Thu, 10 Sep 2020

Package gutenbergr (with last version 0.1.5) was removed from CRAN

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

2019-09-10 0.1.5
2018-01-26 0.1.4
2017-06-19 0.1.3
2016-06-24 0.1.2
2016-05-16 0.1.1
2016-05-03 0.1

Permanent link
Package chromoR (with last version 1.0) was removed from CRAN

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

2014-02-11 1.0

Permanent link
Package ezpickr (with last version 2.0.0) was removed from CRAN

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

2019-11-17 2.0.0
2019-10-27 1.2.0
2019-09-07 1.1.0
2019-04-22 1.0.5
2019-03-23 1.0.4
2019-02-28 1.0.3
2019-02-24 1.0.2
2019-02-16 1.0.1
2019-02-02 1.0.0
2018-12-02 0.1.3
2018-11-30 0.1.2
2018-11-28 0.1.1

Permanent link
Package googleCloudRunner updated to version 0.3.0 with previous version 0.2.0 dated 2020-05-02

Title: R Scripts in the Google Cloud via Cloud Run, Cloud Build and Cloud Scheduler
Description: Tools to easily enable R scripts in the Google Cloud Platform. Utilise cloud services such as Cloud Run <https://cloud.google.com/run/> for R over HTTP, Cloud Build <https://cloud.google.com/cloud-build/> for Continuous Delivery and Integration services and Cloud Scheduler <https://cloud.google.com/scheduler/> for scheduled scripts.
Author: Mark Edmondson [aut, cre] (<https://orcid.org/0000-0002-8434-3881>), Sunholo Ltd [cph]
Maintainer: Mark Edmondson <r@sunholo.com>

Diff between googleCloudRunner versions 0.2.0 dated 2020-05-02 and 0.3.0 dated 2020-09-10

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More information about googleCloudRunner at CRAN
Permanent link

Package cchs updated to version 0.4.2 with previous version 0.4.1 dated 2019-02-18

Title: Cox Model for Case-Cohort Data with Stratified Subcohort-Selection
Description: Contains a function, also called 'cchs', that calculates Estimator III of Borgan et al (2000), <DOI:10.1023/A:1009661900674>. This estimator is for fitting a Cox proportional hazards model to data from a case-cohort study where the subcohort was selected by stratified simple random sampling.
Author: E. Jones
Maintainer: E. Jones <edmundjones79@gmail.com>

Diff between cchs versions 0.4.1 dated 2019-02-18 and 0.4.2 dated 2020-09-10

 DESCRIPTION |    8 ++++----
 MD5         |    6 +++---
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 4 files changed, 13 insertions(+), 9 deletions(-)

More information about cchs at CRAN
Permanent link

Package DRIP updated to version 1.5 with previous version 1.4 dated 2018-10-07

Title: Discontinuous Regression and Image Processing
Description: This is a collection of functions for discontinuous regression analysis and image processing (DRIP). A recent addition is the blind image deblurring via jump-preserving extrapolation. This version removes the dependence on the GNU Scientific Library.
Author: Yicheng Kang <kangx276@umn.edu>
Maintainer: Yicheng Kang <kangx276@umn.edu>

Diff between DRIP versions 1.4 dated 2018-10-07 and 1.5 dated 2020-09-10

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More information about DRIP at CRAN
Permanent link

Package fsbrain updated to version 0.4.0 with previous version 0.3.0 dated 2020-06-21

Title: Managing and Visualizing Brain Surface Data
Description: Provides high-level access to 'FreeSurfer' <http://freesurfer.net/> neuroimaging data on the level of subjects and groups. Load morphometry data, surfaces and brain parcellations based on atlases. Mask data using labels, load data for specific atlas regions only, and visualize data and results directly in 'R'.
Author: Tim Schäfer [aut, cre] (<https://orcid.org/0000-0002-3683-8070>)
Maintainer: Tim Schäfer <ts+code@rcmd.org>

Diff between fsbrain versions 0.3.0 dated 2020-06-21 and 0.4.0 dated 2020-09-10

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Package SSHAARP (with last version 1.0.0) was removed from CRAN

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

2020-04-27 1.0.0

Permanent link
Package tcgsaseq updated to version 2.0.5 with previous version 1.8.1 dated 2018-12-06

Title: Time-Course Gene Set Analysis for RNA-Seq Data
Description: Analyze RNA-seq data with variance component score test accounting for data heteroscedasticity through precision weights. Perform both gene-wise and gene set analyses, and can deal with longitudinal data. Method is detailed in: Agniel & Hejblum (2017) <doi: 10.1093/biostatistics/kxx005>, Variance component score test for time-course gene set analysis of longitudinal RNA-seq data, Biostatistics, 18(4):589-604.
Author: Denis Agniel [aut], Boris P. Hejblum [aut, cre], Marine Gauthier [aut]
Maintainer: Boris P. Hejblum <boris.hejblum@u-bordeaux.fr>

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Package MBNMAdose updated to version 0.3.0 with previous version 0.2.7 dated 2020-03-02

Title: Dose-Response MBNMA Models
Description: Fits Bayesian dose-response model-based network meta-analysis (MBNMA) that incorporate multiple doses within an agent by modelling different dose-response functions, as described by Mawdsley et al. (2016) <doi:10.1002/psp4.12091>. By modelling dose-response relationships this can connect networks of evidence that might otherwise be disconnected, and can improve precision on treatment estimates. Several common dose-response functions are provided; others may be added by the user. Various characteristics and assumptions can be flexibly added to the models, such as shared class effects. The consistency of direct and indirect evidence in the network can be assessed using unrelated mean effects models and/or by node-splitting at the treatment level.
Author: Hugo Pedder [aut, cre], Lujin Li [rev], Adil Karim [ctb]
Maintainer: Hugo Pedder <hugopedder@gmail.com>

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Package CalSim updated to version 0.5.1 with previous version 0.3.2 dated 2019-05-20

Title: The Calibration Simplex
Description: Generates the calibration simplex (a generalization of the reliability diagram) for three-category probability forecasts, as proposed by Wilks (2013) <doi:10.1175/WAF-D-13-00027.1>.
Author: Johannes Resin
Maintainer: Johannes Resin <johannes.resin@h-its.org>

