Wed, 14 Apr 2021

Package reReg updated to version 1.4.0 with previous version 1.3.0 dated 2020-07-22

Title: Recurrent Event Regression
Description: A comprehensive collection of practical and easy-to-use tools for regression analysis of recurrent events, with or without the presence of a (possibly) informative terminal event. The modeling framework is based on a joint frailty scale-change model, that includes models described in Wang et al. (2001) <doi:10.1198/016214501753209031>, Huang and Wang (2004) <doi:10.1198/016214504000001033>, Xu et al. (2017) <doi:10.1080/01621459.2016.1173557>, and Xu et al. (2019) <doi:10.5705/SS.202018.0224> as special cases. The implemented estimating procedure does not require any parametric assumption on the frailty distribution. The package also allows the users to specify different model forms for both the recurrent event process and the terminal event.
Author: Sy Han (Steven) Chiou [aut, cre], Chiung-Yu Huang [aut]
Maintainer: Sy Han (Steven) Chiou <schiou@utdallas.edu>

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Package inti updated to version 0.2.0 with previous version 0.1.3 dated 2021-03-20

Title: Tools and Statistical Procedures in Plant Science
Description: The 'inti' package is part of the 'inkaverse' project for developing different procedures and tools used in plant science and experimental designs. The mean aim of the package is to support researchers during the planning of experiments and data collection (tarpuy()), data analysis and graphics (yupana()) , and technical writing (rtciles()). Learn more about the 'inkaverse' project at <https://inkaverse.com/>.
Author: Flavio Lozano-Isla [aut, cre] (<https://orcid.org/0000-0002-0714-669X>)
Maintainer: Flavio Lozano-Isla <flavjack@gmail.com>

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Package haven updated to version 2.4.0 with previous version 2.3.1 dated 2020-06-01

Title: Import and Export 'SPSS', 'Stata' and 'SAS' Files
Description: Import foreign statistical formats into R via the embedded 'ReadStat' C library, <https://github.com/WizardMac/ReadStat>.
Author: Hadley Wickham [aut, cre], Evan Miller [aut, cph] (Author of included ReadStat code), RStudio [cph, fnd]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package ddiv updated to version 0.1.1 with previous version 0.1.0 dated 2018-09-28

Title: Data Driven I-v Feature Extraction
Description: The Data Driven I-V Feature Extraction is used to extract Current-Voltage (I-V) features from I-V curves. I-V curves indicate the relationship between current and voltage for a solar cell or Photovoltaic (PV) modules. The I-V features such as maximum power point (Pmp), shunt resistance (Rsh), series resistance (Rs),short circuit current (Isc), open circuit voltage (Voc), fill factor (FF), current at maximum power (Imp) and voltage at maximum power(Vmp) contain important information of the performance for PV modules. The traditional method uses the single diode model to model I-V curves and extract I-V features. This package does not use the diode model, but uses data-driven a method which select different linear parts of the I-V curves to extract I-V features. This method also uses a sampling method to calculate uncertainties when extracting I-V features. Also, because of the partially shaded array, "steps" occurs in I-V curves. The "Segmented Regression" method is used to identify steps in I-V curves. This material is based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy Technologies Office (SETO) Agreement Number DE-EE0007140. Further information can be found in the following paper. [1] Ma, X. et al, 2019. <doi:10.1109/JPHOTOV.2019.2928477>.
Author: Wei-Heng Huang [aut] (<https://orcid.org/0000-0002-6609-4981>), Xuan Ma [aut] (<https://orcid.org/0000-0003-2361-2846>), Jiqi Liu [aut] (<https://orcid.org/0000-0003-2016-4160>), Menghong Wang [ctb] (<https://orcid.org/0000-0001-7349-699X>), Alan J. Curran [ctb] (<https://orcid.org/0000-0002-4505-8359>), Justin S. Fada [ctb] (<https://orcid.org/0000-0002-0029-5051>), Jean-Nicolas Jaubert [ctb] (<https://orcid.org/0000-0002-9663-6999>), Jing Sun [ctb] (<https://orcid.org/0000-0002-4313-2316>), Jennifer L. Braid [ctb] (<https://orcid.org/0000-0002-0677-7756>), Jenny Brynjarsdottir [ctb] (<https://orcid.org/0000-0003-1859-4962>), Roger H. French [aut, cph] (<https://orcid.org/0000-0002-6162-0532>), Megan M. Morbitzer [ctb, cre] (<https://orcid.org/0000-0002-9847-2350>)
Maintainer: Megan M. Morbitzer <mmm308@case.edu>

