Thu, 08 Apr 2021

Package epitweetr updated to version 0.1.28 with previous version 0.1.24 dated 2020-10-23

Title: Early Detection of Public Health Threats from Twitter Data
Description: It allows you to automatically monitor trends of tweets by time, place and topic aiming at detecting public health threats early through the detection of signals (e.g. an unusual increase in the number of tweets). It was designed to focus on infectious diseases, and it can be extended to all hazards or other fields of study by modifying the topics and keywords.
Author: Francisco Orchard [aut, ctr] (<https://orcid.org/0000-0001-5793-3301>, Author of the package and original code), Laura Espinosa [aut, cre, fnd] (<https://orcid.org/0000-0003-0748-9657>, Project manager, author of the design and concept of the package, and package maintainer), Ariana Wijermans [ctb] (Contributor to the design and concept of the package), Thomas Mollet [ctb, fnd] (Business owner of the project, and contributor to the design and concept of the package), Adrian Prodan [ctb], Thomas Czernichow [ctb], Maria Prieto Gonzalez [ctb], Esther Kissling [ctb], Michael Höhle [ctb]
Maintainer: Laura Espinosa <laura.espinosa@ecdc.europa.eu>

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Package vtable updated to version 1.3.1 with previous version 1.2.7 dated 2021-03-01

Title: Variable Table for Variable Documentation
Description: Automatically generates HTML variable documentation including variable names, labels, classes, value labels (if applicable), value ranges, and summary statistics. See the vignette "vtable" for a package overview.
Author: Nick Huntington-Klein [aut, cre]
Maintainer: Nick Huntington-Klein <nhuntington-klein@seattleu.edu>

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Package TPLSr updated to version 1.0.3 with previous version 1.0.1 dated 2020-11-02

Title: Thresholded Partial Least Squares Model for Neuroimaging Data
Description: Uses thresholded partial least squares algorithm to create a regression or classification model. For more information, see Lee, Bradlow, and Kable <doi:10.1101/2021.02.09.430524>.
Author: Sangil Lee [aut, cre]
Maintainer: Sangil Lee <sangillee3rd@gmail.com>

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Package sensobol updated to version 1.0.1 with previous version 1.0.0 dated 2021-01-26

Title: Computation of Variance-Based Sensitivity Indices
Description: It allows to rapidly compute, bootstrap and plot up to third-order Sobol'-based sensitivity indices using several state-of-the-art first and total-order estimators. Sobol' indices can be computed either for models that yield a scalar as a model output or for systems of differential equations. The package also provides a suit of benchmark tests functions and several options to obtain publication-ready figures of the model output uncertainty and sensitivity-related analysis. An overview of Sobol'-based sensitivity indices can be found in Saltelli et al. (2008, ISBN:9780470059975) and in Puy, Lo Piano, Saltelli, and Levin (2021) <arXiv:2101.10103>.
Author: Arnald Puy [aut, cre] (<https://orcid.org/0000-0001-9469-2156>), Bertrand Ioos [ctb] (Author of included 'sensitivity' fragments), Gilles Pujol [ctb] (Author of included 'sensitivity' fragments), RStudio [cph] (Copyright holder of included 'sensitivity' fragments)
Maintainer: Arnald Puy <arnald.puy@pm.me>

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Package rdwd updated to version 1.5.0 with previous version 1.4.0 dated 2020-08-01

Title: Select and Download Climate Data from 'DWD' (German Weather Service)
Description: Handle climate data from the 'DWD' ('Deutscher Wetterdienst', see <https://www.dwd.de/EN/climate_environment/cdc/cdc_node_en.html> for more information). Choose observational time series from meteorological stations with 'selectDWD()'. Find raster data from radar and interpolation according to <https://bookdown.org/brry/rdwd/raster-data.html>. Download (multiple) data sets with progress bars and no re-downloads through 'dataDWD()'. Read both tabular observational data and binary gridded datasets with 'readDWD()'.
Author: Berry Boessenkool
Maintainer: Berry Boessenkool <berry-b@gmx.de>

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Package presize updated to version 0.2.3 with previous version 0.1.3 dated 2020-09-02

Title: Precision Based Sample Size Calculation
Description: Bland (2009) <doi:10.1136/bmj.b3985> recommended to base study sizes on the width of the confidence interval rather the power of a statistical test. The goal of 'presize' is to provide functions for such precision based sample size calculations. For a given sample size, the functions will return the precision (width of the confidence interval), and vice versa.
Author: Armando Lenz [aut], Alan G. Haynes [cre, aut], Andreas Limacher [aut], Odile Stalder [ctb]
Maintainer: Alan G. Haynes <alan.haynes@ctu.unibe.ch>

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Package PReMiuM updated to version 3.2.5 with previous version 3.2.3 dated 2019-11-02

Title: Dirichlet Process Bayesian Clustering, Profile Regression
Description: Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership. The package allows Bernoulli, Binomial, Poisson, Normal, survival and categorical response, as well as Normal and discrete covariates. It also allows for fixed effects in the response model, where a spatial CAR (conditional autoregressive) term can be also included. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection. The main reference for the package is Liverani, Hastie, Azizi, Papathomas and Richardson (2015) <doi:10.18637/jss.v064.i07>.
Author: David I. Hastie, Silvia Liverani <liveranis@gmail.com> and Sylvia Richardson with contributions from Aurore J. Lavigne, Lucy Leigh, Lamiae Azizi, Xi Liu, Ruizhu Huang, Austin Gratton, Wei Jing
Maintainer: Silvia Liverani <liveranis@gmail.com>

