Sat, 18 Jul 2020

Package MVNtestchar updated to version 1.1.2 with previous version 1.1.0 dated 2020-07-03

Title: Test for Multivariate Normal Distribution Based on a Characterization
Description: Provides a test of multivariate normality of an unknown sample that does not require estimation of the nuisance parameters, the mean and covariance matrix. Rather, a sequence of transformations removes these nuisance parameters and results in a set of sample matrices that are positive definite. These matrices are uniformly distributed on the space of positive definite matrices in the unit hyper-rectangle if and only if the original data is multivariate normal (Fairweather, 1973, Doctoral dissertation, University of Washington). The package performs a goodness of fit test of this hypothesis. In addition to the test, functions in the package give visualizations of the support region of positive definite matrices for bivariate samples.
Author: William Fairweather [aut, cre]
Maintainer: William Fairweather <wrf343@flowervalleyconsulting.com>

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New package MALDIrppa with initial version 1.0.3
Package: MALDIrppa
Type: Package
Title: MALDI Mass Spectrometry Data Robust Pre-Processing and Analysis
Version: 1.0.3
Date: 2020-07-17
Author: Javier Palarea-Albaladejo
Maintainer: Javier Palarea-Albaladejo <javier.palarea@bioss.ac.uk>
Depends: R (>= 3.2.5), MALDIquant, signal, robustbase, lattice
ByteCompile: yes
Description: Provides methods for quality control and robust pre-processing and analysis of MALDI mass spectrometry data.
License: GPL (>= 2)
Repository: CRAN
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-07-18 14:16:39 UTC; Japal
Date/Publication: 2020-07-19 00:10:10 UTC

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Package immcp updated to version 0.9.1 with previous version 0.8.3 dated 2020-06-09

Title: Candidate Prescriptions Discovery Based on Pathway Fingerprint
Description: The pathway fingerprint is a method to indicate the profile of significant pathways being influenced by drugs, which may hint drug functions. Through the similarity of pathway fingerprints, the potential relationship between disease and prescription can be found. Ye (2012) <doi: 10.1007/s13238-012-2011-z>.
Author: Yuanlong Hu [aut, cre]
Maintainer: Yuanlong Hu <huyuanlong1996@163.com>

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Package dragon updated to version 1.0.1 with previous version 1.0.0 dated 2020-07-16

Title: Deep Time Redox Analysis of the Geobiology Ontology Network
Description: Create, visualize, manipulate, and analyze bipartite mineral-chemistry networks for set of focal element(s) across deep-time on Earth. The method is described in Spielman and Moore (2020) <doi:10.31223/osf.io/z7k9q>.
Author: Stephanie J. Spielman [aut, cre] (<https://orcid.org/0000-0002-9090-4788>)
Maintainer: Stephanie J. Spielman <spielman@rowan.edu>

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Package alakazam updated to version 1.0.2 with previous version 1.0.1 dated 2020-05-11

Title: Immunoglobulin Clonal Lineage and Diversity Analysis
Description: Provides methods for high-throughput adaptive immune receptor repertoire sequencing (AIRR-Seq; Rep-Seq) analysis. In particular, immunoglobulin (Ig) sequence lineage reconstruction, lineage topology analysis, diversity profiling, amino acid property analysis and gene usage. Citations: Gupta and Vander Heiden, et al (2017) <doi:10.1093/bioinformatics/btv359>, Stern, Yaari and Vander Heiden, et al (2014) <doi:10.1126/scitranslmed.3008879>.
Author: Namita Gupta [aut], Susanna Marquez [aut], Nima Nouri [aut], Ruoyi Jiang [aut], Julian Zhou [aut], Kenneth Hoehn [aut], Daniel Gadala-Maria [ctb], Jason Vander Heiden [cre, aut], Steven Kleinstein [aut, cph]
Maintainer: Jason Vander Heiden <jason.vanderheiden@gmail.com>

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Package metan updated to version 1.7.0 with previous version 1.6.1 dated 2020-06-07

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>

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Package ImpactEffectsize updated to version 0.6.0 with previous version 0.5.0 dated 2020-06-26

Title: Calculation and Visualization of the Impact Effect Size Measure
Description: A non-parametric effect size measure capturing changes in central tendency or shape of data distributions. The package provides the necessary functions to calculate and plot the Impact effect size measure between two groups.
Author: Jorn Lotsch[aut,cre], Alfred Ultsch[aut]
Maintainer: Jorn Lotsch <j.loetsch@em.uni-frankfurt.de>

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Package glmpca updated to version 0.2.0 with previous version 0.1.0 dated 2019-09-27

Title: Dimension Reduction of Non-Normally Distributed Data
Description: Implements a generalized version of principal components analysis (GLM-PCA) for dimension reduction of non-normally distributed data such as counts or binary matrices. Townes FW, Hicks SC, Aryee MJ, Irizarry RA (2019) <doi:10.1186/s13059-019-1861-6>. Townes FW (2019) <arXiv:1907.02647>.
Author: F. William Townes [aut, cre, cph], Kelly Street [aut], Jake Yeung [ctb]
Maintainer: F. William Townes <will.townes@gmail.com>

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Package sensitivity updated to version 1.22.0 with previous version 1.21.0 dated 2020-06-02

Title: Global Sensitivity Analysis of Model Outputs
Description: A collection of functions for factor screening, global sensitivity analysis and robustness analysis. Most of the functions have to be applied on model with scalar output, but several functions support multi-dimensional outputs.
Author: Bertrand Iooss, Sebastien Da Veiga, Alexandre Janon and Gilles Pujol, with contributions from Baptiste Broto, Khalid Boumhaout, Thibault Delage, Reda El Amri, Jana Fruth, Laurent Gilquin, Joseph Guillaume, Loic Le Gratiet, Paul Lemaitre, Amandine Marrel, Anouar Meynaoui, Barry L. Nelson, Filippo Monari, Roelof Oomen, Oldrich Rakovec, Bernardo Ramos, Olivier Roustant, Eunhye Song, Jeremy Staum, Roman Sueur, Taieb Touati, Frank Weber
Maintainer: Bertrand Iooss <biooss@yahoo.fr>

