Mon, 30 Nov 2020

Package Tplyr updated to version 0.2.2 with previous version 0.2.1 dated 2020-11-10

Title: A Grammar of Clinical Data Summary
Description: A tool created to simplify the data manipulation necessary to create clinical reports.
Author: Eli Miller [aut] (<https://orcid.org/0000-0002-2127-9456>), Mike Stackhouse [aut, cre] (<https://orcid.org/0000-0001-6030-723X>), Ashley Tarasiewicz [aut], Nathan Kosiba [aut] (<https://orcid.org/0000-0001-5359-4234>), Atorus Research LLC [cph]
Maintainer: Mike Stackhouse <mike.stackhouse@atorusresearch.com>

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Package sglg updated to version 0.1.8 with previous version 0.1.7 dated 2020-09-19

Title: Fitting Semi-Parametric Generalized log-Gamma Regression Models
Description: Set of tools to fit a linear multiple or semi-parametric regression models and non-informative right-censoring may be considered. Under this setup, the localization parameter of the response variable distribution is modeled by using linear multiple regression or semi-parametric functions, whose non-parametric components may be approximated by natural cubic spline or P-splines. The supported distribution for the model error is a generalized log-gamma distribution which includes the generalized extreme value and standard normal distributions as important special cases.
Author: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com> and G. Paula and L. Vanegas
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>

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Package sfheaders updated to version 0.4.0 with previous version 0.3.0 dated 2020-10-31

Title: Converts Between R Objects and Simple Feature Objects
Description: Converts between R and Simple Feature 'sf' objects, without depending on the Simple Feature library. Conversion functions are available at both the R level, and through 'Rcpp'.
Author: David Cooley [aut, cre], Michael Sumner [ctb]
Maintainer: David Cooley <david.cooley.au@gmail.com>

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Package scdhlm updated to version 0.5.1 with previous version 0.5.0 dated 2020-11-08

Title: Estimating Hierarchical Linear Models for Single-Case Designs
Description: Provides a set of tools for estimating hierarchical linear models and effect sizes based on data from single-case designs. Functions are provided for calculating standardized mean difference effect sizes that are directly comparable to standardized mean differences estimated from between-subjects randomized experiments, as described in Hedges, Pustejovsky, and Shadish (2012) <DOI:10.1002/jrsm.1052>; Hedges, Pustejovsky, and Shadish (2013) <DOI:10.1002/jrsm.1086>; and Pustejovsky, Hedges, and Shadish (2014) <DOI:10.3102/1076998614547577>. Includes an interactive web interface.
Author: James Pustejovsky [aut, cre], Man Chen [aut], Bethany Hamilton [aut]
Maintainer: James Pustejovsky <jepusto@gmail.com>

Diff between scdhlm versions 0.5.0 dated 2020-11-08 and 0.5.1 dated 2020-11-30

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Package PSS.Health updated to version 0.1.5 with previous version 0.1.4 dated 2020-11-12

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 equivalence, non-inferiority and superiority), association, Pearson's correlation coefficient, 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.
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 0.1.4 dated 2020-11-12 and 0.1.5 dated 2020-11-30

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Package pagedown updated to version 0.13 with previous version 0.12 dated 2020-10-13

Title: Paginate the HTML Output of R Markdown with CSS for Print
Description: Use the paged media properties in CSS and the JavaScript library 'paged.js' to split the content of an HTML document into discrete pages. Each page can have its page size, page numbers, margin boxes, and running headers, etc. Applications of this package include books, letters, reports, papers, business cards, resumes, and posters.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Romain Lesur [aut, cph] (<https://orcid.org/0000-0002-0721-5595>), Brent Thorne [aut] (<https://orcid.org/0000-0002-1099-3857>), Xianying Tan [aut] (<https://orcid.org/0000-0002-6072-3521>), Christophe Dervieux [ctb] (<https://orcid.org/0000-0003-4474-2498>), Atsushi Yasumoto [ctb] (<https://orcid.org/0000-0002-8335-495X>), RStudio, PBC [cph], Adam Hyde [ctb] (paged.js in resources/js/), Min-Zhong Lu [ctb] (resume.css in resources/css/), Zulko [ctb] (poster-relaxed.css in resources/css/)
Maintainer: Yihui Xie <xie@yihui.name>

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Package lme4 updated to version 1.1-26 with previous version 1.1-25 dated 2020-10-23

Title: Linear Mixed-Effects Models using 'Eigen' and S4
Description: Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".
Author: Douglas Bates [aut] (<https://orcid.org/0000-0001-8316-9503>), Martin Maechler [aut] (<https://orcid.org/0000-0002-8685-9910>), Ben Bolker [aut, cre] (<https://orcid.org/0000-0002-2127-0443>), Steven Walker [aut] (<https://orcid.org/0000-0002-4394-9078>), Rune Haubo Bojesen Christensen [ctb] (<https://orcid.org/0000-0002-4494-3399>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>), Bin Dai [ctb], Fabian Scheipl [ctb] (<https://orcid.org/0000-0001-8172-3603>), Gabor Grothendieck [ctb], Peter Green [ctb] (<https://orcid.org/0000-0002-0238-9852>), John Fox [ctb], Alexander Bauer [ctb], Pavel N. Krivitsky [ctb, cph] (<https://orcid.org/0000-0002-9101-3362>, shared copyright on simulate.formula)
Maintainer: Ben Bolker <bbolker+lme4@gmail.com>

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Package landsepi updated to version 1.0.2 with previous version 1.0.1 dated 2020-07-02

Title: Landscape Epidemiology and Evolution
Description: A stochastic, spatially-explicit, demo-genetic model simulating the spread and evolution of a plant pathogen in a heterogeneous landscape to assess resistance deployment strategies. It is based on a spatial geometry for describing the landscape and allocation of different cultivars, a dispersal kernel for the dissemination of the pathogen, and a SEIR ('Susceptible-Exposed-Infectious-Removed’) structure with a discrete time step. It provides a useful tool to assess the performance of a wide range of deployment options with respect to their epidemiological, evolutionary and economic outcomes. Loup Rimbaud, Julien Papaïx, Jean-François Rey, Luke G Barrett, Peter H Thrall (2018) <doi:10.1371/journal.pcbi.1006067>.
Author: Loup Rimbaud [aut], Julien Papaix [aut], Jean-Francois Rey [cre], Jean-Loup Gaussen [ctb]
Maintainer: Jean-Francois Rey <jean-francois.rey@inrae.fr>

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Package jcp updated to version 1.1 with previous version 1.0 dated 2019-03-22

Title: Joint Change Point Detection
Description: Procedures for joint detection of changes in both expectation and variance in univariate sequences. Performs a statistical test of the null hypothesis of the absence of change points. In case of rejection performs an algorithm for change point detection. References - Bivariate change point detection (2019+), Michael Messer.
Author: Michael Messer
Maintainer: Michael Messer <michael.messer@tuwien.ac.at>

Diff between jcp versions 1.0 dated 2019-03-22 and 1.1 dated 2020-11-30

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Package inline updated to version 0.3.17 with previous version 0.3.16 dated 2020-09-06

Title: Functions to Inline C, C++, Fortran Function Calls from R
Description: Functionality to dynamically define R functions and S4 methods with 'inlined' C, C++ or Fortran code supporting the .C and .Call calling conventions.
Author: Oleg Sklyar, Duncan Murdoch, Mike Smith, Dirk Eddelbuettel, Romain Francois, Karline Soetaert, Johannes Ranke
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package idiogramFISH updated to version 1.16.8 with previous version 1.16.7 dated 2020-10-15

Title: Idiograms with Marks and Karyotype Indices
Description: Plot idiograms of karyotypes, plasmids, circular chr. having a set of data.frames for chromosome data and optionally mark data. Two styles of chromosomes can be used: without or with visible chromatids (when not circular). Supports micrometers, cM and Mb or any unit. Two styles of centromeres are available: triangular and rounded; and six styles of marks: square (squareLeft), dots, cM (cMLeft), cenStyle, upArrow, downArrow; its legend (label) can be drawn inline or to the right of karyotypes. Idiograms can also be plotted in concentric circles. It is possible to calculate chromosome indices by Levan et al. (1964) <doi:10.1111/j.1601-5223.1964.tb01953.x>, karyotype indices of Watanabe et al. (1999) <doi:10.1007/PL00013869> and Romero-Zarco (1986) <doi:10.2307/1221906> and classify chromosomes by morphology Guerra (1986) and Levan et al. (1964).
Author: Fernando Roa [aut, cre], Mariana PC Telles [ctb]
Maintainer: Fernando Roa <froao@unal.edu.co>

