Mon, 20 Apr 2020

Package withr updated to version 2.2.0 with previous version 2.1.2 dated 2018-03-15

Title: Run Code 'With' Temporarily Modified Global State
Description: A set of functions to run code 'with' safely and temporarily modified global state. Many of these functions were originally a part of the 'devtools' package, this provides a simple package with limited dependencies to provide access to these functions.
Author: Jim Hester [aut, cre], Kirill Müller [aut], Kevin Ushey [aut], Hadley Wickham [aut], Winston Chang [aut], Richard Cotton [ctb], RStudio [cph]
Maintainer: Jim Hester <james.f.hester@gmail.com>

Diff between withr versions 2.1.2 dated 2018-03-15 and 2.2.0 dated 2020-04-20

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Package RiskPortfolios updated to version 2.1.4 with previous version 2.1.3 dated 2020-04-19

Title: Computation of Risk-Based Portfolios
Description: Collection of functions designed to compute risk-based portfolios as described in Ardia et al. (2017) <doi:10.1007/s10479-017-2474-7> and Ardia et al. (2017) <doi:10.21105/joss.00171>.
Author: David Ardia [aut, cre, cph] (<https://orcid.org/0000-0003-2823-782X>), Kris Boudt [aut], Jean-Philippe Gagnon-Fleury [aut]
Maintainer: David Ardia <david.ardia.ch@gmail.com>

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Package bayesGARCH updated to version 2.1.5 with previous version 2.1.4 dated 2020-04-19

Title: Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations
Description: Provides the bayesGARCH() function which performs the Bayesian estimation of the GARCH(1,1) model with Student's t innovations as described in Ardia (2008) <doi:10.1007/978-3-540-78657-3>.
Author: David Ardia [aut, cre, cph] (<https://orcid.org/0000-0003-2823-782X>)
Maintainer: David Ardia <david.ardia.ch@gmail.com>

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Package AdMit updated to version 2.1.5 with previous version 2.1.4 dated 2020-04-19

Title: Adaptive Mixture of Student-t Distributions
Description: Provides functions to perform the fitting of an adaptive mixture of Student-t distributions to a target density through its kernel function as described in Ardia et al. (2009) <doi:10.18637/jss.v029.i03>. The mixture approximation can then be used as the importance density in importance sampling or as the candidate density in the Metropolis-Hastings algorithm to obtain quantities of interest for the target density itself.
Author: David Ardia [aut, cre, cph] (<https://orcid.org/0000-0003-2823-782X>), Lennart Hoogerheide [ctb], Herman van Dijk [ctb]
Maintainer: David Ardia <david.ardia.ch@gmail.com>

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Package spant updated to version 1.4.0 with previous version 1.3.0 dated 2020-04-03

Title: MR Spectroscopy Analysis Tools
Description: Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data. <https://martin3141.github.io/spant/>.
Author: Martin Wilson [cre, aut], John Muschelli [ctb]
Maintainer: Martin Wilson <martin@pipegrep.co.uk>

Diff between spant versions 1.3.0 dated 2020-04-03 and 1.4.0 dated 2020-04-20

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Package RWsearch updated to version 4.8.0 with previous version 4.7.0 dated 2020-02-15

Title: Lazy Search in R Packages, Task Views, CRAN, the Web. All-in-One Download
Description: Search by keywords in R packages, task views, CRAN, the web and display the results in the console or in txt, html or pdf files. Download the whole documentation of packages (html index, pdf manual, vignettes, source code, etc) with a single instruction. Visualize the package dependencies and CRAN checks. Explore CRAN archive. Use the above functions for task view maintenance. Use quick links and 70 web search engines to explore the web. A lazy evaluation of non-standard content is available throughout the package and eases the use of many functions.
Author: Patrice Kiener [aut, cre] (<https://orcid.org/0000-0002-0505-9920>)
Maintainer: Patrice Kiener <fattailsr@inmodelia.com>

Diff between RWsearch versions 4.7.0 dated 2020-02-15 and 4.8.0 dated 2020-04-20

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Package MVNtestchar updated to version 1.0.2 with previous version 1.0.1 dated 2020-04-18

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

Diff between MVNtestchar versions 1.0.1 dated 2020-04-18 and 1.0.2 dated 2020-04-20

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Package sparklyr updated to version 1.2.0 with previous version 1.1.0 dated 2020-01-10

Title: R Interface to Apache Spark
Description: R interface to Apache Spark, a fast and general engine for big data processing, see <http://spark.apache.org>. This package supports connecting to local and remote Apache Spark clusters, provides a 'dplyr' compatible back-end, and provides an interface to Spark's built-in machine learning algorithms.
Author: Javier Luraschi [aut], Kevin Kuo [aut] (<https://orcid.org/0000-0001-7803-7901>), Kevin Ushey [aut], JJ Allaire [aut], Samuel Macedo [ctb], Hossein Falaki [aut], Lu Wang [aut], Andy Zhang [aut], Yitao Li [aut, cre], RStudio [cph], The Apache Software Foundation [aut, cph]
Maintainer: Yitao Li <yitao@rstudio.com>