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Package gramEvol updated to version 2.1-4 with previous version 2.1-3 dated 2016-07-04

Title: Grammatical Evolution for R
Description: A native R implementation of grammatical evolution (GE). GE facilitates the discovery of programs that can achieve a desired goal. This is done by performing an evolutionary optimisation over a population of R expressions generated via a user-defined context-free grammar (CFG) and cost function.
Author: Farzad Noorian, Anthony Mihirana de Silva
Maintainer: Farzad Noorian <farzad.noorian@gmail.com>

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Package CsChange updated to version 0.1.6 with previous version 0.1.5 dated 2018-12-11

Title: Testing for Change in C-Statistic
Description: Calculate the confidence interval and p value for change in C-statistic. The adjusted C-statistic is calculated by using formula as "Somers' Dxy rank correlation"/2+0.5. The confidence interval was calculated by using the bootstrap method. The p value was calculated by using the Z testing method. Please refer to the article of Peter Ganz et al. (2016) <doi:10.1001/jama.2016.5951>.
Author: Zhicheng Du, Yuantao Hao
Maintainer: Zhicheng Du<dgdzc@hotmail.com>

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Package varycoef updated to version 0.2.12 with previous version 0.2.11 dated 2020-04-14

Title: Modeling Spatially Varying Coefficients
Description: Implements a maximum likelihood estimation (MLE) method for estimation and prediction in spatially varying coefficient (SVC) models (Dambon et al. (2020) <arXiv:2001.08089>). Covariance tapering (Furrer et al. (2006) <doi:10.1198/106186006X132178>) can be applied such that the method scales to large data.
Author: Jakob A. Dambon [aut, cre] (<https://orcid.org/0000-0001-5855-2017>), Fabio Sigrist [ctb] (<https://orcid.org/0000-0002-3994-2244>), Reinhard Furrer [ctb] (<https://orcid.org/0000-0002-6319-2332>)
Maintainer: Jakob A. Dambon <jakob.dambon@math.uzh.ch>

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 varycoef-0.2.12/varycoef/man/fullSVC_reggrid.Rd      |   47 +-
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 varycoef-0.2.12/varycoef/man/residuals.SVC_mle.Rd    |    6 
 varycoef-0.2.12/varycoef/vignettes/example.html.asis |    2 
 24 files changed, 634 insertions(+), 364 deletions(-)

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Package tint updated to version 0.1.3 with previous version 0.1.2 dated 2019-04-19

Title: 'tint' is not 'Tufte'
Description: A 'tufte'-alike style for 'rmarkdown'. A modern take on the 'Tufte' design for pdf and html vignettes, building on the 'tufte' package with additional contributions from the 'knitr' and 'ggtufte' package, and also acknowledging the key influence of 'envisioned css'.
Author: Dirk Eddelbuettel and Jonathan Gilligan
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between tint versions 0.1.2 dated 2019-04-19 and 0.1.3 dated 2020-07-18

 ChangeLog                     |   40 +++++++++++++++++++++++++++++++++++
 DESCRIPTION                   |    8 +++----
 MD5                           |   30 ++++++++++++++------------
 R/html.R                      |   26 ++++++++++++++--------
 R/utils.R                     |    1 
 README.md                     |   20 ++++++++++++++---
 build/vignette.rds            |binary
 cleanup                       |    8 ++++---
 inst/NEWS.Rd                  |   16 ++++++++++++--
 inst/doc/tintHtmlIntro.R      |    6 ++---
 inst/doc/tintHtmlIntro.Rmd    |   13 ++++++-----
 inst/doc/tintHtmlIntro.html   |   48 ++++++++++++++++++++++++++++--------------
 inst/doc/tintPdfIntro.R       |    6 ++---
 inst/doc/tintPdfIntro.pdf     |binary
 inst/examples/tintBibDemo.Rmd |only
 inst/examples/tintBibDemo.bib |only
 vignettes/tintHtmlIntro.Rmd   |   13 ++++++-----
 17 files changed, 166 insertions(+), 69 deletions(-)

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Package drat updated to version 0.1.8 with previous version 0.1.7 dated 2020-07-10

Title: 'Drat' R Archive Template
Description: Creation and use of R Repositories via helper functions to insert packages into a repository, and to add repository information to the current R session. Two primary types of repositories are support: gh-pages at GitHub, as well as local repositories on either the same machine or a local network. Drat is a recursive acronym: Drat R Archive Template.
Author: Dirk Eddelbuettel with contributions by Carl Boettiger, Neal Fultz, Sebastian Gibb, Colin Gillespie, Jan Górecki, Matt Jones, Thomas Leeper, Steven Pav, Jan Schulz, Christoph Stepper, Felix G.M. Ernst and Patrick Schratz.
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between drat versions 0.1.7 dated 2020-07-10 and 0.1.8 dated 2020-07-18

 ChangeLog              |    8 ++++++++
 DESCRIPTION            |    8 ++++----
 MD5                    |   10 +++++-----
 README.md              |   40 ++++++++++++++++++++--------------------
 inst/NEWS.Rd           |    7 +++++++
 tests/skeleton_git2r.R |   13 ++++++++++---
 6 files changed, 54 insertions(+), 32 deletions(-)