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Package windex updated to version 2.0.2 with previous version 2.0.1 dated 2021-01-13

Title: Analysing Convergent Evolution using the Wheatsheaf Index
Description: Analysing convergent evolution using the Wheatsheaf index, described in Arbuckle et al. (2014) <doi: 10.1111/2041-210X.12195>, and some other random but perhaps useful functions.
Author: Kevin Arbuckle and Amanda Minter
Maintainer: Kevin Arbuckle <kevin.arbuckle@swansea.ac.uk>

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Package geobr updated to version 1.6 with previous version 1.5-1 dated 2021-02-06

Title: Download Official Spatial Data Sets of Brazil
Description: Easy access to official spatial data sets of Brazil as 'sf' objects in R. The package includes a wide range of geospatial data available at various geographic scales and for various years with harmonized attributes, projection and fixed topology.
Author: Rafael H. M. Pereira [aut, cre] (<https://orcid.org/0000-0003-2125-7465>), Caio Nogueira Goncalves [aut], Paulo Henrique Fernandes de Araujo [ctb], Guilherme Duarte Carvalho [ctb], Rodrigo Almeida de Arruda [ctb], Igor Nascimento [ctb], Barbara Santiago Pedreira da Costa [ctb], Welligtton Silva Cavedo [ctb], Pedro R. Andrade [ctb], Alan da Silva [ctb], Carlos Kauê Vieira Braga [ctb], Carl Schmertmann [ctb], Alessandro Samuel-Rosa [ctb], Daniel Ferreira [ctb], Ipea - Institue for Applied Economic Research [cph, fnd]
Maintainer: Rafael H. M. Pereira <rafa.pereira.br@gmail.com>

Diff between geobr versions 1.5-1 dated 2021-02-06 and 1.6 dated 2021-04-14

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Package sasLM updated to version 0.5.2 with previous version 0.5.1 dated 2021-03-16

Title: 'SAS' Linear Model
Description: This is a core implementation of 'SAS' procedures for linear models - GLM, REG, and ANOVA. Some R packages provide type II and type III SS. However, the results of nested and complex designs are often different from those of 'SAS.' Different results does not necessarily mean incorrectness. However, many wants the same results to SAS. This package aims to achieve that. Reference: Littell RC, Stroup WW, Freund RJ (2002, ISBN:0-471-22174-0).
Author: Kyun-Seop Bae [aut]
Maintainer: Kyun-Seop Bae <k@acr.kr>

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Package formatR updated to version 1.9 with previous version 1.8 dated 2021-03-12

Title: Format R Code Automatically
Description: Provides a function tidy_source() to format R source code. Spaces and indent will be added to the code automatically, and comments will be preserved under certain conditions, so that R code will be more human-readable and tidy. There is also a Shiny app as a user interface in this package (see tidy_app()).
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Ed Lee [ctb], Eugene Ha [ctb], Kohske Takahashi [ctb], Pavel Krivitsky [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package DT updated to version 0.18 with previous version 0.17 dated 2021-01-06

Title: A Wrapper of the JavaScript Library 'DataTables'
Description: Data objects in R can be rendered as HTML tables using the JavaScript library 'DataTables' (typically via R Markdown or Shiny). The 'DataTables' library has been included in this R package. The package name 'DT' is an abbreviation of 'DataTables'.
Author: Yihui Xie [aut, cre], Joe Cheng [aut], Xianying Tan [aut], JJ Allaire [ctb], Maximilian Girlich [ctb], Greg Freedman Ellis [ctb], Johannes Rauh [ctb], jQuery contributors [ctb, cph] (jQuery in htmlwidgets/lib), SpryMedia Limited [ctb, cph] (DataTables in htmlwidgets/lib), Brian Reavis [ctb, cph] (selectize.js in htmlwidgets/lib), Leon Gersen [ctb, cph] (noUiSlider in htmlwidgets/lib), Bartek Szopka [ctb, cph] (jquery.highlight.js in htmlwidgets/lib), RStudio, PBC [cph]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between DT versions 0.17 dated 2021-01-06 and 0.18 dated 2021-04-14

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More information about DT at CRAN
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Package blogdown updated to version 1.3 with previous version 1.2 dated 2021-03-04

