Thu, 17 Jun 2021

Package inspector updated to version 1.0.3 with previous version 1.0.2 dated 2020-11-16

Title: Validation of Arguments and Objects in User-Defined Functions
Description: Utility functions that implement and automate common sets of validation tasks. These functions are particularly useful to validate inputs, intermediate objects and output values in user-defined functions, resulting in tidier and less verbose functions.
Author: Pedro Fonseca [aut, cre] (<https://orcid.org/0000-0002-5708-081X>), FCT [fnd]
Maintainer: Pedro Fonseca <pedro.teles.fonseca@phd.iseg.ulisboa.pt>

Diff between inspector versions 1.0.2 dated 2020-11-16 and 1.0.3 dated 2021-06-17

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Package Spillover updated to version 0.1.0.1 with previous version 0.1 dated 2020-09-29

Title: Spillover Index Based on VAR Modelling
Description: A user-friendly tool for estimating both total and directional volatility spillovers based on Diebold and Yilmaz (2009, 2012). It also provides the user with rolling estimation for total and net indices. User can find both orthogonalized and generalized versions for each kind of measures. See Diebold and Yilmaz (2009, 2012) find them at <doi:10.1111/j.1468-0297.2008.02208.x> and <doi:10.1016/j.ijforecast.2011.02.006>.
Author: Jilber Urbina
Maintainer: Jilber Urbina <jurbina@cipadla.com>

Diff between Spillover versions 0.1 dated 2020-09-29 and 0.1.0.1 dated 2021-06-17

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Package smcfcs updated to version 1.6.0 with previous version 1.5.0 dated 2021-04-01

Title: Multiple Imputation of Covariates by Substantive Model Compatible Fully Conditional Specification
Description: Implements multiple imputation of missing covariates by Substantive Model Compatible Fully Conditional Specification. This is a modification of the popular FCS/chained equations multiple imputation approach, and allows imputation of missing covariate values from models which are compatible with the user specified substantive model.
Author: Jonathan Bartlett [aut, cre], Ruth Keogh [aut], Edouard F. Bonneville [aut], Claus Thorn Ekstrøm [ctb]
Maintainer: Jonathan Bartlett <j.w.bartlett@bath.ac.uk>

Diff between smcfcs versions 1.5.0 dated 2021-04-01 and 1.6.0 dated 2021-06-17

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Package orderly updated to version 1.3.0 with previous version 1.0.4 dated 2020-01-12

Title: Lightweight Reproducible Reporting
Description: Order, create and store reports from R. By defining a lightweight interface around the inputs and outputs of an analysis, a lot of the repetitive work for reproducible research can be automated. We define a simple format for organising and describing work that facilitates collaborative reproducible research and acknowledges that all analyses are run multiple times over their lifespans.
Author: Rich FitzJohn [aut, cre], Robert Ashton [aut], Alex Hill [aut], Martin Eden [aut], Wes Hinsley [aut], Emma Russell [aut], James Thompson [aut], Imperial College of Science, Technology and Medicine [cph]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>

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More information about orderly at CRAN
Permanent link

Package modelsummary updated to version 0.8.1 with previous version 0.8.0 dated 2021-05-21

Title: Summary Tables and Plots for Statistical Models and Data: Beautiful, Customizable, and Publication-Ready
Description: Create beautiful and customizable tables to summarize several statistical models side-by-side. Draw coefficient plots, multi-level cross-tabs, dataset summaries, balance tables (a.k.a. "Table 1s"), and correlation matrices. This package supports dozens of statistical models, and it can produce tables in HTML, LaTeX, Word, Markdown, PDF, PowerPoint, Excel, RTF, JPG, or PNG. Tables can easily be embedded in 'Rmarkdown' or 'knitr' dynamic documents.
Author: Vincent Arel-Bundock [aut, cre] (<https://orcid.org/0000-0003-2042-7063>), Joachim Gassen [ctb] (<https://orcid.org/0000-0003-4364-2911>), Nathan Eastwood [ctb], Nick Huntington-Klein [ctb] (<https://orcid.org/0000-0002-7352-3991>), Moritz Schwarz [ctb] (<https://orcid.org/0000-0003-0340-3780>), Benjamin Elbers [ctb] (0000-0001-5392-3448)
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>

Diff between modelsummary versions 0.8.0 dated 2021-05-21 and 0.8.1 dated 2021-06-17

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Package matrixdist updated to version 1.1.0 with previous version 1.0.2 dated 2021-02-26

Title: Statistics for Matrix Distributions
Description: Tools for homogeneous and in-homogeneous phase-type distributions. Methods for functional evaluation, simulation and estimation using the expectation-maximization (EM) algorithm are provided. The methods of this package are based on the following references. Asmussen, S., Nerman, O., & Olsson, M. (1996) <https://www.jstor.org/stable/4616418>, Olsson, M. (1996) <https://www.jstor.org/stable/4616419>. Albrecher, H., & Bladt, M. (2019) <doi:10.1017/jpr.2019.60> Albrecher, H., Bladt, M., & Yslas, J. (2020) <doi:10.1111/sjos.12505> Bladt, M., & Yslas, J. (2020) <arXiv:2011.03219>.
Author: Martin Bladt [aut, cre], Jorge Yslas [aut]
Maintainer: Martin Bladt <martinbladt@gmail.com>

Diff between matrixdist versions 1.0.2 dated 2021-02-26 and 1.1.0 dated 2021-06-17

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Permanent link

Package ade4 updated to version 1.7-17 with previous version 1.7-16 dated 2020-10-28

Title: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences
Description: Tools for multivariate data analysis. Several methods are provided for the analysis (i.e., ordination) of one-table (e.g., principal component analysis, correspondence analysis), two-table (e.g., coinertia analysis, redundancy analysis), three-table (e.g., RLQ analysis) and K-table (e.g., STATIS, multiple coinertia analysis). The philosophy of the package is described in Dray and Dufour (2007) <doi:10.18637/jss.v022.i04>.
Author: Stéphane Dray <stephane.dray@univ-lyon1.fr>, Anne-Béatrice Dufour <anne-beatrice.dufour@univ-lyon1.fr>, and Jean Thioulouse <jean.thioulouse@univ-lyon1.fr>, with contributions from Thibaut Jombart, Sandrine Pavoine, Jean R. Lobry, Sébastien Ollier, Daniel Borcard, Pierre Legendre, Stéphanie Bougeard and Aurélie Siberchicot. Based on earlier work by Daniel Chessel.
Maintainer: Aurélie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>

Diff between ade4 versions 1.7-16 dated 2020-10-28 and 1.7-17 dated 2021-06-17

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New package visualFields with initial version 0.6.2
Package: visualFields
Title: Statistical Methods for Visual Fields
Description: A collection of tools for analyzing the field of vision. It provides a framework for development and use of innovative methods for visualization, statistical analysis, and clinical interpretation of visual-field loss and its change over time. It is intended to be a tool for collaborative research.
Version: 0.6.2
Date: 2021-06-16
Author: Ivan Marin-Franch <imarinfr@optocom.es>
Maintainer: Ivan Marin-Franch <imarinfr@optocom.es>
URL: https://people.eng.unimelb.edu.au/aturpin/opi/index.html
Depends: R (>= 3.5.0)
Imports: stats, utils, grid, flip (>= 2.1), matrixStats, Hmisc, gtools, deldir, spatstat.geom
LazyData: yes
License: GPL (>= 3.0)
NeedsCompilation: no
Packaged: 2021-06-16 11:17:16 UTC; ivanmarin-franch
Repository: CRAN
Date/Publication: 2021-06-17 15:50:02 UTC

More information about visualFields at CRAN
Permanent link

Package nortsTest updated to version 1.0.1 with previous version 1.0.0 dated 2020-07-27

Title: Assessing Normality of Stationary Process
Description: Despite that several tests for normality in stationary processes have been proposed in the literature, consistent implementations of these tests in programming languages are limited. Four normality test are implemented. The Lobato and Velasco's, Epps, Psaradakis and Vavra, and the random projections tests for stationary process. Some other diagnostics such as, unit root test for stationarity, seasonal tests for seasonality, and arch effect test for volatility; are also performed. The package also offers residual diagnostic for linear time series models developed in several packages.
Author: Asael Alonzo Matamoros [aut, cre], Alicia Nieto-Reyes [aut], Rob Hyndman [ctb], Mitchell O'Hara-Wild [ctb], Trapletti A. [ctb]
Maintainer: Asael Alonzo Matamoros <asael.alonzo@gmail.com>