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New package SEMsens with initial version 0.2.6
Package: SEMsens
Type: Package
Title: A Tool for Sensitivity Analysis in Structural Equation Modeling
Version: 0.2.6
Author: Walter Leite [aut], Zuchao Shen [aut]
Maintainer: Walter Leite <walter.leite@coe.ufl.edu>
Description: Perform sensitivity analysis in structural equation modeling using meta-heuristic optimization methods (e.g., ant colony optimization and others). The references for the proposed methods are: (1) Harring, J. R., McNeish, D. M., & Hancock, G. R. (2017) <doi:10.1080/10705511.2018.1506925>; (2) Socha, K., & Dorigo, M. (2008) <doi:10.1016/j.ejor.2006.06.046>. We also thank Dr. Krzysztof Socha for sharing his thesis and R code, which provided the base for the development of this package.
Imports: lavaan, stats
Depends: R (>= 4.0.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: rmarkdown, knitr
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-07-15 00:19:56 UTC; zucha
Repository: CRAN
Date/Publication: 2020-07-18 10:00:05 UTC

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New package rescue with initial version 1.0.3
Package: rescue
Type: Package
Title: Bootstrap Imputation for Single-Cell RNA-Seq Data
Version: 1.0.3
Date: 2020-07-15
Author: Sam Tracy & Ruben Dries
Maintainer: Sam Tracy <seasamgo@gmail.com>
Description: Given a log-transformed expression matrix and list of informative genes: subsample informative genes, cluster samples using shared nearest neighbors clustering, estimate missing expression values with the distribution mean of means extrapolated from these cell clusterings, and return an imputed expression matrix. See Tracy, S., Yuan, G.C. and Dries, R. (2019) <doi:10.1186/s12859-019-2977-0> for more details.
Config/reticulate: list( packages = list( list(package = "pandas"), list(package = "networkx"), list(package = "python-louvain") ) )
Depends: R (>= 3.4.0), utils
Imports: data.table, dbscan (>= 1.1-3), igraph (>= 1.2.4.1), irlba, Matrix, methods, parallel, reticulate (>= 1.14)
License: GPL-2 | GPL-3
LazyData: FALSE
URL: https://github.com/seasamgo/rescue
BugReports: http://github.com/seasamgo/rescue/issues
RoxygenNote: 7.1.1
Encoding: UTF-8
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-07-15 06:39:14 UTC; tracys2
Repository: CRAN
Date/Publication: 2020-07-18 10:00:03 UTC

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Package smicd updated to version 1.1.1 with previous version 1.1.0 dated 2020-04-30

Title: Statistical Methods for Interval-Censored Data
Description: Functions that provide statistical methods for interval-censored (grouped) data. The package supports the estimation of linear and linear mixed regression models with interval-censored dependent variables. Parameter estimates are obtained by a stochastic expectation maximization algorithm. Furthermore, the package enables the direct (without covariates) estimation of statistical indicators from interval-censored data via an iterative kernel density algorithm. Survey and Organisation for Economic Co-operation and Development (OECD) weights can be included into the direct estimation (see, Walter, P. (2019) <doi:10.17169/refubium-1621>).
Author: Paul Walter
Maintainer: Paul Walter <paul.walter@fu-berlin.de>

Diff between smicd versions 1.1.0 dated 2020-04-30 and 1.1.1 dated 2020-07-18

 DESCRIPTION                |   18 +--
 MD5                        |   82 +++++++--------
 NAMESPACE                  |    2 
 NEWS.md                    |    6 +
 R/Exam.R                   |    2 
 R/ICD.R                    |   19 +--
 R/boxcox.lm.est.R          |   35 +++---
 R/boxcox.lme.est.R         |  142 +++++++++++---------------
 R/dclassICD.R              |  240 ++++++++++++++++++++++++---------------------
 R/icc.est.R                |    3 
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 R/lambda.lm.est.R          |   55 +++++-----
 R/lambda.lme.est.R         |   48 ++++-----
 R/log.est.R                |    3 
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 R/plot.kdeAlgo.R           |  155 ++++++++++++++++-------------
 R/plot.sem.R               |  218 ++++++++++++++++++++++++----------------
 R/print.kdeAlgo.R          |    2 
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 R/sem.lm.R                 |  157 ++++++++++++++++-------------
 R/sem.lme.R                |  225 ++++++++++++++++++++++--------------------
 R/semObject.R              |   12 +-
 R/standardError.est.R      |   41 ++++---
 R/standardErrorLM.est.R    |   39 ++++---
 R/standardErrorLME.est.R   |  149 +++++++++++++++------------
 R/summary.sem.R            |  101 +++++++++++-------
 build/vignette.rds         |binary
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 man/Exam.Rd                |    2 
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 man/plot.sem.Rd            |   24 ++--
 man/semLm.Rd               |   42 ++++---
 man/semLme.Rd              |   56 +++++-----
 man/semObject.Rd           |   12 +-
 man/smicd.Rd               |   19 +--
 man/summary.sem.Rd         |    2 
 42 files changed, 1236 insertions(+), 1052 deletions(-)

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New package RenvModule with initial version 1.0
Package: RenvModule
Type: Package
Title: Interface to Allow Full Use of the Environment Modules System for Unix
Version: 1.0
Date: 2020-06-30
Author: Jordan Hayes
Maintainer: Jordan Hayes <jhayes@ucr.edu>
Description: Provides environment modules functionality, which enables use of the Environment Modules system (<http://modules.sourceforge.net/>) from within the R environment. By default the user's login shell environment (ie. "bash -l") will be used to initialize the current session. The module function can also; load or unload specific software, list all the loaded software within the current session, and list all the applications available for loading from the module system. Lastly, the module function can remove all loaded software from the current session.
License: GPL-2
NeedsCompilation: no
Packaged: 2020-07-14 23:25:07 UTC; jhayes
Repository: CRAN
Date/Publication: 2020-07-18 09:40:06 UTC