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Package percentiles updated to version 0.2.2 with previous version 0.2.1 dated 2021-02-15

Title: Calculate (Stratified) Percentiles
Description: Calculate (stratified) percentiles on a data.frame Stratification will split the data.frame into subgroups and calculate percentiles for each independently.
Author: J. Peter Marquardt <peter@kmarquardt.de> [aut, cre]
Maintainer: J. Peter Marquardt <peter@kmarquardt.de>

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Package parameters updated to version 0.13.0 with previous version 0.12.0 dated 2021-02-21

Title: Processing of Model Parameters
Description: Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see support list of insight; Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>, @strengejacke), Dominique Makowski [aut] (<https://orcid.org/0000-0001-5375-9967>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Indrajeet Patil [aut] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Søren Højsgaard [aut], Zen J. Lau [ctb], Vincent Arel-Bundock [ctb] (<https://orcid.org/0000-0003-1995-6531>, @vincentab), Jeffrey Girard [ctb] (<https://orcid.org/0000-0002-7359-3746>, @jeffreymgirard)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package HRW updated to version 1.0-4 with previous version 1.0-3 dated 2019-02-11

Title: Datasets, Functions and Scripts for Semiparametric Regression Supporting Harezlak, Ruppert & Wand (2018)
Description: The book "Semiparametric Regression with R" by J. Harezlak, D. Ruppert & M.P. Wand (2018, Springer; ISBN: 978-1-4939-8851-8) makes use of datasets and scripts to explain semiparametric regression concepts. Each of the book's scripts are contained in this package as well as datasets that are not within other R packages. Functions that aid semiparametric regression analysis are also included.
Author: Jaroslaw Harezlak [aut], David Ruppert [aut], Matt P. Wand [aut, cre]
Maintainer: Matt P. Wand <matt.wand@uts.edu.au>

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Package DHARMa updated to version 0.4.1 with previous version 0.4.0 dated 2021-03-28

Title: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models
Description: The 'DHARMa' package uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed models. Currently supported are linear and generalized linear (mixed) models from 'lme4' (classes 'lmerMod', 'glmerMod'), 'glmmTMB' 'GLMMadaptive' and 'spaMM', generalized additive models ('gam' from 'mgcv'), 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model classes. Moreover, externally created simulations, e.g. posterior predictive simulations from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well. The resulting residuals are standardized to values between 0 and 1 and can be interpreted as intuitively as residuals from a linear regression. The package also provides a number of plot and test functions for typical model misspecification problems, such as over/underdispersion, zero-inflation, and residual spatial and temporal autocorrelation.
Author: Florian Hartig [aut, cre] (<https://orcid.org/0000-0002-6255-9059>), Lukas Lohse [ctb]
Maintainer: Florian Hartig <florian.hartig@biologie.uni-regensburg.de>

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Package rfishbase updated to version 3.1.7 with previous version 3.1.6 dated 2021-02-10

Title: R Interface to 'FishBase'
Description: A programmatic interface to 'FishBase', re-written based on an accompanying 'RESTful' API. Access tables describing over 30,000 species of fish, their biology, ecology, morphology, and more. This package also supports experimental access to 'SeaLifeBase' data, which contains nearly 200,000 species records for all types of aquatic life not covered by 'FishBase.'
Author: Carl Boettiger [cre, aut] (<https://orcid.org/0000-0002-1642-628X>), Scott Chamberlain [aut] (<https://orcid.org/0000-0003-1444-9135>), Duncan Temple Lang [aut], Peter Wainwright [aut], Kevin Cazelles [ctb] (<https://orcid.org/0000-0001-6619-9874>)
Maintainer: Carl Boettiger <cboettig@gmail.com>

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Package lazytrade updated to version 0.5.1 with previous version 0.4.5 dated 2021-03-15

Title: Learn Computer and Data Science using Algorithmic Trading
Description: Provide sets of functions and methods to learn and practice data science using idea of algorithmic trading. Main goal is to process information within "Decision Support System" to come up with analysis or predictions. There are several utilities such as dynamic and adaptive risk management using reinforcement learning and even functions to generate predictions of price changes using pattern recognition deep regression learning. Summary of Methods used: Awesome H2O tutorials: <https://github.com/h2oai/awesome-h2o>, Market Type research of Van Tharp Institute: <https://www.vantharp.com/>, Reinforcement Learning R package: <https://CRAN.R-project.org/package=ReinforcementLearning>.
Author: Vladimir Zhbanko
Maintainer: Vladimir Zhbanko <vladimir.zhbanko@gmail.com>

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Package SUNGEO updated to version 0.2.22 with previous version 0.2.1 dated 2021-02-10

Title: Sub-National Geospatial Data Archive: Geoprocessing Toolkit
Description: Tools for integrating spatially-misaligned GIS datasets. Part of the Sub-National Geospatial Data Archive System (<https://www.nsf.gov/awardsearch/showAward?AWD_ID=1925693&HistoricalAwards=false>).
Author: Jason Byers, Marty Davidson, Yuri M. Zhukov
Maintainer: Yuri M. Zhukov <zhukov@umich.edu>

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Package pewdata updated to version 0.3.2 with previous version 0.3.1 dated 2020-02-05

Title: Reproducible Retrieval of Pew Research Center Datasets
Description: Reproducible, programmatic retrieval of survey datasets from the Pew Research Center.
Author: Frederick Solt [aut, cre], Yue Hu [aut], Eric Persson [ctb]
Maintainer: Frederick Solt <frederick-solt@uiowa.edu>

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Package PSS.Health updated to version 0.1.6 with previous version 0.1.5 dated 2020-11-30