Diff between sparklyr versions 1.1.0 dated 2020-01-10 and 1.2.0 dated 2020-04-20

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Package multgee updated to version 1.7.0 with previous version 1.6.0 dated 2017-07-11

Title: GEE Solver for Correlated Nominal or Ordinal Multinomial Responses
Description: GEE solver for correlated nominal or ordinal multinomial responses using a local odds ratios parameterization.
Author: Anestis Touloumis [aut, cre] (<https://orcid.org/0000-0002-5965-1639>)
Maintainer: Anestis Touloumis <A.Touloumis@brighton.ac.uk>

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Package mkin updated to version 0.9.49.11 with previous version 0.9.49.10 dated 2020-04-18

Title: Kinetic Evaluation of Chemical Degradation Data
Description: Calculation routines based on the FOCUS Kinetics Report (2006, 2014). Includes a function for conveniently defining differential equation models, model solution based on eigenvalues if possible or using numerical solvers. If a C compiler (on windows: 'Rtools') is installed, differential equation models are solved using automatically generated C functions. Please note that no warranty is implied for correctness of results or fitness for a particular purpose.
Author: Johannes Ranke [aut, cre, cph] (<https://orcid.org/0000-0003-4371-6538>), Katrin Lindenberger [ctb], René Lehmann [ctb], Eurofins Regulatory AG [cph]
Maintainer: Johannes Ranke <jranke@uni-bremen.de>

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Package ingredients updated to version 1.2.0 with previous version 1.1 dated 2020-03-11

Title: Effects and Importances of Model Ingredients
Description: Collection of tools for assessment of feature importance and feature effects. Key functions are: feature_importance() for assessment of global level feature importance, ceteris_paribus() for calculation of the what-if plots, partial_dependence() for partial dependence plots, conditional_dependence() for conditional dependence plots, accumulated_dependence() for accumulated local effects plots, aggregate_profiles() and cluster_profiles() for aggregation of ceteris paribus profiles, generic print() and plot() for better usability of selected explainers, generic plotD3() for interactive, D3 based explanations, and generic describe() for explanations in natural language. The package 'ingredients' is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.
Author: Przemyslaw Biecek [aut, cre] (<https://orcid.org/0000-0001-8423-1823>), Hubert Baniecki [aut] (<https://orcid.org/0000-0001-6661-5364>), Adam Izdebski [aut]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>

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Package iBreakDown updated to version 1.2.0 with previous version 1.1.1 dated 2020-04-15

Title: Model Agnostic Instance Level Variable Attributions
Description: Model agnostic tool for decomposition of predictions from black boxes. Supports additive attributions and attributions with interactions. The Break Down Table shows contributions of every variable to a final prediction. The Break Down Plot presents variable contributions in a concise graphical way. This package works for classification and regression models. It is an extension of the 'breakDown' package (Staniak and Biecek 2018) <doi:10.32614/RJ-2018-072>, with new and faster strategies for orderings. It supports interactions in explanations and has interactive visuals (implemented with 'D3.js' library). The methodology behind is described in the 'iBreakDown' article (Gosiewska and Biecek 2019) <arXiv:1903.11420> This package is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.
Author: Przemyslaw Biecek [aut, cre] (<https://orcid.org/0000-0001-8423-1823>), Alicja Gosiewska [aut] (<https://orcid.org/0000-0001-6563-5742>), Hubert Baniecki [aut] (<https://orcid.org/0000-0001-6661-5364>), Adam Izdebski [aut], Dariusz Komosinski [ctb]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>

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Package fishualize updated to version 0.2.0 with previous version 0.1.0 dated 2019-10-24

Title: Color Palettes Based on Fish Species
Description: Implementation of color palettes based on fish species.
Author: Nina M. D. Schiettekatte [cre, aut], Simon J. Brandl [aut], Jordan M. Casey [aut]
Maintainer: Nina M. D. Schiettekatte <nina.schiettekatte@gmail.com>

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Package dabestr updated to version 0.2.5 with previous version 0.2.4 dated 2020-03-21

Title: Data Analysis using Bootstrap-Coupled Estimation
Description: Data Analysis using Bootstrap-Coupled ESTimation. Estimation statistics is a simple framework that avoids the pitfalls of significance testing. It uses familiar statistical concepts: means, mean differences, and error bars. More importantly, it focuses on the effect size of one's experiment/intervention, as opposed to a false dichotomy engendered by P values. An estimation plot has two key features: 1. It presents all datapoints as a swarmplot, which orders each point to display the underlying distribution. 2. It presents the effect size as a bootstrap 95% confidence interval on a separate but aligned axes. Estimation plots are introduced in Ho et al., Nature Methods 2019, 1548-7105. <doi:10.1038/s41592-019-0470-3>. The free-to-view PDF is located at <https://rdcu.be/bHhJ4>.
Author: Joses W. Ho [cre, aut], Tayfun Tumkaya [aut]
Maintainer: Joses W. Ho <joseshowh@gmail.com>

