Wed, 21 Apr 2021

Package cholera updated to version 0.7.5 with previous version 0.7.0 dated 2019-08-28

Title: Amend, Augment and Aid Analysis of John Snow's Cholera Map
Description: Amends errors, augments data and aids analysis of John Snow's map of the 1854 London cholera outbreak.
Author: Peter Li [aut, cre]
Maintainer: Peter Li <lindbrook@gmail.com>

Diff between cholera versions 0.7.0 dated 2019-08-28 and 0.7.5 dated 2021-04-21

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Package SIPDIBGE updated to version 0.1.2 with previous version 0.1.1 dated 2021-01-29

Title: Collection of Household Survey Packages Conducted by IBGE
Description: Provides access to packages developed for downloading, reading and analysing microdata from household surveys conducted by Brazilian Institute of Geography and Statistics - IBGE. More information can be obtained from the official website <https://www.ibge.gov.br/>.
Author: Gabriel Assuncao [aut, cre], Luna Hidalgo [aut], Douglas Braga [ctb]
Maintainer: Gabriel Assuncao <pacotesipd@ibge.gov.br>

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Package NetSimR updated to version 0.1.1 with previous version 0.1.0 dated 2019-08-20

Title: Actuarial Functions for Non-Life Insurance Modelling
Description: Assists actuaries and other insurance modellers in pricing, reserving and capital modelling for non-life insurance and reinsurance modelling. Provides functions that help model excess levels, capping and pure Incurred but not reported claims (pure IBNR). Includes capped mean, exposure curves and increased limit factor curves (ILFs) for LogNormal, Gamma, Pareto, Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes mean, probability density function (pdf), cumulative probability function (cdf) and inverse cumulative probability function for Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes calculating pure IBNR exposure with LogNormal and Gamma distribution for reporting delay.
Author: Yiannis Parizas [aut, cre]
Maintainer: Yiannis Parizas <yiannis.parizas@gmail.com>

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Package trelloR updated to version 0.7.1 with previous version 0.7.0 dated 2021-01-28

Title: Access the Trello API
Description: An R client for the Trello API. Supports free-tier features such as access to private boards, creating and updating cards and other resources, and downloading data in a structured way.
Author: Jakub Chromec [aut, cre]
Maintainer: Jakub Chromec <chromec.jakub@gmail.com>

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Package nlraa updated to version 0.89 with previous version 0.83 dated 2021-01-05

Title: Nonlinear Regression for Agricultural Applications
Description: Additional nonlinear regression functions using self-start (SS) algorithms. One of the functions is the Beta growth function proposed by Yin et al. (2003) <doi:10.1093/aob/mcg029>. There are several other functions with breakpoints (e.g. linear-plateau, plateau-linear, exponential-plateau, plateau-exponential, quadratic-plateau, plateau-quadratic and bilinear), a non-rectangular hyperbola and a bell-shaped curve. Twenty one (21) new self-start (SS) functions in total. This package also supports the publication 'Nonlinear regression Models and applications in agricultural research' by Archontoulis and Miguez (2015) <doi:10.2134/agronj2012.0506>, a book chapter with similar material <doi:10.2134/appliedstatistics.2016.0003.c15> and a publication by Oddi et. al. (2019) in Ecology and Evolution <doi:10.1002/ece3.5543>. The function 'nlsLMList' uses 'nlsLM' for fitting, but it is otherwise almost identical to 'nlme::nlsList'.In addition, this release of the package provides functions for conducting simulations for 'nlme' and 'gnls' objects as well as bootstrapping. These functions are intended to work with the modeling framework of the 'nlme' package. It also provides four vignettes with extended examples.
Author: Fernando Miguez [aut, cre] (<https://orcid.org/0000-0002-4627-8329>), José Pinheiro [ctb, cph] (author of nlme::nlsList, nlme::predict.gnls, nlme::predict.nlme), Douglas Bates [ctb, cph] (author of nlme::nlsList, nlme::predict.gnls, nlme::predict.nlme), R-core [ctb, cph]
Maintainer: Fernando Miguez <femiguez@iastate.edu>

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Package midasml updated to version 0.1.2 with previous version 0.1.0 dated 2021-04-14

