Wed, 23 Sep 2020

Package SailoR updated to version 1.2 with previous version 1.1.2 dated 2020-07-16

Title: An Extension of the Taylor Diagram to Two-Dimensional Vector Data
Description: A new diagram for the verification of vector variables (wind, current, etc) generated by multiple models against a set of observations is presented in this package. It has been designed as a generalization of the Taylor diagram to two dimensional quantities. It is based on the analysis of the two-dimensional structure of the mean squared error matrix between model and observations. The matrix is divided into the part corresponding to the relative rotation and the bias of the empirical orthogonal functions of the data. The full set of diagnostics produced by the analysis of the errors between model and observational vector datasets comprises the errors in the means, the analysis of the total variance of both datasets, the rotation matrix corresponding to the principal components in observation and model, the angle of rotation of model-derived empirical orthogonal functions respect to the ones from observations, the standard deviation of model and observations, the root mean squared error between both datasets and the squared two-dimensional correlation coefficient. See the output of function UVError() in this package.
Author: Jon Sáenz [aut, cph] (<https://orcid.org/0000-0002-5920-7570>), Sheila Carreno-Madinabeitia [aut, cph] (<https://orcid.org/0000-0003-4625-6178>), Santos J. González-Rojí [aut, cre, cph] (<https://orcid.org/0000-0003-4737-0984>), Ganix Esnaola [ctb, cph] (<https://orcid.org/0000-0001-9058-043X>), Gabriel Ibarra-Berastegi [ctb, cph] (<https://orcid.org/0000-0001-8681-3755>), Alain Ulazia [ctb, cph] (<https://orcid.org/0000-0002-4124-2853>)
Maintainer: Santos J. González-Rojí <santosjose.gonzalez@ehu.eus>

Diff between SailoR versions 1.1.2 dated 2020-07-16 and 1.2 dated 2020-09-23

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Package ojsr updated to version 0.1.2 with previous version 0.1.1 dated 2020-07-01

Title: Crawler and Data Scraper for Open Journal System ('OJS')
Description: Crawler for 'OJS' pages and scraper for meta-data from articles. You can crawl 'OJS' archives, issues, articles, galleys, and search results. You can scrape articles metadata from their head tag in html, or from Open Archives Initiative ('OAI') records. Most of these functions rely on 'OJS' routing conventions (<https://docs.pkp.sfu.ca/dev/documentation/en/architecture-routes>).
Author: Gaston Becerra [aut, cre] (<https://orcid.org/0000-0001-9432-8848>)
Maintainer: Gaston Becerra <gaston.becerra@gmail.com>

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Package miic updated to version 1.5.2 with previous version 1.5.1 dated 2020-09-18

Title: Learning Causal or Non-Causal Graphical Models Using Information Theory
Description: We report an information-theoretic method which learns a large class of causal or non-causal graphical models from purely observational data, while including the effects of unobserved latent variables, commonly found in many datasets. Starting from a complete graph, the method iteratively removes dispensable edges, by uncovering significant information contributions from indirect paths, and assesses edge-specific confidences from randomization of available data. The remaining edges are then oriented based on the signature of causality in observational data. This approach can be applied on a wide range of datasets and provide new biological insights on regulatory networks from single cell expression data, genomic alterations during tumor development and co-evolving residues in protein structures. For more information you can refer to: Cabeli et al. PLoS Comp. Bio. 2020 <doi:10.1371/journal.pcbi.1007866>, Verny et al. PLoS Comp. Bio. 2017 <doi:10.1371/journal.pcbi.1005662>.
Author: Vincent Cabeli [aut, cre], Honghao Li [aut], Marcel Ribeiro Dantas [aut], Nadir Sella [aut], Louis Verny [aut], Severine Affeldt [aut], Hervé Isambert [aut]
Maintainer: Vincent Cabeli <vincent.cabeli@curie.fr>

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Package asnipe updated to version 1.1.13 with previous version 1.1.12 dated 2019-08-19

Title: Animal Social Network Inference and Permutations for Ecologists
Description: Implements several tools that are used in animal social network analysis, as described in Whitehead (2007) Analyzing Animal Societies <University of Chicago Press> and Farine & Whitehead (2015) <doi: 10.1111/1365-2656.12418>. In particular, this package provides the tools to infer groups and generate networks from observation data, perform permutation tests on the data, calculate lagged association rates, and performed multiple regression analysis on social network data.
Author: Damien R. Farine <dfarine@ab.mpg.de>
Maintainer: Damien R. Farine <dfarine@ab.mpg.de>

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Package lessR updated to version 3.9.7 with previous version 3.9.6 dated 2020-06-11

Title: Less Code, More Results
Description: Each function accomplishes the work of several or more standard R functions. For example, two function calls, Read() and CountAll(), read the data and generate summary statistics for all variables in the data frame, plus histograms and bar charts as appropriate. Other functions provide for descriptive statistics, a comprehensive regression analysis, analysis of variance and t-test, plotting including the introduced here Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve, reading multiple data formats with the same function call, variable labels, color themes, Trellis graphics and a built-in help system. Also includes a confirmatory factor analysis of multiple indicator measurement models, pedagogical routines for data simulation such as for the Central Limit Theorem, and generation and rendering of R markdown instructions for interpretative output.
Author: David Gerbing, The School of Business, Portland State University
Maintainer: David W. Gerbing <gerbing@pdx.edu>

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Package gimme updated to version 0.7-3 with previous version 0.7-2 dated 2020-09-03

Title: Group Iterative Multiple Model Estimation
Description: Automated identification and estimation of group- and individual-level relations in time series data from within a structural equation modeling framework.
Author: Stephanie Lane [aut, trl], Kathleen Gates [aut, cre], Zachary Fisher [aut], Cara Arizmendi [aut], Peter Molenaar [aut], Michael Hallquist [ctb], Hallie Pike [ctb], Teague Henry [ctb], Kelly Duffy [ctb], Lan Luo [ctb], Adriene Beltz [csp]
Maintainer: KM Gates <gateskm@email.unc.edu>

Diff between gimme versions 0.7-2 dated 2020-09-03 and 0.7-3 dated 2020-09-23

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Package FHtest updated to version 1.5 with previous version 1.4 dated 2017-11-08

Title: Tests for Right and Interval-Censored Survival Data Based on the Fleming-Harrington Class
Description: Functions to compare two or more survival curves with: a) The Fleming-Harrington test for right-censored data based on permutations and on counting processes. b) An extension of the Fleming-Harrington test for interval-censored data based on a permutation distribution and on a score vector distribution.
Author: Ramon Oller, Klaus Langohr
Maintainer: Ramon Oller <ramon.oller@uvic.cat>

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Package rsample updated to version 0.0.8 with previous version 0.0.7 dated 2020-06-04

