Fri, 20 Nov 2020

Package generalCorr updated to version 1.1.6 with previous version 1.1.5 dated 2019-10-30

Title: Generalized Correlations and Various Causal Paths
Description: Since causal paths from data are important for all sciences, the package provides many sophisticated functions. causeSummBlk() gives easy-to-interpret causal paths. Let Z denote control variables and compare two flipped kernel regressions: X=f(Y, Z)+e1 and Y=g(X,Z)+e2. Our criterion Cr1 says that if |e1*Y|>|e2*X| then variation in X is more "exogenous or independent" than in Y and causal path is X to Y. Criterion Cr2 requires |e2|<|e1|. These inequalities between many absolute values are quantified by four orders of stochastic dominance. Our third criterion Cr3 for the causal path X to Y requires new generalized partial correlations to satisfy |r*(x|y,z)|< |r*(y|x,z)|. The function parcorBMany() reports generalized partials between the first variable and all others. The package provides several R functions including get0outliers() for outlier detection, bigfp() for numerical integration by the trapezoidal rule, stochdom2() for stochastic dominance, pillar3D() for 3D charts, canonRho() for generalized canonical correlations, depMeas() measures nonlinear dependence, and causeSummary(mtx) reports summary of causal paths among matrix columns is easiest to use. Several functions whose names begin with 'boot' provide bootstrap statistical inference including a new bootGcRsq() test for "Granger-causality" allowing nonlinear relations. See Vinod (2019) <doi:10.1080/03610918.2015.1122048>.
Author: Prof. H. D. Vinod, Fordham University, NY.
Maintainer: H. D. Vinod <vinod@fordham.edu>

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Package eba updated to version 1.10-0 with previous version 1.9-0 dated 2019-04-02

Title: Elimination-by-Aspects Models
Description: Fitting and testing multi-attribute probabilistic choice models, especially the Bradley-Terry-Luce (BTL) model (Bradley & Terry, 1952 <doi:10.1093/biomet/39.3-4.324>; Luce, 1959), elimination-by-aspects (EBA) models (Tversky, 1972 <doi:10.1037/h0032955>), and preference tree (Pretree) models (Tversky & Sattath, 1979 <doi:10.1037/0033-295X.86.6.542>).
Author: Florian Wickelmaier [aut, cre]
Maintainer: Florian Wickelmaier <wickelmaier@web.de>

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Package BioVenn updated to version 1.1.0 with previous version 1.0.5 dated 2020-11-10

Title: Create Area-Proportional Venn Diagrams from Biological Lists
Description: Creates an area-proportional Venn diagram of 2 or 3 circles. 'BioVenn' is the only R package that can automatically generate an accurate area-proportional Venn diagram by having only lists of (biological) identifiers as input. Also offers the option to map Entrez and/or Affymetrix IDs to Ensembl IDs. In SVG mode, text and numbers can be dragged and dropped. Based on the BioVenn web interface available at <https://www.biovenn.nl>. Hulsen et al. (2008) <doi:10.1186/1471-2164-9-488>.
Author: Tim Hulsen [aut, cre] (<https://orcid.org/0000-0002-0208-8443>)
Maintainer: Tim Hulsen <thulsen@gmail.com>

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Package extremis updated to version 1.0 with previous version 0.90 dated 2018-10-28

Title: Statistics of Extremes
Description: Conducts inference in statistical models for extreme values (de Carvalho et al (2012), <doi:10.1080/03610926.2012.709905>; de Carvalho and Davison (2014), <10.1080/01621459.2013.872651>; Einmahl et al (2016), <doi:10.1111/rssb.12099>).
Author: Miguel de Carvalho [aut, cre], Rodrigo Rubio [aut], Vianey Palacios [aut], Alejandro Jara [ctb], Tim Hanson [ctb]
Maintainer: Miguel de Carvalho <miguel.decarvalho@ed.ac.uk>

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Package nflfastR updated to version 3.2.0 with previous version 3.1.1 dated 2020-10-22

Title: Functions to Efficiently Access NFL Play by Play Data
Description: A set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.
Author: Sebastian Carl [aut], Ben Baldwin [cre, aut], Lee Sharpe [ctb], Maksim Horowitz [ctb], Ron Yurko [ctb], Samuel Ventura [ctb]
Maintainer: Ben Baldwin <bbaldwin206@gmail.com>

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Package MAMS updated to version 1.4.1 with previous version 1.4 dated 2020-11-17

Title: Designing Multi-Arm Multi-Stage Studies
Description: Designing multi-arm multi-stage studies with (asymptotically) normal endpoints and known variance.
Author: Thomas Jaki <jaki.thomas@gmail.com>, Dominic Magirr <d.magirr@gmail.com>, Philip Pallmann <p.pallmann@lancaster.ac.uk>
Maintainer: Thomas Jaki <jaki.thomas@gmail.com>

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Package ENMTools updated to version 1.0.2 with previous version 1.0.1 dated 2020-08-28

Title: Analysis of Niche Evolution using Niche and Distribution Models
Description: Description: Tools for constructing niche models and analyzing patterns of niche evolution. Acts as an interface for many popular modeling algorithms, and allows users to conduct Monte Carlo tests to address basic questions in evolutionary ecology and biogeography. Warren, D.L., R.E. Glor, and M. Turelli (2008) <doi:10.1111/j.1558-5646.2008.00482.x> Glor, R.E., and D.L. Warren (2011) <doi:10.1111/j.1558-5646.2010.01177.x> Warren, D.L., R.E. Glor, and M. Turelli (2010) <doi:10.1111/j.1600-0587.2009.06142.x> Cardillo, M., and D.L. Warren (2016) <doi:10.1111/geb.12455> D.L. Warren, L.J. Beaumont, R. Dinnage, and J.B. Baumgartner (2019) <doi:10.1111/ecog.03900>.
Author: Dan Warren [aut, cre] (<https://orcid.org/0000-0002-8747-2451>), Nick Matzke [ctb], Marcel Cardillo [ctb], John Baumgartner [ctb], Linda Beaumont [ctb], Nicholas Huron [ctb], Marianna Simoes [ctb], Teresa Iglesias [ctb], Russell Dinnage [aut] (<https://orcid.org/0000-0003-0846-2819>)
Maintainer: Dan Warren <dan.l.warren@gmail.com>

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Package d3r updated to version 0.9.1 with previous version 0.9.0 dated 2020-05-25

Title: 'd3.js' Utilities for R
Description: Provides a suite of functions to help ease the use of 'd3.js' in R. These helpers include 'htmltools::htmlDependency' functions, hierarchy builders, and conversion tools for 'partykit', 'igraph,' 'table', and 'data.frame' R objects into the 'JSON' that 'd3.js' expects.
Author: Mike Bostock [aut, cph] (d3.js library in htmlwidgets/lib, http://d3js.org), Kent Russell [aut, cre, cph] (R interface), Gregor Aisch [aut, cph] (d3-jetpack creator, https://github.com/gka/d3-jetpack), Adam Pearce [aut] (core contributor to d3-jetpack), Ben Ortiz [ctb]
Maintainer: Kent Russell <kent.russell@timelyportfolio.com>

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Package amapGeocode updated to version 0.5.0 with previous version 0.4.0 dated 2020-10-17

Title: An Interface to the 'AutoNavi Maps' API Geocoding Services
Description: Getting and parsing data of location geocode/reverse-geocode and administrative regions from 'AutoNavi Maps'<https://lbs.amap.com/api/webservice/summary> API.
Author: Han Chen [aut, cre], Wanyanhan Jiang [ctb]
Maintainer: Han Chen <chenhan28@gmail.com>