Title: Create Blogs and Websites with R Markdown
Description: Write blog posts and web pages in R Markdown. This package supports the static site generator 'Hugo' (<https://gohugo.io>) best, and it also supports 'Jekyll' (<https://jekyllrb.com>) and 'Hexo' (<https://hexo.io>).
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Christophe Dervieux [aut] (<https://orcid.org/0000-0003-4474-2498>), Alison Presmanes Hill [aut] (<https://orcid.org/0000-0002-8082-1890>), Amber Thomas [ctb], Beilei Bian [ctb], Brandon Greenwell [ctb], Brian Barkley [ctb], Deependra Dhakal [ctb], Eric Nantz [ctb], Forest Fang [ctb], Garrick Aden-Buie [ctb], Hiroaki Yutani [ctb], Ian Lyttle [ctb], Jake Barlow [ctb], James Balamuta [ctb], JJ Allaire [ctb], Jon Calder [ctb], Jozef Hajnala [ctb], Juan Manuel Vazquez [ctb], Kevin Ushey [ctb], Leonardo Collado-Torres [ctb], Maëlle Salmon [ctb], Maria Paula Caldas [ctb], Nicolas Roelandt [ctb], Oliver Madsen [ctb], Raniere Silva [ctb], TC Zhang [ctb], Xianying Tan [ctb], RStudio, PBC [cph]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between blogdown versions 1.2 dated 2021-03-04 and 1.3 dated 2021-04-14

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Package testit updated to version 0.13 with previous version 0.12 dated 2020-09-25

Title: A Simple Package for Testing R Packages
Description: Provides two convenience functions assert() and test_pkg() to facilitate testing R packages.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Steven Mortimer [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package servr updated to version 0.22 with previous version 0.21 dated 2020-12-14

Title: A Simple HTTP Server to Serve Static Files or Dynamic Documents
Description: Start an HTTP server in R to serve static files, or dynamic documents that can be converted to HTML files (e.g., R Markdown) under a given directory.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Carson Sievert [ctb], Jesse Anderson [ctb], Ramnath Vaidyanathan [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package RolWinMulCor updated to version 1.2.0 with previous version 1.0.0 dated 2020-08-31

Title: Subroutines to Estimate Rolling Window Multiple Correlation
Description: Rolling Window Multiple Correlation ('RolWinMulCor') estimates the rolling (running) window correlation for the bi- and multi-variate cases between regular (sampled on identical time points) time series, with especial emphasis to ecological data although this can be applied to other kinds of data sets. 'RolWinMulCor' is based on the concept of rolling, running or sliding window and is useful to evaluate the evolution of correlation through time and time-scales. 'RolWinMulCor' contains six functions. The first two focus on the bi-variate case: (1) rolwincor_1win() and (2) rolwincor_heatmap(), which estimate the correlation coefficients and the their respective p-values for only one window-length (time-scale) and considering all possible window-lengths or a band of window-lengths, respectively. The second two functions: (3) rolwinmulcor_1win() and (4) rolwinmulcor_heatmap() are designed to analyze the multi-variate case, following the bi-variate case to visually display the results, but these two approaches are methodologically different. That is, the multi-variate case estimates the adjusted coefficients of determination instead of the correlation coefficients. The last two functions: (5) plot_1win() and (6) plot_heatmap() are used to represent graphically the outputs of the four aforementioned functions as simple plots or as heat maps. The functions contained in 'RolWinMulCor' are highly flexible since these contains several parameters to control the estimation of correlation and the features of the plot output, e.g. to remove the (linear) trend contained in the time series under analysis, to choose different p-value correction methods (which are used to address the multiple comparison problem) or to personalise the plot outputs. The 'RolWinMulCor' package also provides examples with synthetic and real-life ecological time series to exemplify its use. Methods derived from H. Abdi. (2007) <https://personal.utdallas.edu/~herve/Abdi-MCC2007-pretty.pdf>, R. Telford (2013) <https://quantpalaeo.wordpress.com/2013/01/04/, J. M. Polanco-Martinez (2019) <doi:10.1007/s11071-019-04974-y>, and J. M. Polanco-Martinez (2020) <doi:10.1016/j.ecoinf.2020.101163>.
Author: Josue M. Polanco-Martinez [aut, cph, cre] (<https://orcid.org/0000-0001-7164-0185>)
Maintainer: Josue M. Polanco-Martinez <josue.m.polanco@gmail.com>

Diff between RolWinMulCor versions 1.0.0 dated 2020-08-31 and 1.2.0 dated 2021-04-14

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Package pense updated to version 2.0.3 with previous version 2.0.2 dated 2020-10-05