Title: General Resampling Infrastructure
Description: Classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).
Author: Max Kuhn [aut, cre], Fanny Chow [aut], Hadley Wickham [aut], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

Diff between rsample versions 0.0.7 dated 2020-06-04 and 0.0.8 dated 2020-09-23

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Package aziztest updated to version 0.2.0 with previous version 0.1.0 dated 2020-04-01

Title: Novel Statistical Test for Aberration Enrichment
Description: Testing for heterogeneous effects in a case-control setting. The aim here to discover an association that is beyond a mean difference between all cases and all controls. Instead, the signal of interest here is present in only a proportion of the cases. This test should be more powerful than a t-test or Wilcoxon test in this heterogeneous setting. Please cite the corresponding paper: Mezlini et al. (2020) <doi:10.1101/2020.03.23.002972>.
Author: Aziz M. Mezlini [aut,cre,cph]
Maintainer: Aziz M. Mezlini <mmezlini@mgh.harvard.edu>

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New package SLTCA with initial version 0.1.0
Package: SLTCA
Type: Package
Title: Scalable and Robust Latent Trajectory Class Analysis
Description: Conduct latent trajectory class analysis with longitudinal data. Our method supports longitudinal continuous, binary and count data. For more methodological details, please refer to Hart, K.R., Fei, T. and Hanfelt, J.J. (2020), Scalable and robust latent trajectory class analysis using artificial likelihood. Biometrics <doi:10.1111/biom.13366>.
Depends: R (>= 3.3.0)
Imports: stats, geepack, VGAM, Matrix, mvtnorm
Version: 0.1.0
Authors@R: c( person("Kari", "Hart", email = "khart@peddie.org", role = "aut"), person("Teng", "Fei", email = "tfei@emory.edu", role = c("cre","aut"), comment = c(ORCID = "0000-0001-7888-1715")), person("John", "Hanfelt", email = "jhanfel@emory.edu", role = "aut", comment = c(ORCID = "0000-0002-8488-6771")) )
Maintainer: Teng Fei <tfei@emory.edu>
BugReports: https://github.com/tengfei-emory/SLTCA/issues
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-17 18:18:58 UTC; TFEI
Author: Kari Hart [aut], Teng Fei [cre, aut] (<https://orcid.org/0000-0001-7888-1715>), John Hanfelt [aut] (<https://orcid.org/0000-0002-8488-6771>)
Repository: CRAN
Date/Publication: 2020-09-23 15:30:07 UTC

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New package omxr with initial version 0.3.3
Package: omxr
Type: Package
Title: Read and Write Open Matrix Files
Version: 0.3.3
Date: 2020-09-16
Authors@R: c( person("Brian", "Gregor", email = "", role = "aut"), person("Ben", "Stabler", email = "", role = "aut"), person("Greg", "Macfarlane", email = "gregmacfarlane@gmail.com", role = "cre") )
Description: The Open Matrix (OMX) file type is an open specification for sharing data from transportation models. The specification is built on HDF5 <https://www.hdfgroup.org/>; APIs to read and write are available for 'Cube', 'Emme', 'Python', 'Java', and 'R'.
License: Apache License 2.0
LazyData: TRUE
Suggests: knitr, tidyverse
VignetteBuilder: knitr
biocViews: rhdf5, zlibbioc
Imports: rhdf5, hms, zlibbioc, tidyr (>= 0.8.0), readr, dplyr, purrr, magrittr, rlang
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-17 16:53:48 UTC; gregmacfarlane
Author: Brian Gregor [aut], Ben Stabler [aut], Greg Macfarlane [cre]
Maintainer: Greg Macfarlane <gregmacfarlane@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 15:30:03 UTC

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Package multcomp updated to version 1.4-14 with previous version 1.4-13 dated 2020-04-08

Title: Simultaneous Inference in General Parametric Models
Description: Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book "Multiple Comparisons Using R" (Bretz, Hothorn, Westfall, 2010, CRC Press).
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>), Frank Bretz [aut], Peter Westfall [aut], Richard M. Heiberger [ctb], Andre Schuetzenmeister [ctb], Susan Scheibe [ctb]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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New package combinedevents with initial version 0.1.0
Package: combinedevents
Title: Calculate Scores and Marks for Track and Field Combined Events
Version: 0.1.0
Authors@R: person(given = "Katie", family = "Frank", role = c("aut", "cre"), email = "katiexfrank@gmail.com", comment = c(ORCID = "0000-0002-0353-0328"))
Description: Includes functions to calculate scores and marks for track and field combined events competitions. The functions are based on the scoring tables for combined events set forth by the International Association of Athletics Federation (2001) <https://www.worldathletics.org/about-iaaf/documents/technical-information>.
License: GPL-3
URL: https://katie-frank.github.io/combinedevents/, https://github.com/katie-frank/combinedevents
BugReports: https://github.com/katie-frank/combinedevents/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: lubridate, magrittr, rlang, stats, stringr
Suggests: knitr, rmarkdown, testthat, spelling, covr
Depends: R (>= 2.10)
Language: en-US
NeedsCompilation: no
Packaged: 2020-09-17 14:16:45 UTC; katiefrank
Author: Katie Frank [aut, cre] (<https://orcid.org/0000-0002-0353-0328>)
Maintainer: Katie Frank <katiexfrank@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 14:00:02 UTC

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New package AGPRIS with initial version 1.0
Package: AGPRIS
Title: AGricultural PRoductivity in Space
Version: 1.0
Authors@R: person(given = "Edoardo", family = "Baldoni", role = c("aut", "cre"), email = "edoardo.baldoni@gmail.com", comment = c(ORCID = "https://orcid.org/0000-0002-5296-1212"))
Description: Functionalities to simulate space-time data and to estimate dynamic-spatial panel data models. Estimators implemented are the BCML (Elhorst (2010), <doi:10.1016/j.regsciurbeco.2010.03.003>), the MML (Elhorst (2010) <doi:10.1016/j.regsciurbeco.2010.03.003>) and the INLA Bayesian estimator (Lindgren and Rue, (2015) <doi:10.18637/jss.v063.i19>; Bivand, Gomez-Rubio and Rue, (2015) <doi:10.18637/jss.v063.i20>) adapted to panel data. The package contains functions to replicate the analyses of the scientific article entitled "Agricultural Productivity in Space" (Baldoni and Esposti (under revision)).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: methods, Matrix, plyr, rgdal, sp, spdep, spacetime, matrixcalc, maxLik
Suggests: INLA
NeedsCompilation: no
Packaged: 2020-09-17 16:34:57 UTC; Edoardo
Author: Edoardo Baldoni [aut, cre] (<https://orcid.org/0000-0002-5296-1212>)
Maintainer: Edoardo Baldoni <edoardo.baldoni@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 15:20:02 UTC