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Package ipaddress updated to version 0.5.2 with previous version 0.5.1 dated 2020-09-12

Title: Tidy IP Addresses
Description: Classes and functions for working with IP (Internet Protocol) addresses and networks, inspired by the Python 'ipaddress' module. Offers full support for both IPv4 and IPv6 (Internet Protocol versions 4 and 6) address spaces. It is specifically designed to work well with the 'tidyverse'.
Author: David Hall [aut, cre] (<https://orcid.org/0000-0002-2193-0480>)
Maintainer: David Hall <david.hall.physics@gmail.com>

Diff between ipaddress versions 0.5.1 dated 2020-09-12 and 0.5.2 dated 2021-06-17

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Package biclustermd updated to version 0.2.3 with previous version 0.2.2 dated 2020-04-15

Title: Biclustering with Missing Data
Description: Biclustering is a statistical learning technique that simultaneously partitions and clusters rows and columns of a data matrix. Since the solution space of biclustering is in infeasible to completely search with current computational mechanisms, this package uses a greedy heuristic. The algorithm featured in this package is, to the best our knowledge, the first biclustering algorithm to work on data with missing values. Li, J., Reisner, J., Pham, H., Olafsson, S., and Vardeman, S. (2020) Biclustering with Missing Data. Information Sciences, 510, 304–316.
Author: John Reisner [cre, aut, cph], Hieu Pham [ctb, cph], Jing Li [ctb, cph]
Maintainer: John Reisner <johntreisner@gmail.com>

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Package PolyHaplotyper updated to version 1.0.1 with previous version 1.0.0 dated 2021-02-10

Title: Assignment of Haplotypes Based on SNP Dosages in Diploids and Polyploids
Description: Infer the genetic composition of individuals in terms of haplotype dosages for a haploblock, based on bi-allelic marker dosages, for any ploidy level. Reference: Voorrips and Tumino: PolyHaplotyper: haplotyping in polyploids based on bi-allelic marker dosage data. Submitted to BMC Bioinformatics (2021).
Author: Roeland E. Voorrips
Maintainer: Roeland E. Voorrips <roeland.voorrips@wur.nl>

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Package mfGARCH updated to version 0.2.1 with previous version 0.2.0 dated 2020-05-12

Title: Mixed-Frequency GARCH Models
Description: Estimating GARCH-MIDAS (MIxed-DAta-Sampling) models (Engle, Ghysels, Sohn, 2013, <doi:10.1162/REST_a_00300>) and related statistical inference, accompanying the paper "Two are better than one: Volatility forecasting using multiplicative component GARCH models" by Conrad and Kleen (2020, <doi:10.1002/jae.2742>). The GARCH-MIDAS model decomposes the conditional variance of (daily) stock returns into a short- and long-term component, where the latter may depend on an exogenous covariate sampled at a lower frequency.
Author: Onno Kleen [aut, cre] (<https://orcid.org/0000-0003-4731-4640>)
Maintainer: Onno Kleen <r@onnokleen.de>

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Package ichimoku updated to version 0.2.0 with previous version 0.1.2 dated 2021-05-19

Title: Visualization and Tools for Ichimoku Kinko Hyo Strategies
Description: An implementation of 'Ichimoku Kinko Hyo', also commonly known as 'cloud charts'. Static and interactive visualizations with tools for creating, backtesting and development of quantitative 'ichimoku' strategies. As described in Sasaki (1996, ISBN:4925152009), the technique is a refinement on candlestick charting originating from Japan, now in widespread use in technical analysis worldwide. Translating as 'one-glance equilibrium chart', it allows the price action and market structure of financial securities to be determined 'at-a-glance'.
Author: Charlie Gao [aut, cre]
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

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Package ctsem updated to version 3.5.3 with previous version 3.5.2 dated 2021-06-17

Title: Continuous Time Structural Equation Modelling
Description: Hierarchical continuous time state space modelling, for linear and nonlinear systems measured by continuous variables, with limited support for binary data. The subject specific dynamic system is modelled as a stochastic differential equation (SDE), measurement models are typically multivariate normal factor models. Linear mixed effects SDE's estimated via maximum likelihood and optimization are the default. Nonlinearities, (state dependent parameters) and random effects on all parameters are possible, using either max likelihood / max a posteriori optimization (with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling. See <https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf> for details. Priors may be used. For the conceptual overview of the hierarchical Bayesian linear SDE approach, see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>. Exogenous inputs may also be included, for an overview of such possibilities see <https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models> . Stan based functions are not available on 32 bit Windows systems at present. <https://cdriver.netlify.app/> contains some tutorial blog posts.
Author: Charles Driver [aut, cre, cph], Manuel Voelkle [aut, cph], Han Oud [aut, cph], Trustees of Columbia University [cph]
Maintainer: Charles Driver <charles.driver@ibe.uzh.ch>

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Package spatstat.core updated to version 2.2-0 with previous version 2.1-2 dated 2021-04-18

Title: Core Functionality of the 'spatstat' Family
Description: Functionality for data analysis and modelling of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.
Author: Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut], Kasper Klitgaard Berthelsen [ctb], Achmad Choiruddin [ctb], Jean-Francois Coeurjolly [ctb], Ottmar Cronie [ctb], Tilman Davies [ctb], Julian Gilbey [ctb], Yongtao Guan [ctb], Ute Hahn [ctb], Kassel Hingee [ctb], Abdollah Jalilian [ctb], Marie-Colette van Lieshout [ctb], Greg McSwiggan [ctb], Tuomas Rajala [ctb], Suman Rakshit [ctb], Dominic Schuhmacher [ctb], Rasmus Plenge Waagepetersen [ctb], Hangsheng Wang [ctb]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package sparklyr updated to version 1.7.1 with previous version 1.7.0 dated 2021-06-10

Title: R Interface to Apache Spark
Description: R interface to Apache Spark, a fast and general engine for big data processing, see <http://spark.apache.org>. This package supports connecting to local and remote Apache Spark clusters, provides a 'dplyr' compatible back-end, and provides an interface to Spark's built-in machine learning algorithms.
Author: Javier Luraschi [aut], Kevin Kuo [aut] (<https://orcid.org/0000-0001-7803-7901>), Kevin Ushey [aut], JJ Allaire [aut], Samuel Macedo [ctb], Hossein Falaki [aut], Lu Wang [aut], Andy Zhang [aut], Yitao Li [aut, cre] (<https://orcid.org/0000-0002-1261-905X>), Jozef Hajnala [ctb], Maciej Szymkiewicz [ctb] (<https://orcid.org/0000-0003-1469-9396>), Wil Davis [ctb], RStudio [cph], The Apache Software Foundation [aut, cph]
Maintainer: Yitao Li <yitao@rstudio.com>

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Package sigminer updated to version 2.0.2 with previous version 2.0.1 dated 2021-05-19

Title: Extract, Analyze and Visualize Mutational Signatures for Genomic Variations
Description: Genomic alterations including single nucleotide substitution, copy number alteration, etc. are the major force for cancer initialization and development. Due to the specificity of molecular lesions caused by genomic alterations, we can generate characteristic alteration spectra, called 'signature' (Wang, Shixiang, et al. (2020) <DOI:10.1101/2020.04.27.20082404> & Alexandrov, Ludmil B., et al. (2020) <DOI:10.1038/s41586-020-1943-3>). This package helps users to extract, analyze and visualize signatures from genomic alteration records, thus providing new insight into cancer study.
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>), Ziyu Tao [aut] (<https://orcid.org/0000-0003-3272-1227>), Huimin Li [aut] (<https://orcid.org/0000-0003-1683-9057>), Tao Wu [aut] (<https://orcid.org/0000-0002-8999-9628>), Xue-Song Liu [aut, ctb] (<https://orcid.org/0000-0002-7736-0077>), Anand Mayakonda [ctb]
Maintainer: Shixiang Wang <w_shixiang@163.com>

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Package s2 updated to version 1.0.6 with previous version 1.0.5 dated 2021-06-01