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Package ChemoSpecUtils updated to version 0.4.51 with previous version 0.4.38 dated 2020-01-22

Title: Functions Supporting Packages ChemoSpec and ChemoSpec2D
Description: Functions supporting the common needs of packages 'ChemoSpec' and 'ChemoSpec2D'.
Author: Bryan A. Hanson [aut, cre] (<https://orcid.org/0000-0003-3536-8246>)
Maintainer: Bryan A. Hanson <hanson@depauw.edu>

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Package bayesmeta updated to version 2.5 with previous version 2.4 dated 2019-08-06

Title: Bayesian Random-Effects Meta-Analysis
Description: A collection of functions allowing to derive the posterior distribution of the two parameters in a random-effects meta-analysis, and providing functionality to evaluate joint and marginal posterior probability distributions, predictive distributions, shrinkage effects, posterior predictive p-values, etc.
Author: Christian Roever [aut, cre] (<https://orcid.org/0000-0002-6911-698X>), Tim Friede [ctb] (<https://orcid.org/0000-0001-5347-7441>)
Maintainer: Christian Roever <christian.roever@med.uni-goettingen.de>

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Package bnma updated to version 1.1.0 with previous version 1.0.0 dated 2019-12-10

Title: Bayesian Network Meta-Analysis using 'JAGS'
Description: Network meta-analyses using Bayesian framework following Dias et al. (2013) <DOI:10.1177/0272989X12458724>. Based on the data input, creates prior, model file, and initial values needed to run models in 'rjags'. Able to handle binomial, normal and multinomial arm-based data. Can handle multi-arm trials and includes methods to incorporate covariate and baseline risk effects. Includes standard diagnostics and visualization tools to evaluate the results.
Author: Michael Seo [aut, cre], Christopher Schmid [aut]
Maintainer: Michael Seo <swj8874@gmail.com>

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Package fda updated to version 5.1.4 with previous version 2.4.8.1 dated 2020-02-19

Title: Functional Data Analysis
Description: These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer and in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009). Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of the 76 figures in this latter book. Matlab versions are available by ftp from <http://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/>.
Author: J. O. Ramsay <ramsay@psych.mcgill.ca> [aut,cre], Spencer Graves <spencer.graves@effectivedefense.org> [ctb], Giles Hooker <gjh27@cornell.edu> [ctb]
Maintainer: J. O. Ramsay <ramsay@psych.mcgill.ca>

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More information about fda at CRAN
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Package broom updated to version 0.5.6 with previous version 0.5.5 dated 2020-02-29

Title: Convert Statistical Analysis Objects into Tidy Tibbles
Description: Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.
Author: David Robinson [aut], Alex Hayes [aut, cre] (<https://orcid.org/0000-0002-4985-5160>), Matthieu Gomez [ctb], Boris Demeshev [ctb], Dieter Menne [ctb], Benjamin Nutter [ctb], Luke Johnston [ctb], Ben Bolker [ctb], Francois Briatte [ctb], Jeffrey Arnold [ctb], Jonah Gabry [ctb], Luciano Selzer [ctb], Gavin Simpson [ctb], Jens Preussner [ctb], Jay Hesselberth [ctb], Hadley Wickham [ctb], Matthew Lincoln [ctb], Alessandro Gasparini [ctb], Lukasz Komsta [ctb], Frederick Novometsky [ctb], Wilson Freitas [ctb], Michelle Evans [ctb], Jason Cory Brunson [ctb], Simon Jackson [ctb], Ben Whalley [ctb], Michael Kuehn [ctb], Jorge Cimentada [ctb], Erle Holgersen [ctb], Karl Dunkle Werner [ctb]
Maintainer: Alex Hayes <alexpghayes@gmail.com>

Diff between broom versions 0.5.5 dated 2020-02-29 and 0.5.6 dated 2020-04-20

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More information about broom at CRAN
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Package reports (with last version 0.1.4) was removed from CRAN

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

2014-12-21 0.1.4
2013-03-12 0.1.2
2013-03-11 0.1.1

Permanent link
Package HCmodelSets updated to version 1.1.1 with previous version 1.1 dated 2019-12-16

Title: Regression with a Large Number of Potential Explanatory Variables
Description: Software for performing the reduction, exploratory and model selection phases of the procedure proposed by Cox, D.R. and Battey, H.S. (2017) <doi:10.1073/pnas.1703764114> for sparse regression when the number of potential explanatory variables far exceeds the sample size. The software supports linear regression, likelihood-based fitting of generalized linear regression models and the proportional hazards model fitted by partial likelihood.
Author: H. H. Hoeltgebaum
Maintainer: H. H. Hoeltgebaum <hh3015@ic.ac.uk>

Diff between HCmodelSets versions 1.1 dated 2019-12-16 and 1.1.1 dated 2020-04-20

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Package funrar updated to version 1.4.1 with previous version 1.4.0 dated 2020-03-05