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New package modernVA with initial version 0.1.0
Package: modernVA
Type: Package
Title: An Implementation of Two Modern Education-Based Value-Added Models
Version: 0.1.0
Authors@R: c( person(given = "Garritt", family = "L. Page", email = "page@stat.byu.edu", role = c("aut", "cre", "cph")), person(given = "S. McKay", family = "Curtis", email = "s.mckay.curtis@gmail.com", role = c("ctb", "cph")), person(given = "Radford M. Neal", family = "Neal", role = c("ctb", "cph")))
Maintainer: Garritt L. Page <page@stat.byu.edu>
Description: Provides functions that fit two modern education-based value-added models. One of these models is the quantile value-added model. This model permits estimating a school's value-added based on specific quantiles of the post-test distribution. Estimating value-added based on quantiles of the post-test distribution provides a more complete picture of an education institution's contribution to learning for students of all abilities. See Page, G.L.; San Martín, E.; Orellana, J.; Gonzalez, J. (2017) <doi:10.1111/rssa.12195> for more details. The second model is a temporally dependent value-added model. This model takes into account the temporal dependence that may exist in school performance between two cohorts in one of two ways. The first is by modeling school random effects with a non-stationary AR(1) process. The second is by modeling school effects based on previous cohort's post-test performance. In addition to more efficiently estimating value-added, this model permits making statements about the persistence of a schools effectiveness. The standard value-added model is also an option.
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-07-15 00:27:32 UTC; gpage
Author: Garritt L. Page [aut, cre, cph], S. McKay Curtis [ctb, cph], Radford M. Neal Neal [ctb, cph]
Repository: CRAN
Date/Publication: 2020-07-18 09:50:06 UTC

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Package mlr3filters updated to version 0.3.0 with previous version 0.2.0 dated 2020-03-12

Title: Filter Based Feature Selection for 'mlr3'
Description: Extends 'mlr3' with filter methods for feature selection. Besides standalone filter methods built-in methods of any machine-learning algorithm are supported. Partial scoring of multivariate filter methods is supported.
Author: Patrick Schratz [aut, cre] (<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>), Martin Binder [aut]
Maintainer: Patrick Schratz <patrick.schratz@gmail.com>

Diff between mlr3filters versions 0.2.0 dated 2020-03-12 and 0.3.0 dated 2020-07-18

 mlr3filters-0.2.0/mlr3filters/man/mlr_filters_variable_importance.Rd      |only
 mlr3filters-0.3.0/mlr3filters/DESCRIPTION                                 |   14 
 mlr3filters-0.3.0/mlr3filters/MD5                                         |  120 +--
 mlr3filters-0.3.0/mlr3filters/NAMESPACE                                   |    2 
 mlr3filters-0.3.0/mlr3filters/NEWS.md                                     |   21 
 mlr3filters-0.3.0/mlr3filters/R/Filter.R                                  |  310 +++++-----
 mlr3filters-0.3.0/mlr3filters/R/FilterAUC.R                               |    7 
 mlr3filters-0.3.0/mlr3filters/R/FilterAnova.R                             |    7 
 mlr3filters-0.3.0/mlr3filters/R/FilterCMIM.R                              |    6 
 mlr3filters-0.3.0/mlr3filters/R/FilterCarScore.R                          |   11 
 mlr3filters-0.3.0/mlr3filters/R/FilterCorrelation.R                       |   16 
 mlr3filters-0.3.0/mlr3filters/R/FilterDISR.R                              |    7 
 mlr3filters-0.3.0/mlr3filters/R/FilterFindCorrelation.R                   |   16 
 mlr3filters-0.3.0/mlr3filters/R/FilterImportance.R                        |    9 
 mlr3filters-0.3.0/mlr3filters/R/FilterInformationGain.R                   |   10 
 mlr3filters-0.3.0/mlr3filters/R/FilterJMI.R                               |    7 
 mlr3filters-0.3.0/mlr3filters/R/FilterJMIM.R                              |    7 
 mlr3filters-0.3.0/mlr3filters/R/FilterKruskalTest.R                       |   14 
 mlr3filters-0.3.0/mlr3filters/R/FilterMIM.R                               |    7 
 mlr3filters-0.3.0/mlr3filters/R/FilterMRMR.R                              |    7 
 mlr3filters-0.3.0/mlr3filters/R/FilterNJMIM.R                             |    7 
 mlr3filters-0.3.0/mlr3filters/R/FilterPerformance.R                       |   16 
 mlr3filters-0.3.0/mlr3filters/R/FilterPermutation.R                       |only
 mlr3filters-0.3.0/mlr3filters/R/FilterVariance.R                          |   13 
 mlr3filters-0.3.0/mlr3filters/R/flt.R                                     |    9 
 mlr3filters-0.3.0/mlr3filters/R/mlr_filters.R                             |   84 +-
 mlr3filters-0.3.0/mlr3filters/R/reexports.R                               |   18 
 mlr3filters-0.3.0/mlr3filters/R/zzz.R                                     |   27 
 mlr3filters-0.3.0/mlr3filters/README.md                                   |   42 -
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 mlr3filters-0.3.0/mlr3filters/man/mlr_filters_jmi.Rd                      |    6 
 mlr3filters-0.3.0/mlr3filters/man/mlr_filters_jmim.Rd                     |    6 
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 mlr3filters-0.3.0/mlr3filters/man/mlr_filters_mim.Rd                      |    6 
 mlr3filters-0.3.0/mlr3filters/man/mlr_filters_mrmr.Rd                     |    6 
 mlr3filters-0.3.0/mlr3filters/man/mlr_filters_njmim.Rd                    |    6 
 mlr3filters-0.3.0/mlr3filters/man/mlr_filters_performance.Rd              |   14 
 mlr3filters-0.3.0/mlr3filters/man/mlr_filters_permutation.Rd              |only
 mlr3filters-0.3.0/mlr3filters/man/mlr_filters_variance.Rd                 |    8 
 mlr3filters-0.3.0/mlr3filters/tests/testthat.R                            |    8 
 mlr3filters-0.3.0/mlr3filters/tests/testthat/helper.R                     |    6 
 mlr3filters-0.3.0/mlr3filters/tests/testthat/setup.R                      |   24 
 mlr3filters-0.3.0/mlr3filters/tests/testthat/teardown.R                   |    4 
 mlr3filters-0.3.0/mlr3filters/tests/testthat/test_FilterFindCorrelation.R |   10 
 mlr3filters-0.3.0/mlr3filters/tests/testthat/test_FilterImportance.R      |   18 
 mlr3filters-0.3.0/mlr3filters/tests/testthat/test_filter.R                |   64 +-
 mlr3filters-0.3.0/mlr3filters/tests/testthat/test_filter_classif.R        |    5 
 mlr3filters-0.3.0/mlr3filters/tests/testthat/test_filter_regr.R           |    4 
 mlr3filters-0.3.0/mlr3filters/tests/testthat/test_mlr_filters.R           |   10 
 mlr3filters-0.3.0/mlr3filters/tests/testthat/test_partial_scoring.R       |    4 
 63 files changed, 694 insertions(+), 530 deletions(-)