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, 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. 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 0.1.5 dated 2020-11-30 and 0.1.6 dated 2021-04-08

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Package neonstore updated to version 0.4.2 with previous version 0.4.0 dated 2021-03-08

Title: NEON Data Store
Description: The National Ecological Observatory Network (NEON) provides access to its numerous data products through its REST API, <https://data.neonscience.org/data-api/>. This package provides a high-level user interface for downloading and storing NEON data products. While each of NEON data products consist of hundreds or thousands of individual files. Unlike 'neonUtilities', this package will avoid repeated downloading, provides persistent storage, and improves performance. 'neonstore' can also construct a local 'duckdb' database of stacked tables, making it possible to work with tables that are far to big to fit into memory.
Author: Carl Boettiger [aut, cre] (<https://orcid.org/0000-0002-1642-628X>), Quinn Thomas [aut] (<https://orcid.org/0000-0003-1282-7825>), Christine Laney [aut] (<https://orcid.org/0000-0002-4944-2083>), Claire Lunch [aut] (<https://orcid.org/0000-0001-8753-6593>), Noam Ross [ctb] (<https://orcid.org/0000-0002-2136-0000>)
Maintainer: Carl Boettiger <cboettig@gmail.com>

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Package GALLO updated to version 1.2 with previous version 1.1 dated 2020-11-06

Title: Genomic Annotation in Livestock for Positional Candidate LOci
Description: The accurate annotation of genes and Quantitative Trait Loci (QTLs) located within candidate markers and/or regions (haplotypes, windows, CNVs, etc) is a crucial step the most common genomic analyses performed in livestock, such as Genome-Wide Association Studies or transcriptomics. The Genomic Annotation in Livestock for positional candidate LOci (GALLO) is an R package designed to provide an intuitive and straightforward environment to annotate positional candidate genes and QTLs from high-throughput genetic studies in livestock. Moreover, GALLO allows the graphical visualization of gene and QTL annotation results, data comparison among different grouping factors (e.g., methods, breeds, tissues, statistical models, studies, etc.), and QTL enrichment in different livestock species including cattle, pigs, sheep, and chicken, among others.
Author: Pablo Fonseca [aut, cre], Aroa Suarez-Vega [aut], Gabriele Marras [aut], Angela Cánovas [aut]
Maintainer: Pablo Fonseca <pfonseca@uoguelph.ca>

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Package bpDir updated to version 0.1.2 with previous version 0.1.1 dated 2020-05-06

Title: Boxplots for Directional Data
Description: Functions for drawing boxplots for data on (the boundary of) a unit circle (i.e., circular and axial data), from Buttarazzi D., Pandolfo G., Porzio G.C. (2018) <doi:10.1111/biom.12889>.
Author: Davide Buttarazzi [aut, cre]
Maintainer: Davide Buttarazzi <davidebuttarazzi@outlook.com>

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Package RxODE updated to version 1.0.7 with previous version 1.0.6 dated 2021-03-21

Title: Facilities for Simulating from ODE-Based Models
Description: Facilities for running simulations from ordinary differential equation ('ODE') models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The 'VODE' and 'LSODA' are in the public domain. The information is available in the inst/COPYRIGHTS.
Author: Matthew L. Fidler [aut] (<https://orcid.org/0000-0001-8538-6691>), Melissa Hallow [aut], Wenping Wang [aut, cre], Zufar Mulyukov [ctb], Alan Hindmarsh [ctb], Awad H. Al-Mohy [ctb], Matt Dowle [ctb], Cleve Moler [ctb], David Cooley [ctb], Daniel C. Dillon [ctb], Drew Schmidt [ctb], Arun Srinivasan [ctb], Ernst Hairer [ctb], Gerhard Wanner [ctb], Goro Fuji [ctb], Hadley Wickham [ctb], Jack Dongarra [ctb], Linda Petzold [ctb], Martin Maechler [ctb], Matteo Fasiolo [ctb], Morwenn [ctb], Nicholas J. Higham [ctb], Roger B. Sidje [ctb], Simon Frost [ctb], Kevin Ushey [ctb], Yu Feng [ctb]
Maintainer: Wenping Wang <wwang8198@gmail.com>

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Package RsSimulx updated to version 1.0.1 with previous version 1.0.0 dated 2021-01-21

Title: R Speaks 'Simulx'
Description: Provide useful tools which supplement the use of Simulx software and R connectors (Monolix Suite). 'Simulx' is an easy, efficient and flexible application for clinical trial simulations. You need 'Simulx' software to be installed in order to use 'RsSimulx' package. Among others tasks, 'RsSimulx' provides the same functions as package 'mlxR' does with a compatibility with 'Simulx' software.
Author: Clemence Pinaud [aut, cre], Jonathan Chauvin [aut], Marc Lavielle [ctb]
Maintainer: Clemence Pinaud <clemence.pinaud@lixoft.com>

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Package Ravages updated to version 0.1.3 with previous version 0.1.2 dated 2021-03-16

Title: Rare Variant Analysis and Genetic Simulations
Description: Rare variant association tests: burden tests (Bocher et al. 2019 <doi:10.1002/gepi.22210>) and the Sequence Kernel Association Test (Bocher et al. 2021 <doi:10.1038/s41431-020-00792-8>); and genetic simulations.
Author: Ozvan Bocher and Hervé Perdry
Maintainer: Ozvan Bocher <bocherozvan@gmail.com>

Diff between Ravages versions 0.1.2 dated 2021-03-16 and 0.1.3 dated 2021-04-08

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Package TMB updated to version 1.7.20 with previous version 1.7.19 dated 2021-02-05