Title: Functional Rarity Indices Computation
Description: Computes functional rarity indices as proposed by Violle et al. (2017) <doi:10.1016/j.tree.2017.02.002>. Various indices can be computed using both regional and local information. Functional Rarity combines both the functional aspect of rarity as well as the extent aspect of rarity. 'funrar' is presented in Grenié et al. (2017) <doi:10.1111/ddi.12629>.
Author: Matthias Grenié [aut, cre] (<https://orcid.org/0000-0002-4659-7522>), Pierre Denelle [aut] (<https://orcid.org/0000-0001-5037-2281>), Caroline Tucker [aut] (<https://orcid.org/0000-0002-4871-2010>), François Munoz [ths] (<https://orcid.org/0000-0001-8776-4705>), Cyrille Violle [ths] (<https://orcid.org/0000-0002-2471-9226>)
Maintainer: Matthias Grenié <matthias.grenie@gmail.com>

Diff between funrar versions 1.4.0 dated 2020-03-05 and 1.4.1 dated 2020-04-20

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Package DHARMa updated to version 0.3.0 with previous version 0.2.7 dated 2020-02-06

Title: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models
Description: The 'DHARMa' package uses a simulation-based approach to create readily interpretable scaled (quantile) residuals for fitted (generalized) linear mixed models. Currently supported are linear and generalized linear (mixed) models from 'lme4' (classes 'lmerMod', 'glmerMod'), 'glmmTMB' and 'spaMM', generalized additive models ('gam' from 'mgcv'), 'glm' (including 'negbin' from 'MASS', but excluding quasi-distributions) and 'lm' model classes. Moreover, externally created simulations, e.g. posterior predictive simulations from Bayesian software such as 'JAGS', 'STAN', or 'BUGS' can be processed as well. The resulting residuals are standardized to values between 0 and 1 and can be interpreted as intuitively as residuals from a linear regression. The package also provides a number of plot and test functions for typical model misspecification problems, such as over/underdispersion, zero-inflation, and residual spatial and temporal autocorrelation.
Author: Florian Hartig [aut, cre] (<https://orcid.org/0000-0002-6255-9059>)
Maintainer: Florian Hartig <florian.hartig@biologie.uni-regensburg.de>

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Package blackbox updated to version 1.1.32 with previous version 1.1.27 dated 2019-08-20

Title: Black Box Optimization and Exploration of Parameter Space
Description: Performs prediction of a response function from simulated response values, allowing black-box optimization of functions estimated with some error. Includes a simple user interface for such applications, as well as more specialized functions designed to be called by the Migraine software (Rousset and Leblois, 2012 <doi:10.1093/molbev/MSR262>; Leblois et al., 2014 <doi:10.1093/molbev/msu212>; and see URL). The latter functions are used for prediction of likelihood surfaces and implied likelihood ratio confidence intervals, and for exploration of predictor space of the surface. Prediction of the response is based on ordinary Kriging (with residual error) of the input. Estimation of smoothing parameters is performed by generalized cross-validation.
Author: François Rousset [aut, cre, cph] (<https://orcid.org/0000-0003-4670-0371>), Raphaël Leblois [ctb] (<https://orcid.org/0000-0002-3051-4497>)
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

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Package mRpostman updated to version 0.3.1 with previous version 0.3.0 dated 2019-10-17

Title: IMAP Toolkit
Description: IMAP4rev1 (Internet Message Access Protocol, Version 4rev1) functionalities based on the RFC 3501 manual (Crispin, 2003, <doi:10.17487/RFC3501>), its updates, and other related documents. 'mRpostman' makes extensive use of 'curl' and 'libcurl' capabilities, providing functions for mailboxes and electronic messages manipulation.
Author: Allan Quadros [aut, cre]
Maintainer: Allan Quadros <allanvcq@gmail.com>

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Package pensim updated to version 1.3.2 with previous version 1.3.1 dated 2020-03-28

Title: Simulation of High-Dimensional Data and Parallelized Repeated Penalized Regression
Description: Simulation of continuous, correlated high-dimensional data with time to event or binary response, and parallelized functions for Lasso, Ridge, and Elastic Net penalized regression with repeated starts and two-dimensional tuning of the Elastic Net.
Author: Levi Waldron <lwaldron.research@gmail.com>
Maintainer: Levi Waldron <lwaldron.research@gmail.com>

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Package mgm updated to version 1.2-9 with previous version 1.2-7 dated 2019-09-05

Title: Estimating Time-Varying k-Order Mixed Graphical Models
Description: Estimation of k-Order time-varying Mixed Graphical Models and mixed VAR(p) models via elastic-net regularized neighborhood regression. For details see Haslbeck & Waldorp (2020) <doi:10.18637/jss.v093.i08>.
Author: Jonas Haslbeck
Maintainer: Jonas Haslbeck <jonashaslbeck@gmail.com>

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Package climate updated to version 0.9.4 with previous version 0.9.3 dated 2020-03-30