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New package lmtp with initial version 0.0.5
Package: lmtp
Title: Non-Parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies
Version: 0.0.5
Authors@R: c(person(given = "Nicholas", family = "Williams", role = c("aut", "cre", "cph"), email = "niw4001@med.cornell.edu", comment = c(ORCID = "0000-0002-1378-4831")), person(given = "Iván", family = "Díaz", email = "ild2005@med.cornell.edu", role = c("aut", "cph"), comment = c(ORCID = "0000-0001-9056-2047")))
Description: Non-parametric estimators for casual effects based on longitudinal modified treatment policies as described in Diaz, Williams, and Hoffman (<arXiv:2006.01366>), traditional point treatment, and traditional longitudinal effects. Continuous, binary, and categorical treatments are allowed as well are censored outcomes. The treatment mechanism is estimated via a density ratio classification procedure irrespective of treatment variable type. For both continuous and binary outcomes, additive treatment effects can be calculated and relative risks and odds ratios may be calculated for binary outcomes. Estimation is enhanced using the Super Learner from 'sl3' available for download from GitHub using 'remotes::install_github("tlverse/sl3@devel")'.
Depends: R (>= 2.10)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: slider, stats, nnls, cli, utils, R6, generics, origami, future (>= 1.17.0), progressr
Suggests: testthat (>= 2.1.0), covr, rmarkdown, knitr, ranger, twang
Enhances: sl3 (>= 1.3.7)
NeedsCompilation: no
Packaged: 2020-07-14 15:45:39 UTC; Nick
Author: Nicholas Williams [aut, cre, cph] (<https://orcid.org/0000-0002-1378-4831>), Iván Díaz [aut, cph] (<https://orcid.org/0000-0001-9056-2047>)
Maintainer: Nicholas Williams <niw4001@med.cornell.edu>
Repository: CRAN
Date/Publication: 2020-07-18 09:10:02 UTC

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New package labourR with initial version 1.0.0
Package: labourR
Type: Package
Title: Classify Multilingual Labour Market Free-Text to Standardized Hierarchical Occupations
Version: 1.0.0
Authors@R: c( person("Alexandros", "Kouretsis", email = "ako@eworx.gr", role = c("aut", "cre")), person("Andreas", "Bampouris", email = "aba@eworx.gr", role = "aut"), person("Petros", "Morfiris", email = "pem@eworx.gr", role = "aut"), person("Konstantinos", "Papageorgiou", email = "melt@eworx.gr", role = "aut"), person("Stavros", "Ladas", email = "sl@eworx.gr", role = "ctb"), person("Athanassios", "Siaperas", email = "athanassios.siaperas@cedefop.europa.eu", role = "ctb"), person("Philippe", "Tissot", email = "philippe.tissot@cedefop.europa.eu", role = "ctb"), person("Nikos", "Vaslamatzis", email = "nfv@eworx.gr", role = "ctb"), person("Eworx S.A", role = "cph") )
Description: Allows the user to map multilingual free-text of occupations to a broad range of standardized classifications. The package facilitates automatic occupation coding (see, e.g., Gweon et al. (2017) <doi:10.1515/jos-2017-0006> and Turrell et al. (2019) <doi:10.3386/w25837>), where the ISCO to ESCO mapping is exploited to extend the occupations hierarchy, Le Vrang et al. (2014) <doi:10.1109/mc.2014.283>. Document vectorization is performed using the multilingual ESCO corpus. A method based on the nearest neighbor search is used to suggest the closest ISCO occupation.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
URL: https://github.com/AleKoure/labourR
BugReports: https://github.com/AleKoure/labourR/issues
Suggests: knitr, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
Depends: R (>= 3.1.0)
Imports: data.table, cld2, magrittr, stopwords, stringdist
NeedsCompilation: no
Packaged: 2020-07-14 17:03:19 UTC; ale
Author: Alexandros Kouretsis [aut, cre], Andreas Bampouris [aut], Petros Morfiris [aut], Konstantinos Papageorgiou [aut], Stavros Ladas [ctb], Athanassios Siaperas [ctb], Philippe Tissot [ctb], Nikos Vaslamatzis [ctb], Eworx S.A [cph]
Maintainer: Alexandros Kouretsis <ako@eworx.gr>
Repository: CRAN
Date/Publication: 2020-07-18 09:30:07 UTC