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

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

2019-12-06 0.1.0

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Package wrMisc updated to version 1.4.2 with previous version 1.4.1 dated 2020-11-13

Title: Analyze Experimental High-Throughput (Omics) Data
Description: The efficient treatment and convenient analysis of experimental high-throughput (omics) data gets facilitated through this collection of diverse functions. Several functions address advanced object-conversions, like manipulating lists of lists or lists of arrays, reorganizing lists to arrays or into separate vectors, merging of multiple entries, etc. Another set of functions provides speed-optimized calculation of standard deviation (sd), coefficient of variance (CV) or standard error of the mean (SEM) for data in matrixes or means per line with respect to additional grouping (eg n groups of replicates). Other functions facilitate dealing with non-redundant information, by indexing unique, adding counters to redundant or eliminating lines with respect redundancy in a given reference-column, etc. Help is provided to identify very closely matching numeric values to generate (partial) distance matrixes for very big data in a memory efficient manner or to reduce the complexity of large data-sets by combining very close values. Many times large experimental datasets need some additional filtering, adequate functions are provided. Batch reading (or writing) of sets of files and combining data to arrays is supported, too. Convenient data normalization is supported in various different modes, parameter estimation via permutations or boot-strap as well as flexible testing of multiple pair-wise combinations using the framework of 'limma' is provided, too.
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@unistra.fr>

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Package packDAMipd updated to version 0.1.2 with previous version 0.1.0 dated 2020-11-09

Title: Decision Analysis Modelling Package with Parameters Estimation Ability from Individual Patient Level Data
Description: A collection of functions to construct Markov model for model-based cost-effectiveness analysis. This includes creating Markov model (both time homogenous and time dependent models), decision analysis, sensitivity analysis (deterministic and probabilistic). The package allows estimation of parameters for the Markov model from a given individual patient level data, provided the data file follows some standard data entry rules.
Author: Sheeja Manchira Krishnan [aut, cre]
Maintainer: Sheeja Manchira Krishnan <sheejamk@gmail.com>

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Package maptiles updated to version 0.1.1 with previous version 0.1.0 dated 2020-11-10

Title: Download and Display Map Tiles
Description: To create maps from tiles, 'maptiles' downloads, composes and displays tiles from a large number of providers (e.g. 'OpenStreetMap', 'Stamen', 'Esri', 'CARTO', or 'Thunderforest').
Author: Timothée Giraud [cre, aut] (<https://orcid.org/0000-0002-1932-3323>)
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>

Diff between maptiles versions 0.1.0 dated 2020-11-10 and 0.1.1 dated 2020-11-20

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Package exactextractr updated to version 0.5.1 with previous version 0.5.0 dated 2020-10-26

Title: Fast Extraction from Raster Datasets using Polygons
Description: Provides a replacement for the 'extract' function from the 'raster' package that is suitable for extracting raster values using 'sf' polygons.
Author: Daniel Baston [aut, cre], ISciences, LLC [cph]
Maintainer: Daniel Baston <dbaston@isciences.com>

Diff between exactextractr versions 0.5.0 dated 2020-10-26 and 0.5.1 dated 2020-11-20

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Package pathfindR.data updated to version 1.1.1 with previous version 1.1.0 dated 2020-09-21

Title: Data Package for 'pathfindR'
Description: This is a data-only package, containing data needed to run the CRAN package 'pathfindR', a package for enrichment analysis utilizing active subnetworks. This package contains protein-protein interaction network data, data related to gene sets and example input/output data.
Author: Ege Ulgen [cre, cph] (<https://orcid.org/0000-0003-2090-3621>), Ozan Ozisik [aut] (<https://orcid.org/0000-0001-5980-8002>)
Maintainer: Ege Ulgen <egeulgen@gmail.com>

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Package LipidMS updated to version 1.2.0 with previous version 1.1.0 dated 2019-10-21

Title: Lipid Annotation for LC-MS/MS DIA Data
Description: Lipid annotation in untargeted liquid chromatography-data independent acquisition mass spectrometry lipidomics based on fragmentation rules. Alcoriza-Balaguer MI, Garcia-Canaveras JC, Lopez A, Conde I, Juan O, Carretero J, Lahoz A (2019) <doi:10.1021/acs.analchem.8b03409>.
Author: M Isabel Alcoriza-Balaguer, J Carlos Garcia-Canaveras
Maintainer: M Isabel Alcoriza-Balaguer <maribel_alcoriza@iislafe.es>

Diff between LipidMS versions 1.1.0 dated 2019-10-21 and 1.2.0 dated 2020-11-20

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More information about LipidMS at CRAN
Permanent link

Package hNMF updated to version 1.0 with previous version 0.9 dated 2018-10-18

Title: Hierarchical Non-Negative Matrix Factorization
Description: Hierarchical and single-level non-negative matrix factorization. Several NMF algorithms are available.
Author: Nicolas Sauwen
Maintainer: Nicolas Sauwen <nicolas.sauwen@openanalytics.eu>

Diff between hNMF versions 0.9 dated 2018-10-18 and 1.0 dated 2020-11-20

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Package cleanr updated to version 1.3.1 with previous version 1.3.0 dated 2020-01-09

Title: Helps You to Code Cleaner
Description: Check your R code for some of the most common layout flaws. Many tried to teach us how to write code less dreadful, be it implicitly as B. W. Kernighan and D. M. Ritchie (1988) <ISBN:0-13-110362-8> in 'The C Programming Language' did, be it explicitly as R.C. Martin (2008) <ISBN:0-13-235088-2> in 'Clean Code: A Handbook of Agile Software Craftsmanship' did. So we should check our code for files too long or wide, functions with too many lines, too wide lines, too many arguments or too many levels of nesting. Note: This is not a static code analyzer like pylint or the like. Checkout <https://cran.r-project.org/package=lintr> instead.
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>

Diff between cleanr versions 1.3.0 dated 2020-01-09 and 1.3.1 dated 2020-11-20

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Package PxWebApiData updated to version 0.4.0 with previous version 0.3.0 dated 2019-04-11

Title: PX-Web Data by API
Description: Function to read PX-Web data into R via API. The example code reads data from the three national statistical institutes, Statistics Norway, Statistics Sweden and Statistics Finland.
Author: Øyvind Langsrud [aut, cre], Jan Bruusgaard [aut], Solveig Bjørkholt [ctb], Susie Jentoft [ctb]
Maintainer: Øyvind Langsrud <oyl@ssb.no>

Diff between PxWebApiData versions 0.3.0 dated 2019-04-11 and 0.4.0 dated 2020-11-20

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Package DecorateR updated to version 0.1.2 with previous version 0.1.1 dated 2017-02-22

Title: Fit and Deploy DECORATE Trees
Description: DECORATE (Diverse Ensemble Creation by Oppositional Relabeling of Artificial Training Examples) builds an ensemble of J48 trees by recursively adding artificial samples of the training data ("Melville, P., & Mooney, R. J. (2005) <DOI:10.1016/j.inffus.2004.04.001>").
Author: Matthias Bogaert
Maintainer: Matthias Bogaert <Matthias.Bogaert@UGent.Be>

Diff between DecorateR versions 0.1.1 dated 2017-02-22 and 0.1.2 dated 2020-11-20