Title: Interface to Download Meteorological (and Hydrological) Datasets
Description: Automatize downloading of meteorological and hydrological data from publicly available repositories: OGIMET (<http://ogimet.com/index.phtml.en>), University of Wyoming - atmospheric vertical profiling data (<http://weather.uwyo.edu/upperair>), Polish Institute of Meterology and Water Management - National Research Institute (<https://dane.imgw.pl>), and National Oceanic & Atmospheric Administration (NOAA). This package also allows for adding geographical coordinates for each observation.
Author: Bartosz Czernecki [aut, cre] (<https://orcid.org/0000-0001-6496-1386>), Arkadiusz Głogowski [aut] (<https://orcid.org/0000-0002-7587-8892>), Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), IMGW-PIB [ctb] (source of the data)
Maintainer: Bartosz Czernecki <nwp@amu.edu.pl>

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Package arulesCBA updated to version 1.2.0 with previous version 1.1.6 dated 2020-01-08

Title: Classification Based on Association Rules
Description: Provides the infrastructure for association rule-based classification including algorithms like Classification Based on Associations (CBA).
Author: Michael Hahsler [aut, cre, cph], Ian Johnson [aut, cph], Tyler Giallanza [ctb]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

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Package cartography updated to version 2.4.1 with previous version 2.4.0 dated 2020-04-02

Title: Thematic Cartography
Description: Create and integrate maps in your R workflow. This package helps to design cartographic representations such as proportional symbols, choropleth, typology, flows or discontinuities maps. It also offers several features that improve the graphic presentation of maps, for instance, map palettes, layout elements (scale, north arrow, title...), labels or legends. See Giraud and Lambert (2017) <doi:10.1007/978-3-319-57336-6_13>.
Author: Timothée Giraud [cre, aut] (<https://orcid.org/0000-0002-1932-3323>), Nicolas Lambert [aut], Diego Hernangómez [ctb] (<https://orcid.org/0000-0001-8457-4658>), Ian Fellows [cph] (no overlap algorithm for labels, from wordcloud package)
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>

Diff between cartography versions 2.4.0 dated 2020-04-02 and 2.4.1 dated 2020-04-20

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Package sbtools updated to version 1.1.11 with previous version 1.1.10 dated 2020-03-20

Title: USGS ScienceBase Tools
Description: Tools for interacting with U.S. Geological Survey ScienceBase <https://www.sciencebase.gov> interfaces. ScienceBase is a data cataloging and collaborative data management platform. Functions included for querying ScienceBase, and creating and fetching datasets.
Author: David Blodgett [cre], Tim Kern [aut], Luke Winslow [aut], Scott Chamberlain [aut], Alison Appling [aut], Jordan Read [aut]
Maintainer: David Blodgett <dblodgett@usgs.gov>

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Package ie2misc (with last version 0.8.5) was removed from CRAN

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

2016-08-08 0.8.5
2016-07-21 0.8.0

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New package stylo with initial version 0.7.2
Package: stylo
Type: Package
Title: Stylometric Multivariate Analyses
Version: 0.7.2
Date: 2020-04-20
Author: Maciej Eder, Jan Rybicki, Mike Kestemont, Steffen Pielstroem
Maintainer: Maciej Eder <maciejeder@gmail.com>
URL: https://github.com/computationalstylistics/stylo
Depends: R (>= 2.14)
Imports: tcltk, tcltk2, ape, pamr, e1071, class, lattice, tsne
Suggests: stringi, networkD3, readr
Description: Supervised and unsupervised multivariate methods, supplemented by GUI and some visualizations, to perform various analyses in the field of computational stylistics, authorship attribution, etc. For further reference, see Eder et al. (2016), <https://journal.r-project.org/archive/2016/RJ-2016-007/index.html>. You are also encouraged to visit the Computational Stylistics Group's website <https://computationalstylistics.github.io/>, where a reasonable amount of information about the package and related projects are provided.
License: GPL (>= 3)
NeedsCompilation: no
Packaged: 2020-04-20 08:49:59 UTC; m
Repository: CRAN
Date/Publication: 2020-04-20 10:50:03 UTC

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New package OTE with initial version 1.0.1
Package: OTE
Type: Package
Title: Optimal Trees Ensembles for Regression, Classification and Class Membership Probability Estimation
Version: 1.0.1
Date: 2020-04-18
Author: Zardad Khan, Asma Gul, Aris Perperoglou, Osama Mahmoud, Werner Adler, Miftahuddin and Berthold Lausen
Maintainer: Zardad Khan <zardadkhan@awkum.edu.pk>
Description: Functions for creating ensembles of optimal trees for regression, classification (Khan, Z., Gul, A., Perperoglou, A., Miftahuddin, M., Mahmoud, O., Adler, W., & Lausen, B. (2019). (2019) <doi:10.1007/s11634-019-00364-9>) and class membership probability estimation (Khan, Z, Gul, A, Mahmoud, O, Miftahuddin, M, Perperoglou, A, Adler, W & Lausen, B (2016) <doi:10.1007/978-3-319-25226-1_34>) are given. A few trees are selected from an initial set of trees grown by random forest for the ensemble on the basis of their individual and collective performance. Three different methods of tree selection for the case of classification are given. The prediction functions return estimates of the test responses and their class membership probabilities. Unexplained variations, error rates, confusion matrix, Brier scores, etc. are also returned for the test data.
License: GPL (>= 3)
Encoding: UTF-8
Imports: randomForest,stats
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-20 09:32:39 UTC; ZKHAN
Repository: CRAN
Date/Publication: 2020-04-20 10:50:07 UTC

