Wed, 17 Feb 2021

Package SentimentAnalysis updated to version 1.3-4 with previous version 1.3-3 dated 2019-03-26

Title: Dictionary-Based Sentiment Analysis
Description: Performs a sentiment analysis of textual contents in R. This implementation utilizes various existing dictionaries, such as Harvard IV, or finance-specific dictionaries. Furthermore, it can also create customized dictionaries. The latter uses LASSO regularization as a statistical approach to select relevant terms based on an exogenous response variable.
Author: Nicolas Proellochs [aut, cre], Stefan Feuerriegel [aut]
Maintainer: Nicolas Proellochs <nicolas@nproellochs.com>

Diff between SentimentAnalysis versions 1.3-3 dated 2019-03-26 and 1.3-4 dated 2021-02-17

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 35 files changed, 825 insertions(+), 623 deletions(-)

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New package sta with initial version 0.1.5
Package: sta
Version: 0.1.5
Date: 2021-01-20
Title: Seasonal Trend Analysis for Time Series Imagery in R
Authors@R: person("Inder", "Tecuapetla-Gomez", email = "itecuapetla@conabio.gob.mx", role = c("aut", "cre"))
Author: Inder Tecuapetla-Gomez [aut, cre]
Maintainer: Inder Tecuapetla-Gomez <itecuapetla@conabio.gob.mx>
Description: Efficiently estimate shape parameters of periodic time series imagery (raster stacks) with which a statistical seasonal trend analysis (STA) is subsequently performed. STA output can be exported in conventional raster formats. Methods to visualize STA output are also implemented as well as the calculation of additional basic statistics. STA is based on (R. Eastman, F. Sangermano, B. Ghimire, H. Zhu, H. Chen, N. Neeti, Y. Cai, E. Machado and S. Crema, 2009) <doi:10.1080/01431160902755338>.
LazyData: true
License: GPL (>= 2)
Encoding: UTF-8
Depends: raster (>= 2.9-5), R (>= 3.5.0), geoTS (>= 0.1.1), foreach (>= 1.4.4), parallel (>= 3.6.1)
Suggests: sp (>= 1.2-0), grDevices
Imports: methods, trend (>= 1.1.1), doParallel (>= 1.0.14), iterators (>= 1.0.10), mapview (>= 2.7.0), RColorBrewer (>= 1.1-2), rgdal (>= 0.9-1)
NeedsCompilation: no
RoxygenNote: 6.1.1
Packaged: 2021-01-22 02:21:49 UTC; itecuapetla
Repository: CRAN
Date/Publication: 2021-02-17 23:20:02 UTC

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Package specmine.datasets updated to version 0.0.2 with previous version 0.0.1 dated 2020-11-20

Title: Data Sets for 'specmine'
Description: Provides the data sets used to exemplify 'specmine'. The data sets were formerly distributed with 'specmine', however they exceed current CRAN policy for package size.
Author: Christopher Costa <chrisbcl@hotmail.com> [aut], Marcelo Maraschin <mtocsy@gmail.com> [aut], Miguel Rocha <mrocha@di.uminho.pt> [aut, cre], Sara Cardoso <saracardoso501@gmail.com> [aut], Telma Afonso <telma.afonso94@gmail.com> [aut], C. Beleites [cph], Jie Hao [cph], Bruno Pereira <pereirinha_bp@hotmail.com> [aut]
Maintainer: Miguel Rocha <mrocha@di.uminho.pt>

Diff between specmine.datasets versions 0.0.1 dated 2020-11-20 and 0.0.2 dated 2021-02-17

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New package sentometrics with initial version 0.8.3
Package: sentometrics
Type: Package
Title: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
Version: 0.8.3
Authors@R: c(person("Samuel", "Borms", email = "borms_sam@hotmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9533-1870")), person("David", "Ardia", email = "david.ardia@hec.ca", role = c("aut"), comment = c(ORCID = "0000-0003-2823-782X")), person("Keven", "Bluteau", email = "keven.bluteau@unine.ch", role = c("aut"), comment = c(ORCID = "0000-0003-2990-4807")), person("Kris", "Boudt", email = "kris.boudt@vub.be", role = c("aut"), comment = c(ORCID = "0000-0002-1000-5142")), person("Jeroen", "Van Pelt", email = "jeroenvanpelt@hotmail.com", role = c("ctb")), person("Andres", "Algaba", email = "andres.algaba@vub.be", role = c("ctb")))
Maintainer: Samuel Borms <borms_sam@hotmail.com>
Description: Optimized prediction based on textual sentiment, accounting for the intrinsic challenge that sentiment can be computed and pooled across texts and time in various ways. See Ardia et al. (2020) <doi:10.2139/ssrn.3067734>.
Depends: R (>= 3.3.0)
License: GPL (>= 2)
BugReports: https://github.com/SentometricsResearch/sentometrics/issues
URL: https://sentometrics-research.com/sentometrics/
Encoding: UTF-8
LazyData: true
Suggests: covr, doParallel, e1071, NLP, parallel, randomForest, testthat, tm
Imports: caret, compiler, data.table, foreach, ggplot2, glmnet, ISOweek, quanteda, Rcpp (>= 0.12.13), RcppRoll, RcppParallel, stats, stringi, utils
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
RoxygenNote: 7.1.1
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2021-02-17 18:19:16 UTC; saborms
Author: Samuel Borms [aut, cre] (<https://orcid.org/0000-0001-9533-1870>), David Ardia [aut] (<https://orcid.org/0000-0003-2823-782X>), Keven Bluteau [aut] (<https://orcid.org/0000-0003-2990-4807>), Kris Boudt [aut] (<https://orcid.org/0000-0002-1000-5142>), Jeroen Van Pelt [ctb], Andres Algaba [ctb]
Repository: CRAN
Date/Publication: 2021-02-17 22:50:03 UTC

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Package GGIR updated to version 2.3-0 with previous version 2.2-0 dated 2020-11-22

Title: Raw Accelerometer Data Analysis
Description: A tool to process and analyse data collected with wearable raw acceleration sensors as described in Migueles and colleagues (JMPB 2019), and van Hees and colleagues (JApplPhysiol 2014; PLoSONE 2015). The package has been developed and tested for binary data from 'GENEActiv' <https://www.activinsights.com/> and GENEA devices (not for sale), .csv-export data from 'Actigraph' <https://actigraphcorp.com> devices, and .cwa and .wav-format data from 'Axivity' <https://axivity.com>. These devices are currently widely used in research on human daily physical activity. Further, the package can handle accelerometer data file from any other sensor brand providing that the data is stored in csv format and has either no header or a two column header. Also the package allows for external function embedding.
Author: Vincent T van Hees [aut, cre], Zhou Fang [ctb], Jing Hua Zhao [ctb], Joe Heywood [ctb], Evgeny Mirkes [ctb], Severine Sabia [ctb], Joan Capdevila Pujol [ctb], Jairo H Migueles [ctb], Matthew R Patterson [ctb], Dan Jackson [ctb]
Maintainer: Vincent T van Hees <v.vanhees@accelting.com>

Diff between GGIR versions 2.2-0 dated 2020-11-22 and 2.3-0 dated 2021-02-17

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Package cwbtools updated to version 0.3.2 with previous version 0.3.1 dated 2020-07-21

Title: Tools to Create, Modify and Manage 'CWB' Corpora
Description: The 'Corpus Workbench' ('CWB', <http://cwb.sourceforge.net/>) offers a classic and mature approach for working with large, linguistically and structurally annotated corpora. The 'CWB' is memory efficient and its design makes running queries fast (Evert and Hardie 2011, <http://www.stefan-evert.de/PUB/EvertHardie2011.pdf>). The 'cwbtools' package offers pure R tools to create indexed corpus files as well as high-level wrappers for the original C implementation of CWB as exposed by the 'RcppCWB' package <https://CRAN.R-project.org/package=RcppCWB>. Additional functionality to add and modify annotations of corpora from within R makes working with CWB indexed corpora much more flexible and convenient. The 'cwbtools' package in combination with the R packages 'RcppCWB' (<https://CRAN.R-project.org/package=RcppCWB>) and 'polmineR' (<https://CRAN.R-project.org/package=polmineR>) offers a lightweight infrastructure to support the combination of quantitative and qualitative approaches for working with textual data.
Author: Andreas Blaette [aut, cre], Christoph Leonhardt [ctb]
Maintainer: Andreas Blaette <andreas.blaette@uni-due.de>

Diff between cwbtools versions 0.3.1 dated 2020-07-21 and 0.3.2 dated 2021-02-17

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Package cimir updated to version 0.4-1 with previous version 0.4-0 dated 2020-01-22

Title: Interface to the CIMIS Web API
Description: Connect to the California Irrigation Management Information System (CIMIS) Web API. See the CIMIS main page <https://cimis.water.ca.gov> and web API documentation <https://et.water.ca.gov> for more information.
Author: Michael Koohafkan [aut, cre]
Maintainer: Michael Koohafkan <michael.koohafkan@gmail.com>

Diff between cimir versions 0.4-0 dated 2020-01-22 and 0.4-1 dated 2021-02-17

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Package RSmallTelescopes updated to version 1.0.4 with previous version 1.0.3 dated 2021-01-22

Title: Empirical Small Telescopes Analysis
Description: We provide functions to perform an empirical small telescopes analysis. This package contains 2 functions, SmallTelescopes() and EstimatePower(). Users only need to call SmallTelescopes() to conduct the analysis. For more information on small telescopes analysis see Uri Simonsohn (2015) <doi:10.1177/0956797614567341>.
Author: John Ruscio [aut, cre], Samantha Costigan [ctb]
Maintainer: John Ruscio <ruscio@tcnj.edu>

Diff between RSmallTelescopes versions 1.0.3 dated 2021-01-22 and 1.0.4 dated 2021-02-17

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New package ppendemic with initial version 0.1.0
Package: ppendemic
Title: The Red Book of Endemic Plants of Peru
Version: 0.1.0
Authors@R: c(person(given = "Paul Efren", family = "Santos Andrade", role = c("aut", "cre"), email = "paulefrens@gmail.com", comment = c(ORCID = "0000-0002-6635-0375")), person(given = "Lucely L.", family = "Vilca Bustamante", role = "aut", email = "vilca.lu01@gmail.com"))
Date: 2021-02-05
Description: Gives help to access the information from "The Red Book of Endemic Plants of Peru". The package contains a database with cleaned and standardized botanical data including occurrence and taxonomic data. The original source could be found in "León, Blanca, Nigel Pitman, y José Roque. (2006). Introducción a Las Plantas Endémicas Del Perú"<doi:10.15381/rpb.v13i2.1782><https://revistasinvestigacion.unmsm.edu.pe/index.php/rpb/issue/view/153>.
License: MIT + file LICENSE
URL: https://github.com/PaulESantos/ppendemic/
BugReports: https://github.com/PaulESantos/ppendemic/issues
Suggests: knitr, rmarkdown
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0),
Imports: sf, ggplot2, rlang, dplyr
Author: Paul Efren Santos Andrade [aut, cre] (<https://orcid.org/0000-0002-6635-0375>), Lucely L. Vilca Bustamante [aut]
Maintainer: Paul Efren Santos Andrade <paulefrens@gmail.com>
NeedsCompilation: no
Packaged: 2021-02-17 14:03:27 UTC; user
Repository: CRAN
Date/Publication: 2021-02-17 21:10:03 UTC