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New package trendeval with initial version 0.0.1
Package: trendeval
Title: Evaluate Trending Models
Version: 0.0.1
Authors@R: c( person( given = "Dirk", family = "Schumacher", role = c("aut"), email = "mail@dirk-schumacher.net" ), person( given = "Thibaut", family = "Jombart", role = c("aut"), email = "thibautjombart@gmail.com" ), person( given = "Tim", family = "Taylor", role = c("ctb", "cre"), email = "tim.taylor@hiddenelephants.co.uk", comment = c(ORCID = "0000-0002-8587-7113") ) )
Description: Provides a coherent interface for evaluating models fit with the trending package. This package is part of the RECON (<https://www.repidemicsconsortium.org/>) toolkit for outbreak analysis.
URL: https://github.com/reconhub/trendeval
BugReports: https://github.com/reconhub/trendeval/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: trending, yardstick, rsample, ellipsis, stats, tidyr, tibble
Suggests: testthat, dplyr, outbreaks
NeedsCompilation: no
Packaged: 2020-11-19 10:42:55 UTC; tim
Author: Dirk Schumacher [aut], Thibaut Jombart [aut], Tim Taylor [ctb, cre] (<https://orcid.org/0000-0002-8587-7113>)
Maintainer: Tim Taylor <tim.taylor@hiddenelephants.co.uk>
Repository: CRAN
Date/Publication: 2020-11-20 10:50:02 UTC

More information about trendeval at CRAN
Permanent link

Package synoptReg updated to version 1.1.0 with previous version 1.0.2 dated 2020-09-04

Title: Synoptic Climate Classification and Spatial Regionalization of Environmental Data
Description: Set of functions to compute different types of synoptic classification methods and for analysing their effect on environmental variables. More information about the methods used in Lemus-Canovas et al. 2019 <DOI:10.1016/j.atmosres.2019.01.018>, Martin-Vide et al. 2008 <DOI:10.5194/asr-2-99-2008> and Jenkinson and Collison 1977.
Author: Marc Lemus-Canovas [aut, cre] (<https://orcid.org/0000-0002-0925-3827>), Dominic Roye) [aut] (<https://orcid.org/0000-0002-5516-6396>)
Maintainer: Marc Lemus-Canovas <mlemus@ub.edu>

Diff between synoptReg versions 1.0.2 dated 2020-09-04 and 1.1.0 dated 2020-11-20

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New package slopeOP with initial version 1.0.0
Package: slopeOP
Type: Package
Title: Change-in-Slope OP Algorithm with a Finite Number of States
Version: 1.0.0
Authors@R: c( person("Vincent", "Runge", email = "vincent.runge@univ-evry.fr", role = c("aut", "cre")), person("Marco", "Pascucci", role = c("aut")))
Maintainer: Vincent Runge <vincent.runge@univ-evry.fr>
Description: Optimal partitioning algorithm for change-in-slope problem with continuity constraint and a finite number of states. Some constraints can be enforced in the inference: isotonic, unimodal or smoothing. With the function slopeSN() (segment neighborhood) the number of segments to infer is fixed by the user and does not depend on a penalty value.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2020-11-19 12:09:33 UTC; vrunge
Author: Vincent Runge [aut, cre], Marco Pascucci [aut]
Repository: CRAN
Date/Publication: 2020-11-20 10:30:06 UTC

More information about slopeOP at CRAN
Permanent link

Package RMixtCompIO updated to version 4.0.6 with previous version 4.0.5 dated 2020-06-18

Title: Minimal Interface of the C++ 'MixtComp' Library for Mixture Models with Heterogeneous and (Partially) Missing Data
Description: Mixture Composer <https://github.com/modal-inria/MixtComp> is a project to build mixture models with heterogeneous data sets and partially missing data management. It includes models for real, categorical, counting, functional and ranking data. This package contains the minimal R interface of the C++ 'MixtComp' library.
Author: Vincent Kubicki [aut], Christophe Biernacki [aut], Quentin Grimonprez [aut], Serge Iovleff [ctb], Matthieu Marbac-Lourdelle [ctb], Étienne Goffinet [ctb], Patrick Wieschollek [ctb] (for CppOptimizationLibrary), Tobias Wood [ctb] (for CppOptimizationLibrary), Julien Vandaele [ctb, cre]
Maintainer: Julien Vandaele <julien.vandaele@inria.fr>

Diff between RMixtCompIO versions 4.0.5 dated 2020-06-18 and 4.0.6 dated 2020-11-20

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Permanent link

New package reliabilitydiag with initial version 0.1.3
Package: reliabilitydiag
Version: 0.1.3
Title: Reliability Diagrams Using Isotonic Regression
Description: Checking the reliability of predictions via the CORP approach, which generates provably statistically 'C'onsistent, 'O'ptimally binned, and 'R'eproducible reliability diagrams using the 'P'ool-adjacent-violators algorithm. See Dimitriadis, Gneiting, Jordan (2020) <arXiv:2008.03033>.
Authors@R: c( person(given = "Timo", family = "Dimitriadis", role = "aut"), person(given = c("Alexander", "I."), family = "Jordan", role = c("aut", "cre"), email = "alexander.jordan@h-its.org"))
URL: https://github.com/aijordan/reliabilitydiag/
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.1.0)
Imports: magrittr, tidyr, ggplot2, ggExtra, dplyr, purrr, rlang, tibble, vctrs, bde
NeedsCompilation: no
Packaged: 2020-11-19 12:45:07 UTC; aijor
Author: Timo Dimitriadis [aut], Alexander I. Jordan [aut, cre]
Maintainer: Alexander I. Jordan <alexander.jordan@h-its.org>
Repository: CRAN
Date/Publication: 2020-11-20 10:30:09 UTC

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Package readabs updated to version 0.4.6 with previous version 0.4.5.1 dated 2020-10-14

Title: Download and Tidy Time Series Data from the Australian Bureau of Statistics
Description: Downloads, imports, and tidies time series data from the Australian Bureau of Statistics <https://www.abs.gov.au/>.
Author: Matt Cowgill [aut, cre], Zoe Meers [aut], Jaron Lee [aut], David Diviny [aut], Hugh Parsonage [ctb]
Maintainer: Matt Cowgill <mattcowgill@gmail.com>

Diff between readabs versions 0.4.5.1 dated 2020-10-14 and 0.4.6 dated 2020-11-20

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New package pocketapi with initial version 0.1
Package: pocketapi
Title: Wrapper Around the 'Pocket' API
Version: 0.1
Authors@R: c(person("Frie", "Preu", email = "fr1e@pm.me", role = c("aut", "cre")), person("Yannik", "Buhl", email = "yannik.buhl@posteo.de", role = "aut"), person("Max", "Alletsee", email = "max.alletsee@gmail.com", role = "aut"), person("Dorian", "Le Jeune", email = "D.Le-Jeune@gmx.de", role = "ctb"), person("Christoph", "Dworschak", email = "c.dworschak@essex.ac.uk", role = "ctb"), person("Sarah", "Jukna", role = "ctb"), person("CorrelAid e.V.", role = "cph") )
Description: Functions that interface with the 'Pocket' API (<https://getpocket.com/developer/>). Allows the user to get, add, and modify items in their own 'Pocket' account.
Depends: R (>= 3.5.0)
Imports: httr, purrr, tibble, dplyr, glue, jsonlite, magrittr, usethis
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/CorrelAid/pocketapi//issues
URL: https://github.com/CorrelAid/pocketapi/
RoxygenNote: 7.1.1
Suggests: testthat, mockery, covr, httptest, knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-19 08:30:07 UTC; yannik
Author: Frie Preu [aut, cre], Yannik Buhl [aut], Max Alletsee [aut], Dorian Le Jeune [ctb], Christoph Dworschak [ctb], Sarah Jukna [ctb], CorrelAid e.V. [cph]
Maintainer: Frie Preu <fr1e@pm.me>
Repository: CRAN
Date/Publication: 2020-11-20 10:20:02 UTC