Diff between CalSim versions 0.3.2 dated 2019-05-20 and 0.5.1 dated 2020-09-10

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New package Tplyr with initial version 0.1.1
Package: Tplyr
Title: A Grammar of Clinical Data Summary
Version: 0.1.1
Authors@R: c( person(given = "Eli", family = "Miller", role = "aut", email = "Eli.Miller@AtorusResearch.com", comment = c(ORCID = "0000-0002-2127-9456")), person(given = "Mike", family = "Stackhouse", role = c("aut", "cre"), email = "mike.stackhouse@atorusresearch.com", comment = c(ORCID = "0000-0001-6030-723X")), person(given = "Ashley", family = "Tarasiewicz", email = "Ashley.Tarasiewicz@atorusresearch.com", role = "aut"), person(given = "Nathan", family = "Kosiba", email = "Nathan.Kosiba@atorusresearch.com", role = "aut", comment = c(ORCID = "0000-0001-5359-4234")), person(given = "Atorus Research LLC", role = "cph") )
Description: A tool created to simplify the data manipulation necessary to create clinical reports.
License: MIT + file LICENSE
URL: https://github.com/atorus-research/Tplyr
BugReports: https://github.com/atorus-research/Tplyr/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: rlang (>= 0.4.6), assertthat (>= 0.2.1), magrittr (>= 1.5), dplyr (>= 0.8.4), purrr (>= 0.3.3), stringr (>= 1.4.0), tidyr (>= 1.0.2), tidyselect (>= 1.0.0), tibble (>= 3.0.1), lifecycle, forcats (>= 0.4.0)
Suggests: testthat (>= 2.1.0), haven (>= 2.2.0), knitr, rmarkdown, huxtable, tidyverse, readr, kableExtra, pharmaRTF
VignetteBuilder: knitr
RoxygenNote: 7.0.2
RdMacros: lifecycle
NeedsCompilation: no
Packaged: 2020-09-01 14:24:02 UTC; emiller
Author: Eli Miller [aut] (<https://orcid.org/0000-0002-2127-9456>), Mike Stackhouse [aut, cre] (<https://orcid.org/0000-0001-6030-723X>), Ashley Tarasiewicz [aut], Nathan Kosiba [aut] (<https://orcid.org/0000-0001-5359-4234>), Atorus Research LLC [cph]
Maintainer: Mike Stackhouse <mike.stackhouse@atorusresearch.com>
Repository: CRAN
Date/Publication: 2020-09-10 14:20:07 UTC

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New package qbld with initial version 1.0
Package: qbld
Type: Package
Title: Quantile Regression for Binary Longitudinal Data
Version: 1.0
Date: 2020-08-17
Author: Ayush Agarwal [aut, cre], Dootika Vats [ctb]
Maintainer: Ayush Agarwal<ayush.agarwal50@gmail.com>
Description: Implements the Bayesian quantile regression model for binary longitudinal data (QBLD) developed in Rahman and Vossmeyer (2019) <DOI:10.1108/S0731-90532019000040B009>. The model handles both fixed and random effects and implements both a blocked and an unblocked Gibbs sampler for posterior inference.
License: GPL-3
Imports: Rcpp, stats, grDevices, graphics, mcmcse, stableGR, RcppDist, knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo, RcppDist
Depends: R (>= 3.5)
Encoding: UTF-8
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-09-03 07:18:40 UTC; mclaren
Repository: CRAN
Date/Publication: 2020-09-10 14:10:03 UTC

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Package modelStudio updated to version 2.0.0 with previous version 1.2.0 dated 2020-07-15

Title: Interactive Studio for Explanatory Model Analysis
Description: Automate the explanatory analysis of machine learning predictive models. Generate advanced interactive model explanations in the form of a serverless HTML site with only one line of code. This tool is model agnostic, therefore compatible with most of the black box predictive models and frameworks. The main function computes various (instance and dataset level) model explanations and produces a customisable dashboard, which consists of multiple panels for plots with their short descriptions. Easily save the dashboard and share it with others. Tools for Explanatory Model Analysis unite with tools for Exploratory Data Analysis to give a broad overview of the model behavior.
Author: Hubert Baniecki [aut, cre] (<https://orcid.org/0000-0001-6661-5364>), Przemyslaw Biecek [aut] (<https://orcid.org/0000-0001-8423-1823>), Piotr Piatyszek [ctb]
Maintainer: Hubert Baniecki <hbaniecki@gmail.com>

Diff between modelStudio versions 1.2.0 dated 2020-07-15 and 2.0.0 dated 2020-09-10

 DESCRIPTION                        |   38 -
 MD5                                |   51 +-
 NAMESPACE                          |    2 
 NEWS.md                            |   18 
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 R/ms_options.R                     |   22 -
 R/ms_update_observations.R         |   42 +
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 build/vignette.rds                 |binary
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 inst/doc/ms-perks-features.R       |   42 +
 inst/doc/ms-perks-features.Rmd     |   76 +++
 inst/doc/ms-perks-features.html    |  113 ++++-
 inst/doc/ms-r-python-examples.R    |   60 ++
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 tests/testthat/test_2_0.R          |only
 tests/testthat/test_modelStudio.R  |   73 +--
 tests/testthat/test_objects.R      |    7 
 vignettes/ms-perks-features.Rmd    |   76 +++
 vignettes/ms-r-python-examples.Rmd |   94 +++-
 27 files changed, 1865 insertions(+), 717 deletions(-)

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New package mirtsvd with initial version 1.0
Package: mirtsvd
Title: SVD-Based Estimation for Exploratory Item Factor Analysis
Version: 1.0
Authors@R: c( person(given = "Haoran", family = "Zhang", role = c("aut", "cre"), email = "hrzhang16@gmail.com"), person("Yunxiao", "Chen", role = "aut"), person("Xiaoou", "Li", role = "aut") )
Author: Haoran Zhang [aut, cre], Yunxiao Chen [aut], Xiaoou Li [aut]
Maintainer: Haoran Zhang <hrzhang16@gmail.com>
Description: Provides singular value decomposition based estimation algorithms for exploratory item factor analysis (IFA) based on multidimensional item response theory models. For more information, please refer to: Zhang, H., Chen, Y., & Li, X. (2020). A note on exploratory item factor analysis by singular value decomposition. Psychometrika, 1-15, <DOI:10.1007/s11336-020-09704-7>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.1)
Imports: GPArotation, mirtjml, graphics, stats
NeedsCompilation: no
Packaged: 2020-09-03 09:45:30 UTC; zhanghaoran
Repository: CRAN
Date/Publication: 2020-09-10 14:20:03 UTC