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New package zoolog with initial version 0.2.1
Package: zoolog
Title: Zooarchaeological Analysis with Log-Ratios
Version: 0.2.1
Date: 2021-2-13
Authors@R: c( person(c("Jose","M"), "Pozo", role = c("aut", "cre"), email = "josmpozo@gmail.com", comment = c(ORCID = "0000-0002-0759-3510")), person("Silvia", "Valenzuela-Lamas", role = c("aut"), email = "svalenzuela@imf.csic.es", comment = c(ORCID = "0000-0001-9886-0372")), person("Angela", "Trentacoste", role = c("aut"), email = "angela.trentacoste@arch.ox.ac.uk", comment = c(ORCID = "0000-0001-7096-5252")), person("Ariadna", "Nieto-Espinet", role = c("aut"), email = "arinietoespinet@gmail.com", comment = c(ORCID = "0000-0003-2567-1735")), person("Silvia", "Guimarães Chiarelli", role = c("aut"), email = "biguimaraes@hotmail.com", comment = c(ORCID = "0000-0002-3778-3315")))
Description: Includes functions and reference data to generate and manipulate log-ratios (also known as log size index (LSI) values) from measurements obtained on zooarchaeological material. Log ratios are used to compare the relative (rather than the absolute) dimensions of animals from archaeological contexts (Meadow 1999, ISBN: 9783896463883). zoolog is also able to seamlessly integrate data and references with heterogeneous nomenclature, which is internally managed by a zoolog thesaurus. A preliminary version of the zoolog methods was first used by Trentacoste, Nieto-Espinet, and Valenzuela-Lamas (2018) <doi:10.1371/journal.pone.0208109>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, knitr, rmarkdown, ggplot2, stats
Depends: R (>= 3.0)
Imports: utils, stringi, Rdpack (>= 0.7)
RdMacros: Rdpack
VignetteBuilder: knitr
URL: https://josempozo.github.io/zoolog/
NeedsCompilation: no
Packaged: 2021-02-17 12:56:17 UTC; jose
Author: Jose M Pozo [aut, cre] (<https://orcid.org/0000-0002-0759-3510>), Silvia Valenzuela-Lamas [aut] (<https://orcid.org/0000-0001-9886-0372>), Angela Trentacoste [aut] (<https://orcid.org/0000-0001-7096-5252>), Ariadna Nieto-Espinet [aut] (<https://orcid.org/0000-0003-2567-1735>), Silvia Guimarães Chiarelli [aut] (<https://orcid.org/0000-0002-3778-3315>)
Maintainer: Jose M Pozo <josmpozo@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-17 20:50:02 UTC

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New package truthiness with initial version 1.2.4
Package: truthiness
Title: Illusory Truth Longitudinal Study
Version: 1.2.4
Date: 2021-02-17
Authors@R: c( person(given = "Dale", family = "Barr", role = c("aut", "cre"), email = "dalejbarr@protonmail.com"), person(given = "Emma", family = "Henderson", role = c("ctb"), email = "emmahenderson2011@gmail.com"))
URL: https://github.com/dalejbarr/truthiness
Description: Data and functions for analyzing and simulating illusory truth datasets, developed as part of a longitudinal study by Henderson, Barr, and Simons (2020). The illusory truth effect is the observation that people rate repeated statements as more likely to be true than novel statements. We tested the trajectory of the illusory truth effect by collecting truth ratings for statements repeated across four time intervals: immediately, one day, one week, and one month following initial presentation. The package contains the anonymized data from the study along with stimulus materials, as well as functions for analyzing the data, running simulations, and calculating power. Further details about the project are available at <https://osf.io/nvugt/>, which includes Stage 1 of the Registered Report at the Journal of Cognition (<https://osf.io/vqnx2/>).
License: CC BY 4.0
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: ordinal, magrittr, dplyr, MASS, tibble, tidyr, stats, lme4, readr, purrr, rmarkdown, emmeans, DT, Rdpack, ggplot2, forcats, ez
RdMacros: Rdpack
RoxygenNote: 7.1.1
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2021-02-17 11:50:23 UTC; dalebarr
Author: Dale Barr [aut, cre], Emma Henderson [ctb]
Maintainer: Dale Barr <dalejbarr@protonmail.com>
Repository: CRAN
Date/Publication: 2021-02-17 20:40:02 UTC

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New package quarks with initial version 1.0.0
Type: Package
Package: quarks
Title: Simple Methods for Calculating Value at Risk and Expected Shortfall
Version: 1.0.0
Authors@R: person(given = "Sebastian", family = "Letmathe", role = c("aut", "cre"), email = "sebastian.letmathe@uni-paderborn.de", comment = "Paderborn University, Germany")
Description: Enables the user to calculate Value at Risk (VaR) and Expected Shortfall (ES) by means of various types of historical simulation. Currently plain historical simulation as well as age- and volatility-weighted historical simulation are implemented in this package. Volatility weighting is carried out via an exponentially weighted moving average (EWMA). The methods of the package are described in Gurrola-Perez, P. and Murphy, D. (2015) <https://EconPapers.repec.org/RePEc:boe:boeewp:0525>.
License: GPL-3
Depends: R (>= 2.10)
Imports: graphics, stats
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-17 12:01:38 UTC; Letmode
Author: Sebastian Letmathe [aut, cre] (Paderborn University, Germany)
Maintainer: Sebastian Letmathe <sebastian.letmathe@uni-paderborn.de>
Repository: CRAN
Date/Publication: 2021-02-17 20:30:02 UTC

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New package MonoPhy with initial version 1.3
Package: MonoPhy
Type: Package
Title: Explore Monophyly of Taxonomic Groups in a Phylogeny
Version: 1.3
Date: 2021-02-15
Authors@R: c(person("Orlando", "Schwery", role=c("aut", "cre"), email="oschwery@vols.utk.edu"), person("Brian C.", "O'Meara", role=c("aut", "ctb")), person("Peter", "Cowman", role=c("ctb")))
Depends: ape, phytools, phangorn, RColorBrewer, taxize
Description: Requires rooted phylogeny as input and creates a table of genera, their monophyly-status, which taxa cause problems in monophyly etc. Different information can be extracted from the output and a plot function allows visualization of the results in a number of ways. "MonoPhy: a simple R package to find and visualize monophyly issues." Schwery, O. & O'Meara, B.C. (2016) <doi:10.7717/peerj-cs.56>.
License: GPL-3
Suggests: knitr, testthat, paleotree, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-17 08:44:30 UTC; oschwery
Author: Orlando Schwery [aut, cre], Brian C. O'Meara [aut, ctb], Peter Cowman [ctb]
Maintainer: Orlando Schwery <oschwery@vols.utk.edu>
Repository: CRAN
Date/Publication: 2021-02-17 20:10:03 UTC

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New package lingmatch with initial version 1.0.0
Package: lingmatch
Type: Package
Title: Linguistic Matching and Accommodation
Version: 1.0.0
Author: Micah Iserman
Maintainer: Micah Iserman <micah.iserman@gmail.com>
Description: Measure similarity between texts. Offers a variety of processing tools and similarity metrics to facilitate flexible representation of texts and matching. Implements forms of Language Style Matching (Ireland & Pennebaker, 2010) <doi:10.1037/a0020386> and Latent Semantic Analysis (Landauer & Dumais, 1997) <doi:10.1037/0033-295X.104.2.211>.
URL: https://github.com/miserman/lingmatch
BugReports: https://github.com/miserman/lingmatch/issues
Depends: R (>= 3.5), methods, Matrix
Imports: Rcpp, RcppParallel
License: GPL (>= 2)
LazyData: TRUE
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, splot, testthat (>= 2.1.0)
LinkingTo: Rcpp, RcppParallel
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2021-02-17 11:48:26 UTC; Admin
Repository: CRAN
Date/Publication: 2021-02-17 20:30:05 UTC

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New package IPLGP with initial version 0.1.0
Package: IPLGP
Type: Package
Title: Identification of Parental Lines via Genomic Prediction
Version: 0.1.0
Authors@R: c( person("Ping-Yuan", "Chung", email = "r06621204@ntu.edu.tw", role = "cre"), person("Chen-Tuo", "Liao", email = "ctliao@ntu.edu.tw", role = "aut"))
Description: Combining genomic prediction with Monte Carlo simulation, three different strategies are implemented to select parental lines for multiple traits in plant breeding. The selection strategies include (i) GEBV-O considers only genomic estimated breeding values (GEBVs) of the candidate individuals; (ii) GD-O considers only genomic diversity (GD) of the candidate individuals; and (iii) GEBV-GD considers both GEBV and GD. The above method can be seen in Chung PY, Liao CT (2020) <doi:10.1371/journal.pone.0243159>. Multi-trait genomic best linear unbiased prediction (MT-GBLUP) model is used to simultaneously estimate GEBVs of the target traits, and then a selection index is adopted to evaluate the composite performance of an individual.
Imports: ggplot2, sommer, grDevices, stats
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-17 09:22:21 UTC; pingyuan
Author: Ping-Yuan Chung [cre], Chen-Tuo Liao [aut]
Maintainer: Ping-Yuan Chung <r06621204@ntu.edu.tw>
Repository: CRAN
Date/Publication: 2021-02-17 20:20:06 UTC

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New package gpboost with initial version 0.4.0
Package: gpboost
Type: Package
Title: Combining Tree-Boosting with Gaussian Process and Mixed Effects Models
Version: 0.4.0
Date: 2021-02-17
Authors@R: c( person("Fabio", "Sigrist", email = "fabiosigrist@gmail.com", role = c("aut", "cre")), person("Benoit", "Jacob", role = c("cph")), person("Gael", "Guennebaud", role = c("cph")), person("Nicolas", "Carre", role = c("cph")), person("Pierre", "Zoppitelli", role = c("cph")), person("Gauthier", "Brun", role = c("cph")), person("Jean", "Ceccato", role = c("cph")), person("Jitse", "Niesen", role = c("cph")), person("Other authors of Eigen for the included version of Eigen", role = c("ctb","cph")), person("Timothy A.", "Davis", role = c("cph")), person("Guolin", "Ke", role = c("ctb")), person("Damien", "Soukhavong", role = c("ctb")), person("James", "Lamb", role = c("ctb")), person("Other authors of LightGBM for the included version of LightGBM", role = c("ctb")), person("Microsoft Corporation", role = c("cph")), person("Dropbox, Inc.", role = c("cph")), person("Jay", "Loden", role = c("cph")), person("Dave", "Daeschler", role = c("cph")), person("Giampaolo", "Rodola", role = c("cph")), person("Alberto", "Ferreira", role = c("ctb")), person("Daniel", "Lemire", role = c("ctb")), person("Victor", "Zverovich", role = c("cph")), person("IBM Corporation", role = c("ctb")) )
Description: An R package that allows for combining tree-boosting with Gaussian process and mixed effects models. It also allows for independently doing tree-boosting as well as inference and prediction for Gaussian process and mixed effects models. See <https://github.com/fabsig/GPBoost> for more information on the software and Sigrist (2020) <arXiv:2004.02653> for more information on the methodology.
Encoding: UTF-8
License: Apache License (== 2.0) | file LICENSE
URL: https://github.com/fabsig/GPBoost
BugReports: https://github.com/fabsig/GPBoost/issues
NeedsCompilation: yes
Biarch: true
Suggests: testthat
Depends: R (>= 3.5), R6 (>= 2.0)
Imports: data.table (>= 1.9.6), graphics, RJSONIO, Matrix (>= 1.1-0), methods, utils
SystemRequirements: C++11
RoxygenNote: 6.0.1
Packaged: 2021-02-17 10:41:54 UTC; whsigris
Author: Fabio Sigrist [aut, cre], Benoit Jacob [cph], Gael Guennebaud [cph], Nicolas Carre [cph], Pierre Zoppitelli [cph], Gauthier Brun [cph], Jean Ceccato [cph], Jitse Niesen [cph], Other authors of Eigen for the included version of Eigen [ctb, cph], Timothy A. Davis [cph], Guolin Ke [ctb], Damien Soukhavong [ctb], James Lamb [ctb], Other authors of LightGBM for the included version of LightGBM [ctb], Microsoft Corporation [cph], Dropbox, Inc. [cph], Jay Loden [cph], Dave Daeschler [cph], Giampaolo Rodola [cph], Alberto Ferreira [ctb], Daniel Lemire [ctb], Victor Zverovich [cph], IBM Corporation [ctb]
Maintainer: Fabio Sigrist <fabiosigrist@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-17 20:20:02 UTC

More information about gpboost at CRAN
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Package genpathmox updated to version 0.6 with previous version 0.5 dated 2020-11-16

Title: Generalized Pathmox Approach Segmentation Tree Analysis
Description: It provides an interesting solution for handling a high number of segmentation variables in partial least squares structural equation modeling. The package implements the "Pathmox" algorithm (Lamberti, Sanchez, and Aluja,(2016)<doi:10.1002/asmb.2168>) including the F-coefficient test (Lamberti, Sanchez, and Aluja,(2017)<doi:10.1002/asmb.2270>) to detect the path coefficients responsible for the identified differences), the hybrid multi-group approach (Lamberti (2021) <doi:10.1007/s11135-021-01096-9>) and the classical multi-group approaches (parametric and permutation approaches). The package also includes an extension of the "Pathmox" algorithm to the case of linear regression models.
Author: Giuseppe Lamberti [aut, cre]
Maintainer: Giuseppe Lamberti <giuseppelamb@hotmail.com>

Diff between genpathmox versions 0.5 dated 2020-11-16 and 0.6 dated 2021-02-17

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 117 files changed, 1115 insertions(+), 1189 deletions(-)

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Package bkmrhat updated to version 1.0.2 with previous version 1.0.1 dated 2021-01-26