Title: Spherical Geometry Operators Using the S2 Geometry Library
Description: Provides R bindings for Google's s2 library for geometric calculations on the sphere. High-performance constructors and exporters provide high compatibility with existing spatial packages, transformers construct new geometries from existing geometries, predicates provide a means to select geometries based on spatial relationships, and accessors extract information about geometries.
Author: Dewey Dunnington [aut] (<https://orcid.org/0000-0002-9415-4582>), Edzer Pebesma [aut, cre] (<https://orcid.org/0000-0001-8049-7069>), Ege Rubak [aut], Jeroen Ooms [ctb] (configure script), Google, Inc. [cph] (Original s2geometry.io source code)
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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New package pez with initial version 1.2-3
Package: pez
Title: Phylogenetics for the Environmental Sciences
Version: 1.2-3
Author: William D. Pearse, Marc W. Cadotte, Jeannine Cavender-Bares, Anthony R. Ives, Caroline Tucker, Steve C. Walker, Matthew R. Helmus
Maintainer: William D. Pearse <will.pearse@gmail.com>
Description: Eco-phylogenetic and community phylogenetic analyses. Keeps community ecological and phylogenetic data matched up and comparable using 'comparative.comm' objects. Wrappers for common community phylogenetic indices ('pez.shape', 'pez.evenness', 'pez.dispersion', and 'pez.dissimilarity' metrics). Implementation of Cavender-Bares (2004) correlation of phylogenetic and ecological matrices ('fingerprint.regression'). Phylogenetic Generalised Linear Mixed Models (PGLMMs; 'pglmm') following Ives & Helmus (2011) and Rafferty & Ives (2013). Simulation of null assemblages, traits, and phylogenies ('scape', 'sim.meta.comm').
License: GPL-3
VignetteBuilder: knitr
Suggests: knitr (>= 1.6), lme4 (>= 1.1-7), formatR (>= 1.7)
Imports: caper (>= 0.5-2), picante (>= 1.6-2), quantreg (>= 5.05), mvtnorm (>= 1.0-0), vegan (>= 2.0-10), ade4 (>= 1.6-2), FD (>= 1.0-12), Matrix (>= 1.1-4), methods (>= 3.1.0), animation (>= 2.4-0), phytools (>= 0.6-60)
Depends: ape (>= 3.1-4)
NeedsCompilation: no
Repository: CRAN
Packaged: 2021-06-16 16:13:53 UTC; will
Date/Publication: 2021-06-17 12:00:06 UTC

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Package variables updated to version 1.1-1 with previous version 1.1-0 dated 2021-03-08

Title: Variable Descriptions
Description: Abstract descriptions of (yet) unobserved variables.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package relsurv updated to version 2.2-4 with previous version 2.2-3 dated 2018-11-30

Title: Relative Survival
Description: Contains functions for analysing relative survival data, including nonparametric estimators of net (marginal relative) survival, relative survival ratio, crude mortality, methods for fitting and checking additive and multiplicative regression models, transformation approach, methods for dealing with population mortality tables. Work has been described in Pohar Perme, Pavlic (2018) <doi:10.18637/jss.v087.i08>.
Author: Maja Pohar Perme [aut], Damjan Manevski [aut, cre]
Maintainer: Damjan Manevski <damjan.manevski@mf.uni-lj.si>

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New package RapidoPGS with initial version 2.1.0
Package: RapidoPGS
Title: A Fast and Light Package to Compute Polygenic Risk Scores
Version: 2.1.0
Authors@R: c( person("Guillermo","Reales", role = c("aut", "cre"), email = "gr440@cam.ac.uk", comment = c(ORCID = "0000-0001-9993-3916")), person("Chris", "Wallace", role = "aut", email = "cew54@cam.ac.uk", comment = c(ORCID = "0000-0001-9755-1703")), person("Olly", "Burren", role = "ctb", email = "ob219@cam.ac.uk", comment = c(ORCID = "0000-0002-3388-5760")))
Description: Quickly computes polygenic scores from GWAS summary statistics of either case-control or quantitative traits, without LD matrix computation or parameter tuning. Reales,G., Vigorito, E., Kelemen,M., Wallace,C. (2021) <doi:10.1101/2020.07.24.220392> "RápidoPGS: A rapid polygenic score calculator for summary GWAS data without a test dataset".
License: GPL-3
Depends: R (>= 4.0), data.table, RCurl, curl
Imports: dplyr (>= 1.0.6), GenomicRanges (>= 1.42.0), IRanges (>= 2.24.1), bigsnpr (>= 1.8.1), coloc (>= 5.1.0), bigreadr (>= 0.2.4)
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-06-17 09:01:55 UTC; guille
Author: Guillermo Reales [aut, cre] (<https://orcid.org/0000-0001-9993-3916>), Chris Wallace [aut] (<https://orcid.org/0000-0001-9755-1703>), Olly Burren [ctb] (<https://orcid.org/0000-0002-3388-5760>)
Maintainer: Guillermo Reales <gr440@cam.ac.uk>
Repository: CRAN
Date/Publication: 2021-06-17 10:10:11 UTC

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Package mind updated to version 0.1.1 with previous version 0.1.0 dated 2021-05-21

Title: Multivariate Model Based Inference for Domains
Description: Allows users to produce estimates and MSE for multivariate variables using Linear Mixed Model. The package follows the approach of Datta, Day and Basawa (1999) <doi:10.1016/S0378-3758(98)00147-5>.
Author: Michele D'Alo' [aut], Stefano Falorsi [aut], Andrea Fasulo [aut, cre]
Maintainer: Andrea Fasulo <fasulo@istat.it>

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Package fhircrackr updated to version 1.0.1 with previous version 1.0.0 dated 2021-06-16

Title: Handling HL7 FHIR Resources in R
Description: Useful tools for conveniently downloading FHIR resources in xml format and converting them to R data frames. The package uses FHIR-search to download bundles from a FHIR server, provides functions to save and read xml-files containing such bundles and allows flattening the bundles to data.frames using XPath expressions.
Author: Thomas Peschel [aut, cre], Julia Palm [aut] (<https://orcid.org/0000-0003-1568-5893>), Jens Przybilla [aut], Frank Meineke [aut] (<https://orcid.org/0000-0002-9256-7543>)
Maintainer: Thomas Peschel <tpeschel@imise.uni-leipzig.de>

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Package cvms updated to version 1.3.1 with previous version 1.3.0 dated 2021-06-07

Title: Cross-Validation for Model Selection
Description: Cross-validate one or multiple regression and classification models and get relevant evaluation metrics in a tidy format. Validate the best model on a test set and compare it to a baseline evaluation. Alternatively, evaluate predictions from an external model. Currently supports regression and classification (binary and multiclass). Described in chp. 5 of Jeyaraman, B. P., Olsen, L. R., & Wambugu M. (2019, ISBN: 9781838550134).
Author: Ludvig Renbo Olsen [aut, cre], Hugh Benjamin Zachariae [aut], Indrajeet Patil [ctb] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets)
Maintainer: Ludvig Renbo Olsen <r-pkgs@ludvigolsen.dk>

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Package mark (with last version 0.1.3) was removed from CRAN

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

2021-06-16 0.1.3

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Package opdisDownsampling updated to version 0.5.0 with previous version 0.1.0 dated 2021-03-25

Title: Optimal Distribution Preserving Down-Sampling of Bio-Medical Data
Description: An optimized method for distribution-preserving class-proportional down-sampling of bio-medical data.
Author: Jorn Lotsch[aut,cre], Sebastian Malkusch[aut], Alfred Ultsch[aut]
Maintainer: Jorn Lotsch <j.lotsch@em.uni-frankfurt.de>

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Package DescTools updated to version 0.99.42 with previous version 0.99.41 dated 2021-04-10