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New package flare with initial version 1.7.0
Package: flare
Type: Package
Title: Family of Lasso Regression
Version: 1.7.0
Date: 2020-11-28
Author: Xingguo Li, Tuo Zhao, Lie Wang, Xiaoming Yuan, and Han Liu
Maintainer: Xingguo Li <xingguo.leo@gmail.com>
Depends: R (>= 2.15.0), lattice, MASS, Matrix, igraph
Imports: methods
Description: Provide the implementation of a family of Lasso variants including Dantzig Selector, LAD Lasso, SQRT Lasso, Lq Lasso for estimating high dimensional sparse linear model. We adopt the alternating direction method of multipliers and convert the original optimization problem into a sequential L1 penalized least square minimization problem, which can be efficiently solved by linearization algorithm. A multi-stage screening approach is adopted for further acceleration. Besides the sparse linear model estimation, we also provide the extension of these Lasso variants to sparse Gaussian graphical model estimation including TIGER and CLIME using either L1 or adaptive penalty. Missing values can be tolerated for Dantzig selector and CLIME. The computation is memory-optimized using the sparse matrix output. For more information, please refer to <https://www.jmlr.org/papers/volume16/li15a/li15a.pdf>.
License: GPL-2
Repository: CRAN
NeedsCompilation: yes
Packaged: 2020-11-30 18:10:54 UTC; maomao-xingguo
Date/Publication: 2020-12-01 00:30:16 UTC

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Package cort updated to version 0.3.2 with previous version 0.3.1 dated 2020-05-13

Title: Some Empiric and Nonparametric Copula Models
Description: Provides S4 classes and methods to fit several copula models: The classic empirical checkerboard copula and the empirical checkerboard copula with known margins, see Cuberos, Masiello and Maume-Deschamps (2019) <doi:10.1080/03610926.2019.1586936> are proposed. These two models allow to fit copulas in high dimension with a small number of observations, and they are always proper copulas. Some flexibility is added via a possibility to differentiate the checkerboard parameter by dimension. The last model consist of the implementation of the Copula Recursive Tree algorithm proposed by Laverny, Maume-Deschamps, Masiello and Rullière (2020) <arXiv:2005.02912>, including the localised dimension reduction, which fits a copula by recursive splitting of the copula domain. We also provide an efficient way of mixing copulas, allowing to bag the algorithm into a forest, and a generic way of measuring d-dimensional boxes with a copula.
Author: Oskar Laverny [aut, cre] (<https://orcid.org/0000-0002-7508-999X>)
Maintainer: Oskar Laverny <oskar.laverny@gmail.com>

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Package briskaR updated to version 1.0.1 with previous version 1.0.0 dated 2020-09-15

Title: Biological Risk Assessment
Description: A spatio-temporal exposure-hazard model for assessing biological risk and impact. The model is based on stochastic geometry for describing the landscape and the exposed individuals, a dispersal kernel for the dissemination of contaminants, a set of tools to handle spatio-temporal dataframe and ecotoxicological equations. Walker E, Leclerc M, Rey JF, Beaudouin R, Soubeyrand S, and Messean A, (2017), A Spatio-Temporal Exposure-Hazard Model for Assessing Biological Risk and Impact, Risk Analysis, <doi:10.1111/risa.12941>. Leclerc M, Walker E, Messean A, Soubeyrand S (2018), Spatial exposure-hazard and landscape models for assessing the impact of GM crops on non-target organisms, Science of the Total Environment, 624, 470-479.
Author: Virgile Baudrot [aut], Emily Walker [aut], Jean-Francois Rey [aut, cre], Melen Leclerc [aut], Samuel Soubeyrand [ctb], Marc Bourotte [ctb]
Maintainer: Jean-Francois Rey <jean-francois.rey@inrae.fr>

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Package r5r updated to version 0.2-1 with previous version 0.2-0 dated 2020-10-20

Title: Rapid Realistic Routing with 'R5'
Description: Rapid realistic routing on multimodal transport networks (walk, bike, public transport and car) using 'R5', the Rapid Realistic Routing on Real-world and Reimagined networks <https://github.com/conveyal/r5>. The package allows users to generate detailed routing analysis or calculate travel time matrices using seamless parallel computing on top of the R5 Java machine.
Author: Marcus Saraiva [aut] (<https://orcid.org/0000-0001-6218-2338>), Rafael H. M. Pereira [aut, cre] (<https://orcid.org/0000-0003-2125-7465>), Daniel Herszenhut [aut] (<https://orcid.org/0000-0001-8066-1105>), Carlos Kaue Vieira Braga [aut] (<https://orcid.org/0000-0002-6104-7297>), Ipea - Institue for Applied Economic Research [cph, fnd]
Maintainer: Rafael H. M. Pereira <rafa.pereira.br@gmail.com>

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Package MSG updated to version 0.6 with previous version 0.5 dated 2020-09-09

Title: Data and Functions for the Book Modern Statistical Graphics
Description: A companion to the Chinese book ``Modern Statistical Graphics''.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Lijia Yu [ctb], Xiangyun Huang [ctb], Peng Zhao [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package albatross updated to version 0.2-0 with previous version 0.1-2 dated 2020-10-02

Title: PARAFAC Analysis of Fluorescence Excitation-Emission Matrices
Description: Perform parallel factor analysis (PARAFAC: Hitchcock, 1927) <doi:10.1002/sapm192761164> on fluorescence excitation-emission matrices (FEEMs): handle scattering signal and inner filter effect, scale the dataset, fit the model; perform split-half validation or jack-knifing. A modified approach called "randomised split-half" is also available. The package has a low dependency footprint (only two direct dependencies not in core or recommended; four total non-core/recommended dependencies) and has been tested on a wide range of R versions (including R as old as 3.3.3 from Debian Stretch).
Author: Ivan Krylov [aut, cre], Timur Labutin [ths]
Maintainer: Ivan Krylov <ikrylov@laser.chem.msu.ru>

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Package Directional updated to version 4.5 with previous version 4.4 dated 2020-07-13

Title: A Collection of R Functions for Directional Data Analysis
Description: A collection of functions for directional data (including massive, with millions of observations, data) analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). Other references include a) Phillip J. Paine, Simon P. Preston Michail Tsagris and Andrew T. A. Wood (2018). An elliptically symmetric angular Gaussian distribution. Statistics and Computing 28(3): 689-697. <doi:10.1007/s11222-017-9756-4>. b) Tsagris M. and Alenazi A. (2019). Comparison of discriminant analysis methods on the sphere. Communications in Statistics: Case Studies, Data Analysis and Applications 5(4):467--491. <doi:10.1080/23737484.2019.1684854>. c) P. J. Paine, S. P. Preston, M. Tsagris and Andrew T. A. Wood (2020). Spherical regression models with general covariates and anisotropic errors. Statistics and Computing 30(1): 153--165. <doi:10.1007/s11222-019-09872-2>.
Author: Michail Tsagris, Giorgos Athineou, Anamul Sajib, Eli Amson, Micah J. Waldstein
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package Require updated to version 0.0.9 with previous version 0.0.8 dated 2020-09-10

Title: Installing and Loading R Packages for Reproducible Workflows
Description: A single key function, 'Require' that wraps 'install.packages', 'remotes::install_github', 'versions::install.versions', and 'base::require' that allows for reproducible workflows. As with other functions in a reproducible workflow, this package emphasizes functions that return the same result whether it is the first or subsequent times running the function. Maturing.
Author: Eliot J B McIntire [aut, cre] (<https://orcid.org/0000-0002-6914-8316>), Her Majesty the Queen 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 gateR updated to version 0.1.4 with previous version 0.1.3 dated 2020-11-17

Title: Flow/Mass Cytometry Gating via Spatial Kernel Density Estimation
Description: Estimates statistically significant marker combination values within which one immunologically distinctive group (i.e., disease case) is more associated than another group (i.e., healthy control), successively, using various combinations (i.e., "gates") of markers to examine features of cells that may be different between groups. For a two-group comparison, the 'gateR' package uses the spatial relative risk function that is estimated using the 'sparr' package. Details about the 'sparr' package methods can be found in the tutorial: Davies et al. (2018) <doi:10.1002/sim.7577>. Details about kernel density estimation can be found in J. F. Bithell (1990) <doi:10.1002/sim.4780090616>. More information about relative risk functions using kernel density estimation can be found in J. F. Bithell (1991) <doi:10.1002/sim.4780101112>.
Author: Ian D. Buller [aut, cre, cph] (<https://orcid.org/0000-0001-9477-8582>), Elena Hsieh [ctb] (<https://orcid.org/0000-0003-3969-6597>), Debashis Ghosh [ctb] (<https://orcid.org/0000-0001-6618-1316>), Lance A. Waller [ctb] (<https://orcid.org/0000-0001-5002-8886>), NCI [cph]
Maintainer: Ian D. Buller <ian.buller@nih.gov>