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New package contactdata with initial version 0.1
Package: contactdata
Title: Social Contact Matrices for 152 Countries
Version: 0.1
Authors@R: c(person(given = "Hugo", family = "Gruson", role = c("cre", "aut", "cph"), email = "hugo.gruson+R@normalesup.org", comment = c(ORCID = "0000-0002-4094-1476")), person(given = "Kiesha", family = "Prem", role = "dtc", comment = c(ORCID = "0000-0003-0528-798X")), person(given = c("Alex", "Richard"), family = "Cook", role = "dtc", comment = c(ORCID = "0000-0002-6271-5832")), person(given = "Mark", family = "Jit", role = "dtc", comment = c(ORCID = "0000-0001-6658-8255")))
Description: Data package for the supplementary data in Prem et al. (2017) <doi:10.1371/journal.pcbi.1005697>. Provides easy access to contact data for 152 countries, for use in epidemiological, demographic or social sciences research.
License: MIT + file LICENSE
Depends: R (>= 3.5)
Suggests: countrycode, ggplot2, knitr, rmarkdown, spelling, testthat, covr
URL: https://bisaloo.github.io/contactdata/, https://github.com/bisaloo/contactdata
BugReports: https://github.com/bisaloo/contactdata/issues
Encoding: UTF-8
Language: en-GB
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2020-09-17 11:19:25 UTC; hugo
Author: Hugo Gruson [cre, aut, cph] (<https://orcid.org/0000-0002-4094-1476>), Kiesha Prem [dtc] (<https://orcid.org/0000-0003-0528-798X>), Alex Richard Cook [dtc] (<https://orcid.org/0000-0002-6271-5832>), Mark Jit [dtc] (<https://orcid.org/0000-0001-6658-8255>)
Maintainer: Hugo Gruson <hugo.gruson+R@normalesup.org>
Repository: CRAN
Date/Publication: 2020-09-23 13:50:03 UTC

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New package EquiSurv with initial version 0.1.0
Package: EquiSurv
Type: Package
Title: Modeling, Confidence Intervals and Equivalence of Survival Curves
Version: 0.1.0
Author: Kathrin Moellenhoff
Maintainer: Kathrin Moellenhoff <kathrin.moellenhoff@rub.de>
Description: We provide a non-parametric and a parametric approach to investigate the equivalence (or non-inferiority) of two survival curves, obtained from two given datasets. The test is based on the creation of confidence intervals at pre-specified time points. For the non-parametric approach, the curves are given by Kaplan-Meier curves and the variance for calculating the confidence intervals is obtained by Greenwood's formula. The parametric approach is based on estimating the underlying distribution, where the user can choose between a Weibull, Exponential, Gaussian, Logistic, Log-normal or a Log-logistic distribution. Estimates for the variance for calculating the confidence bands are obtained by a (parametric) bootstrap approach. For this bootstrap censoring is assumed to be exponentially distributed and estimates are obtained from the datasets under consideration. All details can be found in K.Moellenhoff and A.Tresch: Survival analysis under non-proportional hazards: investigating non-inferiority or equivalence in time-to-event data <arXiv:2009.06699>.
Depends: survival, eha, graphics
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-17 08:47:18 UTC; Kathrin
Repository: CRAN
Date/Publication: 2020-09-23 13:30:02 UTC

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Package statgenSTA updated to version 1.0.6 with previous version 1.0.5 dated 2020-06-24

Title: Single Trial Analysis (STA) of Field Trials
Description: Phenotypic analysis of field trials using mixed models with and without spatial components. One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris. Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<http://www.vsni.co.uk/software/asreml-r>).
Author: Bart-Jan van Rossum [aut, cre], Fred van Eeuwijk [ctb] (<https://orcid.org/0000-0003-3672-2921>), Martin Boer [ctb], Marcos Malosetti [ctb] (<https://orcid.org/0000-0002-8150-1397>), Daniela Bustos-Korts [ctb] (<https://orcid.org/0000-0003-3827-6726>), Emilie J. Millet [ctb] (<https://orcid.org/0000-0002-2913-4892>), Joao Paulo [ctb] (<https://orcid.org/0000-0002-4180-0763>), Maikel Verouden [ctb] (<https://orcid.org/0000-0002-4893-3323>), Willem Kruijer [ctb] (<https://orcid.org/0000-0001-7179-1733>), Ron Wehrens [ctb] (<https://orcid.org/0000-0002-8798-5599>), Choazhi Zheng [ctb] (<https://orcid.org/0000-0001-6030-3933>)
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>

Diff between statgenSTA versions 1.0.5 dated 2020-06-24 and 1.0.6 dated 2020-09-23

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 man/statgenSTA-package.Rd           |    1 
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 man/summary.TD.Rd                   |  156 ++++++-------
 man/wheatChl.Rd                     |   30 +-
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 tests/testthat/test-ExtractSpATS.R  |   27 +-
 tests/testthat/test-STA.R           |   37 ++-
 tests/testthat/test-TD.R            |   56 ++++
 tests/testthat/test-TDplots.R       |   45 +++-
 tests/testthat/test-extract.R       |   47 ++--
 vignettes/statgenSTA.Rmd            |   40 ++-
 51 files changed, 2197 insertions(+), 1645 deletions(-)

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Package nasapower updated to version 2.0.0 with previous version 1.1.3 dated 2019-11-18

Title: NASA POWER API Client
Description: Client for 'NASA' 'POWER' global meteorology, surface solar energy and climatology data 'API'. 'POWER' (Prediction Of Worldwide Energy Resource) data are freely available global meteorology and surface solar energy climatology data for download with a resolution of 1/2 by 1/2 arc degree longitude and latitude and are funded through the 'NASA' Earth Science Directorate Applied Science Program. For more on the data themselves, a web-based data viewer and web access, please see <https://power.larc.nasa.gov/>.
Author: Adam H. Sparks [aut, cre] (<https://orcid.org/0000-0002-0061-8359>), Scott Chamberlain [rev] (<https://orcid.org/0000-0003-1444-9135>, Scott Chamberlain reviewed nasapower for rOpenSci, see https://github.com/ropensci/software-review/issues/155), Hazel Kavili [rev] (Hazel Kavili reviewed nasapower for rOpenSci, see https://github.com/ropensci/software-review/issues/155), Alison Boyer [rev] (Alison Boyer reviewed nasapower for rOpenSci, see https://github.com/ropensci/software-review/issues/155)
Maintainer: Adam H. Sparks <adamhsparks@gmail.com>