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Package metan updated to version 1.8.1 with previous version 1.7.0 dated 2020-07-18

Title: Multi Environment Trials Analysis
Description: Performs stability analysis of multi-environment trial data using parametric and non-parametric methods. Parametric methods includes Additive Main Effects and Multiplicative Interaction (AMMI) analysis by Gauch (2013) <doi:10.2135/cropsci2013.04.0241>, Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) <doi:10.1201/9781420040371>, joint Regression Analysis by Eberhart & Russel (1966) (<doi:10.2135/cropsci1966.0011183X000600010011x>), ecovalence by Wricke (1965), genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method <doi:10.12702/1984-7033.v04n01a02>, stability variance by Shukla (1972) <doi:10.1038/hdy.1972.87>, weighted average of absolute scores by Olivoto et al. (2019a) <doi:10.2134/agronj2019.03.0220>, and multi-trait stability index by Olivoto et al. (2019b) <doi:10.2134/agronj2019.03.0221>. Non-parametric methods includes superiority index by Lin & Binns (1988) <doi:10.4141/cjps88-018>, nonparametric measures of phenotypic stability by Huehn (1990) <https://link.springer.com/article/10.1007/BF00024241>, TOP third statistic by Fox et al. (1990) <doi:10.1007/BF00040364>, geometric adaptability index described by Shahbazi (2019) <doi:10.1016/j.scienta.2019.04.047>. Functions for computing biometrical analysis such as path analysis, canonical correlation, partial correlation, clustering analysis, and tools for inspecting, manipulating, summarizing and plotting typical multi-environment trial data are also provided.
Author: Tiago Olivoto [aut, cre, cph] (<https://orcid.org/0000-0002-0241-9636>)
Maintainer: Tiago Olivoto <tiagoolivoto@gmail.com>

Diff between metan versions 1.7.0 dated 2020-07-18 and 1.8.1 dated 2020-09-10

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 112 files changed, 17912 insertions(+), 16192 deletions(-)

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Package lsasim updated to version 2.0.2 with previous version 2.0.1 dated 2019-12-05

Title: Functions to Facilitate the Simulation of Large Scale Assessment Data
Description: Provides functions to simulate data from large-scale educational assessments, including background questionnaire data and cognitive item responses that adhere to a multiple-matrix sampled design.
Author: Tyler Matta [aut], Leslie Rutkowski [aut], David Rutkowski [aut], Yuan-Ling Linda Liaw [aut], Kondwani Kajera Mughogho [ctb], Waldir Leoncio [aut, cre]
Maintainer: Waldir Leoncio <w.l.netto@medisin.uio.no>

Diff between lsasim versions 2.0.1 dated 2019-12-05 and 2.0.2 dated 2020-09-10

 DESCRIPTION                         |   12 ++++----
 MD5                                 |   36 ++++++++++++------------
 R/item_gen.R                        |   54 ++++++++++++++++++------------------
 R/lsasim.R                          |    3 +-
 man/beta_gen.Rd                     |   11 ++++++-
 man/block_design.Rd                 |    3 --
 man/booklet_sample.Rd               |   10 +++++-
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 man/lsasim.Rd                       |    3 --
 man/pisa2012_math_block.Rd          |    6 ++--
 man/pisa2012_math_booklet.Rd        |    6 ++--
 man/pisa2012_math_item.Rd           |    6 ++--
 man/pisa2012_q_cormat.Rd            |    4 ++
 man/pisa2012_q_marginal.Rd          |    4 ++
 man/questionnaire_gen.Rd            |   19 ++++++++++--
 man/questionnaire_gen_family.Rd     |   11 ++++++-
 man/questionnaire_gen_polychoric.Rd |    3 --
 man/response_gen.Rd                 |   13 +++++++-
 man/run_condition_checks.Rd         |   14 ++++++++-
 19 files changed, 147 insertions(+), 82 deletions(-)

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New package listArray with initial version 0.1.1
Package: listArray
Title: Incomplete Array with Arbitrary R Objects as Indices
Version: 0.1.1
Authors@R: person(given = "Sigbert", family = "Klinke", role = c("aut", "cre"), email = "sigbert@hu-berlin.de")
Description: The aim of the package is to create data objects which allow for accesses like x["test"] and x["test","test"].
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-03 12:04:23 UTC; sk
Author: Sigbert Klinke [aut, cre]
Maintainer: Sigbert Klinke <sigbert@hu-berlin.de>
Repository: CRAN
Date/Publication: 2020-09-10 14:40:03 UTC

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New package hermiter with initial version 1.0.0
Package: hermiter
Title: Efficient Sequential and Batch Estimation of Probability Density Functions, Cumulative Distribution Functions and Quantiles
Version: 1.0.0
Authors@R: c( person("Michael","Stephanou",role=c("aut","cre"), email="michael.stephanou@gmail.com"), person("Melvin","Varughese",role="ctb"))
Author: Michael Stephanou [aut, cre], Melvin Varughese [ctb]
Maintainer: Michael Stephanou <michael.stephanou@gmail.com>
Description: Facilitates estimation of the full probability density function, cumulative distribution function and quantile function 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 Iain Macdonald. "Sequential quantiles via Hermite series density estimation." Electronic Journal of Statistics 11.1 (2017): 570-607 <doi:10.1214/17-EJS1245> and Stephanou, Michael and Varughese, Melvin. "On the properties of Hermite series based distribution function estimators." Metrika (2020) <doi:10.1007/s00184-020-00785-z>.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.5), methods
LinkingTo: Rcpp, BH
RoxygenNote: 7.1.1
Suggests: testthat, magrittr, knitr, rmarkdown, dplyr, data.table, ggplot2, DT
VignetteBuilder: knitr
URL: https://github.com/MikeJaredS/hermiter
BugReports: https://github.com/MikeJaredS/hermiter/issues
NeedsCompilation: yes
Packaged: 2020-09-03 12:40:05 UTC; mjste
Repository: CRAN
Date/Publication: 2020-09-10 14:50:02 UTC