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Package scMappR updated to version 0.1.5 with previous version 0.1.4 dated 2020-09-02

Title: Single Cell Mapper
Description: Description of scMappR R package adapted from pre-print. The single cell mapper (scMappR) R package contains a suite of bioinformatic tools that provide experimentally relevant cell-type specific information to a list of differentially expressed genes (DEG). The function "scMappR_and_pathway_analysis" reranks DEGs to generate cell-type specificity scores called cell-weighted fold-changes. Users input a list of DEGs, normalized counts, and a signature matrix into this function. scMappR then re-weights bulk DEGs by cell-type specific expression from the signature matrix, cell-type proportions from RNA-seq deconvolution and the ratio of cell-type proportions between the two conditions to account for changes in cell-type proportion. With cwFold-changes calculated, scMappR uses two approaches to utilize cwFold-changes to complete cell-type specific pathway analysis. The "process_dgTMatrix_lists" function in the scMappR package contains an automated scRNA-seq processing pipeline where users input scRNA-seq count data, which is made compatible for scMappR and other R packages that analyze scRNA-seq data. We further used this to store hundreds up regularly updating signature matrices. The functions "tissue_by_celltype_enrichment", "tissue_scMappR_internal", and "tissue_scMappR_custom" combine these consistently processed scRNAseq count data with gene-set enrichment tools to allow for cell-type marker enrichment of a generic gene list (e.g. GWAS hits). Reference: Sokolowski,D.J., Faykoo-Martinez,M., Erdman,L., Hou,H., Chan,C., Zhu,H., Holmes,M.M., Goldenberg,A. and Wilson,M.D. (2020) Single-cell mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially expressed genes. BioRxiv, 10.1101/2020.08.24.265298.
Author: Dustin Sokolowski [aut, cre], Mariela Faykoo-Martinez [aut], Lauren Erdman [aut], Houyun Hou [aut], Cadia Chan [aut], Helen Zhu [aut], Melissa Holmes [aut], Anna Goldenberg [aut], Michael Wilson [aut]
Maintainer: Dustin Sokolowski <dustin.sokolowski@sickkids.ca>

Diff between scMappR versions 0.1.4 dated 2020-09-02 and 0.1.5 dated 2020-11-30

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More information about scMappR at CRAN
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Package PMCMRplus updated to version 1.7.1 with previous version 1.7.0 dated 2020-10-30

Title: Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended
Description: For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs multiple comparisons tests (Tukey-Kramer test, Scheffe test, LSD-test) and many-to-one tests (Dunnett test) for normally distributed residuals and equal within variance are available. Furthermore, all-pairs tests (Games-Howell test, Tamhane's T2 test, Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one (Tamhane-Dunnett Test) for normally distributed residuals and heterogeneous variances are provided. Van der Waerden's normal scores test for omnibus, all-pairs and many-to-one tests is provided for non-normally distributed residuals and homogeneous variances. The Kruskal-Wallis, BWS and Anderson-Darling omnibus test and all-pairs tests (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- Fligner test) as well as many-to-one (Nemenyi test, Dunn test, U-test) are given for the analysis of variance by ranks. Non-parametric trend tests (Jonckheere test, Cuzick test, Johnson-Mehrotra test, Spearman test) are included. In addition, a Friedman-test for one-way ANOVA with repeated measures on ranks (CRBD) and Skillings-Mack test for unbalanced CRBD is provided with consequent all-pairs tests (Nemenyi test, Siegel test, Miller test, Conover test, Exact test) and many-to-one tests (Nemenyi test, Demsar test, Exact test). A trend can be tested with Pages's test. Durbin's test for a two-way balanced incomplete block design (BIBD) is given in this package as well as Gore's test for CRBD with multiple observations per cell is given. Outlier tests, Mandel's k- and h statistic as well as functions for Type I error and Power analysis as well as generic summary, print and plot methods are provided.
Author: Thorsten Pohlert [aut, cre] (<https://orcid.org/0000-0003-3855-3025>)
Maintainer: Thorsten Pohlert <thorsten.pohlert@gmx.de>

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Package dnr updated to version 0.3.5 with previous version 0.3.4 dated 2018-07-26

Title: Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family
Description: Functions are provided to fit temporal lag models to dynamic networks. The models are build on top of exponential random graph models (ERGM) framework. There are functions for simulating or forecasting networks for future time points. Abhirup Mallik & Zack W. Almquist (2019) Stable Multiple Time Step Simulation/Prediction From Lagged Dynamic Network Regression Models, Journal of Computational and Graphical Statistics, 28:4, 967-979, <DOI: 10.1080/10618600.2019.1594834>.
Author: Abhirup Mallik [aut, cre], Zack Almquist [aut]
Maintainer: Abhirup Mallik <abhirupkgp@gmail.com>

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Package bayescopulareg updated to version 0.1.3 with previous version 0.1.2 dated 2020-05-28

Title: Bayesian Copula Regression
Description: Tools for Bayesian copula generalized linear models (GLMs). The sampling scheme is based on Pitt, Chan, and Kohn (2006) <doi:10.1093/biomet/93.3.537>. Regression parameters (including coefficients and dispersion parameters) are estimated via the adaptive random walk Metropolis approach developed by Haario, Saksman, and Tamminen (1999) <doi:10.1007/s001800050022>. The prior for the correlation matrix is based on Hoff (2007) <doi:10.1214/07-AOAS107>.
Author: Ethan Alt [aut, cre], Yash Bhosale [aut]
Maintainer: Ethan Alt <ethanalt@live.unc.edu>

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Package gfpop updated to version 1.0.1 with previous version 1.0.0 dated 2020-11-25

Title: Graph-Constrained Functional Pruning Optimal Partitioning
Description: Penalized parametric change-point detection by functional pruning dynamic programming algorithm. The successive means are constrained using a graph structure with edges of types null, up, down, std or abs. To each edge we can associate some additional properties: a minimal gap size, a penalty, some robust parameters (K,a). The user can also constrain the inferred means to lie between some minimal and maximal values. Data is modeled by a quadratic cost with possible use of a robust loss, biweight and Huber (see edge parameters K and a). Other losses are also available with log-linear representation or a log-log representation.
Author: Vincent Runge [aut, cre], Toby Hocking [aut], Guillem Rigaill [aut], Gaetano Romano [aut], Fatemeh Afghah [aut], Paul Fearnhead [aut], Michel Koskas [ctb], Arnaud Liehrmann [ctb]
Maintainer: Vincent Runge <vincent.runge@univ-evry.fr>

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Package FunnelPlotR updated to version 0.3.2 with previous version 0.3.1 dated 2020-09-16

Title: Funnel Plots for Comparing Institutional Performance
Description: An implementation of methods presented by Spiegelhalter (2005) <doi:10.1002/sim.1970> Funnel plots for comparing institutional performance, for standardised ratios, ratios of counts and proportions with additive overdispersion adjustment.
Author: Chris Mainey [aut, cre] (<https://orcid.org/0000-0002-3018-6171>), Matthew Bass [ctb]
Maintainer: Chris Mainey <chris.mainey@uhb.nhs.uk>

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Package BFpack updated to version 0.3.1 with previous version 0.2.1 dated 2020-05-11

Title: Flexible Bayes Factor Testing of Scientific Expectations
Description: Implementation of various default Bayes factors for testing statistical hypotheses. The package is intended for applied quantitative researchers in the social and behavioral sciences, medical research, and related fields. The Bayes factor tests can be executed for statistical models such as univariate and multivariate normal linear models, generalized linear models, special cases of linear mixed models, survival models, relational event models. Parameters that can be tested are location parameters (e.g., regression coefficients), variances (e.g., group variances), and measures of association (e.g,. bivariate correlations). The statistical underpinnings are described in Mulder, Hoijtink, and Xin (2019) <arXiv:1904.00679>, Mulder and Gelissen (2019) <arXiv:1807.05819>, Mulder (2016) <DOI:10.1016/j.jmp.2014.09.004>, Mulder and Fox (2019) <DOI:10.1214/18-BA1115>, Mulder and Fox (2013) <DOI:10.1007/s11222-011-9295-3>, Boeing-Messing, van Assen, Hofman, Hoijtink, and Mulder <DOI:10.1037/met0000116>, Hoijtink, Mulder, van Lissa, and Gu, (2018) <DOI:10.31234/osf.io/v3shc>, Gu, Mulder, and Hoijtink, (2018) <DOI:10.1111/bmsp.12110>, Hoijtink, Gu, and Mulder, (2018) <DOI:10.1111/bmsp.12145>, and Hoijtink, Gu, Mulder, and Rosseel, (2018) <DOI:10.1037/met0000187>.
Author: Joris Mulder [aut, cre], Caspar van Lissa [aut, ctb], Donald R. Williams [aut, ctb], Xin Gu [aut], Anton Olsson-Collentine [aut, ctb], Florian Boeing-Messing [aut, ctb], Jean-Paul Fox [aut, ctb], Janosch Menke [ctb], Robbie van Aert [ctb], Barry Brown [ctb], James Lovato [ctb], Kathy Russell [ctb], Lapack 3.8 [ctb], Jack Dongarra [ctb], Jim Bunch [ctb], Cleve Moler [ctb], Gilbert Stewart [ctb], John Burkandt [ctb], Ashwith Rego [ctb], Alexander Godunov [ctb], Alan Miller [ctb], Jean-Pierre Moreau [ctb], The R Core Team [cph]
Maintainer: Joris Mulder <j.mulder3@tilburguniversity.edu>