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New package hacksaw with initial version 0.0.1
Package: hacksaw
Title: Additional Tools for Splitting and Cleaning Data
Version: 0.0.1
Authors@R: person(given = "David", family = "Ranzolin", role = c("aut", "cre", "cph"), email = "daranzolin@gmail.com")
Description: Move between data frames and lists more efficiently with precision splitting via 'dplyr' verbs. Easily cast variables to different data types. Keep rows with NAs. Shift row values.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: dplyr, purrr, rlang, utils, tidyselect, tibble, zeallot, magrittr
Suggests: testthat, knitr, rmarkdown, tidyr
NeedsCompilation: no
Packaged: 2020-07-14 18:57:57 UTC; davidranzolin
Author: David Ranzolin [aut, cre, cph]
Maintainer: David Ranzolin <daranzolin@gmail.com>
Repository: CRAN
Date/Publication: 2020-07-18 09:40:02 UTC

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New package FertBoot with initial version 0.4.0
Package: FertBoot
Type: Package
Title: Fertilizer Response Curve Analysis by Bootstrapping Residuals
Version: 0.4.0
Authors@R: c(person("Ting Fung (Ralph)", "Ma", email = "tingfung.ma@wisc.edu", role = c("cre", "aut")), person("Hannah", "Francis", email = "hrfrancis@wisc.edu", role = "aut"), person("Matt", "Ruark", role = "ctb"))
Maintainer: Ting Fung (Ralph) Ma <tingfung.ma@wisc.edu>
Description: Quantify variability (such as confidence interval) of fertilizer response curves and optimum fertilizer rates using bootstrapping residuals with several popular non-linear and linear models.
Imports: stats, nls.multstart, simpleboot
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-07-14 17:17:17 UTC; Ralph
Author: Ting Fung (Ralph) Ma [cre, aut], Hannah Francis [aut], Matt Ruark [ctb]
Repository: CRAN
Date/Publication: 2020-07-18 09:32:17 UTC

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New package fastkmedoids with initial version 1.0
Package: fastkmedoids
Type: Package
Title: Faster K-Medoids Clustering Algorithms: FastPAM, FastCLARA, FastCLARANS
Version: 1.0
Date: 2020-07-13
Author: Xun Li
Maintainer: Xun Li <lixun910@gmail.com>
Description: R wrappers of C++ implementation of Faster K-Medoids clustering algorithms (FastPAM, FastCLARA and FastCLARANS) proposed in Erich Schubert, Peter J. Rousseeuw 2019 <doi:10.1007/978-3-030-32047-8_16>.
Depends: methods
License: GPL (>= 2)
Collate: RcppExports.R KmedoidsResult.R
Encoding: UTF-8
Imports: Rcpp (>= 1.0.1)
LinkingTo: Rcpp
RoxygenNote: 7.1.0
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2020-07-14 17:15:09 UTC; xunli
Repository: CRAN
Date/Publication: 2020-07-18 09:30:10 UTC

More information about fastkmedoids at CRAN
Permanent link

New package rbibutils with initial version 1.0.2
Package: rbibutils
Type: Package
Title: Convert Between Bibliography Formats
Version: 1.0.2
Date: 2020-07-16
Authors@R: c( person(given = c("Georgi", "N."), family = "Boshnakov", role = c("aut", "cre", "cph"), email = "georgi.boshnakov@manchester.ac.uk", comment = "R port, modifications to bibutils' C code" ), person(given = "Chris", family = "Putman", role = c("aut", "cph"), comment = "src/*, author of the bibutils libraries, https://sourceforge.net/projects/bibutils/"), person(given = "Richard", family = "Mathar", role = c("ctb", "cph"), comment = "src/addsout.c"), person(given = "Johannes", family = "Wilm", role = c("ctb", "cph"), comment = "src/biblatexin.c, src/bltypes.c") )
Description: Converts between a number of bibliography formats, including 'BibTeX', 'BibLaTeX' and 'Bibentry'. Includes a port of the 'bibutils' utilities by Chris Putnam <https://sourceforge.net/projects/bibutils/>. Supports all bibliography formats and character encodings implemented in 'bibutils'.
License: GPL-2
URL: https://geobosh.github.io/rbibutils/ (website), https://github.com/GeoBosh/rbibutils (devel)
BugReports: https://github.com/GeoBosh/rbibutils/issues
Depends: R (>= 2.10)
Imports: utils, tools, xml2
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Suggests: testthat
Packaged: 2020-07-16 10:45:00 UTC; georgi
Author: Georgi N. Boshnakov [aut, cre, cph] (R port, modifications to bibutils' C code), Chris Putman [aut, cph] (src/*, author of the bibutils libraries, https://sourceforge.net/projects/bibutils/), Richard Mathar [ctb, cph] (src/addsout.c), Johannes Wilm [ctb, cph] (src/biblatexin.c, src/bltypes.c)
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>
Repository: CRAN
Date/Publication: 2020-07-18 08:50:02 UTC

More information about rbibutils at CRAN
Permanent link

Package timetk updated to version 2.2.0 with previous version 2.1.0 dated 2020-07-03

Title: A Tool Kit for Working with Time Series in R
Description: Easy visualization, wrangling, and feature engineering of time series data for forecasting and machine learning prediction. Methods discussed herein are commonplace in machine learning, and have been cited in various literature. Refer to "Calendar Effects" in papers such as Taieb, Souhaib Ben. "Machine learning strategies for multi-step-ahead time series forecasting." Universit Libre de Bruxelles, Belgium (2014): 75-86. <http://souhaib-bentaieb.com/pdf/2014_phd.pdf>.
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>

Diff between timetk versions 2.1.0 dated 2020-07-03 and 2.2.0 dated 2020-07-18

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More information about timetk at CRAN
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Package lazyarray updated to version 1.1.0 with previous version 1.0.0 dated 2020-06-24