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Package multiclassPairs updated to version 0.4.0 with previous version 0.3.1 dated 2020-11-16

Title: Build MultiClass Pair-Based Classifiers using TSPs or RF
Description: A toolbox to train a single sample classifier that uses in-sample feature relationships. The relationships are represented as feature1 < feature2 (e.g. gene1 < gene2). We provide two options to go with. First is based on 'switchBox' package which uses Top-score pairs algorithm. Second is a novel implementation based on random forest algorithm. For simple problems we recommend to use one-vs-rest using TSP option due to its simplicity and for being easy to interpret. For complex problems RF performs better. Both lines filter the features first then combine the filtered features to make the list of all the possible rules (i.e. rule1: feature1 < feature2, rule2: feature1 < feature3, etc...). Then the list of rules will be filtered and the most important and informative rules will be kept. The informative rules will be assembled in an one-vs-rest model or in an RF model. We provide a detailed description with each function in this package to explain the filtration and training methodology in each line.
Author: Nour-al-dain Marzouka
Maintainer: Nour-al-dain Marzouka <Nour-al-dain.Marzouka@med.lu.se>

Diff between multiclassPairs versions 0.3.1 dated 2020-11-16 and 0.4.0 dated 2020-11-20

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Package mclust updated to version 5.4.7 with previous version 5.4.6 dated 2020-04-11

Title: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
Description: Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.
Author: Chris Fraley [aut], Adrian E. Raftery [aut] (<https://orcid.org/0000-0002-6589-301X>), Luca Scrucca [aut, cre] (<https://orcid.org/0000-0003-3826-0484>), Thomas Brendan Murphy [ctb] (<https://orcid.org/0000-0002-5668-7046>), Michael Fop [ctb] (<https://orcid.org/0000-0003-3936-2757>)
Maintainer: Luca Scrucca <luca.scrucca@unipg.it>

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Package IPDFileCheck updated to version 0.6.4 with previous version 0.6.3 dated 2020-06-12

Title: Basic Functions to Check Readability, Consistency, and Content of an Individual Participant Data File
Description: Basic checks needed with an individual level participant data from randomised controlled trial. This checks files for existence, read access and individual columns for formats. The checks on format is currently implemented for gender and age formats.
Author: Sheeja Manchira Krishnan
Maintainer: Sheeja Manchira Krishnan <sheejamk@gmail.com>

Diff between IPDFileCheck versions 0.6.3 dated 2020-06-12 and 0.6.4 dated 2020-11-20

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New package finetune with initial version 0.0.1
Package: finetune
Title: Additional Functions for Model Tuning
Version: 0.0.1
Authors@R: c(person(given = "Max", family = "Kuhn", role = c("aut", "cre"), email = "max@rstudio.com", comment = c(ORCID = "0000-0003-2402-136X")), person(given = "RStudio", role = "cph"))
Description: The ability to tune models is important. 'finetune' enhances the 'tune' package by providing more specialized methods for finding reasonable values of model tuning parameters. Two racing methods described by Kuhn (2014) <arXiv:1405.6974> are included. An iterative search method using generalized simulated annealing (Bohachevsky, Johnson and Stein, 1986) <doi:10.1080/00401706.1986.10488128> is also included.
URL: https://github.com/tidymodels/finetune, https://finetune.tidymodels.org
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1.9000
Suggests: spelling, BradleyTerry2, lme4, rsample, recipes (>= 0.1.15), modeldata, rpart, parsnip, testthat, covr, discrim, klaR
Language: en-US
Depends: tune (>= 0.1.2)
Imports: tibble, rlang, yardstick, workflows, purrr, cli, dials, dplyr, utils, tidyr, tidyselect, ggplot2
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2020-11-19 14:05:07 UTC; max
Author: Max Kuhn [aut, cre] (<https://orcid.org/0000-0003-2402-136X>), RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>
Repository: CRAN
Date/Publication: 2020-11-20 10:30:15 UTC

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Package EvidenceSynthesis updated to version 0.2.1 with previous version 0.2.0 dated 2020-11-19

Title: Synthesizing Causal Evidence in a Distributed Research Network
Description: Routines for combining causal effect estimates and study diagnostics across multiple data sites in a distributed study, without sharing patient-level data. Allows for normal and non-normal approximations of the data-site likelihood of the effect parameter.
Author: Martijn Schuemie [aut, cre], Marc A. Suchard [aut], Observational Health Data Science and Informatics [cph]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

Diff between EvidenceSynthesis versions 0.2.0 dated 2020-11-19 and 0.2.1 dated 2020-11-20

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New package ciftiTools with initial version 0.1.6.0
Package: ciftiTools
Type: Package
Title: Tools for Reading and Visualizing CIFTI Brain Files
Version: 0.1.6.0
Authors@R: c( person(given = "Amanda", family = "Mejia", email = "mandy.mejia@gmail.com", role = c("aut", "cre")), person(given = "Damon", family = "Pham", email = "damondpham@gmail.com", role = c("ctb"), comment = c(ORCID = "0000-0001-7563-4727")))
Maintainer: Amanda Mejia <mandy.mejia@gmail.com>
Description: CIFTI files contain brain imaging data in "gray-ordinates", which represent the gray matter as cortical surface vertices (left and right) and subcortical voxels (cerebellum, basal ganglia, and other deep gray matter). 'ciftiTools' uses the Connectome Workbench to read CIFTI files into R and apply common pre-processing steps (e.g. smoothing, resampling). It also provides tools for visualizing the cortical surface with GIFTI files, and for visualizing the subcortical volume.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: gifti (> 0.7.5), grDevices, oro.nifti, RNifti, RColorBrewer, xml2
Suggests: fields, ggplot2, ggpubr, knitr, rmarkdown, papayar, rgl, testthat (>= 2.1.0), covr
RoxygenNote: 7.1.1
URL: https://github.com/mandymejia/ciftiTools
BugReports: https://github.com/mandymejia/ciftiTools/issues
NeedsCompilation: no
Packaged: 2020-11-19 02:52:18 UTC; damon
Author: Amanda Mejia [aut, cre], Damon Pham [ctb] (<https://orcid.org/0000-0001-7563-4727>)
Repository: CRAN
Date/Publication: 2020-11-20 10:20:05 UTC

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Package ASSA updated to version 2.0 with previous version 1.0 dated 2018-05-14

Title: Applied Singular Spectrum Analysis (ASSA)
Description: Functions to model and decompose time series into principal components using singular spectrum analysis (de Carvalho and Rua (2017) <doi:10.1016/j.ijforecast.2015.09.004>; de Carvalho et al (2012) <doi:10.1016/j.econlet.2011.09.007>).
Author: Miguel de Carvalho [aut, cre], Gabriel Martos [aut]
Maintainer: Miguel de Carvalho <miguel.decarvalho@ed.ac.uk>