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Package etm updated to version 1.1 with previous version 1.0.5.1 dated 2020-01-29

Title: Empirical Transition Matrix
Description: The etm (empirical transition matrix) package permits to estimate the matrix of transition probabilities for any time-inhomogeneous multistate model with finite state space using the Aalen-Johansen estimator. Functions for data preparation and for displaying are also included (Allignol et al., 2011 <doi:10.18637/jss.v038.i04>). Functionals of the Aalen-Johansen estimator, e.g., excess length-of-stay in an intermediate state, can also be computed (Allignol et al. 2011 <doi:10.1007/s00180-010-0200-x>).
Author: Arthur Allignol
Maintainer: Arthur Allignol <arthur.allignol@gmail.com>

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Package creditmodel updated to version 1.1.9 with previous version 1.1.8 dated 2020-03-18

Title: Toolkit for Credit Modeling, Analysis and Visualization
Description: Provides a highly efficient R tool suite for Credit Modeling, Analysis and Visualization. Contains infrastructure functionalities such as data exploration and preparation, missing values treatment, outliers treatment, variable derivation, variable selection, dimensionality reduction, grid search for hyper parameters, data mining and visualization, model evaluation, strategy analysis etc. This package is designed to make the development of binary classification models (machine learning based models as well as credit scorecard) simpler and faster.
Author: Dongping Fan [aut, cre]
Maintainer: Dongping Fan <fdp@pku.edu.cn>

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Package COVID19 updated to version 1.0.0 with previous version 0.3.0 dated 2020-04-11

Title: Coronavirus COVID-19 (2019-nCoV) Epidemic Datasets
Description: Unified tidy format datasets of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic across several sources. The data are downloaded in real-time, cleaned and matched with exogenous variables. Vintage databases are also supported.
Author: Emanuele Guidotti [aut, cre] (<https://orcid.org/0000-0002-8961-6623>), David Ardia [ctb] (<https://orcid.org/0000-0003-2823-782X>)
Maintainer: Emanuele Guidotti <emanuele.guidotti@unine.ch>

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Package datasailr (with last version 0.8.3) was removed from CRAN

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

2020-04-18 0.8.3

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Package switchr updated to version 0.14.3 with previous version 0.14.2 dated 2020-01-25

Title: Installing, Managing, and Switching Between Distinct Sets of Installed Packages
Description: Provides an abstraction for managing, installing, and switching between sets of installed R packages. This allows users to maintain multiple package libraries simultaneously, e.g. to maintain strict, package-version-specific reproducibility of many analyses, or work within a development/production release paradigm. Introduces a generalized package installation process which supports multiple repository and non-repository sources and tracks package provenance.
Author: Gabriel Becker[aut, cre]
Maintainer: Gabriel Becker <gabembecker@gmail.com>

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Package insight updated to version 0.8.3 with previous version 0.8.2 dated 2020-03-06

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>), Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package BARIS updated to version 1.1.0 with previous version 1.0.0 dated 2020-02-24

Title: Access and Import Data from the French Open Data Portal
Description: Allows the user to access and import data from the rich French open data portal through the provided free API <https://doc.data.gouv.fr/api/reference/>. The portal is free, and no credential is required for extracting datasets.
Author: Mohamed El Fodil Ihaddaden
Maintainer: Mohamed El Fodil Ihaddaden <ihaddaden.fodeil@gmail.com>

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Package svUnit updated to version 1.0.3 with previous version 0.7-12 dated 2014-03-02

Title: 'SciViews' - Unit, Integration and System Testing
Description: A complete unit test system and functions to implement its GUI part.
Author: Philippe Grosjean [aut, cre] (<https://orcid.org/0000-0002-2694-9471>)
Maintainer: Philippe Grosjean <phgrosjean@sciviews.org>

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New package offlineChange with initial version 0.0.4
Package: offlineChange
Title: Detect Multiple Change Points from Time Series
Version: 0.0.4
Authors@R: c( person("Jiahuan", "Ye", email = "jiahuanye431@gmail.com", role = c("aut","trl","cre")), person("Jie", "Ding", email = "dingj@umn.edu", role = c("aut")))
Description: Detect the number and locations of change points. The locations can be either exact or in terms of ranges, depending on the available computational resource. The method is based on Jie Ding, Yu Xiang, Lu Shen, Vahid Tarokh (2017) <doi:10.1109/TSP.2017.2711558>.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: graphics, utils, stats, methods, Rcpp (>= 1.0.1)
LinkingTo: Rcpp
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL:
NeedsCompilation: yes
Packaged: 2020-04-19 10:07:55 UTC; Jiahuan
Author: Jiahuan Ye [aut, trl, cre], Jie Ding [aut]
Maintainer: Jiahuan Ye <jiahuanye431@gmail.com>
Repository: CRAN
Date/Publication: 2020-04-20 08:00:02 UTC