Title: Persistent Large Data Array with Lazy-Loading on Demand
Description: Multi-threaded serialization of compressed array that fully utilizes modern solid state drives. It allows to store and load extremely large data on demand within seconds without occupying too much memories. With data stored on hard drive, a lazy-array data can be loaded, shared across multiple R sessions. For arrays with partition mode on, multiple R sessions can write to a same array simultaneously along the last dimension (partition). The internal storage format is provided by 'fstcore' package geared by 'LZ4' and 'ZSTD' compressors.
Author: Zhengjia Wang [aut, cre, cph], Mark Klik [ctb, cph] (Copyright holder of fstcore package)
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>

Diff between lazyarray versions 1.0.0 dated 2020-06-24 and 1.1.0 dated 2020-07-18

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Package wrProteo updated to version 1.1.3 with previous version 1.1.2 dated 2020-07-15

Title: Proteomics Data Analysis Functions
Description: Data analysis of proteomics experiments by mass spectrometry is supported by this collection of functions mostly dedicated to the analysis of (bottom-up) quantitative (XIC) data. Fasta-formatted proteomes (eg from UniProt Consortium <doi:10.1093/nar/gky1049>) can be read with automatic parsing and multiple annotation types (like species origin, abbreviated gene names, etc) extracted. Quantitative proteomics (Schubert et al 2017 <doi:10.1038/nprot.2017.040>) measurements frequently contain multiple NA values, due to physical absence of given peptides in some samples, limitations in sensitivity or other reasons. The functions provided here help to inspect graphically the data to investigate the nature of NA-values via their respective replicate measurements and to help/confirm the choice of NA-replacement by low random values. Dedicated filtering and statistical testing using the framework of package 'limma' <doi:10.18129/B9.bioc.limma> can be run, enhanced by multiple rounds of NA-replacements to provide robustness towards rare stochastic events. Multi-species samples, as frequently used in benchmark-tests (eg Navarro et al 2016 <doi:10.1038/nbt.3685>, Ramus et al 2016 <doi:10.1016/j.jprot.2015.11.011>), can be run with special options separating the data into sub-groups during normalization and testing. Subsequently, ROC curves (Hand and Till 2001 <doi:10.1023/A:1010920819831>) can be constructed to compare multiple analysis approaches.
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@unistra.fr>

Diff between wrProteo versions 1.1.2 dated 2020-07-15 and 1.1.3 dated 2020-07-18

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More information about wrProteo at CRAN
Permanent link

Package vosonSML updated to version 0.29.13 with previous version 0.29.10 dated 2020-04-25

Title: Collecting Social Media Data and Generating Networks for Analysis
Description: A suite of tools for collecting and constructing networks from social media data. Provides easy-to-use functions for collecting data across popular platforms (Twitter, YouTube and Reddit) and generating different types of networks for analysis.
Author: Timothy Graham, Robert Ackland, Chung-hong Chan, Bryan Gertzel
Maintainer: Bryan Gertzel <bryan.gertzel@anu.edu.au>

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Package set6 updated to version 0.1.7 with previous version 0.1.6 dated 2020-07-17

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>

Diff between set6 versions 0.1.6 dated 2020-07-17 and 0.1.7 dated 2020-07-18

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Package rms updated to version 6.0-1 with previous version 6.0-0 dated 2020-06-04

Title: Regression Modeling Strategies
Description: Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. 'rms' is a collection of functions that assist with and streamline modeling. It also contains functions for binary and ordinal logistic regression models, ordinal models for continuous Y with a variety of distribution families, and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. 'rms' works with almost any regression model, but it was especially written to work with binary or ordinal regression models, Cox regression, accelerated failure time models, ordinary linear models, the Buckley-James model, generalized least squares for serially or spatially correlated observations, generalized linear models, and quantile regression.
Author: Frank E Harrell Jr <fh@fharrell.com>
Maintainer: Frank E Harrell Jr <fh@fharrell.com>

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Package rasterdiv updated to version 0.2-1 with previous version 0.2-0 dated 2020-06-11

Title: Diversity Indices for Numerical Matrices
Description: Providing functions to calculate indices of diversity on numerical matrices based on information theory. The rationale behind the package is described in Rocchini, Marcantonio and Ricotta (2017) <doi:10.1016/j.ecolind.2016.07.039>.
Author: Matteo Marcantonio [aut, cre], Martina Iannacito [aut, ctb], Elisa Thouverai [aut, ctb], Daniele Da Re [aut], Clara Tattoni [aut], Giovanni Bacaro [aut], Saverio Vicario [aut, ctb], Carlo Ricotta [aut], Duccio Rocchini [aut, ctb]
Maintainer: Matteo Marcantonio <marcantoniomatteo@gmail.com>

Diff between rasterdiv versions 0.2-0 dated 2020-06-11 and 0.2-1 dated 2020-07-18

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Package nombre updated to version 0.2.0 with previous version 0.1.0 dated 2020-05-25

Title: Number Names
Description: Converts numeric vectors to character vectors of English number names. Provides conversion to cardinals, ordinals, numerators, and denominators. Supports negative and non-integer numbers.
Author: Alexander Rossell Hayes [aut, cre] (<https://orcid.org/0000-0001-9412-0457>)
Maintainer: Alexander Rossell Hayes <alexander@rossellhayes.com>

Diff between nombre versions 0.1.0 dated 2020-05-25 and 0.2.0 dated 2020-07-18

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Package folderfun updated to version 0.1.4 with previous version 0.1.3 dated 2020-07-14

Title: Creates and Manages Folder Functions for Portable Large-Scale R Analysis
Description: If you find yourself working on multiple different projects in R, you'll want a series of folders pointing to raw data, processed data, plot results, intermediate table outputs, etc. This package makes it easier to do that by providing a quick and easy way to create and use functions for project-level directories.
Author: Nathan C. Sheffield [aut, cre], Michal Stolarczyk [ctb], Vince Reuter [ctb]
Maintainer: Nathan C. Sheffield <nathan@code.databio.org>