Diff between nasapower versions 1.1.3 dated 2019-11-18 and 2.0.0 dated 2020-09-23

 nasapower-1.1.3/nasapower/R/create_icasa.R                            |only
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 nasapower-2.0.0/nasapower/DESCRIPTION                                 |   57 -
 nasapower-2.0.0/nasapower/MD5                                         |   74 -
 nasapower-2.0.0/nasapower/NAMESPACE                                   |    1 
 nasapower-2.0.0/nasapower/NEWS.md                                     |  141 +-
 nasapower-2.0.0/nasapower/R/deprecated_create_met.R                   |only
 nasapower-2.0.0/nasapower/R/get_power.R                               |   41 
 nasapower-2.0.0/nasapower/R/internal_functions.R                      |  114 +-
 nasapower-2.0.0/nasapower/R/nasapower-package.R                       |   48 
 nasapower-2.0.0/nasapower/R/parameters_data.R                         |  107 +
 nasapower-2.0.0/nasapower/README.md                                   |   67 -
 nasapower-2.0.0/nasapower/build/vignette.rds                          |binary
 nasapower-2.0.0/nasapower/data/parameters.rda                         |binary
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 nasapower-2.0.0/nasapower/inst/doc/nasapower_states_example.Rmd       |  330 +++---
 nasapower-2.0.0/nasapower/inst/doc/nasapower_states_example.html      |  524 +++++----
 nasapower-2.0.0/nasapower/man/create_met.Rd                           |   26 
 nasapower-2.0.0/nasapower/man/get_power.Rd                            |   36 
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 nasapower-2.0.0/nasapower/tests/testthat/helper-nasapower.R           |only
 nasapower-2.0.0/nasapower/tests/testthat/test-get_power.R             |  177 ++-
 nasapower-2.0.0/nasapower/tests/testthat/test-internal_functions.R    |  353 +++---
 nasapower-2.0.0/nasapower/vignettes/create-climatology-brick-1.png    |binary
 nasapower-2.0.0/nasapower/vignettes/create-single-raster-1.png        |binary
 nasapower-2.0.0/nasapower/vignettes/create_coords-1.png               |binary
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 nasapower-2.0.0/nasapower/vignettes/create_coords-3.png               |binary
 nasapower-2.0.0/nasapower/vignettes/nasapower.Rmd                     |  368 ++----
 nasapower-2.0.0/nasapower/vignettes/nasapower.Rmd.orig                |  251 +---
 nasapower-2.0.0/nasapower/vignettes/nasapower_states_example.Rmd      |  330 +++---
 nasapower-2.0.0/nasapower/vignettes/nasapower_states_example.Rmd.orig |   59 -
 nasapower-2.0.0/nasapower/vignettes/plot-fig1-1.png                   |binary
 nasapower-2.0.0/nasapower/vignettes/precompile.R                      |    4 
 41 files changed, 2122 insertions(+), 2007 deletions(-)

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Package cronR updated to version 0.4.2 with previous version 0.4.0 dated 2018-03-08

Title: Schedule R Scripts and Processes with the 'cron' Job Scheduler
Description: Create, edit, and remove 'cron' jobs on your unix-alike system. The package provides a set of easy-to-use wrappers to 'crontab'. It also provides an RStudio add-in to easily launch and schedule your scripts.
Author: Jan Wijffels [aut, cre, cph], BNOSAC [cph], Kevin Ushey [cph]
Maintainer: Jan Wijffels <jwijffels@bnosac.be>

Diff between cronR versions 0.4.0 dated 2018-03-08 and 0.4.2 dated 2020-09-23

 DESCRIPTION         |   11 -
 MD5                 |   14 +-
 R/cron_rscript.R    |   17 ++
 README.md           |    5 
 build/vignette.rds  |binary
 inst/doc/cronR.R    |    8 -
 inst/doc/cronR.html |  343 +++++++++++++++++++++++++++++++++++++---------------
 man/cron_rscript.Rd |   22 ++-
 8 files changed, 297 insertions(+), 123 deletions(-)

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Package schoRsch updated to version 1.8 with previous version 1.7 dated 2019-11-12

Title: Tools for Analyzing Factorial Experiments
Description: Offers a helping hand to psychologists and other behavioral scientists who routinely deal with experimental data from factorial experiments. It includes several functions to format output from other R functions according to the style guidelines of the APA (American Psychological Association). This formatted output can be copied directly into manuscripts to facilitate data reporting. These features are backed up by a toolkit of several small helper functions, e.g., offering out-of-the-box outlier removal. The package lends its name to Georg "Schorsch" Schuessler, ingenious technician at the Department of Psychology III, University of Wuerzburg. For details on the implemented methods, see Roland Pfister and Markus Janczyk (2016) <doi: 10.20982/tqmp.12.2.p147>.
Author: Roland Pfister, Markus Janczyk
Maintainer: Roland Pfister <roland.pfister@psychologie.uni-wuerzburg.de>

Diff between schoRsch versions 1.7 dated 2019-11-12 and 1.8 dated 2020-09-23

 DESCRIPTION     |    8 ++++----
 MD5             |    6 +++---
 R/anova_out.R   |    8 ++++++--
 man/schoRsch.Rd |    9 +++++----
 4 files changed, 18 insertions(+), 13 deletions(-)

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New package RSmallTelescopes with initial version 1.0.2
Package: RSmallTelescopes
Title: Empirical Small Telescopes Analysis
Version: 1.0.2
Authors@R: c( person(given = "John", family = "Ruscio", role = c("aut", "cre"), email = "ruscio@tcnj.edu"), person(given = "Samantha", family = "Costigan", role = c("ctb"), email = "costigs1@tcnj.edu"))
Description: We provide functions to perform an empirical small telescopes analysis. This package contains 2 functions, SimulatePower() and EstimatePower(). Users only need to call SimulatePower() to conduct the analysis. For more information on small telescopes analysis see Uri Simonsohn (2015) <doi:10.1177/0956797614567341>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-16 18:21:48 UTC; ruthec
Author: John Ruscio [aut, cre], Samantha Costigan [ctb]
Maintainer: John Ruscio <ruscio@tcnj.edu>
Repository: CRAN
Date/Publication: 2020-09-23 09:10:08 UTC

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New package path.chain with initial version 0.2.0
Package: path.chain
Type: Package
Title: Concise Structure for Chainable Paths
Version: 0.2.0
Authors@R: person(given = "Krzysztof", family = "Joachimiak", role = c("aut", "cre"), email = "joachimiak.krzysztof@gmail.com", comment = c(ORCID = "0000-0003-4780-7947"))
Description: Provides path_chain class and functions, which facilitates loading and saving directory structure in YAML configuration files via 'config' package. The file structure you created during exploration can be transformed into legible section in the config file, and then easily loaded for further usage.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/krzjoa/path.chain/issues
URL: https://github.com/krzjoa/path.chain, https://krzjoa.github.io/path.chain/
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, config, yaml, fs, magrittr
VignetteBuilder: knitr
Imports: rlang, stringi, logger
NeedsCompilation: no
Packaged: 2020-09-16 21:03:38 UTC; krzysztof
Author: Krzysztof Joachimiak [aut, cre] (<https://orcid.org/0000-0003-4780-7947>)
Maintainer: Krzysztof Joachimiak <joachimiak.krzysztof@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 09:20:03 UTC