Title: Parallel Chain Tools for Bayesian Kernel Machine Regression
Description: Bayesian kernel machine regression (from the 'bkmr' package) is a Bayesian semi-parametric generalized linear model approach under identity and probit links. There are a number of functions in this package that extend Bayesian kernel machine regression fits to allow multiple-chain inference and diagnostics, which leverage functions from the 'future', 'rstan', and 'coda' packages. Reference: Bobb, J. F., Henn, B. C., Valeri, L., & Coull, B. A. (2018). Statistical software for analyzing the health effects of multiple concurrent exposures via Bayesian kernel machine regression. ; <doi:10.1186/s12940-018-0413-y>.
Author: Alexander Keil [aut, cre]
Maintainer: Alexander Keil <akeil@unc.edu>

Diff between bkmrhat versions 1.0.1 dated 2021-01-26 and 1.0.2 dated 2021-02-17

 DESCRIPTION                    |    8 
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 13 files changed, 353 insertions(+), 325 deletions(-)

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New package xutils with initial version 0.0.1
Package: xutils
Title: Utility Functions of Fangzhou Xie
Version: 0.0.1
Authors@R: person(given = "Fangzhou", family = "Xie", role = c("aut", "cre"), email = "fangzhou.xie@rutgers.edu", comment = c(ORCID = "https://orcid.org/0000-0001-7702-093X"))
Description: This is a collection of some useful functions when dealing with text data. Currently it only contains a very efficient function of decoding HTML entities in character vectors by Rcpp routine.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/fangzhou-xie/xutils
BugReports: https://github.com/fangzhou-xie/xutils/issues
LinkingTo: Rcpp
Imports: Rcpp
Suggests: knitr, rmarkdown, textutils, bench, xml2
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-02-17 03:12:17 UTC; xiefangzhou
Author: Fangzhou Xie [aut, cre] (<https://orcid.org/0000-0001-7702-093X>)
Maintainer: Fangzhou Xie <fangzhou.xie@rutgers.edu>
Repository: CRAN
Date/Publication: 2021-02-17 19:50:02 UTC

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New package uni.survival.tree with initial version 1.3
Package: uni.survival.tree
Type: Package
Title: A Survival Tree Based on Stabilized Score Tests
Version: 1.3
Author: Takeshi Emura and Wei-Chern Hsu
Maintainer: Takeshi Emura <takeshiemura@gmail.com>
Description: A classification (decision) tree is constructed from survival data. The method is a robust version of the logrank tree, where the variance is stabilized. This function returns a classification tree for a given survival dataset. The decision of making inner nodes (splitting criterion) is based on the univariate score tests. The decision of declaring terminal nodes (stopping criterion) is the P-value threshold given by an argument. This tree construction algorithm is proposed by Emura et al. (2021, in review).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: survival,compound.Cox
NeedsCompilation: no
Packaged: 2021-02-17 00:39:25 UTC; biouser
Repository: CRAN
Date/Publication: 2021-02-17 19:50:05 UTC

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New package spacefillr with initial version 0.1.0
Package: spacefillr
Type: Package
Title: Space-Filling Random and Quasi-Random Sequences
Version: 0.1.0
Authors@R: c(person("Tyler", "Morgan-Wall", email = "tylermw@gmail.com", role = c("aut", "cph", "cre"), comment = c(ORCID = "0000-0002-3131-3814")), person("Andrew", "Helmer", role = c("ctb", "cph")), person("Leonhard", "Grünschloß", role = c("ctb", "cph")))
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>
Description: Generates random and quasi-random space-filling sequences. Supports the following sequences: 'Halton', 'Sobol', 'Owen'-scrambled 'Sobol', progressive jittered, progressive multi-jittered ('PMJ'), 'PMJ' with blue noise, 'PMJ02', and 'PMJ02' with blue noise. Includes a 'C++' 'API'. Methods derived from "Constructing Sobol sequences with better two-dimensional projections" (2012) <doi:10.1137/070709359> S. Joe and F. Y. Kuo, and "Progressive Multi-Jittered Sample Sequences" (2018) <https://graphics.pixar.com/library/ProgressiveMultiJitteredSampling/paper.pdf> Christensen, P., Kensler, A. and Kilpatrick, C.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/tylermorganwall/spacefillr
BugReports: https://github.com/tylermorganwall/spacefillr/issues
SystemRequirements: C++14
NeedsCompilation: yes
Packaged: 2021-02-17 00:22:00 UTC; tyler
Author: Tyler Morgan-Wall [aut, cph, cre] (<https://orcid.org/0000-0002-3131-3814>), Andrew Helmer [ctb, cph], Leonhard Grünschloß [ctb, cph]
Repository: CRAN
Date/Publication: 2021-02-17 19:40:03 UTC

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New package provDebugR with initial version 1.0
Package: provDebugR
Title: A Time-Travelling Debugger
Version: 1.0
Date: 2021-02-16
Authors@R: c( person("Orenna", "Brand", email = "o.brand@columbia.edu", role = "aut"), person("Elizabeth", "Fong", email = "fong22e@mtholyoke.edu", role = "aut"), person("Barbara", "Lerner", email = "blerner@mtholyoke.edu", role = "cre"), person("Rose", "Sheehan", email = "sheeh22r@mtholyoke.edu", role = "aut"), person("Joseph", "Wonsil", email = "jwonsil@carthage.edu", role = "aut"), person("Emery", "Boose", email = "boose@fas.harvard.edu", role = "aut") )
Description: Uses provenance post-execution to help the user understand and debug their script by providing functions to look at intermediate steps and data values, their forwards and backwards lineage, and to understand the steps leading up to warning and error messages. 'provDebugR' uses provenance produced by 'rdtLite' (available on CRAN), stored in PROV-JSON format.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: httr, jsonlite, provGraphR, provParseR, textutils,
Suggests: knitr, rdtLite, rdt, testthat
Additional_repositories: https://end-to-end-provenance.github.io/drat/
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2021-02-16 23:29:16 UTC; blerner
Author: Orenna Brand [aut], Elizabeth Fong [aut], Barbara Lerner [cre], Rose Sheehan [aut], Joseph Wonsil [aut], Emery Boose [aut]
Maintainer: Barbara Lerner <blerner@mtholyoke.edu>
Repository: CRAN
Date/Publication: 2021-02-17 19:40:06 UTC

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New package pharmaRTF with initial version 0.1.2
Package: pharmaRTF
Type: Package
Title: Enhanced RTF Wrapper for Use with Existing Table Packages
Version: 0.1.2
Authors@R: c( person(family = "Miller", given = "Eli", email = "eli.miller@atorusresearch.com", role = "aut", comment = c(ORCID = "0000-0002-2127-9456")), person(family = "Tarasiewicz", given = "Ashley", email = "Ashley.Tarasiewicz@atorusresearch.com", role = "aut"), person(family = "Stackhouse", given = "Michael", email = "mike.stackhouse@atorusresearch.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-6030-723X")), person(given = "Atorus Research LLC", role = "cph") )
Description: Enhanced RTF wrapper written in R for use with existing R tables packages such as 'Huxtable' or 'GT'. This package fills a gap where tables in certain packages can be written out to RTF, but cannot add certain metadata or features to the document that are required/expected in a report for a regulatory submission, such as multiple levels of titles and footnotes, making the document landscape, and controlling properties such as margins.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
BugReports: https://github.com/atorus-research/pharmaRTF/issues
Encoding: UTF-8
LazyData: true
Imports: assertthat (>= 0.2.1), stringr (>= 1.4.0), purrr (>= 0.3.3), huxtable (>= 4.7.1)
Suggests: testthat (>= 2.1.0), dplyr (>= 0.8.4), readr (>= 1.3.1), gt (>= 0.2.0), magrittr (>= 1.5), knitr (>= 1.28), rmarkdown (>= 2.1), readxl (>= 1.3.1), kableExtra (>= 1.1.0), plyr (>= 1.8.5), tidyverse (>= 1.3.0)
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-16 20:36:00 UTC; eli.miller
Author: Eli Miller [aut] (<https://orcid.org/0000-0002-2127-9456>), Ashley Tarasiewicz [aut], Michael Stackhouse [aut, cre] (<https://orcid.org/0000-0001-6030-723X>), Atorus Research LLC [cph]
Maintainer: Michael Stackhouse <mike.stackhouse@atorusresearch.com>
Repository: CRAN
Date/Publication: 2021-02-17 19:20:02 UTC

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New package NAEPirtparams with initial version 1.0.0
Package: NAEPirtparams
Version: 1.0.0
Date: 2021-02-16
Title: IRT Parameters for the National Assessment of Education Progress
Author: Sun-joo Lee [aut, cre], Eric Buehler [aut], Paul Bailey [ctb]
Maintainer: Sun-joo Lee <sjlee@air.org>
Description: This data package contains the Item Response Theory (IRT) parameters for the National Center for Education Statistics (NCES) items used on the National Assessment of Education Progress (NAEP) from 1990 to 2015. The values in these tables are used along with NAEP data to turn student item responses into scores and include information about item difficulty, discrimination, and guessing parameter for 3 parameter logit (3PL) items. Parameters for Generalized Partial Credit Model (GPCM) items are also included. The adjustments table contains the information regarding the treatment of items (e.g., deletion of an item or a collapsing of response categories), when these items did not appear to fit the item response models used to describe the NAEP data. Transformation constants change the score estimates that are obtained from the IRT scaling program to the NAEP reporting metric. Values from the years 2000 - 2013 were taken from the NCES website <https://nces.ed.gov/nationsreportcard/> and values from 1990 - 1998 and 2015 were extracted from their NAEP data files. All subtest names were reduced and homogenized to one word (e.g. "Reading to gain information" became "information"). The various subtest names for univariate transformation constants were all homogenized to "univariate".
License: GPL-2
Depends: R (>= 3.5.0)
NeedsCompilation: no
Encoding: UTF-8
RoxygenNote: 7.1.1
LazyData: true
Packaged: 2021-02-16 20:29:02 UTC; sjlee
Repository: CRAN
Date/Publication: 2021-02-17 19:10:03 UTC

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New package healthyverse with initial version 1.0.0
Package: healthyverse
Title: Easily Install and Load the 'healthyverse'
Version: 1.0.0
Authors@R: c( person("Steven","Sanderson", email = "spsanderson@gmail.com", role = c("aut","cre")), person("Steven Sanderson", role = "cph"))
Description: The 'healthyverse' is a set of packages that work in harmony because they share common data representations and 'API' design. This package is designed to make it easy to install and load multiple 'healthyverse' packages in a single step.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.2)
Suggests: knitr, rmarkdown, roxygen2
VignetteBuilder: knitr
Imports: healthyR, healthyR.data, healthyR.ts, dplyr, purrr, tibble, magrittr, rlang (>= 0.1.2), crayon, rstudioapi, cli
NeedsCompilation: no
Packaged: 2021-02-17 02:51:01 UTC; Steve
Author: Steven Sanderson [aut, cre], Steven Sanderson [cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-17 19:50:08 UTC

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New package CDatanet with initial version 0.0.1
Package: CDatanet
Type: Package
Title: Modeling Count Data with Peer Effects
Version: 0.0.1
Date: 2021-02-08
Authors@R: person("Elysée Aristide", "Houndetoungan", role = c("cre","aut"), email = "ariel92and@gmail.com")
Description: Likelihood-based estimation and data generation from a class of models used to estimate peer effects on count data by controlling for the network endogeneity. This class includes count data models with social interactions (Houndetoungan 2020; <doi:10.2139/ssrn.3721250>), spatial tobit models (Xu and Lee 2015; <doi:10.1016/j.jeconom.2015.05.004>), and spatial linear-in-means models (Lee 2004; <doi:10.1111/j.1468-0262.2004.00558.x>).
License: GPL-3
Encoding: UTF-8
BugReports: https://github.com/ahoundetoungan/CDatanet/issues
URL: https://github.com/ahoundetoungan/CDatanet
LazyData: true
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.0), Formula, formula.tools, ddpcr, Matrix
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
RoxygenNote: 7.1.1
Suggests: ggplot2, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-02-17 04:27:16 UTC; haache
Author: Elysée Aristide Houndetoungan [cre, aut]
Maintainer: Elysée Aristide Houndetoungan <ariel92and@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-17 20:00:03 UTC