Title: Estimation and Prediction Methods for High-Dimensional Mixed Frequency Time Series Data
Description: The 'midasml' package implements estimation and prediction methods for high-dimensional mixed-frequency (MIDAS) time-series and panel data regression models. The regularized MIDAS models are estimated using orthogonal (e.g. Legendre) polynomials and sparse-group LASSO (sg-LASSO) estimator. For more information on the `midasml' approach see Babii, Ghysels, and Striaukas (2021, JBES forthcoming) <doi:10.1080/07350015.2021.1899933>. The package is equipped with the fast implementation of the sg-LASSO estimator by means of proximal block coordinate descent. High-dimensional mixed frequency time-series data can also be easily manipulated with functions provided in the package.
Author: Jonas Striaukas [cre, aut], Andrii Babii [aut], Eric Ghysels [aut], Alex Kostrov [ctb] (Contributions to analytical gradients for non-linear low-dimensional MIDAS estimation code)
Maintainer: Jonas Striaukas <jonas.striaukas@gmail.com>

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Package synoptReg updated to version 1.2.1 with previous version 1.2.0 dated 2021-04-20

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>, Jenkinson and Collison 1977.
Author: Marc Lemus-Canovas [aut, cre] (<https://orcid.org/0000-0002-0925-3827>), Dominic Roye [ctb] (<https://orcid.org/0000-0002-5516-6396>)
Maintainer: Marc Lemus-Canovas <mlemus@ub.edu>

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Package superb updated to version 0.9.5.0 with previous version 0.9.4.2 dated 2021-03-20

Title: Get Precision of Means Under Various Designs and Sampling Schemes
Description: Computes standard error and confidence interval of various descriptive statistics under various designs and sampling schemes. The main function, superbPlot(), can either return a plot or a dataframe with the statistic and its precision interval so that other plotting package can be used. See Cousineau (2017) <doi:10.5709/acp-0214-z> for a review or Cousineau (2005) <doi:10.20982/tqmp.01.1.p042>, Morey (2008) <doi:10.20982/tqmp.04.2.p061>, Baguley (2012) <doi:10.3758/s13428-011-0123-7>, Cousineau & Laurencelle (2016) <doi:10.1037/met0000055>, Cousineau & O'Brien (2014) <doi:10.3758/s13428-013-0441-z>, Calderini & Harding <doi:10.20982/tqmp.15.1.p001>.
Author: Denis Cousineau [aut, cre], Bradley Harding [ctb], Marc-Andre Goulet [ctb], Jesika Walker [art]
Maintainer: Denis Cousineau <denis.cousineau@uottawa.ca>

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Package RiskPortfolios updated to version 2.1.5 with previous version 2.1.4 dated 2020-04-20

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 stevedata updated to version 0.4.0 with previous version 0.3.1 dated 2021-04-07

Title: Steve's Toy Data for Teaching About a Variety of Methodological, Social, and Political Topics
Description: This is a collection of various kinds of data with broad uses for teaching. My students, and academics like me who teach the same topics I teach, should find this useful if their teaching workflow is also built around the R programming language. The applications are multiple but mostly cluster on topics of statistical methodology, international relations, and political economy.
Author: Steve Miller [aut, cre] (<https://orcid.org/0000-0003-4072-6263>)
Maintainer: Steve Miller <steven.v.miller@gmail.com>

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Package gpboost updated to version 0.6.0 with previous version 0.5.0 dated 2021-03-12

Title: Combining Tree-Boosting with Gaussian Process and Mixed Effects Models
Description: An R package that allows for combining tree-boosting with Gaussian process and mixed effects models. It also allows for independently doing tree-boosting as well as inference and prediction for Gaussian process and mixed effects models. See <https://github.com/fabsig/GPBoost> for more information on the software and Sigrist (2020) <arXiv:2004.02653> for more information on the methodology.
Author: Fabio Sigrist [aut, cre], Benoit Jacob [cph], Gael Guennebaud [cph], Nicolas Carre [cph], Pierre Zoppitelli [cph], Gauthier Brun [cph], Jean Ceccato [cph], Jitse Niesen [cph], Other authors of Eigen for the included version of Eigen [ctb, cph], Timothy A. Davis [cph], Guolin Ke [ctb], Damien Soukhavong [ctb], James Lamb [ctb], Other authors of LightGBM for the included version of LightGBM [ctb], Microsoft Corporation [cph], Dropbox, Inc. [cph], Jay Loden [cph], Dave Daeschler [cph], Giampaolo Rodola [cph], Alberto Ferreira [ctb], Daniel Lemire [ctb], Victor Zverovich [cph], IBM Corporation [ctb], Keith O'Hara [cph]
Maintainer: Fabio Sigrist <fabiosigrist@gmail.com>