Title: Tools for Descriptive Statistics
Description: A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.
Author: Andri Signorell [aut, cre], Ken Aho [ctb], Andreas Alfons [ctb], Nanina Anderegg [ctb], Tomas Aragon [ctb], Chandima Arachchige [ctb], Antti Arppe [ctb], Adrian Baddeley [ctb], Kamil Barton [ctb], Ben Bolker [ctb], Hans W. Borchers [ctb], Frederico Caeiro [ctb], Stephane Champely [ctb], Daniel Chessel [ctb], Leanne Chhay [ctb], Nicholas Cooper [ctb], Clint Cummins [ctb], Michael Dewey [ctb], Harold C. Doran [ctb], Stephane Dray [ctb], Charles Dupont [ctb], Dirk Eddelbuettel [ctb], Claus Ekstrom [ctb], Martin Elff [ctb], Jeff Enos [ctb], Richard W. Farebrother [ctb], John Fox [ctb], Romain Francois [ctb], Michael Friendly [ctb], Tal Galili [ctb], Matthias Gamer [ctb], Joseph L. Gastwirth [ctb], Vilmantas Gegzna [ctb], Yulia R. Gel [ctb], Sereina Graber [ctb], Juergen Gross [ctb], Gabor Grothendieck [ctb], Frank E. Harrell Jr [ctb], Richard Heiberger [ctb], Michael Hoehle [ctb], Christian W. Hoffmann [ctb], Soeren Hojsgaard [ctb], Torsten Hothorn [ctb], Markus Huerzeler [ctb], Wallace W. Hui [ctb], Pete Hurd [ctb], Rob J. Hyndman [ctb], Christopher Jackson [ctb], Matthias Kohl [ctb], Mikko Korpela [ctb], Max Kuhn [ctb], Detlew Labes [ctb], Friederich Leisch [ctb], Jim Lemon [ctb], Dong Li [ctb], Martin Maechler [ctb], Arni Magnusson [ctb], Ben Mainwaring [ctb], Daniel Malter [ctb], George Marsaglia [ctb], John Marsaglia [ctb], Alina Matei [ctb], David Meyer [ctb], Weiwen Miao [ctb], Giovanni Millo [ctb], Yongyi Min [ctb], David Mitchell [ctb], Franziska Mueller [ctb], Markus Naepflin [ctb], Daniel Navarro [ctb], Henric Nilsson [ctb], Klaus Nordhausen [ctb], Derek Ogle [ctb], Hong Ooi [ctb], Nick Parsons [ctb], Sandrine Pavoine [ctb], Tony Plate [ctb], Luke Prendergast [ctb], Roland Rapold [ctb], William Revelle [ctb], Tyler Rinker [ctb], Brian D. Ripley [ctb], Caroline Rodriguez [ctb], Nathan Russell [ctb], Nick Sabbe [ctb], Ralph Scherer [ctb], Venkatraman E. Seshan [ctb], Michael Smithson [ctb], Greg Snow [ctb], Karline Soetaert [ctb], Werner A. Stahel [ctb], Alec Stephenson [ctb], Mark Stevenson [ctb], Ralf Stubner [ctb], Matthias Templ [ctb], Duncan Temple Lang [ctb], Terry Therneau [ctb], Yves Tille [ctb], Luis Torgo [ctb], Adrian Trapletti [ctb], Joshua Ulrich [ctb], Kevin Ushey [ctb], Jeremy VanDerWal [ctb], Bill Venables [ctb], John Verzani [ctb], Pablo J. Villacorta Iglesias [ctb], Gregory R. Warnes [ctb], Stefan Wellek [ctb], Hadley Wickham [ctb], Rand R. Wilcox [ctb], Peter Wolf [ctb], Daniel Wollschlaeger [ctb], Joseph Wood [ctb], Ying Wu [ctb], Thomas Yee [ctb], Achim Zeileis [ctb]
Maintainer: Andri Signorell <andri@signorell.net>

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Package bayesforecast updated to version 1.0.1 with previous version 0.0.1 dated 2021-01-22

Title: Bayesian Time Series Modeling with Stan
Description: Fit Bayesian time series models using 'Stan' for full Bayesian inference. A wide range of distributions and models are supported, allowing users to fit Seasonal ARIMA, ARIMAX, Dynamic Harmonic Regression, GARCH, t-student innovation GARCH models, asymmetric GARCH, Random Walks, stochastic volatility models for univariate time series. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with typical visualization methods, information criteria such as loglik, AIC, BIC WAIC, Bayes factor and leave-one-out cross-validation methods. References: Hyndman (2017) <doi:10.18637/jss.v027.i03>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
Author: Asael Alonzo Matamoros [aut, cre], Cristian Cruz Torres [aut], Andres Dala [ctb], Rob Hyndman [ctb], Mitchell O'Hara-Wild [ctb]
Maintainer: Asael Alonzo Matamoros <asael.alonzo@gmail.com>

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New package vampyr with initial version 1.1.1
Package: vampyr
Title: Factor Analysis Controlling the Effects of Response Bias
Version: 1.1.1
Date: 2021-06-17
Author: David Navarro-Gonzalez, Andreu Vigil-Colet, Pere J. Ferrando, Urbano Lorenzo-Seva, Jorge N. Tendeiro
Maintainer: David Navarro-Gonzalez <david.navarro@urv.cat>
Description: Vampirize the response biases from a dataset! Performs factor analysis controlling the effects of social desirability and acquiescence using the method described in Ferrando, Lorenzo-Seva & Chico (2009) <doi:10.1080/10705510902751374>.
Depends: R (>= 2.10)
Imports: stats, psych, EFA.MRFA, GPArotation, PCovR, moments, corpcor, lavaan, fungible, semPlot
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-06-17 07:17:21 UTC; David
Repository: CRAN
Date/Publication: 2021-06-17 08:30:02 UTC

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New package recogito with initial version 0.1.1
Package: recogito
Title: Interactive Annotation of Text and Images
Version: 0.1.1
Authors@R: c( person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'jan.wijffels@vub.be'), person('Vrije Universiteit Brussel - DIGI: Brussels Platform for Digital Humanities', role = 'cph'), person('Pelagios Network', role = 'cph', comment = "code in inst/htmlwidgets/lib"))
Description: Annotate text with entities and the relations between them. Annotate areas of interest in images with your labels. Providing 'htmlwidgets' bindings to the 'recogito' <https://github.com/recogito/recogito-js> and 'annotorious' <https://github.com/recogito/annotorious> libraries.
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
URL: https://github.com/DIGI-VUB/recogito
Suggests: shiny, magick, opencv
Imports: htmlwidgets, htmltools, jsonlite
NeedsCompilation: no
Packaged: 2021-06-16 09:05:02 UTC; Jan
Author: Jan Wijffels [aut, cre, cph], Vrije Universiteit Brussel - DIGI: Brussels Platform for Digital Humanities [cph], Pelagios Network [cph] (code in inst/htmlwidgets/lib)
Maintainer: Jan Wijffels <jan.wijffels@vub.be>
Repository: CRAN
Date/Publication: 2021-06-17 08:20:02 UTC

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New package MSiP with initial version 1.3.7
Package: MSiP
Title: 'MassSpectrometry' Interaction Prediction
Version: 1.3.7
Authors@R: c( person("Matineh", "Rahmatbakhsh", , "matinerb.94@gmail.com", c("aut", "cre")))
Description: The 'MSiP' is a computational approach to predict protein-protein interactions from large-scale affinity purification mass 'spectrometry' (AP-MS) data. This approach includes both spoke and matrix models for interpreting AP-MS data in a network context. The "spoke" model considers only bait-prey interactions, whereas the "matrix" model assumes that each of the identified proteins (baits and prey) in a given AP-MS experiment interacts with each of the others. The spoke model has a high false-negative rate, whereas the matrix model has a high false-positive rate. Although, both statistical models have merits, a combination of both models has shown to increase the performance of machine learning classifiers in terms of their capabilities in discrimination between true and false positive interactions.
Depends: R (>= 3.6.0)
Imports: dplyr (>= 1.0.6), tibble (>= 3.1.2), tidyr (>= 1.1.3), magrittr (>= 2.0.1), plyr (>= 1.8.6), PRROC (>= 1.3.1), caret (>= 6.0.88), e1071 (>= 1.7.7), mice (>= 3.13.0), pROC (>= 1.17.0.1), ranger (>= 0.12.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: knitr, markdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-06-16 18:52:36 UTC; Matine
Author: Matineh Rahmatbakhsh [aut, cre]
Maintainer: Matineh Rahmatbakhsh <matinerb.94@gmail.com>
Repository: CRAN
Date/Publication: 2021-06-17 08:20:05 UTC