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Package bbreg updated to version 2.0.1 with previous version 2.0.0 dated 2020-11-30

Title: Bessel and Beta Regressions via Expectation-Maximization Algorithm for Continuous Bounded Data
Description: Functions to fit, via Expectation-Maximization (EM) algorithm, the Bessel and Beta regressions to a data set with a bounded continuous response variable. The Bessel regression is a new and robust approach proposed in the literature. The EM version for the well known Beta regression is another major contribution of this package. See the reference Barreto-Souza, Mayrink and Simas (2020) <arXiv:2003.05157> for details.
Author: Vinicius Mayrink [cre, aut] (<https://orcid.org/0000-0002-5683-8326>), Alexandre B. Simas [aut] (<https://orcid.org/0000-0003-2562-2829>), Wagner Barreto-Souza [aut] (<https://orcid.org/0000-0003-0831-7881>)
Maintainer: Vinicius Mayrink <vdinizm@gmail.com>

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More information about bbreg at CRAN
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Package questionr updated to version 0.7.4 with previous version 0.7.3 dated 2020-10-05

Title: Functions to Make Surveys Processing Easier
Description: Set of functions to make the processing and analysis of surveys easier : interactive shiny apps and addins for data recoding, contingency tables, dataset metadata handling, and several convenience functions.
Author: Julien Barnier [aut, cre], François Briatte [aut], Joseph Larmarange [aut]
Maintainer: Julien Barnier <julien.barnier@cnrs.fr>

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Package tm1r updated to version 1.1.7 with previous version 1.1.6 dated 2020-11-14

Title: The Integration Between 'IBM COGNOS TM1' and R
Description: Useful functions to connect to 'TM1' <https://www.ibm.com/uk-en/products/planning-and-analytics> instance from R via REST API. With the functions in the package, data can be imported from 'TM1' via mdx view or native view, data can be sent to 'TM1', processes and chores can be executed, and cube and dimension metadata information can be taken.
Author: Muhammed Ali Onder
Maintainer: Muhammed Ali Onder <muhammedalionder@gmail.com>

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Package mRpostman updated to version 1.0.0 with previous version 0.9.0.0 dated 2020-09-16

Title: An IMAP Client for R
Description: An easy-to-use IMAP client that provides tools for message searching, selective fetching of message attributes, mailbox management, attachment extraction, and several other IMAP features, paving the way for e-mail data analysis.
Author: Allan Quadros [aut, cre] (<https://orcid.org/0000-0003-3250-5380>)
Maintainer: Allan Quadros <allanvcq@gmail.com>

Diff between mRpostman versions 0.9.0.0 dated 2020-09-16 and 1.0.0 dated 2020-11-30

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Package emstreeR updated to version 2.2.2 with previous version 2.2.0 dated 2019-05-08

Title: Tools for Fast Computing and Plotting Euclidean Minimum Spanning Trees
Description: Fast and easily computes an Euclidean Minimum Spanning Tree (EMST) from data. This package relies on 'RcppMLPACK' to provide an R interface to the Dual-Tree Boruvka algorithm (March, Ram, Gray, 2010, <doi:10.1145/1835804.1835882>) implemented in 'mlpack', the C++ Machine Learning Library (Curtin et. al., 2013). The Dual-Tree Boruvka is theoretically and empirically the fastest algorithm for computing an EMST. This package also provides functions and an S3 method for readily plotting Minimum Spanning Trees (MST) using either the style of the 'base', 'scatterplot3d', or 'ggplot2' libraries.
Author: Allan Quadros [aut, cre]
Maintainer: Allan Quadros <allanvcq@gmail.com>

Diff between emstreeR versions 2.2.0 dated 2019-05-08 and 2.2.2 dated 2020-11-30

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Package CenBAR updated to version 0.1.1 with previous version 0.1.0 dated 2020-02-26

Title: Broken Adaptive Ridge AFT Model with Censored Data
Description: Broken adaptive ridge estimator for censored data is used to select variables and estimate their coefficients in the semi-parametric accelerated failure time model for right-censored survival data.
Author: Zhihua Sun [aut, cre], Chunyu Yu [aut], Gang Li [aut], Kani Chen [ctb], Yi Liu [ctb]
Maintainer: Zhihua Sun <zhihuasun@ouc.edu.cn>

Diff between CenBAR versions 0.1.0 dated 2020-02-26 and 0.1.1 dated 2020-11-30

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New package BTYD with initial version 2.4.1
Package: BTYD
Type: Package
Title: Implementing BTYD Models with the Log Sum Exp Patch
Version: 2.4.1
Authors@R: c(person("Lukasz", "Dziurzynski", role="aut"), person("Edward", "Wadsworth", role="aut"), person("Peter", "Fader", role="ctb"), person("Elea", "McDonnell Feit", role="ctb"), person("Daniel", "McCarthy", role=c("aut", "ctb")), person("Bruce", "Hardie", role="ctb"), person("Arun", "Gopalakrishnan", role="ctb"), person("Eric", "Schwartz", role="ctb"), person("Yao", "Zhang", role="ctb"), person("Gabi", "Huiber", role=c("ctb", "cre"), email="ghuiber@gmail.com"))
Maintainer: Gabi Huiber <ghuiber@gmail.com>
Description: Functions for data preparation, parameter estimation, scoring, and plotting for the BG/BB (Fader, Hardie, and Shang 2010 <doi:10.1287/mksc.1100.0580>), BG/NBD (Fader, Hardie, and Lee 2005 <doi:10.1287/mksc.1040.0098>) and Pareto/NBD and Gamma/Gamma (Fader, Hardie, and Lee 2005 <doi:10.1509/jmkr.2005.42.4.415>) models.
License: GPL-3
Collate: 'data.R' 'BTYD.R' 'bgbb.R' 'bgnbd.R' 'pnbd.R' 'dc.R' 'spend.R'
Depends: R(>= 3.5), hypergeo, optimx, dplyr
Imports: Matrix
Suggests: knitr, rmarkdown
VignetteBuilder: knitr, rmarkdown
Author: Lukasz Dziurzynski [aut], Edward Wadsworth [aut], Peter Fader [ctb], Elea McDonnell Feit [ctb], Daniel McCarthy [aut, ctb], Bruce Hardie [ctb], Arun Gopalakrishnan [ctb], Eric Schwartz [ctb], Yao Zhang [ctb], Gabi Huiber [ctb, cre]
NeedsCompilation: no
Encoding: UTF-8
RoxygenNote: 7.1.1
Packaged: 2020-11-18 22:58:37 UTC; ghuiber
Repository: CRAN
Date/Publication: 2020-11-30 12:30:02 UTC

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New package TraitStats with initial version 1.0.0
Package: TraitStats
Title: Statistical Data Analysis for Randomized Block Design Experiments
Version: 1.0.0
Date: 2020-11-28
Authors@R: c( person(given="Nitesh",family="Shirur Devaraja",email="mail@niteshgpb.in",role = c("aut", "cre")), person(given="Parashuram",family="Patroti",email="parashuram@millets.res.in",role = "aut"), person(given="Shilpa",family="Parashuram",email="shilpa9193@gmail.com",role = "aut"), person(given="Manoj",family="Katiyar",role="ctb"), person(given="Aravind",family="J",role="ctb",comment="Reference material of augmentedRCBD"), person(given="Sunil",family="Kumar",role="ctb"))
Maintainer: Nitesh Shirur Devaraja <mail@niteshgpb.in>
Description: Functions for analysis of bulk data generated from experiments in Randomized block design as per Panse and Sukhatme (1954) <https://books.google.co.in/books?id=Efo9AAAAYAAJ>. Computes analysis of variance; Descriptive statistics parameter like Mean, Minimum, Maximum, CV, Standard error of mean, Standard Error of deviation, CD; Genetic parameter statistics Genotypic Coefficient of Variation, Phenotypic Coefficient of Variation, Heritability in broad sense, Genetic Advance and Genetic Advance per cent mean; Variance and Co-variance matrix of genotypic, phenotypic and environmental; Correlation of genotypic, phenotypic and environmental. Further includes directly publication ready tables.
URL: https://www.niteshgpb.in/traitstats/
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: utils, stats, lattice, rlist, grid, gridExtra, qpdf
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2020-11-28 06:35:32 UTC; ADMIN
Author: Nitesh Shirur Devaraja [aut, cre], Parashuram Patroti [aut], Shilpa Parashuram [aut], Manoj Katiyar [ctb], Aravind J [ctb] (Reference material of augmentedRCBD), Sunil Kumar [ctb]
Repository: CRAN
Date/Publication: 2020-11-30 11:40:06 UTC