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New package ptspotter with initial version 1.0
Package: ptspotter
Title: Helper Functions for Use with "ProjectTemplate"
Version: 1.0
Authors@R: c(person(given = "Rich", family = "Leyshon", role = c("aut", "cph", "cre"), email = "leyshonrr@hotmail.co.uk"), person(given = "Andrew", family = "Simmons", role = "ctb", email = "akwsimmo@gmail.com"))
Description: Utility functions produced specifically for (but not limited to) working with 'ProjectTemplate' data pipelines. This package helps to quickly create and manage sequentially numbered scripts, quickly set up logging with 'log4r' and functions to help debug and monitor procedures.
License: MIT + file LICENSE
URL: https://github.com/r-leyshon/ptspotter
BugReports: https://github.com/r-leyshon/ptspotter/issues
Encoding: UTF-8
Depends: this.path(>= 0.2.0), log4r (>= 0.3.2), beepr(>= 1.3)
Imports: pryr (>= 0.1.4), stringi (>= 1.5.3), stringr (>= 1.4.0), utils (>= 4.0.4)
Suggests: ProjectTemplate (>= 0.9.3), testthat
NeedsCompilation: no
Packaged: 2021-04-21 07:34:08 UTC; richardleyshon
Author: Rich Leyshon [aut, cph, cre], Andrew Simmons [ctb]
Maintainer: Rich Leyshon <leyshonrr@hotmail.co.uk>
Repository: CRAN
Date/Publication: 2021-04-21 12:00:02 UTC

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Package inferference updated to version 1.0.2 with previous version 1.0.0 dated 2017-11-24

Title: Methods for Causal Inference with Interference
Description: Provides methods for estimating causal effects in the presence of interference described in B. Saul and M. Hugdens (2017) <doi:10.18637/jss.v082.i02>. Currently it implements the inverse-probability weighted (IPW) estimators proposed by E.J. Tchetgen Tchetgen and T.J. Vanderweele (2012) <doi:10.1177/0962280210386779>.
Author: Bradley Saul
Maintainer: Bradley Saul <bradleysaul@gmail.com>

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New package abess with initial version 0.1.0
Package: abess
Title: Adaptive Best Subset Selection in Polynomial Time
Version: 0.1.0
Date: 2021-04-21
Authors@R: c( person(given = "Jin", family = "Zhu", email = "zhuj37@mail2.sysu.edu.cn", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8550-5822")), person(given = "Kangkang", family = "Jiang", email = "jiangkk3@mail2.sysu.edu.cn", role = c("aut")), person(given = "Yanhang", family = "Zhang", email = "zhangyh98@ruc.edu.cn", role = c("aut")), person(given = "Liyuan", family = "Hu", email = "huly5@mail2.sysu.edu.cn", role = c("aut")), person(given = "Junxian", family = "Zhu", email = "zhujunx@mail2.sysu.edu.cn", role = c("aut")), person(given = "Canhong", family = "Wen", email = "wencanhong@gmail.com", role = c("aut")), person(given = "Heping", family = "Zhang", email = "heping.zhang@yale.edu", role = c("aut"), comment = c(ORCID = "0000-0002-0688-4076")), person(given = "Xueqin", family = "Wang", email = "wangxq20@ustc.edu.cn", role = c("aut"), comment = c(ORCID = "0000-0001-5205-9950")) )
Maintainer: Jin Zhu <zhuj37@mail2.sysu.edu.cn>
Description: Extremely efficient toolkit for solving the best subset selection problem in linear regression, logistic regression, Poisson regression, Cox proportional hazard model, multiple-response Gaussian, and multinomial regression. It implements and generalizes algorithms designed in <doi:10.1073/pnas.2014241117> that exploits a novel sequencing-and-splicing technique to guarantee exact support recovery and globally optimal solution in polynomial times.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: Rcpp, MASS, methods, Matrix
LinkingTo: Rcpp, RcppEigen
SystemRequirements: C++11
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/abess-team/abess, https://abess-team.github.io/abess/
BugReports: https://github.com/abess-team/abess/issues
NeedsCompilation: yes
Packaged: 2021-04-21 06:10:14 UTC; JinZhu
Author: Jin Zhu [aut, cre] (<https://orcid.org/0000-0001-8550-5822>), Kangkang Jiang [aut], Yanhang Zhang [aut], Liyuan Hu [aut], Junxian Zhu [aut], Canhong Wen [aut], Heping Zhang [aut] (<https://orcid.org/0000-0002-0688-4076>), Xueqin Wang [aut] (<https://orcid.org/0000-0001-5205-9950>)
Repository: CRAN
Date/Publication: 2021-04-21 12:00:05 UTC