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New package mshap with initial version 0.1.0
Package: mshap
Title: Multiplicative SHAP Values for Two-Part Models
Version: 0.1.0
Authors@R: person(given = "Spencer", family = "Matthews", role = c("aut", "cre"), email = "srmatthews98@gmail.com")
Description: Allows for the computation of mSHAP values on two-part models as proposed by Matthews, S. and Hartman, B. (2021) <arXiv:2106.08990>. Also contains functions for simple plotting of the results (or any SHAP values). For information about the TreeSHAP algorithm that mSHAP builds on, see Lundberg, S.M., Erion, G., Chen, H., DeGrave, A., Prutkin, J.M., Nair, B., Katz, R., Himmelfarb, J., Bansal, N., Lee, S.I. (2020) <doi:10.1038/s42256-019-0138-9>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: magrittr (>= 1.5), purrr (>= 0.3.4), dplyr (>= 1.0.4), forcats, stringr, ggplot2, ggbeeswarm, rlang, tidyr, tidyselect
Suggests: rmarkdown, knitr, insuranceData, reticulate, caret, testthat (>= 3.0.0), covr
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-06-17 00:57:16 UTC; spencer.matthews
Author: Spencer Matthews [aut, cre]
Maintainer: Spencer Matthews <srmatthews98@gmail.com>
Repository: CRAN
Date/Publication: 2021-06-17 08:40:02 UTC

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New package mBvs with initial version 1.5
Package: mBvs
Title: Bayesian Variable Selection Methods for Multivariate Data
Version: 1.5
Date: 2021-6-16
Author: Kyu Ha Lee, Mahlet G. Tadesse, Brent A. Coull, Jacqueline R. Starr
Maintainer: Kyu Ha Lee <klee15239@gmail.com>
Description: Bayesian variable selection methods for data with multivariate responses and multiple covariates. The package contains implementations of multivariate Bayesian variable selection methods for continuous data (Lee et al., Biometrics, 2017 <doi: 10.1111/biom.12557>) and zero-inflated count data (Lee et al., Biostatistics, 2020 <doi:10.1093/biostatistics/kxy067>).
License: GPL (>= 2)
Depends: R (>= 3.5.0)
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2021-06-17 01:56:01 UTC; kyuhalee
Repository: CRAN
Date/Publication: 2021-06-17 08:30:05 UTC

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New package luz with initial version 0.1.0
Package: luz
Title: Higher Level 'API' for 'torch'
Version: 0.1.0
Authors@R: c( person("Daniel", "Falbel", email = "daniel@rstudio.com", role = c("aut", "cre", "cph")), person(family = "RStudio", role = c("cph")) )
Description: A high level interface for 'torch' providing utilities to reduce the the amount of code needed for common tasks, abstract away torch details and make the same code work on both the 'CPU' and 'GPU'. It's flexible enough to support expressing a large range of models. It's heavily inspired by 'fastai' by Howard et al. (2020) <arXiv:2002.04688>, 'Keras' by Chollet et al. (2015) and 'Pytorch Lightning' by Falcon et al. (2019) <doi:10.5281/zenodo.3828935>.
License: MIT + file LICENSE
URL: https://mlverse.github.io/luz/, https://github.com/mlverse/luz
Encoding: UTF-8
Imports: torch (>= 0.4.0), magrittr, zeallot, rlang, coro, glue, progress, R6, generics, purrr, ellipsis, fs, prettyunits, cli
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), covr, Metrics, withr, vdiffr, ggplot2, dplyr
VignetteBuilder: knitr
Collate: 'accelerator.R' 'utils.R' 'callbacks.R' 'callbacks-interrupt.R' 'callbacks-profile.R' 'context.R' 'metrics.R' 'metrics-auc.R' 'module-plot.R' 'module-print.R' 'module.R' 'reexports.R' 'serialization.R'
NeedsCompilation: no
Packaged: 2021-06-16 17:56:07 UTC; dfalbel
Author: Daniel Falbel [aut, cre, cph], RStudio [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>
Repository: CRAN
Date/Publication: 2021-06-17 08:40:04 UTC

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New package gridpattern with initial version 0.1.2
Package: gridpattern
Title: 'grid' Pattern Grobs
Version: 0.1.2
Authors@R: c(person("Mike", "FC", role = "aut", comment = "Patterns extracted from ggpattern"), person("Trevor L", "Davis", role=c("aut", "cre"), email="trevor.l.davis@gmail.com"), person("Thomas Lin", "Pedersen", role = "ctb", comment = "new_data_frame() copied from ggplot2"))
Description: Provides 'grid' grobs that fill in a user-defined area with various patterns. Includes enhanced versions of the geometric and image-based patterns originally contained in the 'ggpattern' package as well as original 'pch', 'polygon_tiling', 'regular_polygon', and 'weave' patterns plus support for custom user-defined patterns.
URL: https://trevorldavis.com/R/gridpattern/, https://github.com/trevorld/gridpattern
BugReports: https://github.com/trevorld/gridpattern/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.4.0)
Imports: glue, grDevices, grid, magick, memoise, png, rlang, sf, utils
Suggests: ambient, knitr, rmarkdown, testthat, vdiffr
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2021-06-15 17:33:11 UTC; trevorld
Author: Mike FC [aut] (Patterns extracted from ggpattern), Trevor L Davis [aut, cre], Thomas Lin Pedersen [ctb] (new_data_frame() copied from ggplot2)
Maintainer: Trevor L Davis <trevor.l.davis@gmail.com>
Repository: CRAN
Date/Publication: 2021-06-17 08:10:02 UTC

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New package drughelper with initial version 0.1.0
Package: drughelper
Title: Drug Identification and Drug Name Correction with Automatic Updates
Version: 0.1.0
Authors@R: c(person("Javier Garcia", "Developer", role = c("aut", "cre"), email = "a905125@alumni.unav.es"), person("Fernando Carazo", "Developer", role = "aut"), person("Tecnun", role = "cph"))
Description: Contains a function which identifies and corrects the names of a set of drugs between clinical phases 1-4 with a periodically actualized drug database.
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: progress, utils, readr
Suggests: knitr, rmarkdown, BiocGenerics, RUnit
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2021-06-16 08:16:50 UTC; Javier
Author: Javier Garcia Developer [aut, cre], Fernando Carazo Developer [aut], Tecnun [cph]
Maintainer: Javier Garcia Developer <a905125@alumni.unav.es>
Repository: CRAN
Date/Publication: 2021-06-17 08:10:06 UTC

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New package c2d4u.tools with initial version 1.2
Package: c2d4u.tools
Title: 'c2d4u' - CRAN Packages for 'Ubuntu'
Version: 1.2
Date: 2021-06-16
Author: Neal Fultz
Maintainer: Neal Fultz <nfultz@gmail.com>
Description: The 'c2d4u' project provides precompiled CRAN packages for 'Ubuntu' users. They can be installed into user libraries without requiring root permissions.
URL: https://github.com/nfultz/c2d4u.tools
License: GPL-3
Encoding: UTF-8
OS_type: unix
SystemRequirements: Ubuntu: at least apt-get and apt-cache.
NeedsCompilation: no
Packaged: 2021-06-16 19:21:49 UTC; nfultz
Repository: CRAN
Date/Publication: 2021-06-17 08:30:07 UTC

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Package base2grob (with last version 0.0.3) was removed from CRAN

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

2018-04-25 0.0.3
2018-03-15 0.0.2

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New package XPolaris with initial version 1.0.1
Package: XPolaris
Title: Retrieving Soil Data from POLARIS
Version: 1.0.1
Authors@R: c( person("Luiz", "Moro Rosso", email = "lhmrosso@ksu.edu", role = "cre"), person("Andre", "Borja Reis", email = "andrefbr@ksu.edu", role = "aut"), person("Adrian", "Correndo", email = "correndo@ksu.edu", role = "aut"), person("Ignacio", "Ciampitti", email = "ciampitti@ksu.edu", role = "aut"))
Description: The POLARIS database <http://hydrology.cee.duke.edu/POLARIS/> is a 30-meter probabilistic soil series map of the contiguous United States (US). It represents an optimization of the Soil Survey Geographic database. This R package facilitates the access to large amounts of soil data within the US, currently stored online as raster images (TIFF).
License: MIT + file LICENSE
URL: https://github.com/lhmrosso/XPolaris
BugReports: https://github.com/lhmrosso/XPolaris/issues
Encoding: UTF-8
LazyData: true
Suggests: covr, knitr, mapproj, maps, methods, rgdal, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 2.10)
Imports: dplyr, ggplot2, magrittr, purrr, raster, sf, tidyr, utils
NeedsCompilation: no
Packaged: 2021-06-16 01:17:15 UTC; lhmrosso
Author: Luiz Moro Rosso [cre], Andre Borja Reis [aut], Adrian Correndo [aut], Ignacio Ciampitti [aut]
Maintainer: Luiz Moro Rosso <lhmrosso@ksu.edu>
Repository: CRAN
Date/Publication: 2021-06-17 07:50:09 UTC