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New package duckdb with initial version 0.2.1
Package: duckdb
Title: DBI Package for the DuckDB Database Management System
Version: 0.2.1
Authors@R: c(person(given = "Hannes", family = "Mühleisen", role = c("aut", "cre"), email = "hannes@cwi.nl", comment = c(ORCID = "0000-0001-8552-0029")), person(given = "Mark", family = "Raasveldt", role = "aut", email = "mark.raasveldt@cwi.nl", comment = c(ORCID = "0000-0001-5005-6844")), person(given = "DuckDB Contributors", role = "aut"), person("Apache Software Foundation", role = "cph"), person("PostgreSQL Global Development Group", role = "cph"), person("The Regents of the University of California", role = "cph"), person("Cameron Desrochers", role = "cph"), person("Victor Zverovich", role = "cph"), person("RAD Game Tools", role = "cph"), person("Valve Software", role = "cph"), person("Rich Geldreich", role = "cph"), person("Tenacious Software LLC", role = "cph"), person("The RE2 Authors", role = "cph"), person("Google Inc.", role = "cph"), person("Steven G. Johnson", role = "cph"), person("Jiahao Chen", role = "cph"), person("Tony Kelman", role = "cph"), person("Jonas Fonseca", role = "cph"), person("Lukas Fittl", role = "cph"))
Description: The DuckDB project is an embedded analytical data management system with support for the Structured Query Language (SQL). This package includes all of DuckDB and a R Database Interface (DBI) connector.
License: MPL
URL: https://duckdb.org/, https://github.com/cwida/duckdb
BugReports: https://github.com/cwida/duckdb/issues
Depends: DBI, R (>= 3.5.0)
Imports: methods, utils
Suggests: callr, DBItest, dbplyr, nycflights13, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2020-09-03 07:57:12 UTC; hannes
Author: Hannes Mühleisen [aut, cre] (<https://orcid.org/0000-0001-8552-0029>), Mark Raasveldt [aut] (<https://orcid.org/0000-0001-5005-6844>), DuckDB Contributors [aut], Apache Software Foundation [cph], PostgreSQL Global Development Group [cph], The Regents of the University of California [cph], Cameron Desrochers [cph], Victor Zverovich [cph], RAD Game Tools [cph], Valve Software [cph], Rich Geldreich [cph], Tenacious Software LLC [cph], The RE2 Authors [cph], Google Inc. [cph], Steven G. Johnson [cph], Jiahao Chen [cph], Tony Kelman [cph], Jonas Fonseca [cph], Lukas Fittl [cph]
Maintainer: Hannes Mühleisen <hannes@cwi.nl>
Repository: CRAN
Date/Publication: 2020-09-10 14:10:12 UTC

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New package diffviewer with initial version 0.1.0
Package: diffviewer
Title: HTML Widget to Show File Differences
Version: 0.1.0
Authors@R: c(person(given = "Hadley", family = "Wickham", role = c("aut", "cre"), email = "hadley@rstudio.com"), person(given = "Joshua", family = "Kunst", role = "aut"), person(given = "Winston", family = "Chang", role = "aut", email = "winston@rstudio.com"), person(given = "RStudio", role = "cph"), person(given = "Paul", family = "Fitzpatrick", role = "cph", comment = "Author of included daff.js library"), person(given = "Rodrigo", family = "Fernandes", role = "cph", comment = "Author of included diff2html library"), person(given = "JQuery Foundation", role = "cph", comment = "Author of included jquery library"), person(given = "Kevin", family = "Decker", role = "cph", comment = "Author of included jsdiff library"), person(given = "Matthew", family = "Holt", role = "cph", comment = "Author of incldued PapaParse library"), person(given = "Huddle", role = "cph", comment = "Author of included resemble library"))
Description: A HTML widget that shows differences between files (text, images, and data frames).
License: MIT + file LICENSE
URL: https://github.com/r-lib/diffviewer
BugReports: https://github.com/r-lib/diffviewer/issues
Imports: htmlwidgets, jsonlite
Suggests: covr, shiny
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-03 13:19:20 UTC; hadley
Author: Hadley Wickham [aut, cre], Joshua Kunst [aut], Winston Chang [aut], RStudio [cph], Paul Fitzpatrick [cph] (Author of included daff.js library), Rodrigo Fernandes [cph] (Author of included diff2html library), JQuery Foundation [cph] (Author of included jquery library), Kevin Decker [cph] (Author of included jsdiff library), Matthew Holt [cph] (Author of incldued PapaParse library), Huddle [cph] (Author of included resemble library)
Maintainer: Hadley Wickham <hadley@rstudio.com>
Repository: CRAN
Date/Publication: 2020-09-10 14:50:08 UTC

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Package BIGL updated to version 1.5.3 with previous version 1.5.2 dated 2020-07-24

Title: Biochemically Intuitive Generalized Loewe Model
Description: Response surface methods for drug synergy analysis. Available methods include generalized and classical Loewe formulations as well as Highest Single Agent methodology. Response surfaces can be plotted in an interactive 3-D plot and formal statistical tests for presence of synergistic effects are available. Implemented methods and tests are described in the article "BIGL: Biochemically Intuitive Generalized Loewe null model for prediction of the expected combined effect compatible with partial agonism and antagonism" by Koen Van der Borght, Annelies Tourny, Rytis Bagdziunas, Olivier Thas, Maxim Nazarov, Heather Turner, Bie Verbist & Hugo Ceulemans (2017) <doi:10.1038/s41598-017-18068-5>.
Author: Heather Turner, Annelies Tourny, Olivier Thas, Maxim Nazarov, Rytis Bagdziunas
Maintainer: Maxim Nazarov <maxim.nazarov@openanalytics.eu>

Diff between BIGL versions 1.5.2 dated 2020-07-24 and 1.5.3 dated 2020-09-10

 DESCRIPTION               |   10 +++++-----
 MD5                       |   12 ++++++------
 R/generalizedLoewe.R      |    4 ++--
 R/hsa.R                   |    4 ++--
 inst/NEWS                 |    2 ++
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Package metathis updated to version 1.0.3 with previous version 1.0.1 dated 2020-03-01