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New package mlquantify with initial version 0.1.4
Package: mlquantify
Type: Package
Title: Algorithms for Class Distribution Estimation
Version: 0.1.4
Authors@R: c( person("Andre", "Maletzke", email = "andregustavom@gmail.com", role = c("aut","cre")), person("Everton", "Cherman", email = "evertoncherman@gmail.com", role = "ctb"), person("Denis", "dos Reis", email = "denismr@gmail.com", role = "ctb"), person("Gustavo", "Batista", email = "g.batista@unsw.edu.au", role = "ths"))
Maintainer: Andre Maletzke <andregustavom@gmail.com>
Description: Quantification is a prominent machine learning task that has received an increasing amount of attention in the last years. The objective is to predict the class distribution of a data sample. This package is a collection of machine learning algorithms for class distribution estimation. This package include algorithms from different paradigms of quantification. These methods are described in the paper: A. Maletzke, W. Hassan, D. dos Reis, and G. Batista. The importance of the test set size in quantification assessment. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI20, pages 2640–2646, 2020. <doi:10.24963/ijcai.2020/366>.
License: GPL (>= 2.0)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Author: Andre Maletzke [aut, cre], Everton Cherman [ctb], Denis dos Reis [ctb], Gustavo Batista [ths]
RoxygenNote: 7.1.1
BugReports: https://github.com/andregustavom/mlquantify/issues
URL: https://github.com/andregustavom/mlquantify
Imports: caret, randomForest, stats
Suggests: CORElearn
Packaged: 2020-09-16 16:11:44 UTC; andregustavom
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2020-09-23 09:20:08 UTC

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New package fusionchartsR with initial version 0.0.1
Package: fusionchartsR
Type: Package
Version: 0.0.1
Title: Embedding 'FusionCharts Javascript' Library in R
Description: FusionCharts provides awesome and minimalist functions to make beautiful interactive charts <https://www.fusioncharts.com/>.
Authors@R: person(given = "Alex", family = "Yahiaoui Martinez", role = c("aut", "cre"), email = "yahiaoui-martinez.alex@outlook.com")
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: htmlwidgets, jsonlite, magrittr
Suggests: rmarkdown, knitr, shiny, testthat
NeedsCompilation: no
Packaged: 2020-09-16 16:28:11 UTC; yahia
Author: Alex Yahiaoui Martinez [aut, cre]
Maintainer: Alex Yahiaoui Martinez <yahiaoui-martinez.alex@outlook.com>
Repository: CRAN
Date/Publication: 2020-09-23 09:10:03 UTC

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New package corona with initial version 0.3.0
Package: corona
Title: Coronavirus ('Rona') Data Exploration
Version: 0.3.0
Depends: R (>= 3.5.0), plyr
Imports: gganimate, ggplot2, gridExtra, qicharts2, reshape2
Authors@R: person(given = "Jo", family = "van Schalkwyk", role = c("aut", "cre"), email = "jvanschalkwyk@gmail.com", comment = c(ORCID = "0000-0002-0082-5243"))
Maintainer: Jo van Schalkwyk <jvanschalkwyk@gmail.com>
Description: Manipulate and view coronavirus data and other societally relevant data at a basic level.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-09-17 01:16:56 UTC; jo
Author: Jo van Schalkwyk [aut, cre] (<https://orcid.org/0000-0002-0082-5243>)
Repository: CRAN
Date/Publication: 2020-09-23 09:30:03 UTC

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New package wordsalad with initial version 0.2.0
Package: wordsalad
Title: Provide Tools to Extract and Analyze Word Vectors
Version: 0.2.0
Authors@R: person(given = "Emil", family = "Hvitfeldt", role = c("aut", "cre"), email = "emilhhvitfeldt@gmail.com", comment = c(ORCID = "0000-0002-0679-1945"))
Description: Provides access to various word embedding methods (GloVe, fasttext and word2vec) to extract word vectors using a unified framework to increase reproducibility and correctness.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: tibble, text2vec, word2vec, fastTextR
Suggests: testthat
URL: https://github.com/EmilHvitfeldt/wordsalad
BugReports: https://github.com/EmilHvitfeldt/wordsalad/issues
NeedsCompilation: no
Packaged: 2020-09-15 20:34:24 UTC; emilhvitfeldthansen
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 08:10:03 UTC

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New package twenty48 with initial version 0.1.0
Package: twenty48
Title: Play a Game of 2048 in the Console
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: Generates a game of 2048 that can be played in the console. Supports grids of arbitrary sizes, undoing the last move, and resuming a game that was exited during the current session.
License: MIT + file LICENSE
URL: https://github.com/rossellhayes/twenty48
BugReports: https://github.com/rossellhayes/twenty48/issues
Depends: R (>= 2.10)
Imports: crayon, R6
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-16 08:18:35 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: 2020-09-23 08:40:03 UTC

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New package tibblify with initial version 0.1.0
Package: tibblify
Title: Rectangle Nested Lists
Version: 0.1.0
Authors@R: person(given = "Maximilian", family = "Girlich", role = c("aut", "cre"), email = "maximilian.girlich@outlook.com")
Description: A tool to rectangle a nested list, that is to convert it into a tibble. This is done automatically or according to a given specification. A common use case is for nested lists coming from parsing JSON files or the JSON response of REST APIs. It is supported by the 'vctrs' package and therefore offers a wide support of vector types.
License: GPL-3
Suggests: testthat, knitr, rmarkdown, covr, spelling
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: crayon, rlang, vctrs, purrr, tibble
VignetteBuilder: knitr
Depends: R (>= 3.4.0)
URL: https://github.com/mgirlich/tibblify
BugReports: https://github.com/mgirlich/tibblify/issues
Language: en-US
NeedsCompilation: no
Packaged: 2020-09-16 06:55:20 UTC; mgirlich
Author: Maximilian Girlich [aut, cre]
Maintainer: Maximilian Girlich <maximilian.girlich@outlook.com>
Repository: CRAN
Date/Publication: 2020-09-23 08:40:07 UTC

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New package T4cluster with initial version 0.1.0
Package: T4cluster
Type: Package
Title: Tools for Cluster Analysis
Version: 0.1.0
Authors@R: c(person("Kisung", "You", role = c("aut", "cre"), email = "kyoustat@gmail.com",comment=c(ORCID="0000-0002-8584-459X")))
Encoding: UTF-8
Description: Cluster analysis is one of the most fundamental problems in data science. We provide a variety of algorithms from clustering to the learning on the space of partitions. See Hennig, Meila, and Rocci (2016, ISBN:9781466551886) for general exposition to cluster analysis.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.5), Rdpack, Rdimtools, maotai, stats, utils
URL: http://kyoustat.com/T4cluster/
BugReports: https://github.com/kyoustat/T4cluster/issues
LinkingTo: Rcpp, RcppArmadillo
RdMacros: Rdpack
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-09-16 03:43:35 UTC; kisung
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyoustat@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 08:30:02 UTC