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New package TailClassifier with initial version 0.1.0
Package: TailClassifier
Title: Tail Classifier for Thick-Tailed Discrete Data
Version: 0.1.0
Author: Jialin Zhang (JZ)
Maintainer: Jialin Zhang (JZ) <jzhang@math.msstate.edu>
Description: Function TailClassifier() in this package is a Tail-Classifier function. The function suggests one of the following types of tail for your discrete data: 1) Power decaying tail; 2) Sub-exponential decaying tail; and 3) Near-exponential decaying tail.
License: GPL-3
Encoding: UTF-8
Imports: readr
NeedsCompilation: no
Packaged: 2021-06-16 14:34:33 UTC; jz505
Repository: CRAN
Date/Publication: 2021-06-17 07:50:11 UTC

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Package simplevis updated to version 4.1.0 with previous version 4.0.0 dated 2021-06-04

Title: Simple 'ggplot2' Visualisation with Less Brainpower and Typing
Description: Wrapper functions to make 'ggplot2' visualisation easier with less brainpower and typing.
Author: David Hodge [aut, cre] (<https://orcid.org/0000-0002-3868-7501>), Statistics New Zealand [cph]
Maintainer: David Hodge <davidhodge931@gmail.com>

Diff between simplevis versions 4.0.0 dated 2021-06-04 and 4.1.0 dated 2021-06-17

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 simplevis-4.1.0/simplevis/R/gg_bar.R                              |   60 +++---
 simplevis-4.1.0/simplevis/R/gg_boxplot.R                          |   56 ++---
 simplevis-4.1.0/simplevis/R/gg_hbar.R                             |   70 +++----
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Package rbibutils updated to version 2.2.1 with previous version 2.2 dated 2021-06-10

Title: Read 'Bibtex' Files and Convert Between Bibliography Formats
Description: Read and write 'Bibtex' files. Convert between bibliography formats, including 'Bibtex', 'Biblatex', 'Endnote', and 'Bibentry'. Includes a port of the 'bibutils' utilities by Chris Putnam <https://sourceforge.net/projects/bibutils/>. Supports all bibliography formats and character encodings implemented in 'bibutils'.
Author: Georgi N. Boshnakov [aut, cre] (R port, R code, new C code and modifications to bibutils' C code, conversion to Bibentry (R and C code)), Chris Putman [aut] (src/*, author of the bibutils libraries, https://sourceforge.net/projects/bibutils/), Richard Mathar [ctb] (src/addsout.c), Johannes Wilm [ctb] (src/biblatexin.c, src/bltypes.c)
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

Diff between rbibutils versions 2.2 dated 2021-06-10 and 2.2.1 dated 2021-06-17

 DESCRIPTION                   |    8 -
 MD5                           |   27 ++---
 NEWS.md                       |    7 +
 build/partial.rdb             |binary
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 15 files changed, 257 insertions(+), 128 deletions(-)

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Package rBayesianOptimization updated to version 1.2.0 with previous version 1.1.0 dated 2016-09-14

Title: Bayesian Optimization of Hyperparameters
Description: A Pure R implementation of Bayesian Global Optimization with Gaussian Processes.
Author: Yachen Yan [aut, cre]
Maintainer: Yachen Yan <yanyachen21@gmail.com>

Diff between rBayesianOptimization versions 1.1.0 dated 2016-09-14 and 1.2.0 dated 2021-06-17

 DESCRIPTION                      |   13 -
 MD5                              |   33 +-
 NAMESPACE                        |   52 ++--
 R/BayesianOptimization.R         |  436 +++++++++++++++++++--------------------
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New package rayvertex with initial version 0.2.3
Package: rayvertex
Title: 3D Software Rasterizer
Version: 0.2.3
Date: 2021-06-05
Authors@R: c(person("Tyler", "Morgan-Wall", email = "tylermw@gmail.com", role = c("aut", "cph", "cre"), comment = c(ORCID = "0000-0002-3131-3814")), person("Syoyo", "Fujita", role=c("ctb", "cph")), person("Vilya", "Harvey", role = c("ctb", "cph")), person("G-Truc Creation", role = c("ctb", "cph")), person("Sean", "Barrett", role = c("ctb", "cph")))
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>
Description: Rasterize images using a 3D software renderer. 3D scenes are created either by importing external files, building scenes out of the included objects, or by constructing meshes manually. Supports point and directional lights, anti-aliased lines, shadow mapping, transparent objects, translucent objects, multiple materials types, reflection, refraction, environment maps, multicore rendering, bloom, tone-mapping, and screen-space ambient occlusion.
License: GPL (>= 3)
Copyright: file inst/COPYRIGHTS
Imports: magrittr, Rcpp (>= 1.0.6), grDevices, rayimage, png, digest
Suggests: Rvcg, magick, raster
LinkingTo: Rcpp, spacefillr, RcppThread
URL: https://www.rayvertex.com, https://github.com/tylermorganwall/rayvertex
BugReports: https://github.com/tylermorganwall/rayvertex/issues
NeedsCompilation: yes
Packaged: 2021-06-15 18:08:36 UTC; tyler
Author: Tyler Morgan-Wall [aut, cph, cre] (<https://orcid.org/0000-0002-3131-3814>), Syoyo Fujita [ctb, cph], Vilya Harvey [ctb, cph], G-Truc Creation [ctb, cph], Sean Barrett [ctb, cph]
Repository: CRAN
Date/Publication: 2021-06-17 07:20:02 UTC

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New package Randomuseragent with initial version 0.0.1
Package: Randomuseragent
Title: Filtering and Randomly Sampling Real User-Agent Strings
Version: 0.0.1
Authors@R: person(given = "Fangzhou", family = "Xie", role = c("aut", "cre"), email = "fangzhou.xie@rutgers.edu", comment = c(ORCID = "https://orcid.org/0000-0001-7702-093X"))
Description: Based on data of real user-agent strings, we can set filtering conditions and randomly sample user-agent strings from the user-agent string pool.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5)
Suggests: dplyr, knitr, markdown, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/fangzhou-xie/Randomuseragent, https://fangzhou-xie.github.io/Randomuseragent/index.html
BugReports: https://github.com/fangzhou-xie/randomuseragent/issues
NeedsCompilation: no
Packaged: 2021-06-16 14:57:04 UTC; xiefangzhou
Author: Fangzhou Xie [aut, cre] (<https://orcid.org/0000-0001-7702-093X>)
Maintainer: Fangzhou Xie <fangzhou.xie@rutgers.edu>
Repository: CRAN
Date/Publication: 2021-06-17 08:00:04 UTC

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Package minerva updated to version 1.5.10 with previous version 1.5.8 dated 2019-05-27

Title: Maximal Information-Based Nonparametric Exploration for Variable Analysis
Description: Wrapper for 'minepy' implementation of Maximal Information-based Nonparametric Exploration statistics (MIC and MINE family). Detailed information of the ANSI C implementation of 'minepy' can be found at <http://minepy.readthedocs.io/en/latest>.
Author: Michele Filosi [aut, cre], Roberto Visintainer [aut], Davide Albanese [aut], Samantha Riccadonna [ctb], Giuseppe Jurman [ctb], Cesare Furlanello [ctb]
Maintainer: Michele Filosi <michele.filosi@gmail.com>

Diff between minerva versions 1.5.8 dated 2019-05-27 and 1.5.10 dated 2021-06-17

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 13 files changed, 139 insertions(+), 69 deletions(-)