Diff between ASSA versions 1.0 dated 2018-05-14 and 2.0 dated 2020-11-20

 DESCRIPTION       |   11 -
 MD5               |   45 ++++--
 NAMESPACE         |   46 ++++--
 R/isst.R          |only
 R/itsframe.R      |only
 R/misst.R         |only
 R/mitsframe.R     |only
 R/msst.R          |  382 ++++++++++++++++++++++--------------------------------
 R/msstc.R         |  124 +++++++++++++++--
 R/mtsframe.R      |   28 ++-
 R/predict.R       |only
 R/sst.R           |  281 ++++++++++++++++-----------------------
 R/tsframe.R       |only
 R/workhorse.R     |  319 ++++++++++++++++++++++++---------------------
 data/merval.RData |only
 man/ASSA.Rd       |    2 
 man/brexit.Rd     |    5 
 man/isst.Rd       |only
 man/itsframe.Rd   |only
 man/merval.Rd     |only
 man/misst.Rd      |only
 man/mitsframe.Rd  |only
 man/msst.Rd       |   86 +++++-------
 man/msstc.Rd      |   69 ++++-----
 man/mtsframe.Rd   |   28 ++-
 man/predict.Rd    |only
 man/sst.Rd        |  118 +++++-----------
 man/tsframe.Rd    |only
 src/ASSA_init.c   |    8 -
 src/AUTOCOV.f90   |only
 src/YYi.f90       |only
 src/Yi.f90        |only
 32 files changed, 775 insertions(+), 777 deletions(-)

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Package AggregateR updated to version 0.1.1 with previous version 0.1.0 dated 2020-11-18

Title: Aggregate Numeric, Date and Categorical Variables
Description: Convenience functions for aggregating a data frame or data table. Currently mean, sum and variance are supported. For Date variables, the recency and duration are supported. There is also support for dummy variables in predictive contexts. Code has been completely re-written in data.table for computational speed.
Author: Matthias Bogaert, Michel Ballings, Dirk Van den Poel
Maintainer: Matthias Bogaert <matthias.bogaert@ugent.be>

Diff between AggregateR versions 0.1.0 dated 2020-11-18 and 0.1.1 dated 2020-11-20

 DESCRIPTION      |    8 ++++----
 MD5              |    9 +++++----
 R/Aggregate.R    |   32 +++++++++++++++++---------------
 README.md        |only
 inst/NEWS        |    7 ++++++-
 man/Aggregate.Rd |    4 ++--
 6 files changed, 34 insertions(+), 26 deletions(-)

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New package adheRenceRX with initial version 1.0.0
Package: adheRenceRX
Type: Package
Title: Assess Medication Adherence from Pharmaceutical Claims Data
Version: 1.0.0
Date: 2020-10-27
Authors@R: person("Brennan", "Beal", email = "brennanbeal@gmail.com", role = c("aut", "cre"))
Description: A (mildly) opinionated set of functions to help assess medication adherence for researchers working with medication claims data. Medication adherence analyses have several complex steps that are often convoluted and can be time-intensive. The focus is to create a set of functions using "tidy principles" geared towards transparency, speed, and flexibility while working with adherence metrics. All functions perform exactly one task with an intuitive name so that a researcher can handle details (often achieved with vectorized solutions) while we handle non-vectorized tasks common to most adherence calculations such as adjusting fill dates and determining episodes of care. The methodologies in referenced in this package come from Canfield SL, et al (2019) "Navigating the Wild West of Medication Adherence Reporting in Specialty Pharmacy" <doi:10.18553/jmcp.2019.25.10.1073>.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.5), anytime, tidyr, dplyr, purrr, lubridate, rlang
LinkingTo: Rcpp
RoxygenNote: 7.1.0
Depends: R (>= 2.10)
LazyData: true
Suggests: testthat, spelling
URL: https://github.com/btbeal/adheRenceRX
BugReports: https://github.com/btbeal/adheRenceRX/issues
Language: en-US
NeedsCompilation: yes
Packaged: 2020-11-19 18:09:29 UTC; btbeal
Author: Brennan Beal [aut, cre]
Maintainer: Brennan Beal <brennanbeal@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-20 10:40:10 UTC

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New package specmine.datasets with initial version 0.0.1
Package: specmine.datasets
Type: Package
Title: Data Sets for 'specmine'
Version: 0.0.1
Author: Christopher Costa <chrisbcl@hotmail.com> [aut], Marcelo Maraschin <mtocsy@gmail.com> [aut], Miguel Rocha <mrocha@di.uminho.pt> [aut, cre], Sara Cardoso <saracardoso501@gmail.com> [aut], Telma Afonso <telma.afonso94@gmail.com> [aut], C. Beleites [cph], Jie Hao [cph], Bruno Pereira <pereirinha_bp@hotmail.com> [aut]
Maintainer: Miguel Rocha <mrocha@di.uminho.pt>
Depends: R (>= 4.0.0)
Imports: xcms
NeedsCompilation: no
LazyData: true
Description: Provides the data sets used to exemplify 'specmine'. The data sets were formerly distributed with 'specmine', however they exceed current CRAN policy for package size.
Encoding: UTF-8
License: GPL (>= 2)
Packaged: 2020-11-17 10:48:44 UTC; Asus
Repository: CRAN
Date/Publication: 2020-11-20 09:40:02 UTC

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New package simrec with initial version 1.0.0
Package: simrec
Title: Simulation of Recurrent Event Data for Non-Constant Baseline Hazard
Version: 1.0.0
Date: 2020-11-10
Authors@R: c( person("Katharina", "Ingel", role = "aut", email = "ingel@uni-mainz.de"), person("Antje", "Jahn-Eimermacher", role = "aut"), person("Stella", "Preussler", role = "aut"), person("Federico", "Marini", role = c("aut", "cre"), email = "marinif@uni-mainz.de", comment = c(ORCID = '0000-0003-3252-7758')))
Description: Simulation of recurrent event data for non-constant baseline hazard in the total time model with risk-free intervals and possibly a competing event. Possibility to cut the data to an interim data set. Data can be plotted. Details about the method can be found in Jahn-Eimermacher, A. et al. (2015) <doi:10.1186/s12874-015-0005-2>.
Depends: R (>= 2.10)
Imports: graphics, stats
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, DT
URL: https://github.com/federicomarini/simrec
License: GPL-2
LazyData: true
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-11-18 08:46:18 UTC; fede
Author: Katharina Ingel [aut], Antje Jahn-Eimermacher [aut], Stella Preussler [aut], Federico Marini [aut, cre] (<https://orcid.org/0000-0003-3252-7758>)
Maintainer: Federico Marini <marinif@uni-mainz.de>
Repository: CRAN
Date/Publication: 2020-11-20 09:10:02 UTC