Title: Penalized Elastic Net S/MM-Estimator of Regression
Description: Robust penalized (adaptive) elastic net S and M estimators for linear regression. The methods are proposed in Cohen Freue, G. V., Kepplinger, D., Salibián-Barrera, M., and Smucler, E. (2019) <https://projecteuclid.org/euclid.aoas/1574910036>. The package implements the extensions and algorithms described in Kepplinger, D. (2020) <doi:10.14288/1.0392915>.
Author: David Kepplinger [aut, cre], Matías Salibián-Barrera [aut], Gabriela Cohen Freue [aut]
Maintainer: David Kepplinger <david.kepplinger@gmail.com>

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 pense-2.0.3/pense/DESCRIPTION                                                                                 |   10 
 pense-2.0.3/pense/MD5                                                                                         |   66 
 pense-2.0.3/pense/NEWS.md                                                                                     |    5 
 pense-2.0.3/pense/R/coef-methods.R                                                                            |   76 
 pense-2.0.3/pense/R/control_options.R                                                                         |    6 
 pense-2.0.3/pense/R/elnet.R                                                                                   |    6 
 pense-2.0.3/pense/R/pense_regression.R                                                                        |   17 
 pense-2.0.3/pense/R/print-methods.R                                                                           |    9 
 pense-2.0.3/pense/R/regmest_regression.R                                                                      |    5 
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Package pagedown updated to version 0.14 with previous version 0.13 dated 2020-11-30

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>

Diff between pagedown versions 0.13 dated 2020-11-30 and 0.14 dated 2021-04-14

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More information about pagedown at CRAN
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Package knitr updated to version 1.32 with previous version 1.31 dated 2021-01-27

Title: A General-Purpose Package for Dynamic Report Generation in R
Description: Provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Abhraneel Sarma [ctb], Adam Vogt [ctb], Alastair Andrew [ctb], Alex Zvoleff [ctb], Andre Simon [ctb] (the CSS files under inst/themes/ were derived from the Highlight package http://www.andre-simon.de), Aron Atkins [ctb], Aaron Wolen [ctb], Ashley Manton [ctb], Atsushi Yasumoto [ctb] (<https://orcid.org/0000-0002-8335-495X>), Ben Baumer [ctb], Brian Diggs [ctb], Brian Zhang [ctb], Cassio Pereira [ctb], Christophe Dervieux [ctb], David Hall [ctb], David Hugh-Jones [ctb], David Robinson [ctb], Doug Hemken [ctb], Duncan Murdoch [ctb], Elio Campitelli [ctb], Ellis Hughes [ctb], Emily Riederer [ctb], Fabian Hirschmann [ctb], Fitch Simeon [ctb], Forest Fang [ctb], Frank E Harrell Jr [ctb] (the Sweavel package at inst/misc/Sweavel.sty), Garrick Aden-Buie [ctb], Gregoire Detrez [ctb], Hadley Wickham [ctb], Hao Zhu [ctb], Heewon Jeon [ctb], Henrik Bengtsson [ctb], Hiroaki Yutani [ctb], Ian Lyttle [ctb], Hodges Daniel [ctb], Jake Burkhead [ctb], James Manton [ctb], Jared Lander [ctb], Jason Punyon [ctb], Javier Luraschi [ctb], Jeff Arnold [ctb], Jenny Bryan [ctb], Jeremy Ashkenas [ctb, cph] (the CSS file at inst/misc/docco-classic.css), Jeremy Stephens [ctb], Jim Hester [ctb], Joe Cheng [ctb], Johannes Ranke [ctb], John Honaker [ctb], John Muschelli [ctb], Jonathan Keane [ctb], JJ Allaire [ctb], Johan Toloe [ctb], Jonathan Sidi [ctb], Joseph Larmarange [ctb], Julien Barnier [ctb], Kaiyin Zhong [ctb], Kamil Slowikowski [ctb], Karl Forner [ctb], Kevin K. Smith [ctb], Kirill Mueller [ctb], Kohske Takahashi [ctb], Lorenz Walthert [ctb], Lucas Gallindo [ctb], Marius Hofert [ctb], Martin Modrák [ctb], Michael Chirico [ctb], Michael Friendly [ctb], Michal Bojanowski [ctb], Michel Kuhlmann [ctb], Miller Patrick [ctb], Nacho Caballero [ctb], Nick Salkowski [ctb], Niels Richard Hansen [ctb], Noam Ross [ctb], Obada Mahdi [ctb], Pavel N. Krivitsky [ctb] (<https://orcid.org/0000-0002-9101-3362>), Qiang Li [ctb], Ramnath Vaidyanathan [ctb], Richard Cotton [ctb], Robert Krzyzanowski [ctb], Romain Francois [ctb], Ruaridh Williamson [ctb], Scott Kostyshak [ctb], Sebastian Meyer [ctb], Sietse Brouwer [ctb], Simon de Bernard [ctb], Sylvain Rousseau [ctb], Taiyun Wei [ctb], Thibaut Assus [ctb], Thibaut Lamadon [ctb], Thomas Leeper [ctb], Tim Mastny [ctb], Tom Torsney-Weir [ctb], Trevor Davis [ctb], Viktoras Veitas [ctb], Weicheng Zhu [ctb], Wush Wu [ctb], Zachary Foster [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between knitr versions 1.31 dated 2021-01-27 and 1.32 dated 2021-04-14