Title: HTML Metadata Tags for 'R Markdown' and 'Shiny'
Description: Create meta tags for 'R Markdown' HTML documents and 'Shiny' apps for customized social media cards, for accessibility, and quality search engine indexing. 'metathis' currently supports HTML documents created with 'rmarkdown', 'shiny', 'xaringan', 'pagedown', 'bookdown', and 'flexdashboard'.
Author: Garrick Aden-Buie [aut, cre] (<https://orcid.org/0000-0002-7111-0077>)
Maintainer: Garrick Aden-Buie <garrick@adenbuie.com>

Diff between metathis versions 1.0.1 dated 2020-03-01 and 1.0.3 dated 2020-09-10

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New package dyngen with initial version 0.4.0
Type: Package
Package: dyngen
Title: A Multi-Modal Simulator for Spearheading Single-Cell Omics Analyses
Version: 0.4.0
Authors@R: c(person(given = "Robrecht", family = "Cannoodt", role = c("aut", "cre", "cph"), email = "rcannood@gmail.com", comment = c(ORCID = "0000-0003-3641-729X")), person(given = "Wouter", family = "Saelens", role = "aut", email = "wouter.saelens@ugent.be", comment = c(ORCID = "0000-0002-7114-6248")))
Description: A novel, multi-modal simulation engine for studying dynamic cellular processes at single-cell resolution. 'dyngen' is more flexible than current single-cell simulation engines. It allows better method development and benchmarking, thereby stimulating development and testing of novel computational methods. Cannoodt et al. (2020) <doi:10.1101/2020.02.06.936971>.
License: MIT + file LICENSE
URL: https://github.com/dynverse/dyngen
BugReports: https://github.com/dynverse/dyngen/issues
Depends: R (>= 3.5.0)
Imports: assertthat, dplyr, dynutils (>= 1.0.4), furrr, ggplot2, ggraph (>= 2.0), ggrepel, GillespieSSA2 (>= 0.2.6), grDevices, grid, igraph, lmds, Matrix, methods, patchwork, pbapply, purrr, rlang (>= 0.4.1), stats, tibble, tidygraph, tidyr, utils, viridis
Suggests: covr, dynwrap (>= 1.2.0), knitr, R.rsp, rmarkdown, testthat
VignetteBuilder: knitr, R.rsp
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-02 11:33:59 UTC; rcannood
Author: Robrecht Cannoodt [aut, cre, cph] (<https://orcid.org/0000-0003-3641-729X>), Wouter Saelens [aut] (<https://orcid.org/0000-0002-7114-6248>)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-10 14:00:03 UTC

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Package sparsebn updated to version 0.1.1 with previous version 0.1.0 dated 2019-11-04

Title: Learning Sparse Bayesian Networks from High-Dimensional Data
Description: Fast methods for learning sparse Bayesian networks from high-dimensional data using sparse regularization, as described in Aragam, Gu, and Zhou (2017) <arXiv:1703.04025>. Designed to handle mixed experimental and observational data with thousands of variables with either continuous or discrete observations.
Author: Bryon Aragam [aut, cre], Jiaying Gu [aut], Dacheng Zhang [aut], Qing Zhou [aut]
Maintainer: Bryon Aragam <sparsebn@gmail.com>

Diff between sparsebn versions 0.1.0 dated 2019-11-04 and 0.1.1 dated 2020-09-10

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Package liver updated to version 1.1 with previous version 1.0 dated 2020-08-18

Title: "Eating the Liver of Data Science"
Description: Provides a collection of helper functions that make various techniques from data science more user-friendly for non-experts. In this way, our aim is to allow non-experts to become familiar with the techniques with only a minimal level of coding knowledge. Indeed, following an ancient Persian idiom, we refer to this as "eating the liver of data science" which could be interpreted as "getting intimately close with data science". Examples of procedures we include are: data partitioning for out-of-sample testing, computing Mean Squared Error (MSE) for quantifying prediction accuracy, and data transformation (z-score and min-max). Besides such helper functions, the package also includes several interesting datasets that are useful for multivariate analysis.
Author: Reza Mohammadi [aut, cre] (<https://orcid.org/0000-0001-9538-0648>), Kevin Burke [aut]
Maintainer: Reza Mohammadi <a.mohammadi@uva.nl>

Diff between liver versions 1.0 dated 2020-08-18 and 1.1 dated 2020-09-10

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New package crossmap with initial version 0.1.0
Package: crossmap
Title: Apply Functions to All Combinations of List Elements
Version: 0.1.0
Authors@R: person(given = "Alexander", family = "Rossell Hayes", role = c("aut", "cre", "cph"), email = "alexander@rossellhayes.com", comment = c(ORCID = "0000-0001-9412-0457"))
Description: Provides an extension to the 'purrr' family of mapping functions to apply a function to each combination of elements in a list of inputs. Also includes functions for automatically detecting output type in mapping functions, finding every combination of elements of lists or rows of data frames, and applying multiple models to multiple subsets of a dataset.
License: MIT + file LICENSE
URL: https://github.com/rossellhayes/crossmap
BugReports: https://github.com/rossellhayes/crossmap/issues
Imports: purrr, rlang
Suggests: broom, covr, crayon, dplyr (>= 1.0.0), furrr, future, stats, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Collate: 'errors.R' 'autonames.R' 'isFALSE.R' 'cross_fit.R' 'cross_join.R' 'cross_list.R' 'crossmap-package.R' 'future_map_vec.R' 'future_xmap.R' 'future_xmap_mat.R' 'map_vec.R' 'vectorize.R' 'xmap.R' 'xmap_mat.R'
NeedsCompilation: no
Packaged: 2020-09-02 22:52:45 UTC; Alex
Author: Alexander Rossell Hayes [aut, cre, cph] (<https://orcid.org/0000-0001-9412-0457>)
Maintainer: Alexander Rossell Hayes <alexander@rossellhayes.com>
Repository: CRAN
Date/Publication: 2020-09-10 10:10:03 UTC