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Package processx updated to version 3.4.5 with previous version 3.4.4 dated 2020-09-03

Title: Execute and Control System Processes
Description: Tools to run system processes in the background. It can check if a background process is running; wait on a background process to finish; get the exit status of finished processes; kill background processes. It can read the standard output and error of the processes, using non-blocking connections. 'processx' can poll a process for standard output or error, with a timeout. It can also poll several processes at once.
Author: Gábor Csárdi [aut, cre, cph] (<https://orcid.org/0000-0001-7098-9676>), Winston Chang [aut], RStudio [cph, fnd], Mango Solutions [cph, fnd]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between processx versions 3.4.4 dated 2020-09-03 and 3.4.5 dated 2020-11-30

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New package nsyllable with initial version 1.0
Package: nsyllable
Version: 1.0
Title: Count Syllables in Character Vectors
Description: Counts syllables in character vectors for English words. Imputes syllables as the number of vowel sequences for words not found.
Authors@R: c( person("Kenneth", "Benoit", email = "kbenoit@lse.ac.uk", role = c("cre", "aut", "cph"), comment = c(ORCID = "0000-0002-0797-564X")), person("Carnegie Mellon University", email = "air+cmudict@cs.cmu.edu", role = "cph", comment = "CMU Pronunciation Dictionary (c) 1993-2015") )
License: GPL-3
Depends: R (>= 2.10)
Suggests: knitr, testthat, spelling
URL: https://github.com/quanteda/nsyllable
Encoding: UTF-8
BugReports: https://github.com/quanteda/nsyllable/issues
LazyData: TRUE
Language: en-GB
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-28 17:44:56 UTC; kbenoit
Author: Kenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Carnegie Mellon University [cph] (CMU Pronunciation Dictionary (c) 1993-2015)
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>
Repository: CRAN
Date/Publication: 2020-11-30 11:50:02 UTC

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New package mrgsim.sa with initial version 0.1.0
Package: mrgsim.sa
Type: Package
Title: Sensitivity Analysis with 'mrgsolve'
Version: 0.1.0
Authors@R: c(person("Kyle", "Baron", "", "kylebtwin@imap.cc", c("aut", "cre")))
Maintainer: Kyle Baron <kylebtwin@imap.cc>
Description: Perform sensitivity analysis on ordinary differential equation based models, including ad-hoc graphical analyses based on structured sequences of parameters as well as local sensitivity analysis. Functions are provided for creating inputs, simulating scenarios and plotting outputs.
License: GPL (>= 2)
URL: https://github.com/kylebaron/mrgsim.sa
BugReports: https://github.com/kylebaron/mrgsim.sa/issues
Suggests: testthat, knitr, rmarkdown
Imports: withr, purrr, dplyr, assertthat, rlang, ggplot2, tidyselect, tidyr, methods, tibble, patchwork
Encoding: UTF-8
Language: en-US
Depends: mrgsolve
RoxygenNote: 7.1.1
Collate: 'utils.R' 'parseq.R' 'sens.R' 'AAA.R' 'lsa.R' 'sens_each.R' 'sens_grid.R' 'sens_plot.R' 'sens_run.R' 'seq.R'
NeedsCompilation: no
Packaged: 2020-11-27 21:02:53 UTC; kyleb
Author: Kyle Baron [aut, cre]
Repository: CRAN
Date/Publication: 2020-11-30 11:20:02 UTC

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New package mapSpain with initial version 0.1.1
Package: mapSpain
Type: Package
Title: Administrative Boundaries of Spain
Version: 0.1.1
Authors@R: c(person(given = "Diego", family = "Hernangómez", role = c("aut", "cre", "cph"), email = "diego.hernangomezherrero@gmail.com", comment = c(ORCID = "0000-0001-8457-4658")), person(given = "EuroGraphics", role = "cph", comment = "for the administrative boundaries.") )
Description: Administrative Boundaries of Spain at several levels (CCAA, Provinces, Municipalities) based on the GISCO Eurostat database <https://ec.europa.eu/eurostat/web/gisco>. It also provides a 'leaflet' plugin and the ability of downloading and processing static tiles.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
BugReports: https://github.com/dieghernan/mapSpain/issues
URL: https://dieghernan.github.io/mapSpain/, https://github.com/dieghernan/mapSpain
Depends: R (>= 3.6.0)
Imports: sf (>= 0.9), countrycode (>= 1.2.0), giscoR (>= 0.2.0), raster (>= 3.0), png (>= 0.1-5), slippymath (>= 0.3.1), leaflet (>= 2.0.0)
Suggests: cartography (>= 2.4), rgdal, tinytest
NeedsCompilation: no
Packaged: 2020-11-27 17:27:46 UTC; Diego
Author: Diego Hernangómez [aut, cre, cph] (<https://orcid.org/0000-0001-8457-4658>), EuroGraphics [cph] (for the administrative boundaries.)
Maintainer: Diego Hernangómez <diego.hernangomezherrero@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-30 11:20:05 UTC

More information about mapSpain at CRAN
Permanent link

New package hse with initial version 0.0-14
Package: hse
Version: 0.0-14
Date: 2020-11-28
Title: The hse Distribution
Author: Rolf Turner <r.turner@auckland.ac.nz>
Maintainer: Rolf Turner <r.turner@auckland.ac.nz>
Description: Density (probability), distribution, inverse distribution (quantile) and random data generation functions for the hse ("hope springs eternal") distribution. Functions to calculate rough moment estimates, and maximum likelihood estimates of the parameters of this distribution. Functions to plot the probabilities of the distribution, given the parameter values, and to plot the fitted probabilities given a maximum likelihood fit.
Depends: R (>= 3.2.2)
Suggests: hmm.discnp
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2020-11-27 23:25:47 UTC; rolf
Repository: CRAN
Date/Publication: 2020-11-30 11:30:02 UTC

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New package BNPMIXcluster with initial version 1.3
Package: BNPMIXcluster
Type: Package
Title: Bayesian Nonparametric Model for Clustering with Mixed Scale Variables
Version: 1.3
Date: 2020-11-28
Authors@R: c(person("Christian", "Carmona", role = c("aut", "cre"), email = "carmona@stats.ox.ac.uk", comment = c(ORCID = "0000-0003-0224-4968")), person("Luis", "Nieto-Barajas", role = "aut", email = " lnieto@itam.mx", comment = c(ORCID = "0000-0002-0859-7679")), person("Antonio", "Canale", role = "ctb", email = "antonio.canale@unito.it", comment = c(ORCID = "0000-0002-5403-0040")) )
Description: Model-based approach for clustering of multivariate data, capable of combining different types of variables (continuous, ordinal and nominal) and accommodating for different sampling probabilities in a complex survey design. The model is based on a location mixture model with a Poisson-Dirichlet process prior on the location parameters of the associated latent variables. Details of the underlying model is described in Carmona, C., Nieto-Barajas, L. E., Canale, A. (2016) <arXiv:1612.00083>.
License: MIT + file LICENSE
URL: https://github.com/christianu7/BNPMIXcluster
BugReports: https://github.com/christianu7/BNPMIXcluster/issues
LazyData: TRUE
Depends: R (>= 2.10),
Imports: compiler, gplots, MASS, matrixcalc, mvtnorm, plyr, Rcpp (>= 1.0.5), truncnorm
LinkingTo: Rcpp, RcppArmadillo
Suggests: scatterplot3d
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-11-29 23:19:05 UTC; chris
Author: Christian Carmona [aut, cre] (<https://orcid.org/0000-0003-0224-4968>), Luis Nieto-Barajas [aut] (<https://orcid.org/0000-0002-0859-7679>), Antonio Canale [ctb] (<https://orcid.org/0000-0002-5403-0040>)
Maintainer: Christian Carmona <carmona@stats.ox.ac.uk>
Repository: CRAN
Date/Publication: 2020-11-30 11:10:06 UTC

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Package bbreg updated to version 2.0.0 with previous version 1.0.0 dated 2020-03-20