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New package slgf with initial version 0.1.0
Package: slgf
Type: Package
Title: Bayesian Model Selection with Suspected Latent Grouping Factors
Version: 0.1.0
Date: 2021-02-15
Author: Thomas A. Metzger and Christopher T. Franck
Maintainer: Thomas A. Metzger <metzger.181@osu.edu>
Description: Implements the Bayesian model selection method with suspected latent grouping factor methodology of Metzger and Franck (2020), <doi:10.1080/00401706.2020.1739561>. SLGF detects latent heteroscedasticity or group-based regression effects based on the levels of a user-specified categorical predictor. We encourage you to review examples in vignette("slgf_vignette", "slgf").
License: GPL (>= 2)
Encoding: UTF-8
Imports: Rdpack, numDeriv, utils
RdMacros: Rdpack
LazyData: true
Depends: R (>= 3.5.0)
Suggests: knitr, captioner, formatR, rcrossref, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-16 17:31:17 UTC; metzger.181
Repository: CRAN
Date/Publication: 2021-02-17 18:50:02 UTC

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New package sharpPen with initial version 1.6
Package: sharpPen
Version: 1.6
Title: Penalized Data Sharpening for Local Polynomial Regression
Authors@R: c(person("W.J.", "Braun", role = c("aut"), email = "john.braun@ubc.ca"), person("D.", "Wang", role = c("aut", "cre"), email = "wdy@mail.ubc.ca"), person("X.J.", "Hu", role = c("ctb"), email = "joan_hu@sfu.ca"))
Author: W.J. Braun [aut], D. Wang [aut, cre], X.J. Hu [ctb]
Maintainer: D. Wang <wdy@mail.ubc.ca>
Depends: KernSmooth, MASS, glmnet, np, Matrix
Description: Functions and data sets for penalized data sharpening. Nonparametric regressions are computed subject to smoothness and other kinds of penalties.
License: Unlimited
NeedsCompilation: yes
Packaged: 2021-02-16 18:44:45 UTC; root
Repository: CRAN
Date/Publication: 2021-02-17 18:50:05 UTC

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Package mob updated to version 0.4 with previous version 0.3 dated 2020-11-02

Title: Monotonic Optimal Binning
Description: Generate the monotonic binning and perform the woe (weight of evidence) transformation for the logistic regression used in the consumer credit scorecard development. The woe transformation is a piecewise transformation that is linear to the log odds. For a numeric variable, all of its monotonic functional transformations will converge to the same woe transformation.
Author: WenSui Liu
Maintainer: WenSui Liu <liuwensui@gmail.com>

Diff between mob versions 0.3 dated 2020-11-02 and 0.4 dated 2021-02-17

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Package LLSR updated to version 0.0.3.1 with previous version 0.0.2.19 dated 2019-03-05

Title: Data Analysis of Liquid-Liquid Systems using R
Description: Originally design to characterise Aqueous Two Phase Systems, LLSR provide a simple way to analyse experimental data and obtain phase diagram parameters, among other properties, systematically. The package will include (every other update) new functions in order to comprise useful tools in liquid-liquid extraction research.
Author: Diego F Coelho <diegofcoelho@gmail.com> [aut, cre], Pedro Vitor Oliveira Menezes <pedrod841@hotmail.com> [dtc], Carla Corina dos Santos Porto <carlacorina@hotmail.com.br> [dtc], Jon George Huddleston <Jonathan.Huddleston@brunel.ac.uk> [rev], Elias Basile Tambourgi <eliastam@feq.unicamp.br> [rev]
Maintainer: Diego F Coelho <diegofcoelho@gmail.com>

Diff between LLSR versions 0.0.2.19 dated 2019-03-05 and 0.0.3.1 dated 2021-02-17

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New package ICBioMark with initial version 0.1.0
Package: ICBioMark
Title: Data-Driven Design of Targeted Gene Panels for Estimating Immunotherapy Biomarkers
Version: 0.1.0
Authors@R: c(person(given = "Jacob R.", family = "Bradley", role = c("aut", "cre"), email = "cobrbradley@gmail.com", comment = c(ORCID = "0000-0003-1616-4969")), person(given = "Timothy I.", family = "Cannings", role = c("aut"), email = "Timothy.cannings@sms.ed.ac.uk", comment = c(ORCID = "0000-0002-2111-4168")))
Description: Implementation of the methodology proposed in 'Data-driven design of targeted gene panels for estimating immunotherapy biomarkers', Bradley and Cannings (2021) <arXiv:2102.04296>. This package allows the user to fit generative models of mutation from an annotated mutation dataset, and then further to produce tunable linear estimators of exome-wide biomarkers. It also contains functions to simulate mutation annotated format (MAF) data, as well as to analyse the output and performance of models.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat (>= 2.1.0)
Imports: stats, utils, glmnet, Matrix, dplyr, purrr, latex2exp, matrixStats, ggplot2, gglasso, PRROC
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-02-16 14:40:33 UTC; s1505825
Author: Jacob R. Bradley [aut, cre] (<https://orcid.org/0000-0003-1616-4969>), Timothy I. Cannings [aut] (<https://orcid.org/0000-0002-2111-4168>)
Maintainer: Jacob R. Bradley <cobrbradley@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-17 18:40:02 UTC

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New package CoxICPen with initial version 1.0.0
Package: CoxICPen
Title: Variable Selection for Cox's Model with Interval-Censored Data
Version: 1.0.0
Authors@R: c(person("Qiwei", "Wu", role = c("aut", "cre"), email = "qw235@mail.missouri.edu"), person("Hui", "Zhao", role = c("aut")), person("Jianguo", "Sun", role = c("aut")))
Maintainer: Qiwei Wu <qw235@mail.missouri.edu>
Imports: foreach
Description: Perform variable selection for Cox regression model with interval-censored data by using the methods proposed in Zhao et al. (2020) and Wu et al. (2020). Can deal with both low-dimensional and high-dimensional data.
License: Apache License (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-16 02:34:22 UTC; micha
Author: Qiwei Wu [aut, cre], Hui Zhao [aut], Jianguo Sun [aut]
Repository: CRAN
Date/Publication: 2021-02-17 18:10:02 UTC

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Package rsample updated to version 0.0.9 with previous version 0.0.8 dated 2020-09-23

Title: General Resampling Infrastructure
Description: Classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).
Author: Julia Silge [aut, cre] (<https://orcid.org/0000-0002-3671-836X>), Fanny Chow [aut], Max Kuhn [aut], Hadley Wickham [aut], RStudio [cph]
Maintainer: Julia Silge <julia.silge@rstudio.com>

Diff between rsample versions 0.0.8 dated 2020-09-23 and 0.0.9 dated 2021-02-17

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Package reproducible updated to version 1.2.6 with previous version 1.2.4 dated 2020-12-07

Title: A Set of Tools that Enhance Reproducibility Beyond Package Management
Description: Collection of high-level, machine- and OS-independent tools for making deeply reproducible and reusable content in R. The two workhorse functions are Cache and prepInputs; these allow for: nested caching, robust to environments, and objects with environments (like functions); and data retrieval and processing in continuous workflow environments. In all cases, efforts are made to make the first and subsequent calls of functions have the same result, but vastly faster at subsequent times by way of checksums and digesting. Several features are still under active development, including cloud storage of cached objects, allowing for sharing between users. Several advanced options are available, see ?reproducibleOptions.
Author: Eliot J B McIntire [aut, cre] (<https://orcid.org/0000-0002-6914-8316>), Alex M Chubaty [aut] (<https://orcid.org/0000-0001-7146-8135>), Tati Micheletti [ctb] (<https://orcid.org/0000-0003-4838-8342>), Ceres Barros [ctb] (<https://orcid.org/0000-0003-4036-977X>), Ian Eddy [ctb] (<https://orcid.org/0000-0001-7397-2116>), 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>

Diff between reproducible versions 1.2.4 dated 2020-12-07 and 1.2.6 dated 2021-02-17

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Package RCzechia updated to version 1.6.6 with previous version 1.6.3 dated 2021-01-07

Title: Spatial Objects of the Czech Republic
Description: Administrative regions and other spatial objects of the Czech Republic.
Author: Jindra Lacko
Maintainer: Jindra Lacko <jindra.lacko@gmail.com>

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Package hesim updated to version 0.5.0 with previous version 0.4.2 dated 2020-12-07

Title: Health Economic Simulation Modeling and Decision Analysis
Description: A modular and computationally efficient R package for parameterizing, simulating, and analyzing health economic simulation models. The package supports cohort discrete time state transition models (Briggs et al. 1998) <doi:10.2165/00019053-199813040-00003>, N-state partitioned survival models (Glasziou et al. 1990) <doi:10.1002/sim.4780091106>, and individual-level continuous time state transition models (Siebert et al. 2012) <doi:10.1016/j.jval.2012.06.014>, encompassing both Markov (time-homogeneous and time-inhomogeneous) and semi-Markov processes. Decision uncertainty from a cost-effectiveness analysis is quantified with standard graphical and tabular summaries of a probabilistic sensitivity analysis (Claxton et al. 2005, Barton et al. 2008) <doi:10.1002/hec.985>, <doi:10.1111/j.1524-4733.2008.00358.x>. Use of C++ and data.table make individual-patient simulation, probabilistic sensitivity analysis, and incorporation of patient heterogeneity fast.
Author: Devin Incerti [aut, cre], Jeroen P. Jansen [aut], R Core Team [ctb] (hesim uses some slightly modified C functions from base R)
Maintainer: Devin Incerti <devin.incerti@gmail.com>

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Package flipr updated to version 0.1.1 with previous version 0.1.0 dated 2021-02-16

Title: Flexible Inference via Permutations in R
Description: A flexible permutation framework for hypothesis testing, ANOVA and regression analysis of complex data.
Author: Alessia Pini [aut], Aymeric Stamm [aut, cre] (<https://orcid.org/0000-0002-8725-3654>), Simone Vantini [aut]
Maintainer: Aymeric Stamm <aymeric.stamm@math.cnrs.fr>

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Package dotwhisker updated to version 0.6.0 with previous version 0.5.0 dated 2018-06-27

Title: Dot-and-Whisker Plots of Regression Results
Description: Quick and easy dot-and-whisker plots of regression results.
Author: Frederick Solt [aut], Yue Hu [aut, cre], Os Keyes [ctb], Ben Bolker [ctb], Stefan Müller [ctb], Thomas Leeper [ctb], Chris Wallace [ctb], Christopher Warshaw [ctb]
Maintainer: Yue Hu <yuehu@tsinghua.edu.cn>

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Package cmsafops updated to version 1.1.0 with previous version 1.0.0 dated 2020-09-17

Title: Tools for CM SAF NetCDF Data
Description: The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (<http://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The 'cmsafops' R-package provides a collection of R-operators for the analysis and manipulation of CM SAF NetCDF formatted data. Other CF conform NetCDF data with time, longitude and latitude dimension should be applicable, but there is no guarantee for an error-free application. CM SAF climate data records are provided for free via (<https://wui.cmsaf.eu/safira>). Detailed information and test data are provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox>).
Author: Steffen Kothe [aut, cre]
Maintainer: Steffen Kothe <Steffen.Kothe@dwd.de>

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More information about cmsafops at CRAN
Permanent link

New package AWAPer with initial version 0.1.46
Package: AWAPer
Type: Package
Title: Catchment Area Weighted Climate Data Anywhere in Australia
Version: 0.1.46
Authors@R: c( person("Tim", "Peterson", email = "tim.peterson@monash.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1885-0826")), person("Conrad", "Wasko", email = "conrad.wasko@unimelb.edu.au", role = "ctb", comment = c(ORCID = "0000-0002-9166-8289")))
Maintainer: Tim Peterson <tim.peterson@monash.edu>
Description: NetCDF files of the Bureau of Meteorology Australian Water Availability Project daily national climate grids are built and used for the efficient extraction of point and catchment area weighted precipitation, minimum temperature, maximum temperature, vapour pressure, solar radiation and various measures of evapotranspiration. For details on the source climate data see <http://www.bom.gov.au/jsp/awap/>.
Depends: R (>= 3.5)
Imports: Evapotranspiration (>= 1.14), ncdf4, utils, raster, chron, maptools, sp, zoo, methods, xts, stats
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
BugReports: https://github.com/peterson-tim-j/AWAPer/issues
URL: https://github.com/peterson-tim-j/AWAPer
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
SystemRequirements: 7z (Windows only)
NeedsCompilation: no
Packaged: 2021-02-17 02:59:15 UTC; timjp
Author: Tim Peterson [aut, cre] (<https://orcid.org/0000-0002-1885-0826>), Conrad Wasko [ctb] (<https://orcid.org/0000-0002-9166-8289>)
Repository: CRAN
Date/Publication: 2021-02-17 17:40:02 UTC

More information about AWAPer at CRAN
Permanent link

Package descstat updated to version 0.1-2 with previous version 0.1-0 dated 2020-12-08