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New package SlaPMEG with initial version 1.0.0
Package: SlaPMEG
Type: Package
Title: Pathway Testing for Longitudinal Omics
Version: 1.0.0
Author: Mitra Ebrahimpoor
Maintainer: Mitra Ebrahimpoor <mitra.ebrahimpoor@gmail.com>
Description: A self-contained hypothesis is tested for a given pathway of longitudinal omics. 'SlaPMEG' is a two-step procedure. First, a shared latent process mixed model is fitted over the longitudinal measures of omics in a pathway. This shared model allows deviation from the shared process at subject level (a random intercept, slope, or both per subject) and also at omic level (a random effect per omic). These random effects summarize the longitudinal trend of the observations which can be used to test for group differences using 'Globaltest' in the second step. If the pathway is large or the shared effect is small, the package fits a series of pairwise models and estimates the shared random effects based on them.
License: GPL (>= 2)
Date: 2020-09-05
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: lme4 (>= 1.1.21), lcmm (>= 1.8.1), globaltest (>= 5.36.0), magic (>= 1.5.9), reshape2 (>= 1.4.3), ggplot2 (>= 3.2.1), mvtnorm
NeedsCompilation: no
Packaged: 2020-09-15 19:37:47 UTC; mebrahimpoor
Repository: CRAN
Date/Publication: 2020-09-23 08:10:08 UTC

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New package RJcluster with initial version 0.1.0
Package: RJcluster
Title: RJ Clustering Algorithm
Version: 0.1.0
Authors@R: c(person(given = "Rachael", family = "Shudde", role = c("aut", "cre"), email = "rachael.shudde@gmail.com"), person(given = "Shahina", family = "Rahman", role = c("aut"), email = "srahman@stat.tamu.edu"), person(given = "Valen", family = "Johnson", role = c("aut"), email = "vejohnson@exchange.tamu.edu"))
Description: Clustering algorithm for high dimensional data. This algorithm is ideal for data where n << p.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.2), matrixStats, infotheo, rlang, stats, graphics, profvis, mclust, doParallel, foreach, parallel
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 2.1.0), knitr, rmarkdown
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2020-09-15 18:02:51 UTC; rachaelshudde
Author: Rachael Shudde [aut, cre], Shahina Rahman [aut], Valen Johnson [aut]
Maintainer: Rachael Shudde <rachael.shudde@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-23 08:00:06 UTC

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New package mmb with initial version 0.13.3
Package: mmb
Type: Package
Title: Arbitrary Dependency Mixed Multivariate Bayesian Models
Version: 0.13.3
Author: Sebastian Hönel
Maintainer: Sebastian Hönel <sebastian.honel@lnu.se>
Description: Supports Bayesian models with full and partial (hence arbitrary) dependencies between random variables. Discrete and continuous variables are supported, and conditional joint probabilities and probability densities are estimated using Kernel Density Estimation (KDE). The full general form, which implements an extension to Bayes' theorem, as well as the simple form, which is just a Bayesian network, both support regression through segmentation and KDE and estimation of probability or relative likelihood of discrete or continuous target random variables. This package also provides true statistical distance measures based on Bayesian models. Furthermore, these measures can be facilitated on neighborhood searches, and to estimate the similarity and distance between data points. Related work is by Bayes (1763) <doi:10.1098/rstl.1763.0053> and by Scutari (2010) <doi:10.18637/jss.v035.i03>.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/MrShoenel/R-mmb
BugReports: https://github.com/MrShoenel/R-mmb/issues
LazyData: true
VignetteBuilder: knitr
Suggests: devtools, testthat, covr, e1071, caret, knitr, rmarkdown, ggplot2, ggpubr, cowplot, philentropy, Rtsne
RoxygenNote: 7.1.1
Imports: Rdpack, datasets, stats, foreach, parallel, doParallel
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2020-09-15 19:37:43 UTC; Admin
Repository: CRAN
Date/Publication: 2020-09-23 08:00:02 UTC

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New package MABOUST with initial version 1.0.0
Package: MABOUST
Type: Package
Title: Multi-Armed Bayesian Ordinal Utility-Based Sequential Trial
Version: 1.0.0
Author: Andrew Chapple
Maintainer: Andrew Chapple <achapp@lsuhsc.edu>
Description: Conducts and simulates the MABOUST design, including making interim decisions to stop a treatment for inferiority or stop the trial early for superiority or equivalency.
License: GPL-2
Imports: Rcpp (>= 0.12.18)
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-09-15 20:00:10 UTC; achapp
Repository: CRAN
Date/Publication: 2020-09-23 08:10:15 UTC

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Package crmReg updated to version 1.0.2 with previous version 1.0.1 dated 2020-04-06

Title: Cellwise Robust M-Regression and SPADIMO
Description: Method for fitting a cellwise robust linear M-regression model (CRM, Filzmoser et al. (2020) <DOI:10.1016/j.csda.2020.106944>) that yields both a map of cellwise outliers consistent with the linear model, and a vector of regression coefficients that is robust against vertical outliers and leverage points. As a by-product, the method yields an imputed data set that contains estimates of what the values in cellwise outliers would need to amount to if they had fit the model. The package also provides diagnostic tools for analyzing casewise and cellwise outliers using sparse directions of maximal outlyingness (SPADIMO, Debruyne et al. (2019) <DOI:10.1007/s11222-018-9831-5>).
Author: Peter Filzmoser [aut], Sebastiaan Hoppner [aut, cre], Irene Ortner [aut], Sven Serneels [aut], Tim Verdonck [aut]
Maintainer: Sebastiaan Hoppner <sebastiaan.hoppner@gmail.com>

Diff between crmReg versions 1.0.1 dated 2020-04-06 and 1.0.2 dated 2020-09-23

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Package centrifugeR updated to version 0.1.5 with previous version 0.1.4 dated 2020-04-17

Title: Non-Trivial Balance of Centrifuge Rotors
Description: Find the numbers of tubes that can be loaded in centrifuge rotors in a single operation and show how to balance these tubes in cases of equal or unequal masses. Refer to Pham (2020) <doi:10.31224/osf.io/4xs38> for more information on package functionality.
Author: Duy Nghia Pham [aut, cre] (<https://orcid.org/0000-0003-1349-1710>)
Maintainer: Duy Nghia Pham <nghiapham@yandex.com>

Diff between centrifugeR versions 0.1.4 dated 2020-04-17 and 0.1.5 dated 2020-09-23

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Package DRomics updated to version 2.1-3 with previous version 2.1-2 dated 2020-09-22