Title: Template Model Builder: A General Random Effect Tool Inspired by 'ADMB'
Description: With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates.
Author: Kasper Kristensen [aut, cre, cph], Brad Bell [cph], Hans Skaug [ctb], Arni Magnusson [ctb], Casper Berg [ctb], Anders Nielsen [ctb], Martin Maechler [ctb], Theo Michelot [ctb], Mollie Brooks [ctb], Alex Forrence [ctb], Christoffer Moesgaard Albertsen [ctb], Cole Monnahan [ctb]
Maintainer: Kasper Kristensen <kaskr@dtu.dk>

Diff between TMB versions 1.7.19 dated 2021-02-05 and 1.7.20 dated 2021-04-08

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New package ZIprop with initial version 0.1.0
Package: ZIprop
Title: Permutations Tests and Performance Indicator for Zero-Inflated Proportions Response
Version: 0.1.0
Date: 2021-04-04
Author: Melina Ribaud
Maintainer: Melina Ribaud <melina.ribaud@gmail.com>
Description: Permutations tests to identify factor correlated to zero-inflated proportions response. Provide a performance indicator based on Spearman correlation to quantify the part of correlation explained by the selected set of factors. See details for the method at the following preprint e.g.: <https://hal.archives-ouvertes.fr/hal-02936779v3>.
URL: https://gitlab.paca.inrae.fr/meribaud/ziprop
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), rgenoud, purrr, data.table, parallel
NeedsCompilation: no
Packaged: 2021-04-07 15:54:51 UTC; melinaribaud
Repository: CRAN
Date/Publication: 2021-04-08 12:00:02 UTC

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New package rD3plot with initial version 1.0.10
Package: rD3plot
Version: 1.0.10
Date: 2021-04-07
Title: Interactive Networks, Timelines, Barplots, Galleries with 'D3.js'
Description: Creates interactive analytic graphs with 'R'. It joins the data analysis power of R and the visualization libraries of JavaScript in one package. The package provides interactive networks, timelines, barplots, image galleries and evolving networks. Graphs are represented as 'D3.js' graphs embedded in a web page ready for its interactive analysis and exploration.
License: GPL-2 | GPL-3
Depends: R (>= 3.5.0)
Imports: igraph (>= 1.0.1)
Suggests: shiny
NeedsCompilation: no
Authors@R: c( person("Modesto", "Escobar", email = "modesto@usal.es", role = c("aut", "cph","cre"), comment = c(ORCID = "0000-0003-2072-6071")), person("Carlos", "Prieto", email = "cprietos@usal.es", role = c("aut"), comment = c(ORCID = "0000-0001-8178-9768")), person("David", "Barrios", email = "metal@usal.es", role = "aut") )
Maintainer: Modesto Escobar <modesto@usal.es>
Encoding: UTF-8
Packaged: 2021-04-07 09:23:31 UTC; Modesto
Author: Modesto Escobar [aut, cph, cre] (<https://orcid.org/0000-0003-2072-6071>), Carlos Prieto [aut] (<https://orcid.org/0000-0001-8178-9768>), David Barrios [aut]
Repository: CRAN
Date/Publication: 2021-04-08 11:20:02 UTC

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New package GGMnonreg with initial version 1.0.0
Package: GGMnonreg
Title: Non-Regularized Gaussian Graphical Models
Version: 1.0.0
Date: 2021-04-02
Authors@R: person("Donald", "Williams", email = "drwwilliams@ucdavis.edu", role = c("aut", "cre"))
Maintainer: Donald Williams <drwwilliams@ucdavis.edu>
Description: Estimate non-regularized Gaussian graphical models, Ising models, and mixed graphical models. The current methods consist of multiple regression, a non-parametric bootstrap <doi:10.1080/00273171.2019.1575716>, and Fisher z transformed partial correlations <doi:10.1111/bmsp.12173>. Parameter uncertainty, predictability, and network replicability <doi:10.31234/osf.io/fb4sa> are also implemented.
Depends: R (>= 4.0.0)
License: GPL-2
Encoding: UTF-8
Imports: Rdpack, bestglm, GGally, network, sna, Matrix, poibin, parallel, doParallel, foreach, corpcor, psych, MASS, stats, methods, ggplot2, GGMncv
Suggests: qgraph
LazyData: true
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2021-04-07 12:19:13 UTC; Donny
Author: Donald Williams [aut, cre]
Repository: CRAN
Date/Publication: 2021-04-08 11:30:06 UTC

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New package DMLLZU with initial version 0.1.0
Package: DMLLZU
Title: Double Machine Learning
Version: 0.1.0
Authors@R: c( person("Lixiong", "Yang", email = "ylx@lzu.edu.cn",role ="aut"), person("Junchang", "Zhao",email = "zhaojch19@lzu.edu.cn", role = c("aut","cre")))
Description: Yang(2020,<doi:10.1016/j.jeconom.2020.01.018>) come up with Double Machine Learning model ,it is based on this model, using four machine learning methods-- bagging, Boosting, random forest and neural network, and then based on the four models for two different combinations of the integrated model -- linear model combination and random forest .
Author: Lixiong Yang [aut], Junchang Zhao [aut, cre]
Maintainer: Junchang Zhao <zhaojch19@lzu.edu.cn>
Depends: R (>= 3.2)
Imports: rlang, gbm ,lmtest ,nnet , sandwich,randomForest,caret,ISLR
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-07 12:16:46 UTC; zhao
Repository: CRAN
Date/Publication: 2021-04-08 11:30:10 UTC

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Package caracas updated to version 1.1.0 with previous version 1.0.0 dated 2020-05-21