Title: Tools for Descriptive Statistics
Description: A toolbox for descriptive statistics, based on the computation of frequency and contingency tables. Several statistical functions and plot methods are provided to describe univariate or bivariate distributions of factors, integer series and numerical series either provided as individual values or as bins.
Author: Yves Croissant [aut, cre]
Maintainer: Yves Croissant <yves.croissant@univ-reunion.fr>

Diff between descstat versions 0.1-0 dated 2020-12-08 and 0.1-2 dated 2021-02-17

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More information about descstat at CRAN
Permanent link

Package spNNGP updated to version 0.1.5 with previous version 0.1.4 dated 2020-03-30

Title: Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes
Description: Fits univariate Bayesian spatial regression models for large datasets using Nearest Neighbor Gaussian Processes (NNGP) detailed in Finley, Datta, Banerjee (2020) <arXiv:2001.09111>, and Finley, Datta, Cook, Morton, Andersen, and Banerjee (2019) <doi:10.1080/10618600.2018.1537924> and Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091>.
Author: Andrew Finley [aut, cre], Abhirup Datta [aut], Sudipto Banerjee [aut]
Maintainer: Andrew Finley <finleya@msu.edu>

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Package rkeops updated to version 1.4.2.2 with previous version 1.4.2 dated 2021-02-16

Title: Kernel Operations on GPU or CPU, with Autodiff, without Memory Overflows
Description: The 'KeOps' library lets you compute generic reductions of very large arrays whose entries are given by a mathematical formula with CPU and GPU computing support. It combines a tiled reduction scheme with an automatic differentiation engine. It is perfectly suited to the efficient computation of Kernel dot products and the associated gradients, even when the full kernel matrix does not fit into the GPU memory.
Author: Benjamin Charlier [aut] (<http://imag.umontpellier.fr/~charlier/>), Jean Feydy [aut] (<https://www.math.ens.fr/~feydy/>), Joan A. Glaunès [aut] (<https://www.mi.parisdescartes.fr/~glaunes/>), Ghislain Durif [aut, cre] (<https://gdurif.perso.math.cnrs.fr/>), François-David Collin [ctb] (Development-related consulting and support), Daniel Frey [ctb] (Author of the included C++ library 'sequences')
Maintainer: Ghislain Durif <gd.dev@libertymail.net>

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Package ibb updated to version 0.0.2 with previous version 0.0.1 dated 2020-05-11

Title: R Wrapper for Istanbul Municipality Open Data Portal
Description: Call wrappers for Istanbul Metropolitan Municipality's Open Data Portal (Turkish: İstanbul Büyükşehir Belediyesi Açık Veri Portalı) at <https://data.ibb.gov.tr/en/>.
Author: Berk Orbay [aut, cre], Emrah Er [ctb]
Maintainer: Berk Orbay <orbayb@mef.edu.tr>

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Package dfphase1 updated to version 1.1.3 with previous version 1.1.1 dated 2017-01-13

Title: Phase I Control Charts (with Emphasis on Distribution-Free Methods)
Description: Statistical methods for retrospectively detecting changes in location and/or dispersion of univariate and multivariate variables. Data values are assumed to be independent, can be individual (one observation at each instant of time) or subgrouped (more than one observation at each instant of time). Control limits are computed, often using a permutation approach, so that a prescribed false alarm probability is guaranteed without making any parametric assumptions on the stable (in-control) distribution. See G. Capizzi and G. Masarotto (2018) <doi:10.1007/978-3-319-75295-2> for an introduction to the package.
Author: Giovanna Capizzi and Guido Masarotto
Maintainer: Giovanna Capizzi <giovanna.capizzi@unipd.it>

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Package arsenal updated to version 3.6.2 with previous version 3.6.1 dated 2021-02-06

Title: An Arsenal of 'R' Functions for Large-Scale Statistical Summaries
Description: An Arsenal of 'R' functions for large-scale statistical summaries, which are streamlined to work within the latest reporting tools in 'R' and 'RStudio' and which use formulas and versatile summary statistics for summary tables and models. The primary functions include tableby(), a Table-1-like summary of multiple variable types 'by' the levels of one or more categorical variables; paired(), a Table-1-like summary of multiple variable types paired across two time points; modelsum(), which performs simple model fits on one or more endpoints for many variables (univariate or adjusted for covariates); freqlist(), a powerful frequency table across many categorical variables; comparedf(), a function for comparing data.frames; and write2(), a function to output tables to a document.
Author: Ethan Heinzen [aut, cre], Jason Sinnwell [aut], Elizabeth Atkinson [aut], Tina Gunderson [aut], Gregory Dougherty [aut], Patrick Votruba [ctb], Ryan Lennon [ctb], Andrew Hanson [ctb], Krista Goergen [ctb], Emily Lundt [ctb], Brendan Broderick [ctb], Maddie McCullough [art]
Maintainer: Ethan Heinzen <heinzen.ethan@mayo.edu>

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Package NHSDataDictionaRy updated to version 1.2.1 with previous version 1.2.0 dated 2021-02-02

Title: NHS Data Dictionary Toolset for NHS Lookups
Description: Providing a common set of simplified web scraping tools for working with the NHS Data Dictionary <https://datadictionary.nhs.uk/data_elements_overview.html>. The intended usage is to access the data elements section of the NHS Data Dictionary to access key lookups. The benefits of having it in this package are that the lookups are the live lookups on the website and will not need to be maintained. This package was commissioned by the NHS-R community to provide this consistency of lookups.
Author: Gary Hutson
Maintainer: Gary Hutson <g.hutson@nhs.net>

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Package dang updated to version 0.0.13 with previous version 0.0.12 dated 2020-10-14

Title: 'Dang' Associated New Goodies
Description: A collection of utility functions.
Author: Dirk Eddelbuettel with contributions by Brodie Gaslam, Kevin Denny, Kabira Namit, Colin Gillespie, R Core, Josh Ulrich, and others.
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package gfpop updated to version 1.0.3 with previous version 1.0.2 dated 2020-12-01

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], Daniel Grose [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 fritools updated to version 1.3.0 with previous version 1.2.0 dated 2021-01-27

Title: Utilities for the Forest Research Institute of the State Baden-Wuerttemberg
Description: Miscellaneous utilities, tools and helper functions for finding and searching files on disk, searching for and removing R objects from the workspace. These are utilities for packages <https://CRAN.R-project.org/package=cleanr>, <https://CRAN.R-project.org/package=document>, <https://CRAN.R-project.org/package=fakemake>, <https://CRAN.R-project.org/package=packager> and <https://CRAN.R-project.org/package=rasciidoc>. Does not import or depend on any third party party package, but on core R only (i.e it may depend on packages with priority 'base').
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>

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Package cvms updated to version 1.2.1 with previous version 1.2.0 dated 2020-10-18

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

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Package set6 updated to version 0.2.1 with previous version 0.2.0 dated 2020-11-06

Title: R6 Mathematical Sets Interface
Description: An object-oriented package for mathematical sets, upgrading the current gold-standard {sets}. Many forms of mathematical sets are implemented, including (countably finite) sets, tuples, intervals (countably infinite or uncountable), and fuzzy variants. Wrappers extend functionality by allowing symbolic representations of complex operations on sets, including unions, (cartesian) products, exponentiation, and differences (asymmetric and symmetric).
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>), Franz Kiraly [aut]
Maintainer: Raphael Sonabend <raphael.sonabend.15@ucl.ac.uk>

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Package SAMtool updated to version 1.1.1 with previous version 1.1.0 dated 2021-02-02

Title: Stock Assessment Methods Toolkit
Description: Simulation tools for closed-loop simulation are provided for the 'MSEtool' operating model to inform data-rich fisheries. 'SAMtool' provides a conditioning model, assessment models of varying complexity with standardized reporting, model-based management procedures, and diagnostic tools for evaluating assessments inside closed-loop simulation.
Author: Quang Huynh [aut, cre], Tom Carruthers [aut], Adrian Hordyk [aut]
Maintainer: Quang Huynh <quang@bluematterscience.com>

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Package GWmodel updated to version 2.2-4 with previous version 2.2-3 dated 2021-02-07

Title: Geographically-Weighted Models
Description: Techniques from a particular branch of spatial statistics,termed geographically-weighted (GW) models. GW models suit situations when data are not described well by some global model, but where there are spatial regions where a suitably localised calibration provides a better description. 'GWmodel' includes functions to calibrate: GW summary statistics (Brunsdon et al., 2002)<doi: 10.1016/s0198-9715(01)00009-6>, GW principal components analysis (Harris et al., 2011)<doi: 10.1080/13658816.2011.554838>, GW discriminant analysis (Brunsdon et al., 2007)<doi: 10.1111/j.1538-4632.2007.00709.x> and various forms of GW regression (Brunsdon et al., 1996)<doi: 10.1111/j.1538-4632.1996.tb00936.x>; some of which are provided in basic and robust (outlier resistant) forms.
Author: Binbin Lu[aut], Paul Harris[aut], Martin Charlton[aut], Chris Brunsdon[aut], Tomoki Nakaya[aut], Daisuke Murakami[aut],Isabella Gollini[ctb], Yigong Hu[ctb], Fiona H Evans[ctb]
Maintainer: Binbin Lu <binbinlu@whu.edu.cn>

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Package bigreadr updated to version 0.2.2 with previous version 0.2.0 dated 2019-10-18

Title: Read Large Text Files
Description: Read large text files by splitting them in smaller files. Package 'bigreadr' also provides some convenient wrappers around fread() and fwrite() from package 'data.table'.
Author: Florian Privé [aut, cre]
Maintainer: Florian Privé <florian.prive.21@gmail.com>

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 README.md                              |  110 ++++----
 inst/WORDLIST                          |   16 -
 inst/testdata/cars_with_newline.csv    |  102 ++++----
 inst/testdata/cars_without_newline.csv |  100 ++++----
 man/big_fread1.Rd                      |   64 ++---
 man/big_fread2.Rd                      |   80 +++---
 man/bigreadr-package.Rd                |   50 ++--
 man/cbind_df.Rd                        |   46 +--
 man/fread2.Rd                          |   64 ++---
 man/fwrite2.Rd                         |   64 ++---
 man/nlines.Rd                          |   44 +--
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 man/split_file.Rd                      |   94 +++----
 tests/spelling.R                       |    2 
 tests/testthat.R                       |    8 
 tests/testthat/test-bind.R             |  150 ++++++------
 tests/testthat/test-nlines.R           |   66 ++---
 tests/testthat/test-read.R             |  238 +++++++++----------
 tests/testthat/test-split.R            |  184 +++++++-------
 28 files changed, 1174 insertions(+), 1172 deletions(-)

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Package AzureRMR updated to version 2.4.1 with previous version 2.4.0 dated 2021-01-15

Title: Interface to 'Azure Resource Manager'
Description: A lightweight but powerful R interface to the 'Azure Resource Manager' REST API. The package exposes a comprehensive class framework and related tools for creating, updating and deleting 'Azure' resource groups, resources and templates. While 'AzureRMR' can be used to manage any 'Azure' service, it can also be extended by other packages to provide extra functionality for specific services. Part of the 'AzureR' family of packages.
Author: Hong Ooi [aut, cre], Microsoft [cph]
Maintainer: Hong Ooi <hongooi73@gmail.com>

Diff between AzureRMR versions 2.4.0 dated 2021-01-15 and 2.4.1 dated 2021-02-17

 DESCRIPTION                      |    6 +++---
 MD5                              |   12 ++++++------
 NEWS.md                          |    5 +++++
 R/az_resgroup.R                  |    2 +-
 R/az_resource.R                  |   31 ++++++++++++++++---------------
 tests/testthat/test04_resource.R |   28 ++++++++++++++++++++++++++--
 tests/testthat/test06_rbac.R     |   12 +++++++++---
 7 files changed, 66 insertions(+), 30 deletions(-)

