from terra and raster packages. Both functions have been developed to be foundational components of data retrieval and processing in continuous workflow situations. In both functions, efforts are made to make the first and subsequent calls of functions have the same result, but faster at subsequent times by way of checksums and digesting. Several features are still under development, including cloud storage of cached objects allowing for sharing between users. Several advanced options are available, see ?reproducibleOptions().
Author: Eliot J B McIntire [aut, cre] , Alex M Chubaty [aut] , Tati Micheletti [ctb] , Ceres Barros [ctb] , Ian Eddy [ctb] , His Majesty the King in Right of Canada, as represented by the Minister of Natural Resources Canada [cph]
Maintainer: Eliot J B McIntire <eliot.mcintire@canada.ca>

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Package gptoolsStan updated to version 0.2.0 with previous version 0.1.0 dated 2023-12-19

Title: Gaussian Processes on Graphs and Lattices in 'Stan'
Description: Gaussian processes are flexible distributions to model functional data. Whilst theoretically appealing, they are computationally cumbersome except for small datasets. This package implements two methods for scaling Gaussian process inference in 'Stan'. First, a sparse approximation of the likelihood that is generally applicable and, second, an exact method for regularly spaced data modeled by stationary kernels using fast Fourier methods. Utility functions are provided to compile and fit 'Stan' models using the 'cmdstanr' interface. References: Hoffmann and Onnela (2022) <doi:10.48550/arXiv.2301.08836>.
Author: Till Hoffmann [aut, cre] , Jukka-Pekka Onnela [ctb]
Maintainer: Till Hoffmann <thoffmann@hsph.harvard.edu>

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Package srlTS (with last version 0.1.1) was removed from CRAN

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2023-12-14 0.1.1

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Package minimapR (with last version 0.0.1.0) was removed from CRAN

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

2024-07-21 0.0.1.0

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Package qs2 updated to version 0.1.4 with previous version 0.1.3 dated 2024-12-02

Title: Efficient Serialization of R Objects
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.
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]
Maintainer: Travers Ching <traversc@gmail.com>

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 src/qx_dump.h        |    9 ++++++---
 src/qx_functions.cpp |    8 +++++---
 8 files changed, 31 insertions(+), 22 deletions(-)

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