Title: Computer Algebra
Description: Computer algebra via the 'SymPy' library (<https://www.sympy.org/>). This makes it possible to solve equations symbolically, find symbolic integrals, symbolic sums and other important quantities.
Author: Mikkel Meyer Andersen [aut, cre, cph], Søren Højsgaard [aut, cph]
Maintainer: Mikkel Meyer Andersen <mikl@math.aau.dk>

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Package WSGeometry updated to version 1.1 with previous version 1.0 dated 2021-01-05

Title: Compute Wasserstein Barycenters, Geodesics, PCA and Distances
Description: Includes a variety of methods to compute objects related to the 'Wasserstein distance' (also known as 'Kantorovich distance' or 'Earth-Mover distance'). The main effort of this package is to allow for computations of 'Wasserstein barycenter' using regularised, unregularised and stochastic methods. It also provides convenient wrappers to call the 'transport' package with more general inputs. Handy visual tools are provided to showcase, barycenters, animations of optimal transport geodesics and animations of principal components in the 'Wasserstein space'.
Author: Florian Heinemann [aut, cre], Nicholas Bonneel [ctb]
Maintainer: Florian Heinemann <florian.heinemann@uni-goettingen.de>

Diff between WSGeometry versions 1.0 dated 2021-01-05 and 1.1 dated 2021-04-08

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Package msaeDB updated to version 0.2.1 with previous version 0.2.0 dated 2021-03-30

Title: Difference Benchmarking for Multivariate Small Area Estimation
Description: Implements Benchmarking Method for Multivariate Small Area Estimation under Fay Herriot Model. Multivariate Small Area Estimation (MSAE) is a development of Univariate Small Area Estimation that considering the correlation among response variables and borrowing the strength from related areas and auxiliary variables to increase the effectiveness of sample size, the multivariate model in this package is based on multivariate model 1 proposed by Roberto Benavent and Domingo Morales (2016) <doi:10.1016/j.csda.2015.07.013>. Benchmarking in Small Area Estimation is a modification of Small Area Estimation model to guarantee that the aggregate weighted mean of the county predictors equals the corresponding weighted mean of survey estimates. Difference Benchmarking is the simplest benchmarking method but widely used by multiplying empirical best linear unbiased prediction (EBLUP) estimator by the common adjustment factors (J.N.K Rao and Isabel Molina, 2015).
Author: Zaza Yuda Perwira, Azka Ubaidillah
Maintainer: Zaza Yuda Perwira <221710086@stis.ac.id>

Diff between msaeDB versions 0.2.0 dated 2021-03-30 and 0.2.1 dated 2021-04-08

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New package jordan with initial version 1.0-1
Package: jordan
Title: A Suite of Routines for Working with Jordan Algebras
Version: 1.0-1
Authors@R: person(given=c("Robin", "K. S."), family="Hankin", role = c("aut","cre"), email="hankin.robin@gmail.com", comment = c(ORCID = "0000-0001-5982-0415"))
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>
Description: A Jordan algebra is an algebraic object originally designed to study observables in quantum mechanics. Jordan algebras are commutative but non-associative; they satisfy the Jordan identity. The package follows the ideas and notation of K. McCrimmon (2004, ISBN:0-387-95447-3) "A Taste of Jordan Algebras".
License: GPL (>= 2)
Suggests: knitr,rmarkdown
Depends: onion (>= 1.4-0)
VignetteBuilder: knitr
Imports: emulator,methods,mathjaxr
URL: https://github.com/RobinHankin/jordan
BugReports: https://github.com/RobinHankin/jordan/issues
RdMacros: mathjaxr
NeedsCompilation: no
Packaged: 2021-04-06 20:22:29 UTC; rhankin
Author: Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>)
Repository: CRAN
Date/Publication: 2021-04-08 11:00:02 UTC

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Package sclero (with last version 0.2) was removed from CRAN

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

2016-01-21 0.2

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New package VEwaning with initial version 1.1
Package: VEwaning
Title: Vaccine Efficacy Over Time
Version: 1.1
Date: 2021-04-06
Authors@R: c(person("Marie", "Davidian", role = "aut"), person("A.A.", "Tsiatis", role = "aut"), person("Shannon", "Holloway", role = c("aut", "cre"), email = "sthollow@ncsu.edu"))
Description: Implements methods for inference on potential waning of vaccine efficacy and for estimation of vaccine efficacy at a user-specified time after vaccination based on data from a randomized, double-blind, placebo-controlled vaccine trial in which participants may be unblinded and placebo subjects may be crossed over to the study vaccine. The methods also allow adjustment for possible confounding via inverse probability weighting through specification of models for the trial entry process, unblinding mechanisms, and the probability an unblinded placebo participant accepts study vaccine: Tsiatis, A. A. and Davidian, M. (2021) <arXiv:2102.13103> .
License: GPL-2
Depends: R (>= 2.10), survival, stats, graphics, ggplot2
NeedsCompilation: no
Repository: CRAN
Encoding: UTF-8
Collate: 'entryFit.R' 'gFunctions.R' 'estimateb.R' 'estimateu.R' 'ulbound.R' 'pre_dNYu.R' 'pre_dNYb.R' 'esttheta.R' 'plot.VEwaning.R' 'print.VEwaning.R' 'psiFit.R' 'unblindFit.R' 've.R' 'veWaning.R' 'veWaningData.R'
Packaged: 2021-04-06 19:48:27 UTC; sthollow
Author: Marie Davidian [aut], A.A. Tsiatis [aut], Shannon Holloway [aut, cre]
Maintainer: Shannon Holloway <sthollow@ncsu.edu>
Date/Publication: 2021-04-08 08:20:02 UTC