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New package PSSIM with initial version 0.1.0
Package: PSSIM
Type: Package
Title: Test of Independence & Image Structural Similarity Measure PSSIM
Version: 0.1.0
Author: Luann C. Jung, Haiyan Wang, Diego Maldonado, Sharad Silwal, Siti Tolos, Suojin Wang
Maintainer: Haiyan Wang <hwang@ksu.edu>
Description: Test-based Image structural similarity measure and test of independence. This package implements the key functions of two tasks: (1) computing image structural similarity measure PSSIM of Wang, Maldonado and Silwal (2011) <DOI:10.1016/j.csda.2011.04.021>; and (2) test of independence between a response and a covariate in presence of heteroscedastic treatment effects proposed by Wang, Tolos, and Wang (2010) <DOI:10.1002/cjs.10068>.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.5.0)
Imports: stats, parallel
NeedsCompilation: no
Packaged: 2020-09-02 20:06:16 UTC; hwang
Repository: CRAN
Date/Publication: 2020-09-10 09:50:03 UTC

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New package personalized2part with initial version 0.0.1
Package: personalized2part
Type: Package
Title: Two-Part Estimation of Treatment Rules for Semi-Continuous Data
Version: 0.0.1
Authors@R: c( person("Jared", "Huling", role = c("aut", "cre"), email = "jaredhuling@gmail.com", comment = c(ORCID = "0000-0003-0670-4845")) )
Description: Implements the methodology of Huling, Smith, and Chen (2020) <doi:10.1080/01621459.2020.1801449>, which allows for subgroup identification for semi-continuous outcomes by estimating individualized treatment rules. It uses a two-part modeling framework to handle semi-continuous data by separately modeling the positive part of the outcome and an indicator of whether each outcome is positive, but still results in a single treatment rule. High dimensional data is handled with a cooperative lasso penalty, which encourages the coefficients in the two models to have the same sign.
URL: https://github.com/jaredhuling/personalized2part
BugReports: https://github.com/jaredhuling/personalized2part/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: personalized, HDtweedie
LinkingTo: Rcpp, RcppEigen
Imports: Rcpp, foreach, methods
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-09-02 20:55:06 UTC; jared
Author: Jared Huling [aut, cre] (<https://orcid.org/0000-0003-0670-4845>)
Maintainer: Jared Huling <jaredhuling@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-10 10:00:03 UTC

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Package mlr3fselect updated to version 0.2.1 with previous version 0.2.0 dated 2020-08-23

Title: Feature Selection for 'mlr3'
Description: Implements methods for feature selection with 'mlr3', e.g. random search and sequential selection. Various termination criteria can be set and combined. The class 'AutoFSelect' provides a convenient way to perform nested resampling in combination with 'mlr3'.
Author: Marc Becker [aut, cre] (<https://orcid.org/0000-0002-8115-0400>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>)
Maintainer: Marc Becker <marcbecker@posteo.de>

Diff between mlr3fselect versions 0.2.0 dated 2020-08-23 and 0.2.1 dated 2020-09-10

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Package memapp updated to version 2.14 with previous version 2.13 dated 2019-06-04

Title: The Moving Epidemic Method Web Application
Description: The Moving Epidemic Method, created by T Vega and JE Lozano (2012, 2015) <doi:10.1111/j.1750-2659.2012.00422.x>, <doi:10.1111/irv.12330>, allows the weekly assessment of the epidemic and intensity status to help in routine respiratory infections surveillance in health systems. Allows the comparison of different epidemic indicators, timing and shape with past epidemics and across different regions or countries with different surveillance systems. Also, it gives a measure of the performance of the method in terms of sensitivity and specificity of the alert week. 'memapp' is a web application created in the Shiny framework for the 'mem' R package.
Author: Jose E. Lozano [aut, cre]
Maintainer: Jose E. Lozano <lozalojo@gmail.com>

Diff between memapp versions 2.13 dated 2019-06-04 and 2.14 dated 2020-09-10

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New package cms with initial version 0.1.0
Package: cms
Type: Package
Title: Calculate Medicare Reimbursement
Version: 0.1.0
Authors@R: c(person(given = "Vigneshwar", family = "Subramanian", role = c("aut", "cre"), email = "vs347@cornell.edu"), person(given = "Raoul", family = "Wadhwa", role = "aut", email = "raoulwadhwa@gmail.com"), person(given = "Milind", family = "Desai", role = "ctb"))
Description: Uses the 'CMS' application programming interface <https://dnav.cms.gov/api/healthdata> to provide users databases containing yearly Medicare reimbursement rates in the United States. Data can be acquired for the entire United States or only for specific localities. Currently, support is only provided for the Medicare Physician Fee Schedule, but support will be expanded for other 'CMS' databases in future versions.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: assertthat (>= 0.2), dplyr (>= 0.8), magrittr (>= 1.5), readr (>= 1.3), rlang (>= 0.4), rvest (>= 0.3), utils (>= 3.6), xml2 (>= 1.3)
URL: https://github.com/subramv/cms
BugReports: https://github.com/subramv/cms/issues
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-02 16:59:14 UTC; Vigu
Author: Vigneshwar Subramanian [aut, cre], Raoul Wadhwa [aut], Milind Desai [ctb]
Maintainer: Vigneshwar Subramanian <vs347@cornell.edu>
Repository: CRAN
Date/Publication: 2020-09-10 09:20:09 UTC

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New package seededlda with initial version 0.5
Package: seededlda
Type: Package
Title: Seeded-LDA for Topic Modeling
Version: 0.5
Authors@R: c(person("Kohei", "Watanabe", email = "watanabe.kohei@gmail.com", role = c("aut", "cre", "cph")), person("Phan", "Xuan-Hieu", email = "pxhieu@gmail.com", role = c("aut", "cph"), comment = "GibbsLDA++"))
Description: Implements the seeded-LDA model (Lu, Ott, Cardie & Tsou 2010) <doi:10.1109/ICDMW.2011.125> using the quanteda package and the GibbsLDA++ library for semisupervised topic modeling. Seeded-LDA allows users to pre-define topics with keywords to perform theory-driven analysis of textual data in social sciences and humanities (Watanabe & Zhou 2020) <doi:10.1177/0894439320907027>.
License: GPL-3
URL: https://github.com/koheiw/seededlda
BugReports: https://github.com/koheiw/seededlda/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), quanteda (> 2.0), methods
Imports: Matrix
LinkingTo: Rcpp, RcppParallel, RcppArmadillo (>= 0.7.600.1.0), quanteda
Suggests: testthat, quanteda.textmodels
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-09-02 16:12:31 UTC; kohei
Author: Kohei Watanabe [aut, cre, cph], Phan Xuan-Hieu [aut, cph] (GibbsLDA++)
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-10 09:00:03 UTC