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Package muhaz updated to version 1.2.6.4 with previous version 1.2.6.3 dated 2021-04-01

Title: Hazard Function Estimation in Survival Analysis
Description: Produces a smooth estimate of the hazard function for censored data.
Author: S original by Kenneth Hess, R port by R. Gentleman
Maintainer: David Winsemius <dwinsemius@comcast.net>

Diff between muhaz versions 1.2.6.3 dated 2021-04-01 and 1.2.6.4 dated 2021-04-21

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Package waves updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-17

Title: Vis-NIR Spectral Analysis Wrapper
Description: Originally designed application in the context of resource-limited plant research and breeding programs, 'waves' provides an open-source solution to spectral data processing and model development by bringing useful packages together into a streamlined pipeline. This package is wrapper for functions related to the analysis of point visible and near-infrared reflectance measurements. It includes visualization, filtering, aggregation, preprocessing, cross-validation set formation, model training, and prediction functions to enable open-source association of spectral and reference data. This package is documented in a peer-reviewed manuscript in the Plant Phenome Journal <doi:10.1002/ppj2.20012>. Specialized cross-validation schemes are described in detail in Jarquín et al. (2017) <doi:10.3835/plantgenome2016.12.0130>. Example data is from Ikeogu et al. (2017) <doi:10.1371/journal.pone.0188918>.
Author: Jenna Hershberger [aut, cre] (<https://orcid.org/0000-0002-3147-6867>), Michael Gore [ths], NSF BREAD IOS-1543958 [fnd]
Maintainer: Jenna Hershberger <jmh579@cornell.edu>

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Package tidymv updated to version 3.2.1 with previous version 3.2.0 dated 2021-01-05

Title: Tidy Model Visualisation for Generalised Additive Models
Description: Provides functions for visualising generalised additive models and getting predicted values using tidy tools from the 'tidyverse' packages.
Author: Stefano Coretta [aut, cre], Jacolien van Rij [cph] (Imported functions from itsadug), Martijn Wieling [cph] (Imported functions from itsadug)
Maintainer: Stefano Coretta <stefano.coretta@gmail.com>

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Package splines2 updated to version 0.4.3 with previous version 0.4.2 dated 2021-02-21

Title: Regression Spline Functions and Classes
Description: Constructs basis matrix of B-splines, M-splines, I-splines, convex splines (C-splines), periodic M-splines, natural cubic splines, generalized Bernstein polynomials, and their integrals (except C-splines) and derivatives of given order by close-form recursive formulas. It also contains a C++ head-only library integrated with Rcpp. See De Boor (1978) <doi:10.1002/zamm.19800600129>, Ramsay (1988) <doi:10.1214/ss/1177012761>, and Meyer (2008) <doi:10.1214/08-AOAS167> for more information about the spline basis.
Author: Wenjie Wang [aut, cre] (<https://orcid.org/0000-0003-0363-3180>), Jun Yan [aut] (<https://orcid.org/0000-0003-4401-7296>)
Maintainer: Wenjie Wang <wang@wwenjie.org>

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Package speakr updated to version 3.1.1 with previous version 3.1.0 dated 2021-04-19

Title: A Wrapper for the Phonetic Software 'Praat'
Description: It allows running 'Praat' scripts from R and it provides some wrappers for basic plotting. It also adds support for literate markdown tangling. The package is designed to bring reproducible phonetic research into R.
Author: Stefano Coretta [aut, cre]
Maintainer: Stefano Coretta <stefano.coretta@gmail.com>

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Package NNS updated to version 0.6.3.2 with previous version 0.6.3.1 dated 2021-04-20

Title: Nonlinear Nonparametric Statistics
Description: Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization and Stochastic dominance. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).
Author: Fred Viole
Maintainer: Fred Viole <ovvo.financial.systems@gmail.com>

Diff between NNS versions 0.6.3.1 dated 2021-04-20 and 0.6.3.2 dated 2021-04-21

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Package metapack updated to version 0.1.2 with previous version 0.1.1 dated 2021-02-23