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More information about knitr at CRAN
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Package fairness updated to version 1.2.2 with previous version 1.2.1 dated 2021-03-31

Title: Algorithmic Fairness Metrics
Description: Offers calculation, visualization and comparison of algorithmic fairness metrics. Fair machine learning is an emerging topic with the overarching aim to critically assess whether ML algorithms reinforce existing social biases. Unfair algorithms can propagate such biases and produce predictions with a disparate impact on various sensitive groups of individuals (defined by sex, gender, ethnicity, religion, income, socioeconomic status, physical or mental disabilities). Fair algorithms possess the underlying foundation that these groups should be treated similarly or have similar prediction outcomes. The fairness R package offers the calculation and comparisons of commonly and less commonly used fairness metrics in population subgroups. These methods are described by Calders and Verwer (2010) <doi:10.1007/s10618-010-0190-x>, Chouldechova (2017) <doi:10.1089/big.2016.0047>, Feldman et al. (2015) <doi:10.1145/2783258.2783311> , Friedler et al. (2018) <doi:10.1145/3287560.3287589> and Zafar et al. (2017) <doi:10.1145/3038912.3052660>. The package also offers convenient visualizations to help understand fairness metrics.
Author: Nikita Kozodoi [aut, cre], Tibor V. Varga [aut] (<https://orcid.org/0000-0002-2383-699X>)
Maintainer: Nikita Kozodoi <n.kozodoi@icloud.com>

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More information about fairness at CRAN
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Package terra updated to version 1.1-17 with previous version 1.1-4 dated 2021-03-09

Title: Spatial Data Analysis
Description: Methods for spatial data analysis, especially raster data. Methods allow for low-level data manipulation as well as high-level global, local, zonal, and focal computation. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/terra/> to get started. 'terra' is very similar to the 'raster' package; but 'terra' can do more and it simpler to use and it is faster.
Author: Robert J. Hijmans [cre, aut] (<https://orcid.org/0000-0001-5872-2872>), Roger Bivand [ctb] (<https://orcid.org/0000-0003-2392-6140>), Karl Forner [ctb], Jeroen Ooms [ctb] (<https://orcid.org/0000-0002-4035-0289>), Edzer Pebesma [ctb] (<https://orcid.org/0000-0001-8049-7069>)
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

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New package rjpdmp with initial version 1.0.0
Package: rjpdmp
Title: Reversible Jump PDMP Samplers
Version: 1.0.0
Author: Matt Sutton, Augustin Chevalier, Paul Fearnhead, with PolyaGamma simulation code contributed from Jesse Windle and James G. Scott (<https://github.com/jgscott/helloPG>)
Maintainer: Matt Sutton <matt.sutton.stat@gmail.com>
Description: Provides an implementation of the reversible jump piecewise deterministic Markov processes (PDMPs) methods developed in the paper Reversible Jump PDMP Samplers for Variable Selection (Chevallier, Fearnhead, Sutton 2020, <arXiv:2010.11771>). It also contains an implementation of a Gibbs sampler for variable selection in Logistic regression based on Polya-Gamma augmentation.
License: GPL (>= 2)
Encoding: UTF-8
Imports: data.table, Rcpp (>= 0.12.3)
Suggests: MASS
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2021-04-10 10:20:12 UTC; matt
Repository: CRAN
Date/Publication: 2021-04-14 13:10:02 UTC

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Package latrend updated to version 1.1.2 with previous version 1.1.0 dated 2021-03-05

Title: A Framework for Clustering Longitudinal Data
Description: A framework for clustering longitudinal datasets in a standardized way. Provides an interface to existing R packages for clustering longitudinal univariate trajectories, facilitating reproducible and transparent analyses. Additionally, standard tools are provided to support cluster analyses, including repeated estimation, model validation, and model assessment. The interface enables users to compare results between methods, and to implement and evaluate new methods with ease.
Author: Niek Den Teuling [aut, cre] (<https://orcid.org/0000-0003-1026-5080>), Steffen Pauws [ctb], Edwin van den Heuvel [ctb], Copyright © 2021 Koninklijke Philips N.V. [cph]
Maintainer: Niek Den Teuling <niek.den.teuling@philips.com>