Title: Dose Response for Omics
Description: Several functions are provided for dose-response (or concentration-response) characterization from omics data. 'DRomics' is especially dedicated to omics data obtained using a typical dose-response design, favoring a great number of tested doses (or concentrations) rather than a great number of replicates (no need of three replicates). 'DRomics' provides functions 1) to check, normalize and or transform data, 2) to select monotonic or biphasic significantly responding items (e.g. probes, metabolites), 3) to choose the best-fit model among a predefined family of monotonic and biphasic models to describe each selected item, 4) to derive a benchmark dose or concentration and a typology of response from each fitted curve. In the available version data are supposed to be single-channel microarray data in log2, RNAseq data in raw counts, or already pretreated metabolomic data in log scale. In order to link responses across biological levels based on a common method, 'DRomics' also handles apical data as long as they are continuous and follow a Gaussian distribution for each dose or concentration, with a common standard error. For further details see Larras et al (2018) <DOI:10.1021/acs.est.8b04752> at <https://hal.archives-ouvertes.fr/hal-02309919>.
Author: Marie-Laure Delignette-Muller [aut], Elise Billoir [aut], Floriane Larras [ctb], Aurelie Siberchicot [aut, cre]
Maintainer: Aurelie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>

Diff between DRomics versions 2.1-2 dated 2020-09-22 and 2.1-3 dated 2020-09-23

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New package rmdcev with initial version 1.2.3
Package: rmdcev
Type: Package
Title: Kuhn-Tucker and Multiple Discrete-Continuous Extreme Value Models
Version: 1.2.3
Authors@R: c( person(given = "Patrick", family = "Lloyd-Smith", role = c("aut", "cre"), email = "patrick.lloydsmith@usask.ca"), person("Trustees of", "Columbia University", role = "cph"))
Maintainer: Patrick Lloyd-Smith <patrick.lloydsmith@usask.ca>
Description: Estimates and simulates Kuhn-Tucker demand models with individual heterogeneity. The package implements the multiple-discrete continuous extreme value (MDCEV) model and the Kuhn-Tucker specification common in the environmental economics literature on recreation demand. Latent class and random parameters specifications can be implemented and the models are fit using maximum likelihood estimation or Bayesian estimation. All models are implemented in Stan, which is a C++ package for performing full Bayesian inference (see Stan Development Team, 2019) <https://mc-stan.org/>. The package also implements demand forecasting (Pinjari and Bhat (2011) <https://repositories.lib.utexas.edu/handle/2152/23880>) and welfare calculation (Lloyd-Smith (2018) <doi:10.1016/j.jocm.2017.12.002>) for policy simulation.
License: MIT + file LICENSE
Depends: R (>= 3.6.0), Rcpp (>= 1.0.5), methods
Imports: rstan (>= 2.21.0), rstantools (>= 2.1.1), RcppParallel (>= 5.0.1), dplyr (>= 0.7.8), purrr, tibble, tidyr, utils, stats, Formula
LinkingTo: BH (>= 1.72.0), Rcpp, RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.21.0), StanHeaders (>= 2.21.0)
Encoding: UTF-8
LazyData: true
Repository: CRAN
SystemRequirements: GNU make
RoxygenNote: 7.1.1
Biarch: true
Suggests: knitr, rmarkdown, testthat
URL: https://github.com/plloydsmith/rmdcev
BugReports: https://github.com/plloydsmith/rmdcev/issues
Author: Patrick Lloyd-Smith [aut, cre], Trustees of Columbia University [cph]
NeedsCompilation: yes
Packaged: 2020-09-22 04:33:54 UTC; Pat
Date/Publication: 2020-09-23 06:30:02 UTC

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Package mlr3proba updated to version 0.2.2 with previous version 0.2.1 dated 2020-08-28

Title: Probabilistic Supervised Learning for 'mlr3'
Description: Provides extensions for probabilistic supervised learning for 'mlr3'. This includes extending the regression task to probabilistic and interval regression, adding a survival task, and other specialized models, predictions, and measures. mlr3extralearners is available from <https://github.com/mlr-org/mlr3extralearners>.
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>), Franz Kiraly [aut], Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Nurul Ain Toha [ctb], Andreas Bender [ctb] (<https://orcid.org/0000-0001-5628-8611>)
Maintainer: Raphael Sonabend <raphael.sonabend.15@ucl.ac.uk>

Diff between mlr3proba versions 0.2.1 dated 2020-08-28 and 0.2.2 dated 2020-09-23

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Package MAPITR updated to version 1.1.1 with previous version 1.0.5 dated 2020-09-17

Title: MArginal ePIstasis Test for Regions
Description: A genetic analysis tool and variance component model for identifying marginal epistasis between pathways and the rest of the genome. 'MAPITR' uses as input a matrix of genotypes, a vector of phenotypes, and a list of pathways. 'MAPITR' then iteratively tests each pathway for epistasis between any variants within the pathway versus any variants remaining in the rest of the genome. 'MAPITR' returns results in the form of p-values for every pathway indicating whether the null model of there being no epistatic interactions between a pathway and the rest of the genome can be rejected.
Author: Michael Turchin [aut, cre] (<https://orcid.org/0000-0003-3569-1529>), Gregory Darnell [aut, ctb] (<https://orcid.org/0000-0003-0425-940X>), Lorin Crawford [aut, ctb] (<https://orcid.org/0000-0003-0178-8242>), Sohini Ramachandran [aut] (<https://orcid.org/0000-0002-9588-7964>), Peter Carbonetto [ctb] (<https://orcid.org/0000-0003-1144-6780>)
Maintainer: Michael Turchin <michael_turchin@brown.edu>

Diff between MAPITR versions 1.0.5 dated 2020-09-17 and 1.1.1 dated 2020-09-23

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Package IRTBEMM updated to version 1.0.5 with previous version 1.0.4 dated 2020-09-17

Title: Family of Bayesian EMM Algorithm for Item Response Models
Description: Applying the family of the Bayesian Expectation-Maximization-Maximization (BEMM) algorithm to estimate: (1) Three parameter logistic (3PL) model proposed by Birnbaum (1968, ISBN:9780201043105); (2) four parameter logistic (4PL) model proposed by Barton & Lord (1981) <doi:10.1002/j.2333-8504.1981.tb01255.x>; (3) one parameter logistic guessing (1PLG) and (4) one parameter logistic ability-based guessing (1PLAG) models proposed by San Martín et al (2006) <doi:10.1177/0146621605282773>. The BEMM family includes (1) the BEMM algorithm for 3PL model proposed by Guo & Zheng (2019) <doi:10.3389/fpsyg.2019.01175>; (2) the BEMM algorithm for 1PLG model and (3) the BEMM algorithm for 1PLAG model proposed by Guo, Wu, Zheng, & Wang (2018) <https:www.ncme.org/news/past-meetings/2018-recap>; (4) the BEMM algorithm for 4PL model proposed by Zhang, Guo, & Zheng (2018) <https:www.ncme.org/news/past-meetings/2018-recap>; and (5) their maximum likelihood estimation versions proposed by Zheng, Meng, Guo, & Liu (2018) <doi:10.3389/fpsyg.2017.02302>. Thus, both Bayesian modal estimates and maximum likelihood estimates are available.
Author: Shaoyang Guo [aut, cre, cph], Chanjin Zheng [aut], Justin L Kern [aut]
Maintainer: Shaoyang Guo <syguo1992@outlook.com>