Title: Bayesian Meta-Analysis and Network Meta-Analysis
Description: Contains functions performing Bayesian inference for meta-analytic and network meta-analytic models through Markov chain Monte Carlo algorithm. Currently, the package implements Hui Yao, Sungduk Kim, Ming-Hui Chen, Joseph G. Ibrahim, Arvind K. Shah, and Jianxin Lin (2015) <doi:10.1080/01621459.2015.1006065> and Hao Li, Daeyoung Lim, Ming-Hui Chen, Joseph G. Ibrahim, Sungduk Kim, Arvind K. Shah, Jianxin Lin (2021) <doi:10.1002/sim.8983>. For maximal computational efficiency, the Markov chain Monte Carlo samplers for each model, written in C++, are fine-tuned. This software has been developed under the auspices of the National Institutes of Health and Merck & Co., Inc., Kenilworth, NJ, USA.
Author: Daeyoung Lim [aut, cre], Ming-Hui Chen [ctb], Sungduk Kim [ctb], Joseph Ibrahim [ctb], Arvind Shah [ctb], Jianxin Lin [ctb]
Maintainer: Daeyoung Lim <daeyoung.lim@uconn.edu>

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Package gap updated to version 1.2.3-1 with previous version 1.2.2 dated 2020-02-02

Title: Genetic Analysis Package
Description: It is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates. Over years, the package has been developed in-between many projects hence also in line with the name (gap).
Author: Jing Hua Zhao and colleagues with inputs from Kurt Hornik and Brian Ripley
Maintainer: Jing Hua Zhao <jinghuazhao@hotmail.com>

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Package RRTCS updated to version 0.0.4 with previous version 0.0.3 dated 2015-11-03

Title: Randomized Response Techniques for Complex Surveys
Description: Point and interval estimation of linear parameters with data obtained from complex surveys (including stratified and clustered samples) when randomization techniques are used. The randomized response technique was developed to obtain estimates that are more valid when studying sensitive topics. Estimators and variances for 14 randomized response methods for qualitative variables and 7 randomized response methods for quantitative variables are also implemented. In addition, some data sets from surveys with these randomization methods are included in the package.
Author: Beatriz Cobo Rodríguez, María del Mar Rueda García, Antonio Arcos Cebrián
Maintainer: Beatriz Cobo Rodríguez <beacr@ugr.es>

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Package mangoTraining (with last version 1.1) was removed from CRAN

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

2020-06-03 1.1
2017-01-17 1.0-7
2015-12-18 1.0-6

Permanent link
Package Tlasso (with last version 1.0.1) was removed from CRAN

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

2016-09-19 1.0.1

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New package windsoraiR with initial version 0.1.0
Package: windsoraiR
Title: Access the 'Windsor.ai' API
Version: 0.1.0
Authors@R: c(person(given = "Novica", family = "Nakov", role = c("aut", "cre"), email = "nnovica@gmail.com"), person(given = "Windsor.ai", role = "cph", email = "admin@windsor.ai"))
Description: Collect data from the 'Windsor.ai' API <https://www.windsor.ai/api-fields/>.
License: MIT + file LICENSE
URL: https://github.com/windsor-ai/windsoraiR/
BugReports: https://github.com/windsor-ai/windsoraiR/
Depends: R (>= 2.10)
Imports: jsonlite (>= 1.7.2)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2021-04-20 08:33:10 UTC; novica
Author: Novica Nakov [aut, cre], Windsor.ai [cph]
Maintainer: Novica Nakov <nnovica@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-21 07:10:02 UTC

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New package tensorTS with initial version 0.1.0
Package: tensorTS
Title: Factor and Autoregressive Models for Tensor Time Series
Version: 0.1.0
Authors@R: c( person("Zebang", "Li", email = "zl326@stat.rutgers.edu", role=c("aut","cre")), person("Ruofan", "Yu", role = "aut"), person("Rong", "Chen", role = "aut"), person("Yuefeng", "Han", role = "aut"), person("Han", "Xiao", role = "aut"), person("Dan", "Yang", role = "aut"))
Description: Factor and autoregressive models for matrix and tensor valued time series. We provide functions for estimation, simulation and prediction. The models are discussed in Chen et al (2020) <DOI:10.1016/j.jeconom.2020.07.002>, Chen et al (2020) <arXiv:1905.07530>, and Han et al (2020) <arXiv:2006.02611>.
License: GPL (>= 2)
Encoding: UTF-8
Depends: tensor, rTensor, expm
Imports: methods, stats, MASS, abind, Matrix, pracma, graphics
URL: https://github.com/zebang/tensorTS
BugReports: https://github.com/ZeBang/tensorTS/issues
NeedsCompilation: no
Packaged: 2021-04-20 16:42:53 UTC; zeban
Author: Zebang Li [aut, cre], Ruofan Yu [aut], Rong Chen [aut], Yuefeng Han [aut], Han Xiao [aut], Dan Yang [aut]
Maintainer: Zebang Li <zl326@stat.rutgers.edu>
Repository: CRAN
Date/Publication: 2021-04-21 08:00:02 UTC