Diff between folderfun versions 0.1.3 dated 2020-07-14 and 0.1.4 dated 2020-07-18

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New package codemetar with initial version 0.1.9
Type: Package
Package: codemetar
Title: Generate 'CodeMeta' Metadata for R Packages
Version: 0.1.9
Authors@R: c(person(given = "Carl", family = "Boettiger", role = c("aut", "cre", "cph"), email = "cboettig@gmail.com", comment = c(ORCID = "0000-0002-1642-628X")), person(given = "Anna", family = "Krystalli", role = c("rev", "ctb"), comment = c(ORCID = "0000-0002-2378-4915")), person(given = "Toph", family = "Allen", role = "rev", comment = c(ORCID = "0000-0003-4580-091X")), person(given = "Maëlle", family = "Salmon", role = c("ctb", "aut"), comment = c(ORCID = "0000-0002-2815-0399")), person(given = "rOpenSci", role = "fnd", comment = "https://ropensci.org/"), person(given = "Katrin", family = "Leinweber", role = "ctb", comment = c(ORCID = "0000-0001-5135-5758")), person(given = "Noam", family = "Ross", role = "ctb", comment = c(ORCID = "0000-0002-2136-0000")), person(given = "Arfon", family = "Smith", role = "ctb"), person(given = "Jeroen", family = "Ooms", role = "ctb", comment = c(ORCID = "0000-0002-4035-0289")), person(given = "Sebastian", family = "Meyer", role = "ctb", comment = c(ORCID = "0000-0002-1791-9449")), person(given = "Michael", family = "Rustler", role = "ctb", comment = c(ORCID = "0000-0003-0647-7726")), person(given = "Hauke", family = "Sonnenberg", role = "ctb", comment = c(ORCID = "0000-0001-9134-2871")), person(given = "Sebastian", family = "Kreutzer", role = "ctb", comment = c(ORCID = "0000-0002-0734-2199")) )
Description: The 'Codemeta' Project defines a 'JSON-LD' format for describing software metadata, as detailed at <https://codemeta.github.io>. This package provides utilities to generate, parse, and modify 'codemeta.json' files automatically for R packages, as well as tools and examples for working with 'codemeta.json' 'JSON-LD' more generally.
License: GPL-3
URL: https://github.com/ropensci/codemetar, https://docs.ropensci.org/codemetar
BugReports: https://github.com/ropensci/codemetar/issues
Depends: R (>= 3.2.0)
Imports: commonmark, crul, desc, gert, gh, jsonlite (>= 1.6), magrittr, memoise, methods, pingr, pkgbuild, purrr, remotes, sessioninfo, stats, urltools, xml2, cli
Suggests: covr, details, dplyr (>= 0.7.0), jsonld, jsonvalidate, knitr, printr, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
X-schema.org-isPartOf: https://ropensci.org
X-schema.org-keywords: metadata, codemeta, ropensci, citation, credit, linked-data
NeedsCompilation: no
Packaged: 2020-07-17 16:51:02 UTC; cboettig
Author: Carl Boettiger [aut, cre, cph] (<https://orcid.org/0000-0002-1642-628X>), Anna Krystalli [rev, ctb] (<https://orcid.org/0000-0002-2378-4915>), Toph Allen [rev] (<https://orcid.org/0000-0003-4580-091X>), Maëlle Salmon [ctb, aut] (<https://orcid.org/0000-0002-2815-0399>), rOpenSci [fnd] (https://ropensci.org/), Katrin Leinweber [ctb] (<https://orcid.org/0000-0001-5135-5758>), Noam Ross [ctb] (<https://orcid.org/0000-0002-2136-0000>), Arfon Smith [ctb], Jeroen Ooms [ctb] (<https://orcid.org/0000-0002-4035-0289>), Sebastian Meyer [ctb] (<https://orcid.org/0000-0002-1791-9449>), Michael Rustler [ctb] (<https://orcid.org/0000-0003-0647-7726>), Hauke Sonnenberg [ctb] (<https://orcid.org/0000-0001-9134-2871>), Sebastian Kreutzer [ctb] (<https://orcid.org/0000-0002-0734-2199>)
Maintainer: Carl Boettiger <cboettig@gmail.com>
Repository: CRAN
Date/Publication: 2020-07-18 05:40:11 UTC

More information about codemetar at CRAN
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Package dietr updated to version 1.1.0 with previous version 1.0 dated 2019-11-13

Title: Diet Estimated Trophic Levels
Description: Estimates fractional trophic level from quantitative and qualitative diet data and calculates electivity indices in R. Froese & Pauly (2000, ISBN: 9718709991).
Author: Samuel R. Borstein <sam@borstein.com>
Maintainer: Samuel R. Borstein <sam@borstein.com>

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Package BisqueRNA updated to version 1.0.4 with previous version 1.0.3 dated 2020-05-04

Title: Decomposition of Bulk Expression with Single-Cell Sequencing
Description: Provides tools to accurately estimate cell type abundances from heterogeneous bulk expression. A reference-based method utilizes single-cell information to generate a signature matrix and transformation of bulk expression for accurate regression based estimates. A marker-based method utilizes known cell-specific marker genes to measure relative abundances across samples. For more details, see Jew and Alvarez et al (2019) <doi:10.1101/669911>.
Author: Brandon Jew [aut, cre], Marcus Alvarez [aut]
Maintainer: Brandon Jew <brandon.jew@ucla.edu>

Diff between BisqueRNA versions 1.0.3 dated 2020-05-04 and 1.0.4 dated 2020-07-18

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