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New package tidyBdE with initial version 0.1.0
Package: tidyBdE
Title: Download Data from Bank of Spain
Version: 0.1.0
Authors@R: person(given = "Diego", family = "H. Herrero", role = c("aut", "cre", "cph"), email = "dev.dieghernan@gmail.com", comment = c(ORCID = "0000-0001-8457-4658"))
Description: Tools to download data series from 'Banco de España' ('BdE') on 'tibble' format. 'Banco de España' is the national central bank and, within the framework of the Single Supervisory Mechanism ('SSM'), the supervisor of the Spanish banking system along with the European Central Bank. This package is in no way sponsored endorsed or administered by 'Banco de España'.
License: GPL (>= 3)
Encoding: UTF-8
BugReports: https://github.com/rOpenSpain/tidyBdE/issues
URL: https://ropenspain.github.io/tidyBdE/, https://github.com/rOpenSpain/tidyBdE
Depends: R (>= 3.6.0)
Imports: tibble (>= 3.0.0), readr (>= 1.0.0), dplyr (>= 0.7.0), ggplot2 (>= 3.3.0), scales (>= 1.1.0)
Suggests: tidyverse (>= 1.3.0), tinytest
NeedsCompilation: no
Packaged: 2021-04-06 19:37:47 UTC; diego
Author: Diego H. Herrero [aut, cre, cph] (<https://orcid.org/0000-0001-8457-4658>)
Maintainer: Diego H. Herrero <dev.dieghernan@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-08 08:10:03 UTC

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New package nCov2019 with initial version 0.4.3
Package: nCov2019
Title: Exploring 'COVID'-19 Statistics
Version: 0.4.3
Authors@R: c( person("Guangchuang", "Yu", email = "guangchuangyu@gmail.com", role = c("cre", "aut", "cph"), comment = c(ORCID = "0000-0002-6485-8781")), person("Tianzhi", "Wu", email = "wutimze@gmail.com", role = "aut"), person("Erqiang", "Hu", email = "13766876214@163.com", role = "ctb"), person("Patrick", "Tung", email = "tung_patrick@yahoo.com", role = "ctb"), person("Xijin", "Ge", email = "Xijin.Ge@sdstate.edu", role = "ctb") )
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>
Description: Provides easy-to-use programming API to access real time and historical data of 'COVID'-19 cases, vaccine and therapeutics data, and a Shiny app to help users exploring the data. Fetching data using API provided by <https://disease.sh> .
Depends: R (>= 3.6.0)
Imports: downloader, ggplot2, jsonlite, RColorBrewer
Suggests: cowplot, dplyr, DT, ggplotify, grDevices, maps, magick, shiny, shinyBS, shinydashboard, shinycssloaders, remotes, utils, plotly, prettydoc, knitr, rmarkdown, reshape2, ggrepel, shadowtext, tidyr
VignetteBuilder: knitr
License: MIT + file LICENSE
URL: https://github.com/YuLab-SMU/nCov2019
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-06 09:41:04 UTC; ygc
Author: Guangchuang Yu [cre, aut, cph] (<https://orcid.org/0000-0002-6485-8781>), Tianzhi Wu [aut], Erqiang Hu [ctb], Patrick Tung [ctb], Xijin Ge [ctb]
Repository: CRAN
Date/Publication: 2021-04-08 08:30:03 UTC

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New package datagovindia with initial version 0.0.3
Package: datagovindia
Title: Data.gov.in API Wrapper
Version: 0.0.3
Authors@R: c(person(given = "Abhishek", family = "Arora", role = c("cre", "aut"), email = "abhishek.arora1996@gmail.com"), person(given = "Aditya", family = "Chhabra", role = c("aut"), email = "aditya0chhabra@gmail.com"))
Description: This wrapper allows the user to communicate with more than 80,000 API posted on data.gov.in - open data platform of the government of India <https:data.gov.in/ogpl_apis>. It also allows the user to search for the API required through the universe of the API with a better interface than the one the official website provides. Once a user has the ID by using the API discovery functionalities, it allows one to converse with the API using a consistent format across all available API.
License: MIT + file LICENSE
URL: https://github.com/econabhishek/datagovindia
BugReports: https://github.com/econabhishek/datagovindia/issues
Imports: curl, dplyr, httr, magrittr, plyr, stringr, rlang
Encoding: UTF-8
Suggests: rmarkdown, knitr, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-07 07:23:06 UTC; ASUS
Author: Abhishek Arora [cre, aut], Aditya Chhabra [aut]
Maintainer: Abhishek Arora <abhishek.arora1996@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-08 08:30:06 UTC

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New package TeachHist with initial version 0.1.2
Package: TeachHist
Title: A Collection of Amended Histograms Designed for Teaching Statistics
Version: 0.1.2
Authors@R: person("Carsten", "Lange", email = "clange@cpp.edu", role = c("aut", "cre"))
Maintainer: Carsten Lange <clange@cpp.edu>
Description: Statistics students often have problems understanding the relation between a random variable's true scale and its z-values. To allow instructors to better better visualize histograms for these students, the package provides histograms with two horizontal axis containing z-values and the true scale of the variable. The function TeachHistDens() provides a density histogram with two axis. TeachHistCounts() and TeachHistRelFreq() are variations for count and relative frequency histograms, respectively. TeachConfInterv() and TeachHypTest() help instructors to visualize confidence levels and the results of hypothesis tests.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0), ggplot2, dplyr
NeedsCompilation: no
Packaged: 2021-04-06 17:15:22 UTC; clange
Author: Carsten Lange [aut, cre]
Repository: CRAN
Date/Publication: 2021-04-08 07:50:05 UTC