Title: Bessel and Beta Regressions via Expectation-Maximization Algorithm for Continuous Bounded Data
Description: Functions to fit, via Expectation-Maximization (EM) algorithm, the Bessel and Beta regressions to a data set with a bounded continuous response variable. The Bessel regression is a new and robust approach proposed in the literature. The EM version for the well known Beta regression is another major contribution of this package. See the reference Barreto-Souza, Mayrink and Simas (2020) <arXiv:2003.05157> for details.
Author: Vinicius Mayrink [cre, aut] (<https://orcid.org/0000-0002-5683-8326>), Alexandre B. Simas [aut] (<https://orcid.org/0000-0003-2562-2829>), Wagner Barreto-Souza [aut] (<https://orcid.org/0000-0003-0831-7881>)
Maintainer: Vinicius Mayrink <vdinizm@gmail.com>

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Package rgho updated to version 2.0.1 with previous version 2.0.0 dated 2020-04-07

Title: Access WHO Global Health Observatory Data from R
Description: Access WHO Global Health Observatory (<https://www.who.int/data/gho/>) data from R via the Athena web service (<https://apps.who.int/gho/data/node.resources.api>), an application program interface providing a simple query interface to the World Health Organization's data and statistics content.
Author: Antoine Filipovic-Pierucci [aut,cre]
Maintainer: Kevin Zarca <kevin.zarca@gmail.com>

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Package pchc updated to version 0.3 with previous version 0.2 dated 2020-08-28

Title: Bayesian Network Learning with the PCHC and Related Algorithms
Description: Bayesian network learning using the PCHC algorithm. PCHC stands for PC Hill-Climbing. It is a new hybrid algorithm that used PC to construct the skeleton of the BN and then utilizes the Hill-Climbing greedy search. The relevant paper is: Tsagris M. (2021). "A new scalable Bayesian network learning algorithm with applications to economics". Computational Economics (Accepted for publication). <doi:10.1007/s10614-020-10065-7>.
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package diseq updated to version 0.0.14 with previous version 0.0.13 dated 2020-09-21

Title: Estimation Methods for Markets in Disequilibrium
Description: Provides estimation methods for markets in equilibrium and disequilibrium. Specifically, it supports the estimation of an equilibrium and four disequilibrium models with both correlated and independent shocks. It also provides post-estimation analysis tools, such as aggregation and marginal effects calculations. The estimation methods are based on full information maximum likelihood techniques given in Maddala and Nelson (1974) <doi:10.2307/1914215>. They are implemented using the analytic derivative expressions calculated in Karapanagiotis (2020) <doi:10.2139/ssrn.3525622>. The equilibrium estimation constitutes a special case of a system of simultaneous equations. The disequilibrium models, instead, replace the market clearing condition with a short side rule and allow for different specifications of price dynamics.
Author: Pantelis Karapanagiotis [aut, cre] (<https://orcid.org/0000-0001-9871-1908>)
Maintainer: Pantelis Karapanagiotis <pikappa.devel@gmail.com>

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Package vardpoor updated to version 0.20.1 with previous version 0.20.0 dated 2020-05-20

Title: Variance Estimation for Sample Surveys by the Ultimate Cluster Method
Description: Generation of domain variables, linearization of several non-linear population statistics (the ratio of two totals, weighted income percentile, relative median income ratio, at-risk-of-poverty rate, at-risk-of-poverty threshold, Gini coefficient, gender pay gap, the aggregate replacement ratio, the relative median income ratio, median income below at-risk-of-poverty gap, income quintile share ratio, relative median at-risk-of-poverty gap), computation of regression residuals in case of weight calibration, variance estimation of sample surveys by the ultimate cluster method (Hansen, Hurwitz and Madow, Sample Survey Methods And Theory, vol. I: Methods and Applications; vol. II: Theory. 1953, New York: John Wiley and Sons), variance estimation for longitudinal, cross-sectional measures and measures of change for single and multistage stage cluster sampling designs (Berger, Y. G., 2015, <doi:10.1111/rssa.12116>). Several other precision measures are derived - standard error, the coefficient of variation, the margin of error, confidence interval, design effect.
Author: Juris Breidaks [aut], Martins Liberts [aut, cre], Santa Ivanova [aut], Aleksis Jursevskis [ctb], Anthony Damico [ctb], Central Statistical Bureau of Latvia [cph, fnd]
Maintainer: Martins Liberts <martins.liberts@csb.gov.lv>

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 vardpoor-0.20.1/vardpoor/tests/testthat/test_same_domains.R           |    5 
 vardpoor-0.20.1/vardpoor/tests/testthat/test_vardom_vardomh_same.R    |    9 
 66 files changed, 4402 insertions(+), 4318 deletions(-)

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New package nipnTK with initial version 0.1.0
Package: nipnTK
Type: Package
Title: National Information Platforms for Nutrition Anthropometric Data Toolkit
Version: 0.1.0
Authors@R: c( person(given = "Mark", family = "Myatt", comment = c(ORCID = "0000-0003-1119-1474"), email = "mark@brixtonhealth.com", role = "aut"), person(given = "Ernest", family = "Guevarra", comment = c(ORCID = "0000-0002-4887-4415"), email = "ernest@guevarra.io", role = c("aut", "cre")))
Description: An implementation of the National Information Platforms for Nutrition or NiPN's analytic methods for assessing quality of anthropometric datasets that include measurements of weight, height or length, middle upper arm circumference, sex and age. The focus is on anthropometric status but many of the presented methods could be applied to other variables.
License: GPL-3
Depends: R (>= 2.10)
Imports: stats, graphics, bbw, withr
Suggests: testthat, knitr, rmarkdown, tufte, spelling
Encoding: UTF-8
Language: en-GB
LazyData: true
RoxygenNote: 7.1.1
URL: https://nutriverse.io/nipnTK/, https://github.com/nutriverse/nipnTK
BugReports: https://github.com/nutriverse/nipnTK/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-27 13:05:20 UTC; ernest
Author: Mark Myatt [aut] (<https://orcid.org/0000-0003-1119-1474>), Ernest Guevarra [aut, cre] (<https://orcid.org/0000-0002-4887-4415>)
Maintainer: Ernest Guevarra <ernest@guevarra.io>
Repository: CRAN
Date/Publication: 2020-11-30 09:20:02 UTC

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New package modeltime.gluonts with initial version 0.1.0
Package: modeltime.gluonts
Type: Package
Title: 'GluonTS' Deep Learning
Version: 0.1.0
Authors@R: c( person("Matt", "Dancho", email = "mdancho@business-science.io", role = c("aut", "cre")), person("Business Science", role = "cph"))
Description: Use the 'GluonTS' deep learning library inside of 'modeltime'. Available models include 'DeepAR', 'N-BEATS', and 'N-BEATS' Ensemble. Refer to "GluonTS - Probabilistic Time Series Modeling" (<https://ts.gluon.ai/index.html>).
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: modeltime (>= 0.3.1)
Imports: parsnip, timetk, magrittr, rlang (>= 0.1.2), reticulate, tibble, forcats, dplyr, tidyr, purrr, stringr, glue, fs
Suggests: tidyverse, tidymodels, knitr, rmarkdown, roxygen2, testthat
VignetteBuilder: knitr
URL: https://github.com/business-science/modeltime.gluonts
BugReports: https://github.com/business-science/modeltime.gluonts/issues
NeedsCompilation: no
Packaged: 2020-11-27 17:12:13 UTC; mdancho
Author: Matt Dancho [aut, cre], Business Science [cph]
Maintainer: Matt Dancho <mdancho@business-science.io>
Repository: CRAN
Date/Publication: 2020-11-30 09:40:02 UTC

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New package leaflet.multiopacity with initial version 0.1.0
Package: leaflet.multiopacity
Type: Package
Title: Leaflet Multiple Opacity Controls for R
Version: 0.1.0
Authors@R: c( person( given = "Vinícius", family = "Zendron", role = "aut", email = "vinicius.zendron@meantrix.com"), person( "Meantrix", role = c("cre", "cph"), email = "dev@meantrix.com"), person( given = "Yasunori", family = "Kirimoto", role = c("ctb", "cph"), comment = "Leaflet.Control.Opacity JavaScript library") )
Description: Extends Leaflet for R by adding widget to control opacity of multiple layers.
License: MIT + file LICENSE
URL: https://github.com/meantrix/leaflet.multiopacity
URLNote: https://github.com/meantrix/leaflet.multiopacity
BugReports: https://github.com/meantrix/leaflet.multiopacity/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: htmlwidgets, htmltools
Suggests: leaflet, testthat, magrittr, raster, rgdal, covr, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-27 15:55:31 UTC; viniciuszendron
Author: Vinícius Zendron [aut], Meantrix [cre, cph], Yasunori Kirimoto [ctb, cph] (Leaflet.Control.Opacity JavaScript library)
Maintainer: Meantrix <dev@meantrix.com>
Repository: CRAN
Date/Publication: 2020-11-30 09:20:06 UTC