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New package novelforestSG with initial version 1.2.0
Package: novelforestSG
Title: Data for Lai et al. (2021) Appl. Veg. Sci.
Version: 1.2.0
Authors@R: c(person(given = "Hao Ran", family = "Lai", role = c("aut", "cre"), email = "hrlai.ecology@gmail.com", comment = c(ORCID = "0000-0001-6871-0146")), person(given = "Kwek Yan", family = "Chong", role = c("aut"), email = "kwek@nus.edu.sg", comment = c(ORCID = "0000-0003-4754-8957")), person(given = "Alex Thiam Koon", family = "Yee", role = c("aut"), email = "Alex_YEE@nparks.gov.sg", comment = c(ORCID = "0000-0002-6465-0075")), person(given = "Germaine Su Yin", family = "Tan", role = c("ctb"), email = "germaine_1993@hotmail.com"), person(given = "Louise", family = "Neo", role = c("ctb"), email = "neolouise@u.nus.edu"), person(given = "Carmen Yingxin", family = "Kee", role = c("ctb"), email = "carmen.behappy@gmail.com"), person(given = "Hugh Tiang Wah", family = "Tan", role = c("ths"), email = "hughtan@nus.edu.sg"))
Description: The dataset and model used in Lai et al. (2021) Decoupled responses of native and exotic tree diversities to distance from old-growth forest and soil phosphorous in novel secondary forests. Applied Vegetation Science, 24, e12548.
License: CC BY 4.0
URL: https://hrlai.github.io/novelforestSG/, https://github.com/hrlai/novelforestSG, https://doi.org/10.1111/avsc.12548
BugReports: https://github.com/hrlai/novelforestSG/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Suggests: brms (>= 2.10.0), testthat
NeedsCompilation: no
Packaged: 2021-02-15 22:26:46 UTC; haoran
Author: Hao Ran Lai [aut, cre] (<https://orcid.org/0000-0001-6871-0146>), Kwek Yan Chong [aut] (<https://orcid.org/0000-0003-4754-8957>), Alex Thiam Koon Yee [aut] (<https://orcid.org/0000-0002-6465-0075>), Germaine Su Yin Tan [ctb], Louise Neo [ctb], Carmen Yingxin Kee [ctb], Hugh Tiang Wah Tan [ths]
Maintainer: Hao Ran Lai <hrlai.ecology@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-17 10:20:02 UTC

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New package mdgc with initial version 0.1.1
Package: mdgc
Type: Package
Title: Missing Data Imputation Using Gaussian Copulas
Version: 0.1.1
Authors@R: c( person("Benjamin", "Christoffersen", email = "boennecd@gmail.com", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-7182-1346")), person("Alan", "Genz", role = "cph"), person("Frank", "Bretz", role = "cph"), person("Torsten", "Hothorn", role = "cph"), person("R-core", email = "R-core@R-project.org", role = "cph"), person("Ross", "Ihaka", role = "cph"))
Description: Provides functions to impute missing values using Gaussian copulas for mixed data types as described by Christoffersen et al. (2021) <arXiv:2102.02642>. The method is related to Hoff (2007) <doi:10.1214/07-AOAS107> and Zhao and Udell (2019) <arXiv:1910.12845> but differs by making a direct approximation of the log marginal likelihood using an extended version of the Fortran code created by Genz and Bretz (2002) <doi:10.1198/106186002394> in addition to also support multinomial variables.
License: GPL-2
BugReports: https://github.com/boennecd/mdgc/issues
URL: https://github.com/boennecd/mdgc
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
LinkingTo: Rcpp, RcppArmadillo, testthat, BH, psqn
Imports: Rcpp
Suggests: testthat, catdata
SystemRequirements: C++14
NeedsCompilation: yes
Packaged: 2021-02-16 12:19:48 UTC; boennecd
Author: Benjamin Christoffersen [cre, aut] (<https://orcid.org/0000-0002-7182-1346>), Alan Genz [cph], Frank Bretz [cph], Torsten Hothorn [cph], R-core [cph], Ross Ihaka [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-17 10:20:05 UTC

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Package match2C updated to version 1.1.0 with previous version 0.1.0 dated 2020-05-12

Title: Match One Sample using Two Criteria
Description: Multivariate matching in observational studies typically has two goals: 1. to construct treated and control groups that have similar distribution of observed covariates and 2. to produce matched pairs or sets that are homogeneous in a few priority variables. This packages implements a network-flow-based method built around a tripartite graph that can simultaneously achieve both goals. A detailed explanation of the workflow and numerous examples are given in the vignette.
Author: Bo Zhang [aut, cre]
Maintainer: Bo Zhang <bozhan@wharton.upenn.edu>

Diff between match2C versions 0.1.0 dated 2020-05-12 and 1.1.0 dated 2021-02-17

 match2C-0.1.0/match2C/src/try.cpp                             |only
 match2C-1.1.0/match2C/DESCRIPTION                             |   22 ++-
 match2C-1.1.0/match2C/MD5                                     |   56 ++++++----
 match2C-1.1.0/match2C/NAMESPACE                               |   12 +-
 match2C-1.1.0/match2C/R/RcppExports.R                         |    6 -
 match2C-1.1.0/match2C/R/check_balance.R                       |only
 match2C-1.1.0/match2C/R/construct_outcome.R                   |    9 -
 match2C-1.1.0/match2C/R/create_list_from_mat.R                |   32 -----
 match2C-1.1.0/match2C/R/create_list_from_scratch.R            |    8 -
 match2C-1.1.0/match2C/R/create_list_from_scratch_overall.R    |   25 ----
 match2C-1.1.0/match2C/R/dt_Rouse.R                            |    1 
 match2C-1.1.0/match2C/R/match2C-package.R                     |only
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 match2C-1.1.0/match2C/R/match_2C_list.R                       |   32 +----
 match2C-1.1.0/match2C/R/match_2C_mat.R                        |   42 +++----
 match2C-1.1.0/match2C/R/solve_network_flow.R                  |    5 
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 match2C-1.1.0/match2C/man/create_list_from_mat.Rd             |   31 -----
 match2C-1.1.0/match2C/man/create_list_from_scratch.Rd         |    6 -
 match2C-1.1.0/match2C/man/create_list_from_scratch_overall.Rd |   27 ----
 match2C-1.1.0/match2C/man/dt_Rouse.Rd                         |    9 +
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 match2C-1.1.0/match2C/man/revert_dist_list_cpp.Rd             |    4 
 match2C-1.1.0/match2C/man/solve_network_flow.Rd               |    6 -
 match2C-1.1.0/match2C/src/RcppExports.cpp                     |   18 ---
 match2C-1.1.0/match2C/src/init.c                              |only
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 34 files changed, 136 insertions(+), 285 deletions(-)

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New package Ecume with initial version 0.9.0
Package: Ecume
Type: Package
Title: Equality of 2 (or k) Continuous Univariate and Multivariate Distributions
Version: 0.9.0
Authors@R: person("Hector", "Roux de Bezieux", role = c("aut", "cre"), email = "hector.rouxdebezieux@berkeley.edu", comment = c(ORCID = "0000-0002-1489-8339"))
Description: We implement (or re-implements in R) a variety of statistical tools. They are focused on non-parametric two-sample (or k-sample) distribution comparisons in the univariate or multivariate case. See the vignette for more info.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
biocViews: Software, Infrastructure
Imports: stats, spatstat, magrittr, caret, dplyr, e1071, methods, pbapply, kernlab, transport
RoxygenNote: 7.1.1
Suggests: testthat, covr, knitr, rmarkdown
NeedsCompilation: no
Packaged: 2021-02-16 06:46:02 UTC; hector
Author: Hector Roux de Bezieux [aut, cre] (<https://orcid.org/0000-0002-1489-8339>)
Maintainer: Hector Roux de Bezieux <hector.rouxdebezieux@berkeley.edu>
Repository: CRAN
Date/Publication: 2021-02-17 10:30:02 UTC

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New package VSdecomp with initial version 0.1.0
Package: VSdecomp
Title: Variance and Skewness Decomposition
Version: 0.1.0
Authors@R: c( person("Elad", "Guttman", role = c("aut", "cre"), email = "eladguttman@mail.tau.ac.il"), person("Oren", "Danieli", role = "aut"))
Description: Provides decomposition methods for the skewness or the variance of a variable (e.g., wage). By breaking distribution moments into independent components, users can analyze changes in distributions across time or between groups.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: Hmisc, ggplot2, reshape, lfe, rlang
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-02-15 16:57:28 UTC; eladg
Author: Elad Guttman [aut, cre], Oren Danieli [aut]
Maintainer: Elad Guttman <eladguttman@mail.tau.ac.il>
Repository: CRAN
Date/Publication: 2021-02-17 09:50:02 UTC

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Package ROCket updated to version 1.0.1 with previous version 1.0.0 dated 2021-02-11

Title: Simple and Fast ROC Curves
Description: A set of functions for receiver operating characteristic (ROC) curve estimation and area under the curve (AUC) calculation. All functions are designed to work with aggregated data; nevertheless, they can also handle raw samples. In 'ROCket', we distinguish two types of ROC curve representations: 1) parametric curves - the true positive rate (TPR) and the false positive rate (FPR) are functions of a parameter (the score), 2) functions - TPR is a function of FPR. There are several ROC curve estimation methods available. An introduction to the mathematical background of the implemented methods (and much more) can be found in de Zea Bermudez, Gonçalves, Oliveira & Subtil (2014) <https://www.ine.pt/revstat/pdf/rs140101.pdf> and Cai & Pepe (2004) <doi:10.1111/j.0006-341X.2004.00200.x>.
Author: Daniel Lazar [aut, cre]
Maintainer: Daniel Lazar <da-zar@gmx.net>

Diff between ROCket versions 1.0.0 dated 2021-02-11 and 1.0.1 dated 2021-02-17

 DESCRIPTION               |    6 +++---
 MD5                       |   15 +++++++++------
 NAMESPACE                 |    1 +
 R/ROCket.R                |    2 +-
 R/utils.R                 |   18 +++++++++---------
 README.md                 |   27 +++++++++++++--------------
 man/figures               |only
 tests/testthat/test-auc.R |    7 +++++--
 8 files changed, 41 insertions(+), 35 deletions(-)

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New package rKOMICS with initial version 1.0
Package: rKOMICS
Title: Minicircle Sequence Cluster (MSC) Analyses
Version: 1.0
Date: 2021-02-15
Authors@R: c(person("Frederik", "Van den Broeck", role = c("aut"), email = "frederik.vandenbroeck@kuleuven.be"), person("Manon", "Geerts", role = c("aut", "cre"), email = "mgeerts@itg.be") )
Description: It establishes a critical framework to manipulate, explore and extract biologically relevant information from mitochondrial minicircle assemblies in tens to hundreds of samples simultaneously and efficiently. This should facilitate research that aims to develop new molecular markers for identifying species-specific minicircles, or to study the ancestry of parasites for complementary insights into their evolutionary history.
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: ggplot2, ape, circlize, ComplexHeatmap, reshape2, utils, stats, dplyr, factoextra, FactoMineR, ggpubr, magrittr, stringr
Suggests: viridis
biocViews:
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-02-15 10:18:19 UTC; mgeerts
Author: Frederik Van den Broeck [aut], Manon Geerts [aut, cre]
Maintainer: Manon Geerts <mgeerts@itg.be>
Repository: CRAN
Date/Publication: 2021-02-17 09:10:02 UTC

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New package PERMANOVA with initial version 0.1.0
Package: PERMANOVA
Type: Package
Title: Multivariate Analysis of Variance Based on Distances and Permutations
Version: 0.1.0
Author: Laura Vicente-Gonzalez, Jose Luis Vicente-Villardon
Maintainer: Laura Vicente-Gonzalez <laura20vg@usal.es>
Description: Calculates multivariate analysis of variance based on permutations and some associated pictorial representations. The pictorial representation is based on the principal coordinates of the group means. There are some original results that will be published soon.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 4.0.0), Matrix, xtable, MASS, scales, deldir, grDevices, graphics, stats
LazyData: true
NeedsCompilation: no
Packaged: 2021-02-15 10:44:20 UTC; joseluis
Repository: CRAN
Date/Publication: 2021-02-17 09:20:05 UTC

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New package metapack with initial version 0.1.0
Package: metapack
Type: Package
Title: Bayesian Meta-Analysis and Network Meta-Analysis
Version: 0.1.0
Date: 2021-02-06
Authors@R: c( person("Daeyoung", "Lim", email = "daeyoung.lim@uconn.edu", role = c("aut", "cre")), person("Ming-Hui", "Chen", email = "ming-hui.chen@uconn.edu", role = "ctb"), person("Sungduk", "Kim", email = "kims2@mail.nih.gov", role = "ctb"), person("Joseph", "Ibrahim", email = "ibrahim@bios.unc.edu", role = "ctb"), person("Arvind", "Shah", email = "arvind_shah@merck.com", role = "ctb"), person("Jianxin", "Lin", email = "jianxin_lin@merck.com", role = "ctb"))
Description: Contains functions performing Bayesian inference for meta-analytic and network meta-analytic models through Markov chain Monte Carlo algorithm. Currently, the package implements Yao, Kim, Chen, Ibrahim, Shah, and Jianxin Lin (2015) <doi:10.1080/01621459.2015.1006065> and network meta-regression models using heavy-tailed multivariate random effects with covariate-dependent variances. For maximal computational efficiency, the Markov chain Monte Carlo samplers for each model, written in C++, are fine-tuned. This software has been developed under the auspices of the National Institutes of Health and Merck & Co., Inc., Kenilworth, NJ, USA.
License: GPL (>= 3)
Encoding: UTF-8
LazyLoad: yes
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: yes
Imports: Rcpp, ggplot2, methods, gridExtra
Depends: R (>= 3.4)
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, BH
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: http://merlot.stat.uconn.edu/packages/metapack/
BugReports: https://github.com/daeyounglim/metapack/issues
Packaged: 2021-02-15 18:00:20 UTC; dal18007
Author: Daeyoung Lim [aut, cre], Ming-Hui Chen [ctb], Sungduk Kim [ctb], Joseph Ibrahim [ctb], Arvind Shah [ctb], Jianxin Lin [ctb]
Maintainer: Daeyoung Lim <daeyoung.lim@uconn.edu>
Repository: CRAN
Date/Publication: 2021-02-17 10:00:02 UTC