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New package psycModel with initial version 0.3.0
Package: psycModel
Title: Integrated Toolkit for Psychological Analysis and Modeling in R
Version: 0.3.0
Authors@R: person(given = "Jason", family = "Moy", role = c("aut", "cre"), email = "jasonmoy28@gmail.com", comment = c(ORCID = "0000-0001-8795-3311"))
Description: A beginner-friendly R package for modeling in psychology or related field. It allows fitting models, plotting, checking goodness of fit, and model assumption violations all in one place. It also produces beautiful and easy-to-read output.
License: GPL (>= 3)
URL: https://jasonmoy28.github.io/psycModel/
Depends: R (>= 2.10)
Imports: dplyr, ggplot2, glue, lavaan, lifecycle, lme4, lmerTest, parameters, performance, psych, rlang (>= 0.1.2), stringr, tibble, tidyr, utils
Suggests: correlation, covr, cowplot, fansi, ggrepel, GPArotation, gridExtra, interactions, knitr, nFactors, nlme, pagedown, qqplotr, rmarkdown, roxygen2, sandwich, see, semPlot, testthat (>= 3.0.0), tidyselect
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-04-20 16:35:44 UTC; Jasonmoy
Author: Jason Moy [aut, cre] (<https://orcid.org/0000-0001-8795-3311>)
Maintainer: Jason Moy <jasonmoy28@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-21 07:50:02 UTC

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New package LearningStats with initial version 0.1.0
Package: LearningStats
Title: Elemental Descriptive and Inferential Statistics
Version: 0.1.0
Authors@R: c( person("María Isabel", "Borrajo-García", role = c("aut", "cre"), email = "mariaisabel.borrajo@usc.es"), person("Mercedes", "Conde-Amboage", role = "aut", email = "mercedes.amboage@usc.es"), person("Alejandra", "López-Pérez", role = "aut", email = "alejandralopez.perez@usc.es") )
Description: Provides tools to teach students elemental statistics. The main topics covered are descriptive statistics, probability models (discrete and continuous variables) and statistical inference (confidence intervals and hypothesis tests). One of the main advantages of this package is that allows the user to read quite a variety of types of data files with one unique command. Moreover it includes shortcuts to simple but up-to-now not in R descriptive features such a complete frequency table or an histogram with the optimal number of intervals. Related to model distributions (both discrete and continuous), the package allows the student to easy plot the mass/density function, distribution function and quantile function just detailing as input arguments the known population parameters. The inference related tools are basically confidence interval and hypothesis testing. Having defined independent commands for these two tools makes it easier for the student to understand what the software is performing, and it also helps the student to have a better knowledge on which specific tool they need to use in each situation. Moreover, the hypothesis testing commands provide not only the numeric result on the screen but also a very intuitive graph (which includes the statistic distribution, the observed value of the statistic, the rejection area and the p-value) that is very useful for the student to visualise the process. The regression section includes up to now, a simple linear model, with one single command the student can obtain the numeric summary as well as the corresponding diagram with the adjusted regression model and a legend with basic information (formula of the adjusted model and R-squared).
Language: en-GB
License: GPL-2
Encoding: UTF-8
Depends: R (>= 3.5.0)
LazyData: true
Imports: stats, grDevices, graphics, utils, tools, data.table, readxl, haven, readODS
NeedsCompilation: no
Packaged: 2021-04-20 07:13:56 UTC; maribel
Author: María Isabel Borrajo-García [aut, cre], Mercedes Conde-Amboage [aut], Alejandra López-Pérez [aut]
Maintainer: María Isabel Borrajo-García <mariaisabel.borrajo@usc.es>
Repository: CRAN
Date/Publication: 2021-04-21 07:10:05 UTC