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Package states updated to version 0.3.1 with previous version 0.3.0 dated 2020-12-11

Title: Create Panels of Independent States
Description: Create panel data consisting of independent states from 1816 to the present. The package includes the Gleditsch & Ward (G&W) and Correlates of War (COW) lists of independent states, as well as helper functions for working with state panel data and standardizing other data sources to create country-year/month/etc. data.
Author: Andreas Beger [cre, aut] (<https://orcid.org/0000-0003-1883-3169>)
Maintainer: Andreas Beger <adbeger@gmail.com>

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Package svgtools updated to version 1.0.3 with previous version 1.0.1 dated 2021-03-03

Title: Manipulate SVG (Template) Files of Charts
Description: The purpose of this package is to manipulate SVG files that are templates of charts the user wants to produce. In vector graphics one copes with x-/y-coordinates of elements (e.g. lines, rectangles, text). Their scale is often dependent on the program that is used to produce the graphics. In applied statistics one usually has numeric values on a fixed scale (e.g. percentage values between 0 and 100) to show in a chart. Basically, 'svgtools' transforms the statistical values into coordinates and widths/heights of the vector graphics. This is done by stackedBar() for bar charts, by linesSymbols() for charts with lines and/or symbols (dot markers) and scatterSymbols() for scatterplots.
Author: Konrad Oberwimmer [aut, cre], Christian Wimmer [aut], Michael Bruneforth [ctb]
Maintainer: Konrad Oberwimmer <konrad.oberwimmer@iqs.gv.at>

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Package PAMA updated to version 1.0.0 with previous version 0.1.1 dated 2020-04-09

Title: Rank Aggregation with Partition Mallows Model
Description: Rank aggregation aims to achieve a better ranking list given multiple observations. 'PAMA' implements Partition-Mallows model for rank aggregation where the rankers' quality are different. Both Bayesian inference and Maximum likelihood estimation (MLE) are provided. It can handle partial list as well. When covariates information is available, this package can make inference by incorporating the covariate information. More information can be found in the paper "Integrated Partition-Mallows Model and Its Inference for Rank Aggregation". The paper is accepted by Journal of the American Statistical Association.
Author: Wanchuang Zhu [cre, aut]
Maintainer: Wanchuang Zhu <andy.chou.sub@gmail.com>

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Package midasml updated to version 0.1.0 with previous version 0.0.6 dated 2021-03-12

Title: Estimation and Prediction Methods for High-Dimensional Mixed Frequency Time Series Data
Description: The 'midasml' package implements estimation and prediction methods for high-dimensional mixed-frequency (MIDAS) time-series and panel data regression models. The regularized MIDAS models are estimated using orthogonal (e.g. Legendre) polynomials and sparse-group LASSO (sg-LASSO) estimator. For more information on the `midasml' approach see Babii, Ghysels, and Striaukas (2021, JBES forthcoming) <doi:10.1080/07350015.2021.1899933>. The package is equipped with the fast implementation of the sg-LASSO estimator by means of proximal block coordinate descent. High-dimensional mixed frequency time-series data can also be easily manipulated with functions provided in the package.
Author: Jonas Striaukas [cre, aut], Andrii Babii [aut], Eric Ghysels [aut], Alex Kostrov [ctb] (Contributions to analytical gradients for non-linear low-dimensional MIDAS estimation code)
Maintainer: Jonas Striaukas <jonas.striaukas@gmail.com>

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Package hockeystick updated to version 0.5.0 with previous version 0.4.0 dated 2021-02-05