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New package rbace with initial version 0.2.0
Package: rbace
Type: Package
Title: 'Bielefeld' Academic Search Engine ('BASE') Client
Description: Interface to the API for the 'Bielefeld' Academic Search Engine ('BASE') (<https://www.base-search.net/>). 'BASE' is a search engine for more than 150 million scholarly documents from more than 7000 sources. Methods are provided for searching for documents, as well as getting information on higher level groupings of documents: collections and repositories within collections. Search includes faceting, so you can get a high level overview of number of documents across a given variable (e.g., year). 'BASE' asks users to respect a rate limit, but does not enforce it themselves; we enforce that rate limit.
Version: 0.2.0
Authors@R: c(person("Scott", "Chamberlain", role = c("aut", "cre"), email = "myrmecocystus@gmail.com", comment = c(ORCID="0000-0003-1444-9135")))
License: MIT + file LICENSE
URL: https://docs.ropensci.org/rbace/, https://github.com/ropensci/rbace
BugReports: https://github.com/ropensci/rbace/issues
Encoding: UTF-8
Language: en-US
LazyLoad: yes
Imports: crul, xml2, data.table, tibble
Suggests: testthat, vcr, webmockr
RoxygenNote: 7.1.1
X-schema.org-applicationCategory: Literature
X-schema.org-keywords: text-ming, literature, scholarly, citations, search
X-schema.org-isPartOf: https://ropensci.org
NeedsCompilation: no
Packaged: 2020-09-02 15:32:14 UTC; sckott
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-10 09:00:07 UTC

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New package multiclassPairs with initial version 0.1.6
Package: multiclassPairs
Type: Package
Title: Build MultiClass Pair-Based Classifiers using TSPs or RF
Version: 0.1.6
Author: Nour-al-dain Marzouka
Maintainer: Nour-al-dain Marzouka <Nour-al-dain.Marzouka@med.lu.se>
Description: A toolbox to train a single sample classifier that uses in-sample feature relationships. The relationships are represented as feature1 < feature2 (e.g. gene1 < gene2). We provide two options to go with. First is based on 'switchBox' package which uses Top-score pairs algorithm. Second is a novel implementation based on random forest algorithm. For simple problems we recommend to use one-vs-rest using TSP option due to its simplicity and for being easy to interpret. For complex problems RF performs better. Both lines filter the features first then combine the filtered features to make the list of all the possible rules (i.e. rule1: feature1 < feature2, rule2: feature1 < feature3, etc...). Then the list of rules will be filtered and the most important and informative rules will be kept. The informative rules will be assembled in an one-vs-rest model or in an RF model. We provide a detailed description with each function in this package to explain the filtration and training methodology in each line.
License: GPL (>= 2)
Encoding: UTF-8
biocViews: Classification
Depends: R (>= 4.0.0)
Imports: methods, utils, stats, graphics, grDevices, ranger, Boruta, dunn.test, Biobase, switchBox
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-02 12:44:02 UTC; no5462ma
Repository: CRAN
Date/Publication: 2020-09-10 08:40:02 UTC

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Package MASSTIMATE updated to version 2.0-1 with previous version 2.0 dated 2020-09-03

Title: Body Mass Estimation Equations for Vertebrates
Description: Estimation equations are from a variety of sources and associated error estimation.
Author: Nicolas E. Campione
Maintainer: Nicolas E. Campione <ncampion@une.edu.au>

Diff between MASSTIMATE versions 2.0 dated 2020-09-03 and 2.0-1 dated 2020-09-10

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Package fastTextR updated to version 2.0.0 with previous version 1.0 dated 2017-05-12

Title: An Interface to the 'fastText' Library
Description: An interface to the 'fastText' library <https://github.com/facebookresearch/fastText>. The package can be used for text classification and to learn word vectors. An example how to use 'fastTextR' can be found in the 'README' file.
Author: Florian Schwendinger [aut], Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>

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Package stressaddition updated to version 3.0.2 with previous version 3.0.1 dated 2020-08-03

Title: Modelling Tri-Phasic Concentration-Response Relationships
Description: The stress addition approach is an alternative to the traditional concentration addition or effect addition models. It allows the modelling of tri-phasic concentration-response relationships either as single toxicant experiments, in combination with an environmental stressor or as mixtures of two toxicants. See Liess et al. (2019) <doi:10.1038/s41598-019-51645-4>.
Author: Sebastian Henz [aut, cre] (<https://orcid.org/0000-0001-8299-8852>), Matthias Liess [aut] (<https://orcid.org/0000-0002-3321-8909>), Naeem Shahid [ctb] (<https://orcid.org/0000-0001-6581-1654>), Helmholtz-Zentrum fuer Umweltforschung GmbH - UFZ [cph, fnd]
Maintainer: Sebastian Henz <bastihz.dev@posteo.de>

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Package shinybusy updated to version 0.2.1 with previous version 0.2.0 dated 2019-10-29

Title: Busy Indicator for 'Shiny' Applications
Description: Add indicators (spinner, progress bar, gif) in your 'shiny' applications to show the user that the server is busy.
Author: Fanny Meyer [aut], Victor Perrier [aut, cre], Silex Technologies [fnd] (https://www.silex-ip.com)
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>

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Package Require updated to version 0.0.8 with previous version 0.0.7 dated 2020-08-18

Title: Installing and Loading R Packages for Reproducible Workflows
Description: A single key function, 'Require' that wraps 'install.packages', 'remotes::install_github', 'versions::install.versions', and 'base::require' that allows for reproducible workflows. As with other functions in a reproducible workflow, this package emphasizes functions that return the same result whether it is the first or subsequent times running the function. Maturing.
Author: Eliot J B McIntire [aut, cre] (<https://orcid.org/0000-0002-6914-8316>), Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada [cph]
Maintainer: Eliot J B McIntire <eliot.mcintire@canada.ca>

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Package NBDesign updated to version 2.0.0 with previous version 1.0.0 dated 2018-11-19