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New package ShellChron with initial version 0.2.8
Package: ShellChron
Title: Builds Chronologies from Oxygen Isotope Profiles in Shells
Version: 0.2.8
Authors@R: person(given = "Niels", family = "de Winter", role = c("aut", "cre"), email = "niels_de_winter@live.nl", comment = c(ORCID = "0000-0002-1453-5407"))
Description: Takes as input a stable oxygen isotope (d18O) profile measured in growth direction (D) through a shell + uncertainties in both variables (d18O_err & D_err). It then models the seasonality in the d18O record by fitting a combination of a growth and temperature sine wave to year-length chunks of the data (see Judd et al., (2018) <doi:10.1016/j.palaeo.2017.09.034>). This modelling is carried out along a sliding window through the data and yields estimates of the day of the year (Julian Day) and local growth rate for each data point. Uncertainties in both modelling routine and the data itself are propagated and pooled to obtain a confidence envelope around the age of each data point in the shell. The end result is a shell chronology consisting of estimated ages of shell formation relative to the annual cycle with their uncertainties. All formulae in the package serve this purpose, but the user can customize the model (e.g. number of days in a year and the mineralogy of the shell carbonate) through input parameters.
Imports: rtop (>= 0.5.14), zoo (>= 1.8.7), ggplot2 (>= 3.2.1), ggpubr (>= 0.4.0), tidyverse (>= 1.3.0), tidyr (>= 1.1.1), scales (>= 1.1.0), dplyr, magrittr
License: GPL-3
URL: https://github.com/nielsjdewinter/ShellChron
BugReports: https://github.com/nielsjdewinter/ShellChron/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-11-18 12:41:45 UTC; Convernaum
Author: Niels de Winter [aut, cre] (<https://orcid.org/0000-0002-1453-5407>)
Maintainer: Niels de Winter <niels_de_winter@live.nl>
Repository: CRAN
Date/Publication: 2020-11-20 09:40:05 UTC

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New package qst with initial version 0.1.2
Package: qst
Type: Package
Title: Store Tables in SQL Database
Version: 0.1.2
Author: Magnus Thor Torfason
Maintainer: Magnus Thor Torfason <m@zulutime.net>
Description: Provides functions for quickly writing (and reading back) a data.frame to file in 'SQLite' format. The name stands for *Store Tables using 'SQLite'*, or alternatively for *Quick Store Tables* (either way, it could be pronounced as *Quest*). For data.frames containing the supported data types it is intended to work as a drop-in replacement for the 'write_*()' and 'read_*()' functions provided by similar packages.
License: MIT + file LICENCE
Language: en-US
Encoding: UTF-8
LazyData: true
Imports: RSQLite, DBI, dplyr, dbplyr, tibble, magrittr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-18 21:10:30 UTC; magnus
Repository: CRAN
Date/Publication: 2020-11-20 10:00:02 UTC

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New package onlineretail with initial version 0.1.0
Package: onlineretail
Type: Package
Title: Online Retail Dataset
Version: 0.1.0
Date: 2020-11-14
Authors@R: c( person(given="Allan", family="Quadros", role = c("aut", "cre"), email = "allanvcq@gmail.com", comment = c(ORCID = "0000-0003-3250-5380")))
Description: Transactions occurring for a UK-based and registered, non-store online retail between 01/12/2010 and 09/12/2011. This dataset is included in this package with permission of the donor, Dr. Daqing Chen.
Depends: R (>= 3.5.0)
License: CC0
URL: https://github.com/allanvc/onlineretail/
BugReports: https://github.com/allanvc/onlineretail/issues/
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-17 16:32:46 UTC; allan
Author: Allan Quadros [aut, cre] (<https://orcid.org/0000-0003-3250-5380>)
Maintainer: Allan Quadros <allanvcq@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-20 09:10:05 UTC

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New package MetaIntegration with initial version 0.1.1
Type: Package
Package: MetaIntegration
Title: Ensemble Meta-Prediction Framework
Version: 0.1.1
Description: An ensemble meta-prediction framework to integrate multiple regression models into a current study. Gu, T., Taylor, J.M.G. and Mukherjee, B. (2020) <arXiv:2010.09971>. A meta-analysis framework along with two weighted estimators as the ensemble of empirical Bayes estimators, which combines the estimates from the different external models. The proposed framework is flexible and robust in the ways that (i) it is capable of incorporating external models that use a slightly different set of covariates; (ii) it is able to identify the most relevant external information and diminish the influence of information that is less compatible with the internal data; and (iii) it nicely balances the bias-variance trade-off while preserving the most efficiency gain. The proposed estimators are more efficient than the naive analysis of the internal data and other naive combinations of external estimators.
Authors@R: c( person(given = "Tian", family = "Gu", role = c("aut"), email = "gutian@umich.edu"), person(given = "Bhramar", family = "Mukherjee", role = c("aut"), email = "bhramar@umich.edu"), person(given = "Michael", family = "Kleinsasser", role = c("cre"), email = "mkleinsa@umich.edu") )
Maintainer: Michael Kleinsasser <mkleinsa@umich.edu>
License: GPL-2
Encoding: UTF-8
LazyData: true
Biarch: true
Depends: R (>= 3.5.0)
Imports: Rsolnp, corpcor, MASS, knitr
URL: https://github.com/umich-biostatistics/MetaIntegration
BugReports: https://github.com/umich-biostatistics/MetaIntegration/issues
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-17 15:39:03 UTC; mkleinsa
Author: Tian Gu [aut], Bhramar Mukherjee [aut], Michael Kleinsasser [cre]
Repository: CRAN
Date/Publication: 2020-11-20 09:40:08 UTC

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New package LFDR.MME with initial version 1.0
Package: LFDR.MME
Type: Package
Title: Estimating Local False Discovery Rates Using the Method of Moments
Version: 1.0
Date: 2020-11-17
Author: Ali Karimnezhad
Maintainer: Ali Karimnezhad <ali.karimnezhad@gmail.com>
Description: Estimation of the local false discovery rate using the method of moments.
Depends: R(>= 2.14.2)
Encoding: UTF-8
biocViews: Bayesian, MathematicalBiology, MultipleComparison
License: GPL-3
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-18 02:52:23 UTC; alikarimnezhad
Repository: CRAN
Date/Publication: 2020-11-20 09:10:08 UTC

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New package kerTests with initial version 0.1.2
Package: kerTests
Type: Package
Title: Generalized Kernel Two-Sample Tests
Version: 0.1.2
Author: Hoseung Song and Hao Chen
Maintainer: Hoseung Song <hosong@ucdavis.edu>
Description: New kernel-based test and fast tests for testing whether two samples are from the same distribution. They work well particularly for high-dimensional data.
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-11-18 17:38:59 UTC; hoseung
Repository: CRAN
Date/Publication: 2020-11-20 09:50:02 UTC

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New package HeckmanEM with initial version 0.1.1
Package: HeckmanEM
Type: Package
Title: Fit Normal or Student-t Heckman Selection Models
Version: 0.1.1
Authors@R: c(person("Marcos", "Prates", role=c("aut","cre","trl"), email="marcosop@est.ufmg.br"), person("Victor", "Lachos", role="aut"), person("Dipak", "Dey", role="aut"))
Author: Marcos Prates [aut, cre, trl], Victor Lachos [aut], Dipak Dey [aut]
Maintainer: Marcos Prates <marcosop@est.ufmg.br>
Description: Maximum likelihood estimation by an EM algorithm of Heckman-type sample selection Normal or Student-t models. The reference is Lachos, Prates and Dey (2020) <arXiv:2006.08036>.
Imports: mvtnorm (>= 1.1-0), sampleSelection (>= 1.2-6), MomTrunc (>= 5.79), PerformanceAnalytics (>= 2.0.4)
License: GPL (>= 2.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-17 19:55:33 UTC; marcos
Repository: CRAN
Date/Publication: 2020-11-20 09:50:05 UTC