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Package jpndistrict updated to version 0.3.6 with previous version 0.3.5 dated 2020-04-02

Title: Create Japanese Administration Area and Office Maps
Description: Utilizing the data that Japanese administration area provided by the National Land Numerical Information download service (<http://nlftp.mlit.go.jp/ksj/index.html>). This package provide map data is based on the Digital Map 25000 (Map Image) published by Geospatial Information Authority of Japan (Approval No.603FY2017 information usage <http://www.gsi.go.jp>).
Author: Shinya Uryu [aut, cre] (<https://orcid.org/0000-0002-0493-6186>), Geospatial Information Authority of Japan [dtc] (This package data sets, National Land numerical information by the Geographical Survey Institute with the approval of Geographical Survey Institute Head (Approval No.603FY2017 information usage))
Maintainer: Shinya Uryu <suika1127@gmail.com>

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Package interep updated to version 0.3.1 with previous version 0.3.0 dated 2019-10-14

Title: Interaction Analysis of Repeated Measure Data
Description: Extensive penalized variable selection methods have been developed in the past two decades for analyzing high dimensional omics data, such as gene expressions, single nucleotide polymorphisms (SNPs), copy number variations (CNVs) and others. However, lipidomics data have been rarely investigated by using high dimensional variable selection methods. This package incorporates our recently developed penalization procedures to conduct interaction analysis for high dimensional lipidomics data with repeated measurements. The core module of this package is developed in C++. The development of this software package and the associated statistical methods have been partially supported by an Innovative Research Award from Johnson Cancer Research Center, Kansas State University.
Author: Fei Zhou, Jie Ren, Xiaoxi Li, Cen Wu, Yu Jiang
Maintainer: Fei Zhou <feiz@ksu.edu>

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Package tibble updated to version 3.0.1 with previous version 3.0.0 dated 2020-03-30

Title: Simple Data Frames
Description: Provides a 'tbl_df' class (the 'tibble') that provides stricter checking and better formatting than the traditional data frame.
Author: Kirill Müller [aut, cre], Hadley Wickham [aut], Romain Francois [ctb], Jennifer Bryan [ctb], RStudio [cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

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Package spaMM updated to version 3.2.0 with previous version 3.1.27 dated 2020-03-10

Title: Mixed-Effect Models, Particularly Spatial Models
Description: Inference based on mixed-effect models, including generalized linear mixed models with spatial correlations and models with non-Gaussian random effects (e.g., Beta). Both classical geostatistical models, and Markov random field models on irregular grids, can be fitted. Variation in residual variance (heteroscedasticity) can itself be represented by a generalized linear mixed model. Various approximations of likelihood or restricted likelihood are implemented, in particular h-likelihood (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) and Laplace approximation.
Author: François Rousset [aut, cre, cph] (<https://orcid.org/0000-0003-4670-0371>), Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut] (<https://orcid.org/0000-0003-0637-2959>), GSL authors [ctb] (src/gsl_bessel.*)
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

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Package qdap updated to version 2.4.1 with previous version 2.3.6 dated 2020-01-09

Title: Bridging the Gap Between Qualitative Data and Quantitative Analysis
Description: Automates many of the tasks associated with quantitative discourse analysis of transcripts containing discourse including frequency counts of sentence types, words, sentences, turns of talk, syllables and other assorted analysis tasks. The package provides parsing tools for preparing transcript data. Many functions enable the user to aggregate data by any number of grouping variables, providing analysis and seamless integration with other R packages that undertake higher level analysis and visualization of text. This affords the user a more efficient and targeted analysis. 'qdap' is designed for transcript analysis, however, many functions are applicable to other areas of Text Mining/ Natural Language Processing.
Author: Tyler Rinker [aut, cre], Bryan Goodrich [ctb], Dason Kurkiewicz [ctb]
Maintainer: Tyler Rinker <tyler.rinker@gmail.com>

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Package nnTensor updated to version 1.0.4 with previous version 1.0.2 dated 2019-10-25

Title: Non-Negative Tensor Decomposition
Description: Some functions for performing non-negative matrix factorization, non-negative CANDECOMP/PARAFAC (CP) decomposition, non-negative Tucker decomposition, and generating toy model data. See Andrzej Cichock et al (2009) <doi:10.1002/9780470747278> and the reference section of GitHub README.md <https://github.com/rikenbit/nnTensor>, for details of the methods.
Author: Koki Tsuyuzaki, Manabu Ishii, Itoshi Nikaido
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>

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Package networktools updated to version 1.2.3 with previous version 1.2.2 dated 2020-02-13

Title: Tools for Identifying Important Nodes in Networks
Description: Includes assorted tools for network analysis. Bridge centrality; goldbricker; MDS, PCA, & eigenmodel network plotting.
Author: Payton Jones [aut, cre]
Maintainer: Payton Jones <payton_jones@g.harvard.edu>

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Package IndependenceTests updated to version 0.3 with previous version 0.2 dated 2012-12-11