Title: Design and Monitoring of Clinical Trials with Negative Binomial Endpoint
Description: Calculate various functions needed for design and monitoring clinical trials with negative binomial endpoint with variable follow-up. This version has a few changes compared to the previous version 1.0.0, including (1) correct a typo in Type 1 censoring, mtbnull=bnull and (2) restructure the code to account for shape parameter equal to zero, i.e. Poisson scenario.
Author: Xiaodong Luo [aut, cre], Sanofi [cph]
Maintainer: Xiaodong Luo <Xiaodong.Luo@sanofi.com>

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Package KoulMde updated to version 3.2.1 with previous version 3.2.0 dated 2020-09-09

Title: Koul's Minimum Distance Estimation in Regression and Image Segmentation Problems
Description: Many methods are developed to deal with two major statistical problems: image segmentation and nonparametric estimation in various regression models. Image segmentation is nowadays gaining a lot of attention from various scientific subfields. Especially, image segmentation has been popular in medical research such as magnetic resonance imaging (MRI) analysis. When a patient suffers from some brain diseases such as dementia and Parkinson's disease, those diseases can be easily diagnosed in brain MRI: the area affected by those diseases is brightly expressed in MRI, which is called a white lesion. For the purpose of medical research, locating and segment those white lesions in MRI is a critical issue; it can be done manually. However, manual segmentation is very expensive in that it is error-prone and demands a huge amount of time. Therefore, supervised machine learning has emerged as an alternative solution. Despite its powerful performance in a classification problem such as hand-written digits, supervised machine learning has not shown the same satisfactory result in MRI analysis. Setting aside all issues of the supervised machine learning, it exposed a critical problem when employed for MRI analysis: it requires time-consuming data labeling. Thus, there is a strong demand for an unsupervised approach, and this package - based on Hira L. Koul (1986) <DOI:10.1214/aos/1176350059> - proposes an efficient method for simple image segmentation - here, "simple" means that an image is black-and-white - which can easily be applied to MRI analysis. This package includes a function GetSegImage(): when a black-and-white image is given as an input, GetSegImage() separates an area of white pixels - which corresponds to a white lesion in MRI - from the given image. For the second problem, consider linear regression model and autoregressive model of order q where errors in the linear regression model and innovations in the autoregression model are independent and symmetrically distributed. Hira L. Koul (1986) <DOI:10.1214/aos/1176350059> proposed a nonparametric minimum distance estimation method by minimizing L2-type distance between certain weighted residual empirical processes. He also proposed a simpler version of the loss function by using symmetry of the integrating measure in the distance. Kim (2018) <DOI:10.1080/00949655.2017.1392527> proposed a fast computational method which enables practitioners to compute the minimum distance estimator of the vector of general multiple regression parameters for several integrating measures. This package contains three functions: KoulLrMde(), KoulArMde(), and Koul2StageMde(). The former two provide minimum distance estimators for linear regression model and autoregression model, respectively, where both are based on Koul's method. These two functions take much less time for the computation than those based on parametric minimum distance estimation methods. Koul2StageMde() provides estimators for regression and autoregressive coefficients of linear regression model with autoregressive errors through minimum distant method of two stages. The new version is written in Rcpp and dramatically reduces computational time.
Author: Jiwoong Kim <jwboys26 at gmail.com>
Maintainer: Jiwoong Kim <jwboys26@gmail.com>

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Package hadron updated to version 3.1.2 with previous version 3.1.0 dated 2020-07-05

Title: Analysis Framework for Monte Carlo Simulation Data in Physics
Description: Toolkit to perform statistical analyses of correlation functions generated from Lattice Monte Carlo simulations. In particular, a class 'cf' for correlation functions and methods to analyse those are defined. This includes (blocked) bootstrap (based on the 'boot' package) and jackknife, but also an automatic determination of integrated autocorrelation times. 'hadron' also provides a very general function bootstrap.nlsfit() to bootstrap a non-linear least squares fit. More specific functions are provided to extract hadronic quantities from Lattice Quantum Chromodynamics simulations, a particular Monte Carlo simulation,(see e.g. European Twisted Mass Collaboration, P. Boucaud et al. (2008) <doi:10.1016/j.cpc.2008.06.013>). Here, to determine energy eigenvalues of hadronic states, specific fitting routines and in particular the generalised eigenvalue method (see e.g. B. Blossier et al. (2009) <doi:10.1088/1126-6708/2009/04/094> and M. Fischer et al. (2020) <https://inspirehep.net/literature/1792113>) are implemented. In addition, input/output and plotting routines are available.
Author: Bartosz Kostrzewa [aut], Johann Ostmeyer [aut], Martin Ueding [aut], Carsten Urbach [aut, cre], Nikolas Schlage [ctb], Markus Werner [ctb], Ferenc Pittler [ctb], Matthias Fischer [ctb], Vittorio Lubicz [ctb]
Maintainer: Carsten Urbach <urbach@hiskp.uni-bonn.de>

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Package CCAMLRGIS updated to version 3.0.6 with previous version 3.0.5 dated 2020-07-30

Title: Antarctic Spatial Data Manipulation
Description: Loads and creates spatial data, including layers and tools that are relevant to the activities of the Commission for the Conservation of Antarctic Marine Living Resources. Provides two categories of functions: load functions and create functions. Load functions are used to import existing spatial layers from the online CCAMLR GIS such as the ASD boundaries. Create functions are used to create layers from user data such as polygons and grids.
Author: Stephane Thanassekos [aut, cre], Keith Reid [aut], Lucy Robinson [aut], Michael D. Sumner [ctb], Roger Bivand [ctb]
Maintainer: Stephane Thanassekos <stephane.thanassekos@ccamlr.org>

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Package autoFRK (with last version 1.3.2) was removed from CRAN

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

2020-09-09 1.3.2
2020-08-26 1.3.1
2020-05-27 1.3.0
2019-12-11 1.2.0
2019-03-29 1.1.0
2018-04-05 1.0.0

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Package tradestatistics (with last version 1.0) was removed from CRAN

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

2020-04-03 1.0
2019-12-04 0.2.7
2019-09-19 0.2.5
2019-09-17 0.2.4
2019-08-28 0.2.3
2019-04-21 0.2
2019-04-06 0.1

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Package rmdcev (with last version 1.2.0) was removed from CRAN

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

2020-08-14 1.2.0
2019-11-22 1.1.1
2019-06-21 0.9.0

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Package o2geosocial (with last version 1.0.0) was removed from CRAN

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2020-08-26 1.0.0

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