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New package h3jsr with initial version 1.2.2
Package: h3jsr
Title: Access Uber's H3 Library
Version: 1.2.2
Date: 2021-06-16
Authors@R: person("Lauren", "O'Brien", email = "obrlsoilau@gmail.com", role = c('aut', 'cre'), comment = c(ORCID = "0000-0002-7336-2171"))
Description: Provides access to Uber's H3 library for geospatial indexing via its JavaScript transpile 'h3-js' <https://github.com/uber/h3-js> and 'V8' <https://github.com/jeroen/v8>.
License: Apache License (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
SystemRequirements: V8 engine version 6+ is needed for modern JS and WASM support. On Debian / Ubuntu install either libv8-dev or libnode-dev, on Fedora use v8-devel.
Imports: geojsonsf, methods, purrr, sf, tidyr, utils, V8
Suggests: covr, dplyr, ggplot2, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-06-16 10:20:42 UTC; leobr
Author: Lauren O'Brien [aut, cre] (<https://orcid.org/0000-0002-7336-2171>)
Maintainer: Lauren O'Brien <obrlsoilau@gmail.com>
Repository: CRAN
Date/Publication: 2021-06-17 07:50:02 UTC

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Package GenEst updated to version 1.4.6 with previous version 1.4.5.1 dated 2021-02-13

Title: Generalized Mortality Estimator
Description: Command-line and 'shiny' GUI implementation of the GenEst models for estimating bird and bat mortality at wind and solar power facilities, following Dalthorp, et al. (2018) <doi:10.3133/tm7A2>.
Author: Daniel Dalthorp [aut, cre], Juniper Simonis [aut], Lisa Madsen [aut], Manuela Huso [aut], Paul Rabie [aut], Jeffrey Mintz [aut], Robert Wolpert [aut], Jared Studyvin [aut], Franzi Korner-Nievergelt [aut]
Maintainer: Daniel Dalthorp <ddalthorp@protonmail.com>

Diff between GenEst versions 1.4.5.1 dated 2021-02-13 and 1.4.6 dated 2021-06-17

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 20 files changed, 151 insertions(+), 109 deletions(-)

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Package bignum updated to version 0.2.1 with previous version 0.2.0 dated 2021-06-13

Title: Arbitrary-Precision Integer and Floating-Point Mathematics
Description: Classes for storing and manipulating arbitrary-precision integer vectors and high-precision floating-point vectors. These extend the range and precision of the 'integer' and 'double' data types found in R. This package utilizes the 'Boost.Multiprecision' C++ library. It is specifically designed to work well with the 'tidyverse' collection of R packages.
Author: David Hall [aut, cre, cph] (<https://orcid.org/0000-0002-2193-0480>)
Maintainer: David Hall <david.hall.physics@gmail.com>

Diff between bignum versions 0.2.0 dated 2021-06-13 and 0.2.1 dated 2021-06-17

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 tests/testthat/_snaps/format.md |   20 --------------------
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New package bayesplay with initial version 0.9.0
Package: bayesplay
Title: The Bayes Factor Playground
Version: 0.9.0
Author: Lincoln J Colling
Maintainer: Lincoln J Colling <lincoln@colling.net.nz>
Description: A lightweight modelling syntax for defining likelihoods and priors and for computing Bayes factors for simple one parameter models. It includes functionality for computing and plotting priors, likelihoods, and model predictions. Additional functionality is included for computing and plotting posteriors.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: testthat, covr, knitr, rmarkdown, markdown, vdiffr, ggplot2
VignetteBuilder: knitr
Imports: methods, gginnards
NeedsCompilation: no
Packaged: 2021-06-14 16:03:22 UTC; lc663
Repository: CRAN
Date/Publication: 2021-06-17 07:50:06 UTC

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Package diffeqr (with last version 1.1.0) was removed from CRAN

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

2021-01-08 1.1.0
2020-08-26 1.0.0
2019-09-22 0.1.3
2019-07-12 0.1.2
2018-04-27 0.1.1
2018-04-24 0.1.0

Permanent link
Package tktdjl2r (with last version 0.2.0) was removed from CRAN

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

2020-12-17 0.2.0
2020-11-11 0.1.0

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Package MAVIS (with last version 1.1.3) was removed from CRAN

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

2017-07-11 1.1.3
2016-06-22 1.1.2
2015-08-05 1.1.1
2015-04-30 1.1
2014-11-28 1.0
2014-11-22 0.2

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Package KODAMA (with last version 1.6) was removed from CRAN

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

2021-04-18 1.6

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Package pez (with last version 1.2-2) was removed from CRAN

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

2020-10-12 1.2-2
2020-07-26 1.2-1
2019-02-27 1.2-0
2016-01-15 1.1-1
2015-08-06 1.1-0
2015-02-11 1.0-0
2014-11-07 0.9-0

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Package himach updated to version 0.2.1 with previous version 0.1.2 dated 2021-04-30

Title: High Mach Finds Routes for Supersonic Aircraft
Description: For supersonic aircraft, flying subsonic over land, High Mach finds the best route between airports. Allows for coastal buffer and potentially closed regions. Uses a minimal model of aircraft performance: the focus is on time saved versus subsonic flight, rather than on vertical flight profile. For modelling and forecasting, not for planning your flight!
Author: David Marsh [aut, cre], EUROCONTROL [fnd, cph]
Maintainer: David Marsh <david.marsh@eurocontrol.int>

Diff between himach versions 0.1.2 dated 2021-04-30 and 0.2.1 dated 2021-06-17

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Package wbacon updated to version 0.5-1 with previous version 0.5 dated 2021-06-15

Title: Weighted BACON Algorithms
Description: The BACON algorithms are methods for multivariate outlier nomination (detection) and robust linear regression by Billor, Hadi, and Velleman (2000) <doi:10.1016/S0167-9473(99)00101-2>. The extension to weighted problems is due to Beguin and Hulliger (2008) <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X200800110616>.
Author: Tobias Schoch [aut, cre] (<https://orcid.org/0000-0002-1640-3395>), R-core [cph] (plot.wbaconlm derives from plot.lm)
Maintainer: Tobias Schoch <tobias.schoch@gmail.com>

Diff between wbacon versions 0.5 dated 2021-06-15 and 0.5-1 dated 2021-06-17

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Package vdiffr updated to version 1.0.1 with previous version 1.0.0 dated 2021-06-08

Title: Visual Regression Testing and Graphical Diffing
Description: An extension to the 'testthat' package that makes it easy to add graphical unit tests. It provides a Shiny application to manage the test cases.
Author: Lionel Henry [cre, aut], Thomas Lin Pedersen [aut] (<https://orcid.org/0000-0002-5147-4711>), RStudio [cph], T Jake Luciani [aut] (svglite), Matthieu Decorde [aut] (svglite), Vaudor Lise [aut] (svglite), Tony Plate [ctb] (svglite: Early line dashing code), David Gohel [ctb] (svglite: Line dashing code and raster code), Yixuan Qiu [ctb] (svglite: Improved styles; polypath implementation), Håkon Malmedal [ctb] (svglite: Opacity code)
Maintainer: Lionel Henry <lionel@rstudio.com>

Diff between vdiffr versions 1.0.0 dated 2021-06-08 and 1.0.1 dated 2021-06-17

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New package spotifyr with initial version 2.2.1
Package: spotifyr
Title: R Wrapper for the 'Spotify' Web API
Version: 2.2.1
Date: 2021-06-09
Authors@R: c( person( given = "Charlie", family = "Thompson", email = "chuck@rcharlie.com", role = c("aut") ), person( given = "Daniel", family = "Antal", email = "daniel.antal@ceemid.eu", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7513-6760") ), person( given = "Josiah", family = "Parry", email = "josiah.parry@yahoo.com", role = "aut", comment = c(ORCID = "0000-0001-9910-865X") ), person( given = "Donal", family = "Phipps", email = "donal.phipps@gmail.com", role = "aut" ), person( given = "Tom", family = "Wolff", email = "tom.wolff@duke.edu", role = "aut" ) )
Description: An R wrapper for pulling data from the 'Spotify' Web API <https://developer.spotify.com/documentation/web-api/> in bulk, or post items on a 'Spotify' user's playlist.
Maintainer: Daniel Antal <daniel.antal@ceemid.eu>
Depends: R (>= 3.3.0)
Imports: dplyr, purrr, tidyr, httr, lubridate, jsonlite, readr, rvest, stringr, tibble, janitor, rlang, ggridges, magrittr, genius, assertthat, xml2
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
URL: https://github.com/charlie86/spotifyr
BugReports: https://github.com/charlie86/spotifyr/issues
NeedsCompilation: no
Packaged: 2021-06-14 18:44:26 UTC; Daniel Antal
Author: Charlie Thompson [aut], Daniel Antal [aut, cre] (<https://orcid.org/0000-0001-7513-6760>), Josiah Parry [aut] (<https://orcid.org/0000-0001-9910-865X>), Donal Phipps [aut], Tom Wolff [aut]
Repository: CRAN
Date/Publication: 2021-06-17 05:50:06 UTC