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New package places with initial version 0.1.1
Package: places
Title: Clusters GPS Data into Places
Version: 0.1.1
Authors@R: person(given = "Katherine", family = "Roehrick", role = c("aut", "cre"), email = "kr.gitcode@gmail.com")
Description: Clusters GPS coordinates into places (i.e., meaningful stops). Additionally, categorizes places into types (e.g., home, cafe, gym). Places are identified as home using a rules-based algorithm defining home as the stop occurring most frequently during the night. Other places (e.g., cafe, gym) are identified using the Google Maps API.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, tidyr, sp, rgdal, geosphere, data.table, rlang, googleway, stringr, stats, hms
Suggests: R.rsp
VignetteBuilder: R.rsp
Depends: R (>= 2.10)
Language: en-US
NeedsCompilation: no
Packaged: 2021-04-06 15:35:03 UTC; kr
Author: Katherine Roehrick [aut, cre]
Maintainer: Katherine Roehrick <kr.gitcode@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-08 07:50:02 UTC

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Package haploReconstruct (with last version 0.1.2) was removed from CRAN

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

2016-10-10 0.1.2

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Package NFP (with last version 0.99.3) was removed from CRAN

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

2019-10-14 0.99.3
2016-11-21 0.99.2
2016-08-31 0.99.1

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

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

2019-03-31 1.0.3

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Package activpalProcessing (with last version 1.0.2) was removed from CRAN

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

2016-12-14 1.0.2
2016-03-28 1.0.1
2016-01-25 1.0

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Package netgsa (with last version 3.1.0) was removed from CRAN

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

2019-03-27 3.1.0
2016-06-16 3.0
2015-03-08 2.0
2014-12-02 1.0

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

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

2020-10-04 0.1.1
2020-06-29 0.1.0

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Package dgodata (with last version 0.0.2) was removed from CRAN

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

2017-02-13 0.0.2

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New package RaceID with initial version 0.2.3
Package: RaceID
Title: Identification of Cell Types and Inference of Lineage Trees from Single-Cell RNA-Seq Data
Version: 0.2.3
Date: 2021-04-07
Author: Dominic Grün <dominic.gruen@gmail.com>
Maintainer: Dominic Grün <dominic.gruen@gmail.com>
Description: Application of 'RaceID' allows inference of cell types and prediction of lineage trees by he StemID2 algorithm. Herman, J.S., Sagar, Grün D. (2018) <DOI:10.1038/nmeth.4662>.
Depends: R (>= 3.5.0)
biocViews:
Imports: coop, compiler, cluster, FateID, FNN, fpc, ggplot2, grDevices, ica, igraph, irlba, locfit, methods, MASS, Matrix, matrixStats, parallel, pheatmap, propr, quadprog, randomForest, Rcpp, RColorBrewer, Rtsne, umap, vegan
LinkingTo: Rcpp (>= 0.11.0)
Suggests: batchelor, DESeq2, knitr, rmarkdown, SummarizedExperiment
VignetteBuilder: knitr
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2021-04-07 21:33:49 UTC; d.grun
Repository: CRAN
Date/Publication: 2021-04-08 06:10:08 UTC

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Package pegas updated to version 1.0 with previous version 0.14 dated 2020-09-16

Title: Population and Evolutionary Genetics Analysis System
Description: Functions for reading, writing, plotting, analysing, and manipulating allelic and haplotypic data, including from VCF files, and for the analysis of population nucleotide sequences and micro-satellites including coalescent analyses, linkage disequilibrium, population structure (Fst, Amova) and equilibrium (HWE), haplotype networks, minimum spanning tree and network, and median-joining networks.
Author: Emmanuel Paradis [aut, cre, cph] (<https://orcid.org/0000-0003-3092-2199>), Thibaut Jombart [aut, cph] (<https://orcid.org/0000-0003-2226-8692>), Zhian N. Kamvar [aut, cph] (<https://orcid.org/0000-0003-1458-7108>), Brian Knaus [aut, cph] (<https://orcid.org/0000-0003-1665-4343>), Klaus Schliep [aut, cph] (<https://orcid.org/0000-0003-2941-0161>), Alastair Potts [aut, cph] (<https://orcid.org/0000-0003-0919-7279>), David Winter [aut, cph] (<https://orcid.org/0000-0002-6165-0029>)
Maintainer: Emmanuel Paradis <Emmanuel.Paradis@ird.fr>

Diff between pegas versions 0.14 dated 2020-09-16 and 1.0 dated 2021-04-08

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Package dartR updated to version 1.9.4 with previous version 1.9.1 dated 2021-04-03

Title: Importing and Analysing SNP and Silicodart Data Generated by Genome-Wide Restriction Fragment Analysis
Description: Functions are provided that facilitate the import and analysis of SNP (single nucleotide polymorphism) and silicodart (presence/absence) data. The main focus is on data generated by DarT (Diversity Arrays Technology). However, once SNP or related fragment presence/absence data from any source is imported into a genlight object many of the functions can be used. Functions are available for input and output of SNP and silicodart data, for reporting on and filtering on various criteria (e.g. CallRate, Heterozygosity, Reproducibility, maximum allele frequency). Advanced filtering is based on Linkage Disequilibrium and HWE (Hardy-Weinberg equilibrium). Other functions are available for visualization after PCoA (Principle Coordinate Analysis), or to facilitate transfer of data between genlight/genind objects and newhybrids, related, phylip, structure, faststructure packages.
Author: Bernd Gruber [aut, cre], Arthur Georges [aut], Jose L. Mijangos [aut], Peter J. Unmack [ctb], Oliver Berry [ctb], Lindsay V. Clark [ctb], Floriaan Devloo-Delva [ctb]
Maintainer: Bernd Gruber <bernd.gruber@canberra.edu.au>