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New package GOxploreR with initial version 1.1.0
Package: GOxploreR
Type: Package
Title: Structural Exploration of the Gene Ontology (GO) Knowledge Base
Version: 1.1.0
Author: Kalifa Manjang, Frank Emmert-Streib, Shailesh Tripathi, Olli Yli-Harja, Matthias Dehmer
Maintainer: Kalifa Manjang <kalifamanjang1@gmail.com>
Description: It provides an effective, efficient, and fast way to explore the Gene Ontology (GO). Given a set of genes, the package contains functions to assess the GO and obtain the terms associated with the genes and the levels of the GO terms. The package provides functions for the three different GO ontology. We discussed the methods explicitly in the following article <doi:10.1038/s41598-020-73326-3>.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: GO.db, igraph, network, ggnetwork, dplyr, biomaRt, annotate, graphics
Depends: R (>= 2.10), ggplot2, gontr
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-18 12:10:27 UTC; kalifa
Repository: CRAN
Date/Publication: 2020-11-20 09:30:03 UTC

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New package gggap with initial version 1.0.1
Package: gggap
Type: Package
Title: Streamlined Creation of Segments on the Y-Axis of 'ggplot2' Plots
Version: 1.0.1
Authors@R: c( person("Carlos", "Morales", role=c("aut", "cre"), email = "carlosmorales777@gmail.com"), person("Jiacheng", "Lou", role = "aut"), person("Jing", "Zhang", role = "aut"), person("Yizhu", "Lvy", role = "aut"), person("Zhi", "Jin", role = "aut") )
Description: The function gggap() streamlines the creation of segments on the y-axis of 'ggplot2' plots which is otherwise not a trivial task to accomplish.
Imports: ggplot2, cowplot, grid
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/cmoralesmx/gggap
BugReports: https://github.com/cmoralesmx/gggap/issues
NeedsCompilation: no
Packaged: 2020-11-17 13:25:12 UTC; cmoralesmx
Author: Carlos Morales [aut, cre], Jiacheng Lou [aut], Jing Zhang [aut], Yizhu Lvy [aut], Zhi Jin [aut]
Maintainer: Carlos Morales <carlosmorales777@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-20 09:20:02 UTC

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New package FSDAM with initial version 2020.11-18
Package: FSDAM
LazyLoad: yes
LazyData: yes
Version: 2020.11-18
Title: Forward Stepwise Deep Autoencoder-Based Monotone NLDR
Authors@R: c(person("Youyi", "Fong", role = "cre", email = "youyifong@gmail.com"), person("Jun", "Xu", role = "aut", email = "junxu8@gmail.com"))
Maintainer: Youyi Fong <youyifong@gmail.com>
Depends: R (>= 3.5.0)
Suggests: R.rsp, RUnit
Imports: kyotil, reticulate (>= 1.10)
VignetteBuilder: R.rsp
Description: FS-DAM performs feature extraction through latent variables identification. Implementation is based on autoencoders with monotonicity and orthogonality constraints.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2020-11-18 17:55:45 UTC; Youyi
Author: Youyi Fong [cre], Jun Xu [aut]
Repository: CRAN
Date/Publication: 2020-11-20 09:50:08 UTC

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Package cli updated to version 2.2.0 with previous version 2.1.0 dated 2020-10-12

Title: Helpers for Developing Command Line Interfaces
Description: A suite of tools to build attractive command line interfaces ('CLIs'), from semantic elements: headings, lists, alerts, paragraphs, etc. Supports custom themes via a 'CSS'-like language. It also contains a number of lower level 'CLI' elements: rules, boxes, trees, and 'Unicode' symbols with 'ASCII' alternatives. It integrates with the 'crayon' package to support 'ANSI' terminal colors.
Author: Gábor Csárdi [aut, cre], Hadley Wickham [ctb], Kirill Müller [ctb]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between cli versions 2.1.0 dated 2020-10-12 and 2.2.0 dated 2020-11-20

 DESCRIPTION                      |    6 +--
 MD5                              |   63 +++++++++++++++++++++++----------------
 NAMESPACE                        |   36 +++++++++++++++++++---
 NEWS.md                          |   18 +++++++++++
 R/ansi-hyperlink.R               |only
 R/boxes.R                        |    7 +---
 R/cli.R                          |    8 +++-
 R/crayon-utils.R                 |only
 R/crayon.R                       |   12 ++++++-
 R/crayonex.R                     |only
 R/format.R                       |    4 +-
 R/print.R                        |    8 ++++
 R/rules.R                        |   21 ++++---------
 R/spinner.R                      |    2 -
 R/status-bar.R                   |    6 ++-
 R/themes.R                       |    8 ++--
 R/tree.R                         |    2 -
 R/tty.R                          |    1 
 R/utils.R                        |    9 +++--
 man/ansi-styles.Rd               |    2 -
 man/ansi_align.Rd                |only
 man/ansi_has_any.Rd              |only
 man/ansi_hide_cursor.Rd          |    7 ++++
 man/ansi_nchar.Rd                |only
 man/ansi_regex.Rd                |only
 man/ansi_strip.Rd                |only
 man/ansi_strsplit.Rd             |only
 man/ansi_substr.Rd               |only
 man/ansi_substring.Rd            |only
 man/cli_dl.Rd                    |    2 -
 man/cli_li.Rd                    |    2 -
 man/cli_ol.Rd                    |    2 -
 man/cli_ul.Rd                    |    2 -
 man/cli_vec.Rd                   |    4 +-
 man/style_hyperlink.Rd           |only
 tests/testthat/test-crayon.R     |    2 -
 tests/testthat/test-crayonex.R   |only
 tests/testthat/test-status-bar.R |   24 +++++++-------
 tests/testthat/test-subprocess.R |    4 +-
 39 files changed, 174 insertions(+), 88 deletions(-)

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New package svgtools with initial version 1.0.0
Package: svgtools
Type: Package
Title: Manipulate SVG (Template) Files of Charts
Version: 1.0.0
Date: 2020-10-30
Authors@R: c(person("Konrad","Oberwimmer",email="konrad.oberwimmer@iqs.gv.at",role=c("aut", "cre")), person("Christian","Wimmer",role="aut"), person("Michael","Bruneforth",role="ctb"))
Description: The purpose of this package is to manipulate SVG files that are templates of charts the user wants to produce. In vector graphics one copes with x-/y-coordinates of elements (e.g. lines, rectangles, text). Their scale is often dependent on the program that is used to produce the graphics. In applied statistics one usually has numeric values on a fixed scale (e.g. percentage values between 0 and 100) to show in a chart. Basically, 'svgtools' transforms the statistical values into coordinates and widths/heights of the vector graphics. This is done by stackedBar() for bar charts, by linesSymbols() for charts with lines and/or symbols (dot markers) and scatterSymbols() for scatterplots.
Encoding: UTF-8
License: GPL-3
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 4.0.0)
Imports: xml2 (>= 1.3.0), stringr (>= 1.4.0), rsvg (>= 2.1), magick (>= 2.4.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-11-17 10:35:33 UTC; k.oberwimmer
Author: Konrad Oberwimmer [aut, cre], Christian Wimmer [aut], Michael Bruneforth [ctb]
Maintainer: Konrad Oberwimmer <konrad.oberwimmer@iqs.gv.at>
Repository: CRAN
Date/Publication: 2020-11-20 09:00:02 UTC