Title: Download and Visualize Essential Climate Change Data
Description: Provides easy access to essential climate change datasets to non-climate experts. Users can download the latest raw data from authoritative sources and view it via pre-defined 'ggplot2' charts. Datasets include atmospheric CO2, instrumental and proxy temperature records, sea levels, Arctic/Antarctic sea-ice, Hurricanes, and Paleoclimate data. Sources include: NOAA Mauna Loa Laboratory <https://www.esrl.noaa.gov/gmd/ccgg/trends/data.html>, NASA GISTEMP <https://data.giss.nasa.gov/gistemp/>, National Snow and Sea Ice Data Center <https://nsidc.org/data/seaice_index/archives>, CSIRO <https://research.csiro.au/slrwavescoast/sea-level/measurements-and-data/sea-level-data/>, NOAA Laboratory for Satellite Altimetry <https://www.star.nesdis.noaa.gov/socd/lsa/SeaLevelRise/> and HURDAT Atlantic Hurricane Database <https://www.aoml.noaa.gov/hrd/hurdat/Data_Storm.html>, Vostok Paleo carbon dioxide and temperature data: <https://cdiac.ess-dive.lbl.gov/trends/co2/vostok.html>.
Author: Hernando Cortina [aut, cre] (<https://orcid.org/0000-0001-6790-4870>)
Maintainer: Hernando Cortina <hch@alum.mit.edu>

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Package diseq updated to version 0.2.1 with previous version 0.1.5 dated 2021-03-02

Title: Estimation Methods for Markets in Equilibrium and Disequilibrium
Description: Provides estimation methods for markets in equilibrium and disequilibrium. Supports the estimation of an equilibrium and four disequilibrium models with both correlated and independent shocks. Also provides post-estimation analysis tools, such as aggregation, marginal effect, and shortage 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>. Standard errors can be estimated by adjusting for heteroscedasticity or clustering. The equilibrium estimation constitutes a case of a system of linear, simultaneous equations. Instead, the disequilibrium models replace the market-clearing condition with a non-linear, 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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New package lookup with initial version 1.0
Package: lookup
Title: Functions Similar to VLOOKUP in Excel
Version: 1.0
Authors@R: person("Kevin","Wright", email="kw.stat@gmail.com", comment=c(ORCID = "0000-0002-0617-8673"), role=c("aut","cre"))
Description: Simple functions to lookup items in key-value pairs. See Mehta (2021) <doi:10.1007/978-1-4842-6613-7_6>.
URL: https://kwstat.github.io/lookup/
BugReports: https://github.com/kwstat/lookup/issues
License: MIT + file LICENSE
Language: en-US
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-12 18:54:06 UTC; wrightkevi
Author: Kevin Wright [aut, cre] (<https://orcid.org/0000-0002-0617-8673>)
Maintainer: Kevin Wright <kw.stat@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-14 09:20:03 UTC

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Package itraxR updated to version 1.2 with previous version 1.1 dated 2021-03-01

Title: Itrax Data Analysis Tools
Description: Parse, trim, join, visualise and analyse data from Itrax sediment core multi-parameter scanners manufactured by Cox Analytical Systems, Sweden. Functions are provided for parsing XRF-peak area files, line-scan optical images, and radiographic images, alongside accompanying metadata. A variety of data wrangling tasks like trimming, joining and reducing XRF-peak area data are simplified. Principle component analysis (PCA), cluster analysis and associated multivariate methods are implemented with appropriate data transformation.
Author: Thomas Bishop
Maintainer: Thomas Bishop <tombishopemail@gmail.com>

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New package codename with initial version 0.1.0
Package: codename
Title: Generation of Code Names for Organizations, People, Projects, and Whatever Else
Version: 0.1.0
Depends: R (>= 3.5.0)
Authors@R: person("Steve", "Miller", email = "steven.v.miller@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4072-6263"))
Maintainer: Steve Miller <steven.v.miller@gmail.com>
Description: This creates code names that a user can consider for their organizations, their projects, themselves, people in their organizations or projects, or whatever else. The user can also supply a numeric seed (and even a character seed) for maximum reproducibility. Use is simple and the code names produced come in various types too, contingent on what the user may be desiring as a code name or nickname.
License: GPL-2
Encoding: UTF-8
LazyData: true
Suggests: tibble
URL: https://github.com/svmiller/codename
BugReports: https://github.com/svmiller/codename/issues/
NeedsCompilation: no
Packaged: 2021-04-12 14:45:54 UTC; steve
Author: Steve Miller [aut, cre] (<https://orcid.org/0000-0003-4072-6263>)
Repository: CRAN
Date/Publication: 2021-04-14 09:00:02 UTC

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Package treasuryTR updated to version 0.1.2 with previous version 0.1.1 dated 2021-03-11

Title: Generate Treasury Total Returns from Yield Data
Description: Generate Total Returns (TR) from bond yield data with fixed maturity, e.g. reported treasury yields. The generated TR series are very close to alternative series that can be purchased (e.g. CRSP, Bloomberg), suggesting they are a high-quality alternative for those, see Swinkels (2019) <doi:10.3390/data4030091>.
Author: Martin Geissmann [aut, cre]
Maintainer: Martin Geissmann <mg@econovo.ch>