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Package bayestestR updated to version 0.9.0 with previous version 0.8.2 dated 2021-01-26

Title: Understand and Describe Bayesian Models and Posterior Distributions
Description: Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors).
Author: Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Indrajeet Patil [aut] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Michael D. Wilson [aut] (<https://orcid.org/0000-0003-4143-7308>), Paul-Christian Bürkner [rev], Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>), Quentin F. Gronau [ctb] (<https://orcid.org/0000-0001-5510-6943>), Sam Crawley [ctb] (<https://orcid.org/0000-0002-7847-0411>)
Maintainer: Dominique Makowski <dom.makowski@gmail.com>

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Package seededlda updated to version 0.6.0 with previous version 0.5.1 dated 2020-12-17

Title: Seeded-LDA for Topic Modeling
Description: Implements the seeded-LDA model (Lu, Ott, Cardie & Tsou 2010) <doi:10.1109/ICDMW.2011.125> using the quanteda package and the GibbsLDA++ library for semisupervised topic modeling. Seeded-LDA allows users to pre-define topics with keywords to perform theory-driven analysis of textual data in social sciences and humanities (Watanabe & Zhou 2020) <doi:10.1177/0894439320907027>.
Author: Kohei Watanabe [aut, cre, cph], Phan Xuan-Hieu [aut, cph] (GibbsLDA++)
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

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Package ozmaps updated to version 0.4.0 with previous version 0.3.6 dated 2020-04-02

Title: Australia Maps
Description: Maps of Australian coastline and administrative regions. Data can be drawn or accessed directly as simple features objects. Includes simple functions for country or state maps of Australia and in-built data sets of administrative regions from the Australian Bureau of Statistics <https://www.abs.gov.au/>. Layers include electoral divisions and local government areas, simplified from the original sources but with sufficient detail to allow mapping of a local municipality.
Author: Michael Sumner [aut, cre], Dianne Cook [ctb], Dario Herenu [ctb]
Maintainer: Michael Sumner <mdsumner@gmail.com>

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Package ds4psy updated to version 0.6.0 with previous version 0.5.0 dated 2020-09-01

Title: Data Science for Psychologists
Description: All datasets and functions required for the examples and exercises of the book "Data Science for Psychologists" (by Hansjoerg Neth, Konstanz University, 2021), available at <https://bookdown.org/hneth/ds4psy/>. The book and course introduce principles and methods of data science to students of psychology and other biological or social sciences. The 'ds4psy' package primarily provides datasets, but also functions for data generation and manipulation (e.g., of text and time data) and graphics that are used in the book and its exercises. All functions included in 'ds4psy' are designed to be explicit and instructive, rather than elegant or efficient.
Author: Hansjoerg Neth [aut, cre] (<https://orcid.org/0000-0001-5427-3141>)
Maintainer: Hansjoerg Neth <h.neth@uni.kn>

Diff between ds4psy versions 0.5.0 dated 2020-09-01 and 0.6.0 dated 2021-04-08

 DESCRIPTION            |   12 -
 MD5                    |   88 ++++++-------
 NAMESPACE              |    4 
 NEWS.md                |   91 +++++++++----
 R/color_fun.R          |   10 -
 R/data.R               |   34 ++---
 R/data_fun.R           |  265 +++++++++++++++++++++++++++++-----------
 R/plot_fun.R           |   52 +++----
 R/start.R              |    5 
 R/text_fun.R           |   56 ++++----
 R/theme_fun.R          |  201 +++++++++++++++++++++++++++---
 R/time_util_fun.R      |   41 +++++-
 R/util_fun.R           |  104 +++++++++++++++
 README.md              |  217 ++++++++++++++++----------------
 build/partial.rdb      |only
 data/Trumpisms.rda     |binary
 data/fame.rda          |binary
 inst/CITATION          |    8 -
 inst/WORDLIST          |    5 
 inst/doc/ds4psy.R      |    4 
 inst/doc/ds4psy.Rmd    |   10 -
 inst/doc/ds4psy.html   |  324 +++++++++++++++++++++++++++++++++++++++++--------
 man/Trumpisms.Rd       |   13 -
 man/dice_2.Rd          |    1 
 man/falsePosPsy_all.Rd |    4 
 man/fame.Rd            |    2 
 man/get_set.Rd         |only
 man/is_equal.Rd        |    1 
 man/is_vector.Rd       |only
 man/is_wholenumber.Rd  |    1 
 man/make_grid.Rd       |    4 
 man/num_as_char.Rd     |    1 
 man/num_as_ordinal.Rd  |    1 
 man/num_equal.Rd       |    1 
 man/plot_fn.Rd         |    3 
 man/plot_fun.Rd        |    3 
 man/plot_n.Rd          |    3 
 man/plot_text.Rd       |    5 
 man/plot_tiles.Rd      |    3 
 man/posPsy_AHI_CESD.Rd |    2 
 man/posPsy_long.Rd     |    2 
 man/posPsy_p_info.Rd   |    2 
 man/posPsy_wide.Rd     |    2 
 man/theme_clean.Rd     |    6 
 man/theme_ds4psy.Rd    |   14 +-
 man/theme_empty.Rd     |only
 vignettes/ds4psy.Rmd   |   10 -
 47 files changed, 1168 insertions(+), 447 deletions(-)

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