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New package bcfrailphdv with initial version 0.1.0
Package: bcfrailphdv
Type: Package
Title: Bivariate Correlated Frailty Models with Varied Variances
Version: 0.1.0
Authors@R: c(person(c("Mesfin", "Tsegaye"), role=c("aut", "cre"), email= "mesfin.tsegaye@ddu.edu.et"), person(c("Yehenew", "Kifle"), role=c("aut","ctb"), email= "yehenew@umbc.edu"))
Description: Fit and simulate bivariate correlated frailty models with proportional hazard structure. Frailty distributions, such as gamma and lognormal models are supported. Frailty variances of the two subjects can be varied or equal. Details on the models are available in book of Wienke (2011,ISBN:978-1-4200-7388-1). Bivariate gamma fit is obtained using the approach given in Iachine (1995) with modifications. Lognormal fit is based on the approach by Ripatti and Palmgren (2000) <doi:10.1111/j.0006-341X.2000.01016.x>. Univariate and bivariate shared gamma frailty model fits are possible. Standard errors of the estimated covariate coefficients and frailty variance parameter are obtained using the approach given in Klein and Moeschberger (2003,ISBN:0-387-95399-X).
Depends: R (>= 3.6.0),survival,bcfrailph
Imports: stats
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-11-27 16:22:30 UTC; user
Author: Mesfin Tsegaye [aut, cre], Yehenew Kifle [aut, ctb]
Maintainer: Mesfin Tsegaye <mesfin.tsegaye@ddu.edu.et>
Repository: CRAN
Date/Publication: 2020-11-30 09:30:02 UTC

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New package srt with initial version 1.0.0
Package: srt
Title: Read Subtitle Files as Tabular Data
Version: 1.0.0
Authors@R: person(given = "Kiernan", family = "Nicholls", role = c("aut", "cre"), email = "kiernann@protonmail.com")
Description: Read 'SubRip' <https://sourceforge.net/projects/subrip/> subtitle files as data frames for easy text analysis or manipulation. Easily shift numeric timings and export subtitles back into valid 'SubRip' timestamp format to sync subtitles and audio.
License: GPL-3
URL: https://github.com/kiernann/srt, https://kiernann.com/srt/
BugReports: https://github.com/kiernann/srt/issues
Suggests: covr (>= 3.5.1), testthat (>= 3.0.0), tibble (>= 3.0.4)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-27 02:17:26 UTC; kiernan
Author: Kiernan Nicholls [aut, cre]
Maintainer: Kiernan Nicholls <kiernann@protonmail.com>
Repository: CRAN
Date/Publication: 2020-11-30 08:50:03 UTC

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Package rasciidoc updated to version 3.0.0 with previous version 2.2.2 dated 2020-11-25

Title: Create Reports Using R and 'asciidoc'
Description: Inspired by Karl Broman`s reader on using 'knitr' with 'asciidoc' (<http://kbroman.org/knitr_knutshell/pages/asciidoc.html>), this is merely a wrapper to 'knitr' and 'asciidoc'.
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>

Diff between rasciidoc versions 2.2.2 dated 2020-11-25 and 3.0.0 dated 2020-11-30

 DESCRIPTION                                |    6 
 MD5                                        |   17 -
 NEWS.md                                    |   13 
 R/internals.R                              |    4 
 R/render.R                                 |   96 ++++--
 inst/doc/An_Introduction_to_rasciidoc.html |  178 ++---------
 inst/files/default.asciidoc                |only
 inst/files/default.html                    |    5 
 inst/runit_tests/runit-render.R            |  432 ++++++++++++++---------------
 man/rasciidoc.Rd                           |   12 
 10 files changed, 357 insertions(+), 406 deletions(-)

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New package PandemicLP with initial version 0.2.0
Package: PandemicLP
Type: Package
Title: Long Term Prediction for Epidemic and Pandemic Data
Version: 0.2.0
Date: 2020-11-25
Authors@R: c(person("Débora", "de Freitas Magalhães", email = "deborafmag@gmail.com", role = "aut"), person("Marta Cristina", "Colozza Bianchi da Costa", email = "marta_bianchi@ufg.br", role = "aut"), person("Guido", "Alberti Moreira", email = "guidoalber@gmail.com", role = c("cre","aut"),comment=c(ORCID="0000-0001-7557-0874")), person("Thais", "Pacheco Menezes", email = "thaispacheco1207@gmail.com", role = "aut"), person("Marcos", "Oliveira Prates", email = "marcosop@est.ufmg.br", role = "ctb",comment=c(ORCID="0000-0001-8077-4898")))
Contact: CovidLP team <covidlp.team@gmail.com>
Maintainer: Guido Alberti Moreira <guidoalber@gmail.com>
Description: Implementation of the methodology described in <http://est.ufmg.br/covidlp/home/pt/> which can be also found in help(models). Implemented models are currently the Poisson distribution. The mean function can be the basic generalized logistic form, or the seasonal effect which has under- or over-reporting effects in up to three weekdays, or the two curves form. Bayesian inference is made available through the 'stan' software and its diagnostic functions pool can be used. Plot methods are implemented to mimic the graphics from the 'shiny' app in the URL using the 'plotly' library.
License: GPL-3
Encoding: UTF-8
LazyData: true
Biarch: true
Depends: R (>= 3.5.0), rstan (>= 2.18.1), rstantools (>= 2.1.1), stats
Imports: utils, methods, Rcpp (>= 0.12.0), plotly (>= 4.9.2.1), dplyr (>= 1.0.1), curl (>= 4.3), tidyr (>= 1.1.1)
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
Suggests: knitr, rmarkdown, webshot
URL: <http://est.ufmg.br/covidlp/home/pt/>
VignetteBuilder: knitr
SystemRequirements: GNU make
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-11-26 17:13:11 UTC; anthorg
Author: Débora de Freitas Magalhães [aut], Marta Cristina Colozza Bianchi da Costa [aut], Guido Alberti Moreira [cre, aut] (<https://orcid.org/0000-0001-7557-0874>), Thais Pacheco Menezes [aut], Marcos Oliveira Prates [ctb] (<https://orcid.org/0000-0001-8077-4898>)
Repository: CRAN
Date/Publication: 2020-11-30 09:00:11 UTC

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New package ellipticalsymmetry with initial version 0.1
Package: ellipticalsymmetry
Title: Elliptical Symmetry Tests
Version: 0.1
Authors@R: c(person(given = "Slađana", family = "Babić", role = c("aut"), email = "sladana.babic@ugent.be", comment = c(ORCID = "https://orcid.org/0000-0001-8076-4665")), person(given = "Marko", family = "Palangetić", role = c("aut", "cre"), email = "marko.palangetic@ugent.be", comment = c(ORCID = "https://orcid.org/0000-0002-6366-0634")), person(given = "Christophe", family = "Ley", role = c("aut"), email = "christophe.ley@ugent.be", comment = c(ORCID = "https://orcid.org/0000-0002-2290-8437")))
Description: Given the omnipresence of the assumption of elliptical symmetry, it is essential to be able to test whether that assumption actually holds true or not for the data at hand. This package provides several statistical tests for elliptical symmetry that are described in Babic et al. (2020) <arXiv:2011.12560>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 2.4.0)
Imports: stats (>= 2.4.0), datasets(>= 2.4.0), ICSNP (>= 1.1.1)
NeedsCompilation: no
Packaged: 2020-11-26 22:00:03 UTC; markopalangetic
Author: Slađana Babić [aut] (<https://orcid.org/0000-0001-8076-4665>), Marko Palangetić [aut, cre] (<https://orcid.org/0000-0002-6366-0634>), Christophe Ley [aut] (<https://orcid.org/0000-0002-2290-8437>)
Maintainer: Marko Palangetić <marko.palangetic@ugent.be>
Repository: CRAN
Date/Publication: 2020-11-30 09:00:02 UTC