Diff between treasuryTR versions 0.1.1 dated 2021-03-11 and 0.1.2 dated 2021-04-14

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Package rBiasCorrection updated to version 0.2.9 with previous version 0.2.8 dated 2021-03-28

Title: Correct Bias in DNA Methylation Analyses
Description: Implementation of the algorithms (with minor modifications) to correct bias in quantitative DNA methylation analyses as described by Moskalev et al. (2011) <doi:10.1093/nar/gkr213>.
Author: Lorenz A. Kapsner [cre, aut, cph] (<https://orcid.org/0000-0003-1866-860X>), Evgeny A. Moskalev [aut]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>

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Package pkgcache updated to version 1.2.1 with previous version 1.2.0 dated 2021-03-01

Title: Cache 'CRAN'-Like Metadata and R Packages
Description: Metadata and package cache for CRAN-like repositories. This is a utility package to be used by package management tools that want to take advantage of caching.
Author: Gábor Csárdi [aut, cre]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between pkgcache versions 1.2.0 dated 2021-03-01 and 1.2.1 dated 2021-04-14

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Package Rinstapkg (with last version 0.1.0) was removed from CRAN

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

2019-06-08 0.1.0

Permanent link
Package wordpressr (with last version 0.2.1) was removed from CRAN

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

2021-02-11 0.2.1
2021-01-04 0.2.0
2020-09-29 0.1.1

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Package r5r (with last version 0.3-3) was removed from CRAN

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

2021-03-09 0.3-3
2021-01-08 0.3-2
2021-01-07 0.3-1
2021-01-05 0.3-0
2020-11-30 0.2-1
2020-10-20 0.2-0

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Package SpatialKWD (with last version 0.3.0) was removed from CRAN

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

2021-03-31 0.3.0

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Package robcp (with last version 0.3.0) was removed from CRAN

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

2021-03-30 0.3.0
2020-01-24 0.2.5
2019-06-03 0.2.4

Permanent link
Package fairmodels updated to version 1.0.1 with previous version 0.2.4 dated 2020-12-12

Title: Flexible Tool for Bias Detection, Visualization, and Mitigation
Description: Measure fairness metrics in one place for many models. Check how big is model's bias towards different races, sex, nationalities etc. Use measures such as Statistical Parity, Equal odds to detect the discrimination against unprivileged groups. Visualize the bias using heatmap, radar plot, biplot, bar chart (and more!). There are various pre-processing and post-processing bias mitigation algorithms implemented. Find more details in (Wiśniewski, Biecek (2021)) <arXiv:2104.00507>.
Author: Jakub Wiśniewski [aut, cre], Przemysław Biecek [aut] (<https://orcid.org/0000-0001-8423-1823>)
Maintainer: Jakub Wiśniewski <jakwisn@gmail.com>

Diff between fairmodels versions 0.2.4 dated 2020-12-12 and 1.0.1 dated 2021-04-14

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Package dataverse updated to version 0.3.8 with previous version 0.3.7 dated 2021-03-08

Title: Client for Dataverse 4+ Repositories
Description: Provides access to Dataverse APIs <https://dataverse.org/> (versions 4-5), enabling data search, retrieval, and deposit. For Dataverse versions <= 3.0, use the archived 'dvn' package <https://cran.r-project.org/package=dvn>.
Author: Will Beasley [aut, cre] (<https://orcid.org/0000-0002-5613-5006>), Thomas J. Leeper [aut] (<https://orcid.org/0000-0003-4097-6326>), Shiro Kuriwaki [aut] (<https://orcid.org/0000-0002-5687-2647>), Philip Durbin [aut] (<https://orcid.org/0000-0002-9528-9470>), Sebastian Karcher [aut] (<https://orcid.org/0000-0001-8249-7388>), Jan Kanis [ctb], Edward Jee [ctb]
Maintainer: Will Beasley <wibeasley@hotmail.com>

Diff between dataverse versions 0.3.7 dated 2021-03-08 and 0.3.8 dated 2021-04-14

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Package prepplot updated to version 1.0 with previous version 0.7 dated 2018-04-05

Title: Prepare Figure Region for Base Graphics
Description: A figure region is prepared, creating a plot region with suitable background color, grid lines or shadings, and providing axes and labeling if not suppressed. Subsequently, information carrying graphics elements can be added (points, lines, barplot with add=TRUE and so forth).
Author: Ulrike Groemping
Maintainer: Ulrike Groemping <groemping@beuth-hochschule.de>

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