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New package grpsel with initial version 1.0.0
Package: grpsel
Title: Group Subset Selection
Version: 1.0.0
Date: 2021-04-21
Authors@R: person("Ryan", "Thompson", email = "ryan.thompson@monash.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9002-0448"))
Description: Provides tools for sparse regression modelling with grouped predictors using the group subset selection penalty. Uses coordinate descent and local search algorithms to rapidly deliver near optimal estimates. The group subset penalty can be combined with a group lasso or ridge penalty for added shrinkage. Linear and logistic regression are supported, as are overlapping groups.
URL: https://github.com/ryan-thompson/grpsel
BugReports: https://github.com/ryan-thompson/grpsel
License: GPL-3
Encoding: UTF-8
Imports: ggplot2, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-04-20 15:49:13 UTC; ryan
Author: Ryan Thompson [aut, cre] (<https://orcid.org/0000-0002-9002-0448>)
Maintainer: Ryan Thompson <ryan.thompson@monash.edu>
Repository: CRAN
Date/Publication: 2021-04-21 07:50:06 UTC

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New package greed with initial version 0.5.0
Package: greed
Title: Clustering and Model Selection with the Integrated Classification Likelihood
Version: 0.5.0
Date: 2021-04-07
Authors@R: c(person(given = "Etienne", family = "Côme", role = c("aut", "cre"), email = "etienne.come@univ-eiffel.fr"), person(given = "Nicolas", family = "Jouvin", role = c("aut")))
URL: https://comeetie.github.io/greed/, https://github.com/comeetie/greed
BugReports: https://github.com/comeetie/greed/issues
Maintainer: Etienne Côme <etienne.come@univ-eiffel.fr>
Description: An ensemble of algorithms that enable the clustering of networks and data matrix such as document/term matrix with different type of generative models. Model selection and clustering is performed in combination by optimizing the Integrated Classification Likelihood (which is equivalent to minimizing the description length). Several models are available such as: Stochastic Block Model, degree corrected Stochastic Block Model, Mixtures of Multinomial, Latent Block Model. The optimization is performed thanks to a combination of greedy local search and a genetic algorithm (see <arXiv:2002:11577> for more details).
License: GPL
Depends: R (>= 2.10)
Imports: Rcpp (>= 1.0.0), Matrix, future, listenv, ggplot2, graphics, methods, stats,RSpectra,ggpubr, MASS,cba
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, knitr, rmarkdown, igraph, dplyr, tibble, tidyr, spelling
Encoding: UTF-8
VignetteBuilder: knitr
Collate: 'RcppExports.R' 'misc.R' 'models_classes.R' 'fit_classes.R' 'cleanpath.R' 'genetic_alg.R' 'hybrid_alg.R' 'alg_classes.R' 'dcsbm.R' 'coclust_dcsbm.R' 'data.R' 'generator.R' 'mvmreg.R' 'gmm.R' 'greed.R' 'sbm.R' 'misssbm.R' 'mm.R' 'multistart_alg.R' 'multsbm.R' 'plot.R'
Language: en-US
NeedsCompilation: yes
Packaged: 2021-04-20 13:04:53 UTC; comeetie
Author: Etienne Côme [aut, cre], Nicolas Jouvin [aut]
Repository: CRAN
Date/Publication: 2021-04-21 07:40:02 UTC

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New package geocmeans with initial version 0.1.1
Package: geocmeans
Title: Implementing Methods for Spatial Fuzzy Unsupervised Classification
Version: 0.1.1
Authors@R: c( person("Jeremy", "Gelb", email = "jeremy.gelb@ucs.inrs.ca",role = c("aut", "cre")), person("Philippe", "Apparicio", email="philippe.apparicio@ucs.inrs.ca", role=c("ctb")))
Maintainer: Jeremy Gelb <jeremy.gelb@ucs.inrs.ca>
Imports: ggplot2 (>= 3.2.1), spdep (>= 1.1.2), reldist (>= 1.6.6), dplyr (>= 0.8.3), fclust (>= 2.1.1), fmsb (>= 0.7.0), broom (>= 0.5.2), future.apply (>= 1.4.0), progressr (>= 0.4.0), reshape2 (>= 1.4.4), sp (>= 1.4-4), stats (>= 3.5)
Depends: R (>= 3.5)
Suggests: knitr (>= 1.28), rmarkdown (>= 2.1), markdown (>= 1.1), maptools (>= 0.9-5), rgeos (>= 0.5-2), future (>= 1.16.0), ppclust (>= 1.1.0), ClustGeo (>= 2.0), car (>= 3.0-7), rgl (>= 0.100), ggpubr (>= 0.2.5), RColorBrewer (>= 1.1-2), kableExtra (>= 1.1.0), viridis (>= 0.5.1), testthat(>= 3.0.0), sf(>= 0.9-8)
License: GPL-2
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
Description: Provides functions to apply spatial fuzzy unsupervised classification, visualize and interpret results. This method is well suited when the user wants to analyze data with a fuzzy clustering algorithm and to account for the spatial dimension of the dataset. Indexes for estimating the spatial consistency and classification quality are proposed in addition. The methods were originally proposed in the field of brain imagerie (seed Cai and al. 2007 <doi:10.1016/j.patcog.2006.07.011> and Zaho and al. 2013 <doi:10.1016/j.dsp.2012.09.016>) and recently applied in geography (see Gelb and Apparicio <doi:10.4000/cybergeo.36414>).
URL: https://github.com/JeremyGelb/geocmeans
BugReports: https://github.com/JeremyGelb/geocmeans/issues
NeedsCompilation: no
Packaged: 2021-04-20 13:00:27 UTC; gelbj
Author: Jeremy Gelb [aut, cre], Philippe Apparicio [ctb]
Repository: CRAN
Date/Publication: 2021-04-21 07:40:07 UTC