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New package dipw with initial version 0.1.0
Package: dipw
Type: Package
Title: Debiased Inverse Propensity Score Weighting
Description: Estimation of the average treatment effect when controlling for high-dimensional confounders using debiased inverse propensity score weighting (DIPW). DIPW relies on the propensity score following a sparse logistic regression model, but the regression curves are not required to be estimable. Despite this, our package also allows the users to estimate the regression curves and take the estimated curves as input to our methods. Details of the methodology can be found in Yuhao Wang and Rajen D. Shah (2020) "Debiased Inverse Propensity Score Weighting for Estimation of Average Treatment Effects with High-Dimensional Confounders" <arXiv:2011.08661>. The package relies on the optimisation software 'MOSEK' <https://www.mosek.com/> which must be installed separately; see the documentation for 'Rmosek'.
Version: 0.1.0
Authors@R: c( person("Yuhao", "Wang", email = "yuhaow.thu@gmail.com", role = c("cre", "aut")), person("Rajen", "Shah", email = "r.shah@statslab.cam.ac.uk", role = "ctb"))
Maintainer: Yuhao Wang <yuhaow.thu@gmail.com>
Imports: glmnet, Rmosek, Matrix, methods, stats
License: GPL-3
Encoding: UTF-8
LazyData: false
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-27 03:28:40 UTC; yuhaow
Author: Yuhao Wang [cre, aut], Rajen Shah [ctb]
Repository: CRAN
Date/Publication: 2020-11-30 09:00:05 UTC

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New package cascadess with initial version 0.1.0
Package: cascadess
Type: Package
Title: A Style Pronoun for 'htmltools' Tags
Version: 0.1.0
Authors@R: c( person("Nathan", "Teetor", email = "nate@haufin.ch", role = c("aut", "cre")), person(family = "The Bootstrap Authors", comment = "Bootstrap library", role = "cph"), person(family = "Twitter, Inc", comment = "Bootstrap library", role = "cph"))
Description: Apply styles to tag elements directly or with the .style pronoun. Using the pronoun, styles are created within the context of a tag element. Change borders, background colors, margins, layouts, and more.
License: MIT + file LICENSE
URL: https://github.com/nteetor/cascadess
BugReports: https://github.com/nteetor/cascadess/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.3)
Imports: crayon, htmltools (>= 0.4.0), magrittr, rlang, utils
Suggests: rmarkdown, shiny, testthat (>= 2.1.0)
Collate: 'align.R' 'utils.R' 'background.R' 'border.R' 'cascadess.R' 'display.R' 'eval-style.R' 'flex.R' 'float.R' 'font.R' 'gap.R' 'height.R' 'margin.R' 'overflow.R' 'padding.R' 'position.R' 'reexports.R' 'responsive.R' 'shadow.R' 'text.R' 'utils-docs.R' 'visible.R' 'width.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2020-11-26 18:32:44 UTC; Nate
Author: Nathan Teetor [aut, cre], The Bootstrap Authors [cph] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library)
Maintainer: Nathan Teetor <nate@haufin.ch>
Repository: CRAN
Date/Publication: 2020-11-30 09:00:08 UTC

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Package mixIndependR updated to version 0.4.3 with previous version 0.4.2 dated 2020-11-26

Title: Genetics and Independence Testing of Mixed Genetic Panels
Description: Developed to deal with multi-locus genotype data, this package is especially designed for those panel which include different type of markers. Basic genetic parameters like allele frequency, genotype frequency, heterozygosity and Hardy-Weinberg test of mixed genetic data can be obtained. In addition, a new test for mutual independence which is compatible for mixed genetic data is developed in this package.
Author: Bing Song
Maintainer: Bing Song <bingsong@my.unthsc.edu>

Diff between mixIndependR versions 0.4.2 dated 2020-11-26 and 0.4.3 dated 2020-11-30

 DESCRIPTION                                   |    6 +++---
 MD5                                           |   18 +++++++++---------
 NAMESPACE                                     |    2 ++
 NEWS.md                                       |    4 ++++
 R/mixIndependK.R                              |   12 +++---------
 R/mixIndependX.R                              |   12 +++---------
 R/read_vcf_gt.R                               |    1 +
 R/splitGenotype.R                             |    1 +
 inst/doc/DistributionBuildingNComparison.html |    2 +-
 inst/doc/HypothesisTest.html                  |    2 +-
 10 files changed, 28 insertions(+), 32 deletions(-)

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Package npreg updated to version 1.0-5 with previous version 1.0-4 dated 2020-08-10

Title: Nonparametric Regression via Smoothing Splines
Description: Multiple and generalized nonparametric regression using smoothing spline ANOVA models and generalized additive models, as described in Helwig (2020) <doi:10.4135/9781526421036885885>. Includes support for Gaussian and non-Gaussian responses, smoothers for multiple types of predictors, interactions between smoothers of mixed types, and eight different methods for smoothing parameter selection.
Author: Nathaniel E. Helwig <helwig@umn.edu>
Maintainer: Nathaniel E. Helwig <helwig@umn.edu>

Diff between npreg versions 1.0-4 dated 2020-08-10 and 1.0-5 dated 2020-11-30

 npreg-1.0-4/npreg/R/tune.theta.R         |only
 npreg-1.0-5/npreg/ChangeLog              |   36 ++++++++++++
 npreg-1.0-5/npreg/DESCRIPTION            |    8 +-
 npreg-1.0-5/npreg/MD5                    |   45 +++++++--------
 npreg-1.0-5/npreg/R/basis_poly.R         |   92 +++++++++++++++++++++++++++----
 npreg-1.0-5/npreg/R/fit_gsm.R            |   24 +++-----
 npreg-1.0-5/npreg/R/fit_sm.R             |   17 ++++-
 npreg-1.0-5/npreg/R/penalty_poly.R       |    5 +
 npreg-1.0-5/npreg/R/penalty_tps.R        |    4 -
 npreg-1.0-5/npreg/R/predict.ss.R         |    4 -
 npreg-1.0-5/npreg/R/psolve.R             |    4 -
 npreg-1.0-5/npreg/R/sm.R                 |   16 ++++-
 npreg-1.0-5/npreg/R/ss.R                 |   12 ++--
 npreg-1.0-5/npreg/R/summary.gsm.R        |   62 ++++++++++++--------
 npreg-1.0-5/npreg/R/summary.sm.R         |    5 +
 npreg-1.0-5/npreg/R/summary.ss.R         |    5 +
 npreg-1.0-5/npreg/R/theta.mle.R          |only
 npreg-1.0-5/npreg/man/NegBin.Rd          |    4 +
 npreg-1.0-5/npreg/man/gsm.Rd             |    2 
 npreg-1.0-5/npreg/man/npreg-internals.Rd |   12 +++-
 npreg-1.0-5/npreg/man/polynomial.Rd      |   11 +++
 npreg-1.0-5/npreg/man/sm.Rd              |    7 +-
 npreg-1.0-5/npreg/man/ss.Rd              |   10 ++-
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 npreg-1.0-5/npreg/man/theta.mle.Rd       |only
 25 files changed, 275 insertions(+), 111 deletions(-)

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Package grobblR updated to version 0.2.0 with previous version 0.1.1 dated 2020-08-28

Title: Creating Flexible, Reproducible 'PDF' Reports
Description: A tool which allows users the ability to intuitively create flexible, reproducible portable document format reports comprised of aesthetically pleasing tables, images, plots and/or text.
Author: Calvin Floyd [aut, cre, cph]
Maintainer: Calvin Floyd <calvin.michael.floyd@gmail.com>

Diff between grobblR versions 0.1.1 dated 2020-08-28 and 0.2.0 dated 2020-11-30

 DESCRIPTION                             |    6 
 MD5                                     |   35 ++--
 NAMESPACE                               |    1 
 NEWS.md                                 |    9 +
 R/alter.R                               |    6 
 R/headings.R                            |  229 ++++++++++++++++++++++++++++++--
 README.md                               |    4 
 inst/doc/grob_layout.html               |    4 
 inst/doc/grob_matrix.R                  |   22 +++
 inst/doc/grob_matrix.Rmd                |   31 ++++
 inst/doc/grob_matrix.html               |  181 ++++++++++++++-----------
 inst/doc/grobblR.html                   |    4 
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 man/alter_at.Rd                         |    5 
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 tests/testthat/test_grob_image.R        |    3 
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 tests/testthat/test_matrix_aesthetics.R |    4 
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 19 files changed, 636 insertions(+), 148 deletions(-)

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Package rsq updated to version 2.1 with previous version 2.0 dated 2020-05-09

Title: R-Squared and Related Measures
Description: Calculate generalized R-squared, partial R-squared, and partial correlation coefficients for generalized linear (mixed) models (including quasi models with well defined variance functions).
Author: Dabao Zhang
Maintainer: Dabao Zhang <zhangdb@stat.purdue.edu>

Diff between rsq versions 2.0 dated 2020-05-09 and 2.1 dated 2020-11-30

 DESCRIPTION      |   10 +-
 MD5              |   16 ++--
 NAMESPACE        |    4 -
 R/rsq.R          |  190 +++++++++++++++++++++++++++++--------------------------
 man/hschool.Rd   |    2 
 man/rsq.glmm.Rd  |    5 -
 man/rsq.lmm.Rd   |    2 
 man/rsq.v.Rd     |    7 --
 man/vresidual.Rd |   14 ++--
 9 files changed, 132 insertions(+), 118 deletions(-)

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