Diff between IRTBEMM versions 1.0.4 dated 2020-09-17 and 1.0.5 dated 2020-09-23

 IRTBEMM-1.0.4/IRTBEMM/src                   |only
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 IRTBEMM-1.0.5/IRTBEMM/NAMESPACE             |    2 
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 IRTBEMM-1.0.5/IRTBEMM/R/BEMM.1PLAG.R        |  555 ++++++++++++++++++++----
 IRTBEMM-1.0.5/IRTBEMM/R/BEMM.1PLG.R         |  443 +++++++++++++++----
 IRTBEMM-1.0.5/IRTBEMM/R/BEMM.3PL.R          |  520 ++++++++++++++++++-----
 IRTBEMM-1.0.5/IRTBEMM/R/BEMM.4PL.R          |  623 ++++++++++++++++++++++------
 IRTBEMM-1.0.5/IRTBEMM/R/ToolBox.R           |  138 ++++--
 IRTBEMM-1.0.5/IRTBEMM/build/partial.rdb     |binary
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 IRTBEMM-1.0.5/IRTBEMM/man/BEMM.1PLG.Rd      |    7 
 IRTBEMM-1.0.5/IRTBEMM/man/BEMM.3PL.Rd       |    7 
 IRTBEMM-1.0.5/IRTBEMM/man/BEMM.4PL.Rd       |    7 
 IRTBEMM-1.0.5/IRTBEMM/man/Input.Checking.Rd |    5 
 17 files changed, 1834 insertions(+), 533 deletions(-)

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New package GMMAT with initial version 1.3.1
Package: GMMAT
Version: 1.3.1
Date: 2020-09-14
Title: Generalized Linear Mixed Model Association Tests
Author: Han Chen, Matthew P. Conomos, Duy T. Pham
Maintainer: Han Chen <Han.Chen.2@uth.tmc.edu>
Description: Perform association tests using generalized linear mixed models (GLMMs) in genome-wide association studies (GWAS) and sequencing association studies. First, GMMAT fits a GLMM with covariate adjustment and random effects to account for population structure and familial or cryptic relatedness. For GWAS, GMMAT performs score tests for each genetic variant as proposed in Chen et al. (2016) <DOI:10.1016/j.ajhg.2016.02.012>. For candidate gene studies, GMMAT can also perform Wald tests to get the effect size estimate for each genetic variant. For rare variant analysis from sequencing association studies, GMMAT performs the variant Set Mixed Model Association Tests (SMMAT) as proposed in Chen et al. (2019) <DOI:10.1016/j.ajhg.2018.12.012>, including the burden test, the sequence kernel association test (SKAT), SKAT-O and an efficient hybrid test of the burden test and SKAT, based on user-defined variant sets.
License: GPL-3
Copyright: See COPYRIGHTS for details.
Imports: Rcpp, SeqArray, SeqVarTools, CompQuadForm, foreach, parallel, Matrix, methods
Suggests: doMC, testthat
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
NeedsCompilation: yes
Depends: R (>= 3.2.0)
Packaged: 2020-09-21 15:50:00 UTC; hchen
Repository: CRAN
Date/Publication: 2020-09-23 06:30:23 UTC

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Package GermaParl updated to version 1.5.2 with previous version 1.5.1 dated 2020-07-27

Title: Download and Augment the Corpus of Plenary Protocols of the German Bundestag
Description: Data package to disseminate the 'GermaParl' corpus of parliamentary debates of the German Bundestag prepared in the 'PolMine Project'. The package includes a small subset of the corpus for demonstration and testing purposes. The package includes functionality to download the full corpus and supplementary data from the open science repository 'Zenodo'.
Author: Andreas Blaette [aut, cre], Christoph Leonhardt [ctb]
Maintainer: Andreas Blaette <andreas.blaette@uni-due.de>

Diff between GermaParl versions 1.5.1 dated 2020-07-27 and 1.5.2 dated 2020-09-23

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 10 files changed, 98 insertions(+), 50 deletions(-)

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Package rBiasCorrection updated to version 0.2.3 with previous version 0.2.2 dated 2020-09-22

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

Diff between rBiasCorrection versions 0.2.2 dated 2020-09-22 and 0.2.3 dated 2020-09-23

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 tests/testthat/test-create_aggregated.R    |   11 ++++++++---
 7 files changed, 27 insertions(+), 19 deletions(-)

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Package quanteda updated to version 2.1.2 with previous version 2.1.1 dated 2020-07-27

Title: Quantitative Analysis of Textual Data
Description: A fast, flexible, and comprehensive framework for quantitative text analysis in R. Provides functionality for corpus management, creating and manipulating tokens and ngrams, exploring keywords in context, forming and manipulating sparse matrices of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and distances, applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses, and more.
Author: Kenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (<https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (<https://orcid.org/0000-0003-4992-4311>), Paul Nulty [aut] (<https://orcid.org/0000-0002-7214-4666>), Adam Obeng [aut] (<https://orcid.org/0000-0002-2906-4775>), Stefan Müller [aut] (<https://orcid.org/0000-0002-6315-4125>), Akitaka Matsuo [aut] (<https://orcid.org/0000-0002-3323-6330>), Jiong Wei Lua [aut], Jouni Kuha [aut] (<https://orcid.org/0000-0002-1156-8465>), William Lowe [aut] (<https://orcid.org/0000-0002-1549-6163>), Christian Müller [ctb], Lori Young [dtc] (Lexicoder Sentiment Dictionary 2015), Stuart Soroka [dtc] (Lexicoder Sentiment Dictionary 2015), Ian Fellows [cph] (authored wordcloud C source code (modified)), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS)
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

Diff between quanteda versions 2.1.1 dated 2020-07-27 and 2.1.2 dated 2020-09-23

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 tests/testthat/test-spacyr-methods.R   |    4 
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 tests/testthat/test-tokens.R           |    5 +
 tests/testthat/test-tokens_recompile.R |    1 
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 40 files changed, 395 insertions(+), 314 deletions(-)

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Package kofdata (with last version 0.1.3.4) was removed from CRAN

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

2020-03-28 0.1.3.4
2019-08-05 0.1.3.3

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