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Package exams.mylearn updated to version 1.3 with previous version 1.2 dated 2020-10-09

Title: Question Generation in the 'MyLearn' XML Format
Description: Randomized multiple-select and single-select question generation for the 'MyLearn' teaching and learning platform. Question templates in the form of the R/exams package (see <http://www.r-exams.org/>) are transformed into XML format required by 'MyLearn'.
Author: Darjus Hosszejni [aut, cre] (<https://orcid.org/0000-0002-3803-691X>)
Maintainer: Darjus Hosszejni <darjus.hosszejni@wu.ac.at>

Diff between exams.mylearn versions 1.2 dated 2020-10-09 and 1.3 dated 2021-02-17

 DESCRIPTION                        |   10 
 MD5                                |   44 +-
 NAMESPACE                          |   57 +-
 R/example_paths.R                  |   56 --
 R/exams.mylearn-package.R          |   55 --
 R/exams2mylearn.R                  |  456 ++++++++++------------
 build/vignette.rds                 |binary
 inst/doc/workflow.R                |   88 ++--
 inst/doc/workflow.Rmd              |  360 +++++++++--------
 inst/doc/workflow.html             |  744 ++++++++++++++-----------------------
 inst/extdata/R-code.Rmd            |   68 +--
 inst/extdata/R-output.Rmd          |   54 +-
 inst/extdata/R-table.Rmd           |   62 +--
 inst/extdata/bullet-points.Rmd     |   74 +--
 inst/extdata/everything.Rmd        |  106 ++---
 inst/extdata/plot.Rmd              |   58 +-
 inst/extdata/single-choice.Rmd     |   68 +--
 inst/extdata/template-multiple.xml |   32 -
 inst/extdata/template-single.xml   |   32 -
 man/example_paths.Rd               |   38 -
 man/exams.mylearn-package.Rd       |   26 -
 man/exams2mylearn.Rd               |  158 +++----
 vignettes/workflow.Rmd             |  360 +++++++++--------
 23 files changed, 1416 insertions(+), 1590 deletions(-)

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New package vitae with initial version 0.4.2
Package: vitae
Title: Curriculum Vitae for R Markdown
Version: 0.4.2
Authors@R: c( person("Mitchell", "O'Hara-Wild", role=c("aut", "cre"), email = "mail@mitchelloharawild.com", comment=c(ORCID = "0000-0001-6729-7695")), person("Rob", "Hyndman", email="Rob.Hyndman@monash.edu", role=c("aut"), comment = c(ORCID = "0000-0002-2140-5352")), person("Yihui", "Xie", role = c("ctb"), comment = c(ORCID = "0000-0003-0645-5666")), person("Albert", "Krewinkel", role = c("cph"), comment = c("Multiple bibliographies lua filter")), person("JooYoung", "Seo", role="ctb", comment = c(ORCID = "0000-0002-4064-6012")))
Description: Provides templates and functions to simplify the production and maintenance of curriculum vitae.
Depends: R (>= 3.5.0)
Imports: rlang, glue, dplyr, rmarkdown (>= 2.2), knitr, xfun, yaml, tibble, vctrs (>= 0.3.3), pillar
Suggests: covr, rorcid, testthat, stringr, htmltools
SystemRequirements: pandoc (>= 2.7) - http://pandoc.org
License: GPL-3
Encoding: UTF-8
BugReports: https://github.com/mitchelloharawild/vitae/issues
URL: https://pkg.mitchelloharawild.com/vitae/, https://github.com/mitchelloharawild/vitae
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-15 07:08:56 UTC; mitchell
Author: Mitchell O'Hara-Wild [aut, cre] (<https://orcid.org/0000-0001-6729-7695>), Rob Hyndman [aut] (<https://orcid.org/0000-0002-2140-5352>), Yihui Xie [ctb] (<https://orcid.org/0000-0003-0645-5666>), Albert Krewinkel [cph] (Multiple bibliographies lua filter), JooYoung Seo [ctb] (<https://orcid.org/0000-0002-4064-6012>)
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>
Repository: CRAN
Date/Publication: 2021-02-17 09:00:02 UTC

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Package vein updated to version 0.9.1.2 with previous version 0.9.1 dated 2021-02-10

Title: Vehicular Emissions Inventories
Description: Elaboration of vehicular emissions inventories, consisting in four stages, pre-processing activity data, preparing emissions factors, estimating the emissions and post-processing of emissions in maps and databases. More details in Ibarra-Espinosa et al (2018) <doi:10.5194/gmd-11-2209-2018>. Before using VEIN you need to know the vehicular composition of your study area, in other words, the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to start with the project to download a template to create a structure of directories and scripts.
Author: Sergio Ibarra-Espinosa [aut, cre, wdc] (<https://orcid.org/0000-0002-3162-1905>)
Maintainer: Sergio Ibarra-Espinosa <sergio.ibarra@usp.br>

Diff between vein versions 0.9.1 dated 2021-02-10 and 0.9.1.2 dated 2021-02-17

 DESCRIPTION          |    8 
 MD5                  |   20 -
 NEWS.md              |    3 
 R/emis.R             |  605 ++++++++++++++++++--------------
 R/emis_cold_td.R     |  643 ++++++++++++++++++----------------
 R/emis_hot_td.R      |  947 +++++++++++++++++++++++++++------------------------
 inst/doc/basics.html |    4 
 man/emis.Rd          |  153 ++++----
 man/emis_cold_td.Rd  |  101 +++--
 man/emis_hot_td.Rd   |  227 +++++++-----
 src/init.c           |  127 +++---
 11 files changed, 1571 insertions(+), 1267 deletions(-)

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Package rayimage updated to version 0.5.1 with previous version 0.3.1 dated 2020-06-28

Title: Image Processing for Simulated Cameras
Description: Uses convolution-based techniques to generate simulated camera bokeh, depth of field, and other camera effects, using an image and an optional depth map. Accepts both filename inputs and in-memory array representations of images and matrices. Includes functions to perform 2D convolutions, reorient and resize images/matrices, add image overlays, generate camera vignette effects, and add titles to images.
Author: Tyler Morgan-Wall
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

Diff between rayimage versions 0.3.1 dated 2020-06-28 and 0.5.1 dated 2021-02-17

 DESCRIPTION                    |   10 +++---
 MD5                            |   45 +++++++++++++++++----------
 NAMESPACE                      |    2 +
 R/RcppExports.R                |    8 +++-
 R/add_image_overlay.R          |   66 ++++++++++++++++++++++++++++++++++++-----
 R/add_padding.R                |only
 R/add_title.R                  |   32 ++++++++++++++-----
 R/generate_2d_disk.R           |   28 +++++++++++++++--
 R/generate_2d_exponential.R    |   20 +++++++++---
 R/generate_2d_gaussian.R       |   20 +++++++++---
 R/plot_image.R                 |    8 ++++
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 R/render_convolution_fft.R     |only
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New package PGRdup with initial version 0.2.3.7
Package: PGRdup
Title: Discover Probable Duplicates in Plant Genetic Resources Collections
Version: 0.2.3.7
Authors@R: c( person(given = "J.", family = "Aravind", email = "j.aravind@icar.gov.in", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4791-442X")), person(given = "J.", family = "Radhamani", email = "jalli.radhamani@icar.gov.in", role = "aut"), person(family = c("Kalyani Srinivasan"), email = "kalyani.srinivasan@icar.gov.in", role = "aut"), person(given = "B.", family = c("Ananda Subhash"), email = "anandasubhash@gmail.com", role = "aut"), person(given = c("Rishi", "Kumar"), family = "Tyagi", email = "rishi.tyagi@icar.gov.in", role = "aut"), person("ICAR-NBGPR", role = "cph", comment = c(url = "www.nbpgr.ernet.in")), person(given = "Maurice", family = "Aubrey", email = "maurice@hevanet.com", comment = "Double Metaphone", role = "ctb"), person(given = "Kevin", family = "Atkinson", email = "kevina@users.sourceforge.net", comment = "Double Metaphone", role = "ctb"), person(given = "Lawrence", family = "Philips", comment = "Double Metaphone", role = "ctb"))
Description: Provides functions to aid the identification of probable/possible duplicates in Plant Genetic Resources (PGR) collections using 'passport databases' comprising of information records of each constituent sample. These include methods for cleaning the data, creation of a searchable Key Word in Context (KWIC) index of keywords associated with sample records and the identification of nearly identical records with similar information by fuzzy, phonetic and semantic matching of keywords.
Depends: R (>= 3.0.2)
Imports: data.table (>= 1.9.3), igraph, stringdist (>= 0.9.4), stringi, ggplot2, grid, gridExtra, methods, utils, stats
Suggests: diagram, wordcloud, microbenchmark, XML, httr, RCurl, knitr, rmarkdown, pander
Copyright: 2014-2020, ICAR-NBPGR
License: GPL-2 | GPL-3
Encoding: latin1
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.1
URL: https://cran.r-project.org/package=PGRdup, https://github.com/aravind-j/PGRdup, https://doi.org/10.5281/zenodo.841963, https://aravind-j.github.io/PGRdup/, https://www.rdocumentation.org/packages/PGRdup
BugReports: https://github.com/aravind-j/PGRdup/issues
NeedsCompilation: yes
Packaged: 2021-02-15 18:48:56 UTC; J. Aravind
Author: J. Aravind [aut, cre] (<https://orcid.org/0000-0002-4791-442X>), J. Radhamani [aut], Kalyani Srinivasan [aut], B. Ananda Subhash [aut], Rishi Kumar Tyagi [aut], ICAR-NBGPR [cph] (www.nbpgr.ernet.in), Maurice Aubrey [ctb] (Double Metaphone), Kevin Atkinson [ctb] (Double Metaphone), Lawrence Philips [ctb] (Double Metaphone)
Maintainer: J. Aravind <j.aravind@icar.gov.in>
Repository: CRAN
Date/Publication: 2021-02-17 09:00:28 UTC

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New package netseg with initial version 1.0-0
Package: netseg
Title: Measures of Network Segregation and Homophily
Version: 1.0-0
Authors@R: person(given = "Michal", family = "Bojanowski", role = c("aut", "cre"), email = "michal2992@gmail.com", comment = c(ORCID = "0000-0001-7503-852X"))
Description: Segregation is a network-level property such that edges between predefined groups of vertices are relatively less likely. Network homophily is a individual-level tendency to form relations with people who are similar on some attribute (e.g. gender, music taste, social status, etc.). In general homophily leads to segregation, but segregation might arise without homophily. This package implements descriptive indices measuring homophily/segregation. It is a computational companion to Bojanowski & Corten (2014) <doi:10.1016/j.socnet.2014.04.001>.
Depends: R (>= 2.10)
Imports: igraph (>= 0.6-0)
License: GPL-2
Encoding: UTF-8
URL: https://mbojan.github.io/netseg/
BugReports: https://github.com/mbojan/netseg/issues
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2021-02-14 23:41:09 UTC; mbojan
Author: Michal Bojanowski [aut, cre] (<https://orcid.org/0000-0001-7503-852X>)
Maintainer: Michal Bojanowski <michal2992@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-17 08:50:02 UTC