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New package sdcLog with initial version 0.1.0
Package: sdcLog
Title: Tools for Statistical Disclosure Control in Research Data Centers
Version: 0.1.0
Authors@R: c(person(given = "Matthias", family = "Gomolka", role = c("aut", "cre"), email = "matthias.gomolka@posteo.de"), person(given = "Tim", family = "Becker", role = "aut"))
Description: Tools for researchers to explicitly show that their results comply to rules for statistical disclosure control imposed by research data centers. These tools help in checking descriptive statistics and models and in calculating extreme values that are not individual data. Also included is a simple function to create log files. The methods used here are described in the "Guidelines for the checking of output based on microdata research" by Bond, Brandt, and de Wolf (2015) <https://ec.europa.eu/eurostat/cros/system/files/dwb_standalone-document_output-checking-guidelines.pdf>.
License: GPL-3
URL: https://github.com/matthiasgomolka/sdcLog
BugReports: https://github.com/matthiasgomolka/sdcLog/issues
Depends: R (>= 3.5)
Imports: broom (>= 0.5.5), checkmate (>= 2.0.0), crayon (>= 1.3.4), data.table (>= 1.12.8), methods
Suggests: callr, covr (>= 3.5.0), devtools, here, knitr, rmarkdown, skimr, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-17 11:23:23 UTC; matthias
Author: Matthias Gomolka [aut, cre], Tim Becker [aut]
Maintainer: Matthias Gomolka <matthias.gomolka@posteo.de>
Repository: CRAN
Date/Publication: 2020-11-20 08:20:02 UTC

More information about sdcLog at CRAN
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New package ciu with initial version 0.1.0
Package: ciu
Type: Package
Title: Contextual Importance and Utility
Version: 0.1.0
Author: Kary Främling
Maintainer: Kary Främling <Kary.Framling@umu.se>
Description: Implementation of the Contextual Importance and Utility (CIU) concepts for Explainable AI (XAI). A recent description of CIU can be found in e.g. Främling (2020) <arXiv:2009.13996>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: graphics, stats, Rcpp, grDevices, ggplot2
Suggests: MASS, caret, gbm
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-16 15:55:35 UTC; framling
Repository: CRAN
Date/Publication: 2020-11-20 08:50:02 UTC

More information about ciu at CRAN
Permanent link

Package triangulr updated to version 1.1.0 with previous version 1.0.0 dated 2020-09-28

Title: High-Performance Triangular Distribution Functions
Description: A collection of high-performance functions for the triangular distribution that consists of the probability density function, cumulative distribution function, quantile function, random variate generator, moment generating function, characteristic function, and expected shortfall function. References: Samuel Kotz, Johan Ren Van Dorp (2004) <doi:10.1142/5720>, Melissa E. O'Neill (2014) <https://www.cs.hmc.edu/tr/hmc-cs-2014-0905.pdf>, David Blackman and Sebastiano Vigna (2018) <arXiv:1805.01407>, and Acerbi, Carlo and Tasche, Dirk. (2002) <doi:10.1111/1468-0300.00091>.
Author: Alvin Nursalim [aut, cre]
Maintainer: Alvin Nursalim <alvin.nursalim@outlook.com>

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Package reporter updated to version 1.0.6 with previous version 1.0.5 dated 2020-11-19

Title: Creates Statistical Reports
Description: Contains functions to create regulatory-style statistical reports. Originally designed to create tables, listings, and figures for the pharmaceutical, biotechnology, and medical device industries, these reports are generalized enough that they could be used in any industry. Generates text, rich-text, and PDF file formats. The package specializes in printing wide and long tables with automatic page wrapping and splitting. Reports can be produced with a minimum of function calls, and without relying on other table packages. The package supports titles, footnotes, page header, page footers, spanning headers, page by variables, and automatic page numbering.
Author: David Bosak
Maintainer: David Bosak <dbosak01@gmail.com>

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More information about reporter at CRAN
Permanent link

Package pointblank updated to version 0.6.0 with previous version 0.5.2 dated 2020-08-28

Title: Validation of Local and Remote Data Tables
Description: Validate data in data frames, 'tibble' objects, 'Spark' 'DataFrames', and database tables (e.g., 'PostgreSQL' and 'MySQL'). Validation pipelines can be made using easily-readable, consecutive validation steps. Upon execution of the validation plan, several reporting options are available. User-defined thresholds for failure rates allow for the determination of appropriate reporting actions. Many other workflows are available including an information management workflow, where the aim is to record, collect, and generate useful information on data tables.
Author: Richard Iannone [aut, cre] (<https://orcid.org/0000-0003-3925-190X>), Mauricio Vargas [aut] (<https://orcid.org/0000-0003-1017-7574>)
Maintainer: Richard Iannone <riannone@me.com>

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Package pillar updated to version 1.4.7 with previous version 1.4.6 dated 2020-07-10

Title: Coloured Formatting for Columns
Description: Provides 'pillar' and 'colonnade' generics designed for formatting columns of data using the full range of colours provided by modern terminals.
Author: Kirill Müller [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

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Package microdemic updated to version 0.6.0 with previous version 0.5.0 dated 2020-01-27

Title: 'Microsoft Academic' API Client
Description: The 'Microsoft Academic Knowledge' API provides programmatic access to scholarly articles in the 'Microsoft Academic Graph' (<https://academic.microsoft.com/>). Includes methods matching all 'Microsoft Academic' API routes, including search, graph search, text similarity, and interpret natural language query string.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Christopher Baker [aut], rOpenSci [fnd] (https://ropensci.org)
Maintainer: Scott Chamberlain <myrmecocystus+r@gmail.com>

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Package LSX updated to version 0.9.5 with previous version 0.9.4 dated 2020-11-02

Title: Model for Semisupervised Text Analysis Based on Word Embeddings
Description: A word embeddings-based semisupervised models for document scaling Watanabe (2020) <doi:10.1080/19312458.2020.1832976>. LSS allows users to analyze large and complex corpora on arbitrary dimensions with seed words exploiting efficiency of word embeddings (SVD, Glove).
Author: Kohei Watanabe [aut, cre, cph]
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

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Package mosaic.find updated to version 0.1.2 with previous version 0.1.1 dated 2020-06-10

Title: Finding Rhythmic and Non-Rhythmic Trends in Multi-Omics Data (MOSAIC)
Description: Provides a function (mosaic_find()) designed to find rhythmic and non-rhythmic trends in multi-omics time course data using model selection and joint modeling, a method called MOSAIC (Multi-Omics Selection with Amplitude Independent Criteria). For more information, see H. De los Santos et al. (2020) <doi:10.1093/bioinformatics/btaa877>.
Author: Hannah De los Santos [aut, cph], Kristin Bennett [aut], Jennifer Hurley [aut, cre], R Development Core Team [aut]
Maintainer: Jennifer Hurley <hurlej2@rpi.edu>

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Package influential updated to version 2.0.1 with previous version 2.0.0 dated 2020-09-25

Title: Identification and Classification of the Most Influential Nodes
Description: Contains functions for the classification and ranking of top candidate features, reconstruction of networks from adjacency matrices and data frames, analysis of the topology of the network and calculation of centrality measures, and identification of the most influential nodes. Also, a function is provided for running SIRIR model, which is the combination of leave-one-out cross validation technique and the conventional SIR model, on a network to unsupervisedly rank the true influence of vertices. Additionally, some functions have been provided for the assessment of dependence and correlation of two network centrality measures as well as the conditional probability of deviation from their corresponding means in opposite direction. Fred Viole and David Nawrocki (2013, ISBN:1490523995). Csardi G, Nepusz T (2006). "The igraph software package for complex network research." InterJournal, Complex Systems, 1695. Adopted algorithms and sources are referenced in function document.
Author: Adrian (Abbas) Salavaty [aut, cre], Mirana Ramialison [ths], Peter D. Currie [ths]
Maintainer: Adrian Salavaty <abbas.salavaty@gmail.com>

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