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Package PSS.Health updated to version 0.2.1 with previous version 0.1.6 dated 2021-04-08

Title: Power and Sample Size for Health Researchers via Shiny
Description: Power and Sample Size for Health Researchers is a Shiny application that brings together a series of functions related to sample size and power calculations for common analysis in the healthcare field. There are functionalities to calculate the power, sample size to estimate or test hypotheses for means and proportions (including test for correlated groups, equivalence, non-inferiority and superiority), association, correlations coefficients, regression coefficients (linear, logistic and Cox), linear mixed model, Cronbach's alpha, interobserver agreement, intraclass correlation coefficients, limit of agreement on Bland-Altman plots, area under the curve, sensitivity and specificity incorporating the prevalence of disease. You can also use the online version at <https://hcpa-unidade-bioestatistica.shinyapps.io/PSS_Health/>.
Author: Rogério Boff Borges [aut, cre] (<https://orcid.org/0000-0002-2548-1889>), Guilherme Serpa Azambuja [aut] (<https://orcid.org/0000-0001-6246-4538>), Aline Castello Branco Mancuso [aut] (<https://orcid.org/0000-0001-6033-8335>), Vanessa Bielefeldt Leotti [aut] (<https://orcid.org/0000-0003-3860-9367>), Vânia Naomi Hirakata [aut] (<https://orcid.org/0000-0003-4645-2080>), Suzi Alves Camey [aut] (<https://orcid.org/0000-0002-5564-081X>), Stela Maris de Jezus Castro [aut] (<https://orcid.org/0000-0001-5862-6709>), Hospital de Clínicas de Porto Alegre [fnd]
Maintainer: Rogério Boff Borges <roborges@hcpa.edu.br>

Diff between PSS.Health versions 0.1.6 dated 2021-04-08 and 0.2.1 dated 2021-06-17

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Package pedSimulate updated to version 1.0.0 with previous version 0.1.2 dated 2021-02-22

Title: Pedigree, Genetic Merit and Phenotype Simulation
Description: Simulate pedigree, genetic merits and phenotypes with random/non-random matings followed by random/non-random selection with different intensities and patterns in males and females. Bijma, P. & Rutten, M. (2002) <https://www.wur.nl/en/Research-Results/Chair-groups/Animal-Sciences/Animal-Breeding-and-Genomics-Group/Research/Software.htm>.
Author: Mohammad Ali Nilforooshan [aut, cre] (<https://orcid.org/0000-0003-0339-5442>)
Maintainer: Mohammad Ali Nilforooshan <m.a.nilforooshan@gmail.com>

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Package DescriptiveWH updated to version 1.0.3 with previous version 1.0.2 dated 2021-06-13

Title: Descriptive Statistics
Description: Exploratory analysis of a data base. Using the functions of this package is possible to filter the data set detecting atypical values (outliers) and to perform exploratory analysis through visual inspection or dispersion measures. With this package you can explore the structure of your data using several parameters at the same time joining statistical parameters with different graphics. Finally, this package aid to confirm or reject the hypothesis that your data structure presents a normal distribution. Therefore this package is useful to get a previous insight of your data before to carry out statistical analysis.
Author: William Herrera-Caceres [aut, cre]
Maintainer: William Herrera-Caceres <williamandresh@hotmail.com>

Diff between DescriptiveWH versions 1.0.2 dated 2021-06-13 and 1.0.3 dated 2021-06-17

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Package realtest updated to version 0.2.1 with previous version 0.1.2 dated 2021-06-04

Title: When Expectations Meet Reality: Realistic Unit Testing
Description: A framework for unit testing for realistic minimalists, where we distinguish between expected, acceptable, current, fallback, ideal, or regressive behaviour. It can also be used for monitoring third-party software projects for changes.
Author: Marek Gagolewski [aut, cre, cph] (<https://orcid.org/0000-0003-0637-6028>)
Maintainer: Marek Gagolewski <marek@gagolewski.com>

Diff between realtest versions 0.1.2 dated 2021-06-04 and 0.2.1 dated 2021-06-17

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Package qrNLMM updated to version 2.2 with previous version 2.1 dated 2021-05-20

Title: Quantile Regression for Nonlinear Mixed-Effects Models
Description: Quantile regression (QR) for Nonlinear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference results for the fixed-effects and variance components. It also provides graphical summaries for assessing the algorithm convergence and fitting results.
Author: Christian E. Galarza <cgalarza88@gmail.com> and Victor H. Lachos <hlachos@ime.unicamp.br>
Maintainer: Christian E. Galarza <cgalarza88@gmail.com>

Diff between qrNLMM versions 2.1 dated 2021-05-20 and 2.2 dated 2021-06-17

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Package ctsem updated to version 3.5.2 with previous version 3.5.0 dated 2021-06-01

Title: Continuous Time Structural Equation Modelling
Description: Hierarchical continuous time state space modelling, for linear and nonlinear systems measured by continuous variables, with limited support for binary data. The subject specific dynamic system is modelled as a stochastic differential equation (SDE), measurement models are typically multivariate normal factor models. Linear mixed effects SDE's estimated via maximum likelihood and optimization are the default. Nonlinearities, (state dependent parameters) and random effects on all parameters are possible, using either max likelihood / max a posteriori optimization (with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling. See <https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf> for details. Priors may be used. For the conceptual overview of the hierarchical Bayesian linear SDE approach, see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>. Exogenous inputs may also be included, for an overview of such possibilities see <https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models> . Stan based functions are not available on 32 bit Windows systems at present. <https://cdriver.netlify.app/> contains some tutorial blog posts.
Author: Charles Driver [aut, cre, cph], Manuel Voelkle [aut, cph], Han Oud [aut, cph], Trustees of Columbia University [cph]
Maintainer: Charles Driver <charles.driver@ibe.uzh.ch>

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Package ciftiTools updated to version 0.3.1 with previous version 0.2.2 dated 2021-03-16

Title: Tools for Reading and Visualizing CIFTI Brain Files
Description: CIFTI files contain brain imaging data in "gray-ordinates", which represent the gray matter as cortical surface vertices (left and right) and subcortical voxels (cerebellum, basal ganglia, and other deep gray matter). 'ciftiTools' uses the Connectome Workbench to read CIFTI files into R and apply common pre-processing steps (e.g. smoothing, resampling). It also provides tools for visualizing the cortical surface with GIFTI files, and for visualizing the subcortical volume.
Author: Amanda Mejia [aut, cre], Damon Pham [aut] (<https://orcid.org/0000-0001-7563-4727>)
Maintainer: Amanda Mejia <mandy.mejia@gmail.com>

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More information about ciftiTools at CRAN
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Package blockCV updated to version 2.1.4 with previous version 2.1.1 dated 2020-02-23

Title: Spatial and Environmental Blocking for K-Fold Cross-Validation
Description: Creating spatially or environmentally separated folds for cross-validation to provide a robust error estimation in spatially structured environments; Investigating and visualising the effective range of spatial autocorrelation in continuous raster covariates to find an initial realistic distance band to separate training and testing datasets spatially described in Valavi, R. et al. (2019) <doi:10.1111/2041-210X.13107>.
Author: Roozbeh Valavi [aut, cre], Jane Elith [aut], José Lahoz-Monfort [aut], Gurutzeta Guillera-Arroita [aut]
Maintainer: Roozbeh Valavi <valavi.r@gmail.com>

Diff between blockCV versions 2.1.1 dated 2020-02-23 and 2.1.4 dated 2021-06-17

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More information about blockCV at CRAN
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