Title: Non-Parametric Tests of Independence Between Random Vectors
Description: Functions for non-parametric tests of independence (mutual or serial) between some quantitative random vectors.
Author: Pierre Lafaye De Micheaux [aut, cre], Martin Bilodeau [aut], Yanan Fan [aut], Spiridon Penev [aut], Donna Salopek [aut]
Maintainer: Pierre Lafaye De Micheaux <lafaye@unsw.edu.au>

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Package ggeffects updated to version 0.14.3 with previous version 0.14.2 dated 2020-03-14

Title: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs
Description: Compute marginal effects from statistical models and returns the result as tidy data frames. These data frames are ready to use with the 'ggplot2'-package. Marginal effects can be calculated for many different models. Interaction terms, splines and polynomial terms are also supported. The main functions are ggpredict(), ggemmeans() and ggeffect(). There is a generic plot()-method to plot the results using 'ggplot2'.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package bayestestR updated to version 0.6.0 with previous version 0.5.3 dated 2020-03-26

Title: Understand and Describe Bayesian Models and Posterior Distributions
Description: Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors).
Author: Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Michael D. Wilson [aut] (<https://orcid.org/0000-0003-4143-7308>), Paul-Christian Bürkner [rev], Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>), Quentin F. Gronau [ctb] (<https://orcid.org/0000-0001-5510-6943>)
Maintainer: Dominique Makowski <dom.makowski@gmail.com>

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Package lbfgsb3 (with last version 2015-2.13.1) was removed from CRAN

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

2019-11-21 2015-2.13.1
2015-02-18 2015-2.13

Permanent link
Package MSGARCH updated to version 2.42 with previous version 2.31 dated 2019-10-24

Title: Markov-Switching GARCH Models
Description: Fit (by Maximum Likelihood or MCMC/Bayesian), simulate, and forecast various Markov-Switching GARCH models as described in Ardia et al. (2019) <doi:10.18637/jss.v091.i04>.
Author: David Ardia [aut] (<https://orcid.org/0000-0003-2823-782X>), Keven Bluteau [aut, cre] (<https://orcid.org/0000-0003-2990-4807>), Kris Boudt [ctb] (<https://orcid.org/0000-0002-1000-5142>), Leopoldo Catania [aut] (<https://orcid.org/0000-0002-0981-1921>), Alexios Ghalanos [ctb], Brian Peterson [ctb], Denis-Alexandre Trottier [aut]
Maintainer: Keven Bluteau <Keven.Bluteau@hec.ca>

Diff between MSGARCH versions 2.31 dated 2019-10-24 and 2.42 dated 2020-04-20

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Package extdplyr updated to version 0.1.5 with previous version 0.1.4 dated 2017-02-27

Title: Data Manipulation Extensions of 'Dplyr' and 'Tidyr'
Description: If 'dplyr' is a grammar for data manipulation, 'extdplyr' is like a short paragraph written in 'dplyr'. 'extdplyr' extends 'dplyr' and 'tidyr' verbs to some common "routines" that manipulate data sets. It uses the same interface and preserves all the features from 'dplyr', has good performance, and supports various data sources.
Author: Yuchen Wang [aut, cre]
Maintainer: Yuchen Wang <ycwang0712@gmail.com>

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Package concurve updated to version 2.5.0 with previous version 2.3.0 dated 2019-12-04

Title: Computes and Plots Compatibility (Confidence) Intervals, P-Values, S-Values, & Likelihood Intervals to Form Consonance, Surprisal, & Likelihood Functions
Description: Allows one to compute compatibility (confidence) intervals for various statistical tests along with their corresponding P-values, S-values, and likelihoods. The intervals can be plotted to create consonance, surprisal, and likelihood functions allowing one to see what effect sizes are compatible with the test model at various compatibility levels rather than being limited to one interval estimate such as 95\%. Functions can also be compared to one another to see how much they overlap with one another and differ. Results can also be exported for Word, Powerpoint, and TeX documents. The package currently supports bootstrapping, linear models, generalized linear models, linear mixed-effects models, survival analysis, and meta-analysis. These methods are discussed by Poole C. (1987) <doi:10.2105/AJPH.77.2.195>, Schweder T, Hjort NL. (2002) <doi:10.1111/1467-9469.00285>, Singh K, Xie M, Strawderman WE. (2007) <arXiv:0708.0976>, Rothman KJ, Greenland S, Lash TL. (2008, ISBN:9781451190052), Greenland S. (2019) <doi:10.1080/00031305.2018.1529625>, Chow ZR, Greenland S. (2019) <arXiv:1909.08579>, and Greenland S, Chow ZR. (2019) <arXiv:1909.08583>.
Author: Zad Rafi [aut, cre] (<https://orcid.org/0000-0003-1545-8199>), Andrew D. Vigotsky [aut] (<https://orcid.org/0000-0003-3166-0688>)
Maintainer: Zad Rafi <zad@lesslikely.com>

Diff between concurve versions 2.3.0 dated 2019-12-04 and 2.5.0 dated 2020-04-20

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More information about concurve at CRAN
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