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New package matrixprofiler with initial version 0.1.3
Type: Package
Package: matrixprofiler
Title: Matrix Profile for R
Version: 0.1.3
Authors@R: c(person(given = "Francisco", family = "Bischoff", role = c("aut", "cre"), email = "fbischoff@med.up.pt", comment = c(ORCID = "https://orcid.org/0000-0002-5301-8672")), person(given = "Michael", family = "Yeh", role = c("res", "ccp", "ctb"), email = "myeh003@ucr.edu", comment = c(ORCID = "https://orcid.org/0000-0002-9807-2963")), person(given = "Diego", family = "Silva", role = c("res", "ccp", "ctb"), email = "diegofs@ufscar.br", comment = c(ORCID = "https://orcid.org/0000-0002-5184-9413")), person(given = "Yan", family = "Zhu", role = c("res", "ccp", "ctb"), email = "yzhu015@ucr.edu", comment = c(ORCID = "https://orcid.org/0000-0002-5952-2108")), person(given = "Hoang", family = "Dau", role = c("res", "ccp", "ctb"), email = "hdau001@ucr.edu", comment = c(ORCID = "https://orcid.org/0000-0003-2439-5185")), person(given = "Michele", family = "Linardi", role = c("res", "ccp", "ctb"), email = "michele.linardi@orange.fr", comment = c(ORCID = "https://orcid.org/0000-0002-3249-2068")))
Maintainer: Francisco Bischoff <fbischoff@med.up.pt>
Description: This is the core functions needed by the 'tsmp' package. The low level and carefully checked mathematical functions are here. These are implementations of the Matrix Profile concept that was created by CS-UCR <http://www.cs.ucr.edu/~eamonn/MatrixProfile.html>.
License: GPL-3
URL: https://github.com/matrix-profile-foundation/matrixprofiler
BugReports: https://github.com/matrix-profile-foundation/matrixprofiler/issues
Depends: R (>= 3.6)
Imports: checkmate (>= 2.0.0), Rcpp (>= 1.0.3), RcppParallel (>= 4.4.4)
Suggests: testthat (>= 3.0.0), debugme (>= 1.0.0), spelling (>= 2.0.0)
LinkingTo: Rcpp (>= 1.0.3), RcppParallel (>= 4.4.4), RcppProgress (>= 0.4.0), RcppThread (>= 0.5.0)
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: yes
RoxygenNote: 7.1.1
SystemRequirements: GNU make
Config/testthat/edition: 3
Config/testthat/parallel: true
Packaged: 2021-02-14 00:55:57 UTC; Franz
Author: Francisco Bischoff [aut, cre] (<https://orcid.org/0000-0002-5301-8672>), Michael Yeh [res, ccp, ctb] (<https://orcid.org/0000-0002-9807-2963>), Diego Silva [res, ccp, ctb] (<https://orcid.org/0000-0002-5184-9413>), Yan Zhu [res, ccp, ctb] (<https://orcid.org/0000-0002-5952-2108>), Hoang Dau [res, ccp, ctb] (<https://orcid.org/0000-0003-2439-5185>), Michele Linardi [res, ccp, ctb] (<https://orcid.org/0000-0002-3249-2068>)
Repository: CRAN
Date/Publication: 2021-02-17 09:00:12 UTC

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Package ldsep updated to version 2.0.2 with previous version 2.0.1 dated 2021-02-12

Title: Linkage Disequilibrium Shrinkage Estimation for Polyploids
Description: Estimate haplotypic or composite pairwise linkage disequilibrium (LD) in polyploids, using either genotypes or genotype likelihoods. Support is provided to estimate the popular measures of LD: the LD coefficient D, the standardized LD coefficient D', and the Pearson correlation coefficient r. All estimates are returned with corresponding standard errors. These estimates and standard errors can then be used for shrinkage estimation. The main functions are ldfast(), ldest(), mldest(), sldest(), plot.lddf(), format_lddf(), and ldshrink(). Details of the methods are available in Gerard (2021a) <doi:10.1111/1755-0998.13349> and Gerard (2021b) <doi:10.1101/2021.02.08.430270>.
Author: David Gerard [aut, cre] (<https://orcid.org/0000-0001-9450-5023>)
Maintainer: David Gerard <gerard.1787@gmail.com>

Diff between ldsep versions 2.0.1 dated 2021-02-12 and 2.0.2 dated 2021-02-17

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Package ipcwswitch updated to version 1.0.4 with previous version 1.0.3 dated 2019-05-15

Title: Inverse Probability of Censoring Weights to Deal with Treatment Switch in Randomized Clinical Trials
Description: Contains functions for formatting clinical trials data and implementing inverse probability of censoring weights to handle treatment switches when estimating causal treatment effect in randomized clinical trials.
Author: Nathalie Graffeo [aut, cre], Aurelien Latouche [aut], Sylvie Chevret [aut]
Maintainer: Nathalie Graffeo <nathalie.graffeo@univ-amu.fr>

Diff between ipcwswitch versions 1.0.3 dated 2019-05-15 and 1.0.4 dated 2021-02-17

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Package hermiter updated to version 2.0.3 with previous version 2.0.2 dated 2021-01-11

Title: Efficient Sequential and Batch Estimation of Univariate and Bivariate Probability Density Functions and Cumulative Distribution Functions along with Quantiles (Univariate) and Spearman's Correlation (Bivariate)
Description: Facilitates estimation of full univariate and bivariate probability density functions and cumulative distribution functions along with full quantile functions (univariate) and Spearman's rank correlation (bivariate) using Hermite series based estimators. These estimators are particularly useful in the sequential setting (both stationary and non-stationary) and one-pass batch estimation setting for large data sets. Based on: Stephanou, Michael, Varughese, Melvin and Macdonald, Iain. "Sequential quantiles via Hermite series density estimation." Electronic Journal of Statistics 11.1 (2017): 570-607 <doi:10.1214/17-EJS1245>, Stephanou, Michael and Varughese, Melvin. "On the properties of Hermite series based distribution function estimators." Metrika (2020) <doi:10.1007/s00184-020-00785-z> and Stephanou, Michael and Varughese, Melvin. "Sequential Estimation of Nonparametric Correlation using Hermite Series Estimators." arXiv Preprint (2020) <arXiv:2012.06287>.
Author: Michael Stephanou [aut, cre], Melvin Varughese [ctb]
Maintainer: Michael Stephanou <michael.stephanou@gmail.com>

Diff between hermiter versions 2.0.2 dated 2021-01-11 and 2.0.3 dated 2021-02-17

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New package germinationmetrics with initial version 0.1.5
Package: germinationmetrics
Title: Seed Germination Indices and Curve Fitting
Version: 0.1.5
Authors@R: c( person(given = "J.", family = "Aravind", email = "j.aravind@icar.gov.in", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4791-442X")), person(given = "S.", family = "Vimala Devi", email = "vimala.devi@icar.gov.in", role = "aut"), person(given = "J.", family = "Radhamani", email = "jalli.radhamani@icar.gov.in", role = "aut"), person(given = c("Sherry", "Rachel"), family = "Jacob", email = "sherry.jacob@icar.gov.in", role = "aut"), person(given = c("Kalyani", "Srinivasan"), email = "kalyani.srinivasan@icar.gov.in", role = "aut"), person("ICAR-NBGPR", role = "cph", comment = c(url = "www.nbpgr.ernet.in")))
Description: Provides functions to compute various germination indices such as germinability, median germination time, mean germination time, mean germination rate, speed of germination, Timson's index, germination value, coefficient of uniformity of germination, uncertainty of germination process, synchrony of germination etc. from germination count data. Includes functions for fitting cumulative seed germination curves using four-parameter hill function and computation of associated parameters. See the vignette for more, including full list of citations for the methods implemented.
Copyright: 2017-2018, ICAR-NBPGR
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Imports: broom, data.table, ggplot2, ggrepel, mathjaxr, minpack.lm, plyr, Rdpack, utils, stats
Suggests: knitr, rmarkdown, reshape2, pander, XML, httr, RCurl
RdMacros: mathjaxr, Rdpack
URL: https://github.com/aravind-j/germinationmetrics, https://aravind-j.github.io/germinationmetrics/ https://CRAN.R-project.org/package=germinationmetrics https://doi.org/10.5281/zenodo.1219630
BugReports: https://github.com/aravind-j/germinationmetrics/issues
NeedsCompilation: no
Packaged: 2021-02-12 18:47:35 UTC; J. Aravind
Author: J. Aravind [aut, cre] (<https://orcid.org/0000-0002-4791-442X>), S. Vimala Devi [aut], J. Radhamani [aut], Sherry Rachel Jacob [aut], Kalyani Srinivasan [aut], ICAR-NBGPR [cph] (www.nbpgr.ernet.in)
Maintainer: J. Aravind <j.aravind@icar.gov.in>
Repository: CRAN
Date/Publication: 2021-02-17 09:00:24 UTC

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New package augmentedRCBD with initial version 0.1.4
Package: augmentedRCBD
Title: Analysis of Augmented Randomised Complete Block Designs
Version: 0.1.4
Authors@R: c( person(given = "J.", family = "Aravind", email = "j.aravind@icar.gov.in", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4791-442X")), person(given = "S.", family = "Mukesh Sankar", email = "mukeshsankar@gmail.com", role = "aut"), person(given = c("Dhammaprakash", "Pandhari"), family = "Wankhede", email = "d.wankhede@icar.gov.in", role = "aut", comment = c(ORCID = "0000-0001-6384-8664")), person(given = "Vikender", family = "Kaur", email = "vikender.kaur@icar.gov.in", role = "aut"), person("ICAR-NBGPR", role = c("cph"), comment = c(url = "www.nbpgr.ernet.in")))
Description: Functions for analysis of data generated from experiments in augmented randomised complete block design according to Federer, W.T. (1961) <doi:10.2307/2527837>. Computes analysis of variance, adjusted means, descriptive statistics, genetic variability statistics etc. Further includes data visualization and report generation functions.
Copyright: 2015-2018, ICAR-NBPGR
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.1)
VignetteBuilder: knitr
RoxygenNote: 7.1.1
URL: https://github.com/aravind-j/augmentedRCBD https://CRAN.R-project.org/package=augmentedRCBD https://aravind-j.github.io/augmentedRCBD/ https://doi.org/10.5281/zenodo.1310011
BugReports: https://github.com/aravind-j/augmentedRCBD/issues
Imports: emmeans, dplyr, flextable, ggplot2, grDevices, methods, moments, multcomp, multcompView, Rdpack, stats, stringi, officer, reshape2, utils
Suggests: knitr, rmarkdown, pander, testthat, agricolae
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2021-02-15 18:31:07 UTC; aravindj
Author: J. Aravind [aut, cre] (<https://orcid.org/0000-0002-4791-442X>), S. Mukesh Sankar [aut], Dhammaprakash Pandhari Wankhede [aut] (<https://orcid.org/0000-0001-6384-8664>), Vikender Kaur [aut], ICAR-NBGPR [cph] (www.nbpgr.ernet.in)
Maintainer: J. Aravind <j.aravind@icar.gov.in>
Repository: CRAN
Date/Publication: 2021-02-17 09:00:26 UTC

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Package discourseGT updated to version 1.1.4 with previous version 1.1.3 dated 2021-01-18

Title: Analyze Group Patterns using Graph Theory in Educational Settings
Description: Analyzes group patterns using discourse analysis data with graph theory mathematics. Takes the order of which individuals talk and converts it to a network edge and weight list. Returns the density, centrality, centralization, and subgroup information for each group. Based on the analytical framework laid out in Chai et al. (2019) <doi:10.1187/cbe.18-11-0222>.
Author: Albert Chai [aut], Andrew Lee [aut], Joshua Le [aut, cre], Katherine Ly [ctb], Kevin Banh [ctb], Priya Pahal [ctb], Stanley Lo [aut]
Maintainer: Joshua Le <jpl038@ucsd.edu>

Diff between discourseGT versions 1.1.3 dated 2021-01-18 and 1.1.4 dated 2021-02-17

 DESCRIPTION     |    8 ++++----
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Package pmwg updated to version 0.2.0 with previous version 0.1.9 dated 2020-09-02

Title: Particle Metropolis Within Gibbs
Description: Provides an R implementation of the Particle Metropolis within Gibbs sampler for model parameter, covariance matrix and random effect estimation. A more general implementation of the sampler based on the paper by Gunawan, D., Hawkins, G. E., Tran, M. N., Kohn, R., & Brown, S. D. (2020) <doi:10.1016/j.jmp.2020.102368>. An HTML tutorial document describing the package is available at <https://newcastlecl.github.io/samplerDoc/> and includes several detailed examples, some background and troubleshooting steps.
Author: Gavin Cooper [aut, cre, trl] (Package creator and maintainer), Reilly Innes [aut], Caroline Kuhne [aut], Jon-Paul Cavallaro [aut], David Gunawan [aut] (Author of original MATLAB code), Guy Hawkins [aut], Scott Brown [aut, trl] (Original translation from MATLAB to R)
Maintainer: Gavin Cooper <gavin@gavincooper.net>

Diff between pmwg versions 0.1.9 dated 2020-09-02 and 0.2.0 dated 2021-02-17

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