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New package DCEtool with initial version 0.0.1
Package: DCEtool
Title: Create, Survey and Analyse Discrete Choice Experiments
Version: 0.0.1
Authors@R: person(given = "Daniel", family = "Perez Troncoso", role = c("aut", "cre"), email = "danielperez@ugr.es", comment = c(ORCID = "0000-0003-0091-8148"))
Description: This app is intended to be a complete package for creating, surveying, and analysing discrete choice experiments. Although all these functionalities are available, the app can also be used only to obtain the design of a discrete choice experiment. Reference: Perez-Troncoso, D. (2021) <https://github.com/danielpereztr/DCEtool>.
License: GPL-3
Encoding: UTF-8
Imports: DT, shiny, shinythemes, survival, idefix, writexl, shinyjs, MASS, stats
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-20 09:43:49 UTC; danie
Author: Daniel Perez Troncoso [aut, cre] (<https://orcid.org/0000-0003-0091-8148>)
Maintainer: Daniel Perez Troncoso <danielperez@ugr.es>
Repository: CRAN
Date/Publication: 2021-04-21 07:30:03 UTC

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New package circle with initial version 0.7.1
Package: circle
Title: R Client Package for Circle CI
Version: 0.7.1
Authors@R: c(person(given = "Patrick", family = "Schratz", role = c("aut", "cre"), email = "patrick.schratz@gmail.com", comment = c(ORCID = "0000-0003-0748-6624")), person(given = "Max", family = "Joseph", role = "rev", comment = "Max reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/356>"), person(given = "Sharla", family = "Gelfand", role = "rev", comment = "Sharla reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/356>"))
Description: Tools for interacting with the 'Circle CI' API (<https://circleci.com/docs/api/v2/>). Besides executing common tasks such as querying build logs and restarting builds, this package also helps setting up permissions to deploy from builds.
License: GPL-3
URL: https://docs.ropensci.org/circle/, https://github.com/ropensci/circle
BugReports: https://github.com/ropensci/circle/issues
Imports: cli (>= 2.0.0), httr, jsonlite
Suggests: clipr, covr, gert, gh, knitr, openssl, purrr, rmarkdown, testthat (>= 3.0.0), usethis (>= 2.0.0), utils, vcr, withr
VignetteBuilder: knitr
Config/testthat/parallel: true
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-20 15:26:29 UTC; pjs
Author: Patrick Schratz [aut, cre] (<https://orcid.org/0000-0003-0748-6624>), Max Joseph [rev] (Max reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/356>), Sharla Gelfand [rev] (Sharla reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/356>)
Maintainer: Patrick Schratz <patrick.schratz@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-21 07:50:10 UTC

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New package ccoptimalmatch with initial version 0.1.0
Package: ccoptimalmatch
Title: Implementation of Case-Control Optimal Matching
Version: 0.1.0
Authors@R: c( person("Pavlos", "Mamouris",role = c("aut", "cre"), email = "pavlos.mamouris@kuleuven.be"), person("Vahid", "Nassiri",role = c("aut", "ctb"), email= "vahid.nassiri@openanalytics.eu"))
Description: Cases are matched to controls in an efficient, optimal and computationally flexible way. It uses the idea of sub-sampling in the level of the case, by creating pseudo-observations of controls. The user can select between replacement and without replacement, the number of controls, and several covariates to match upon. See Mamouris (2021) <doi:10.1186/s12874-021-01256-3> for an overview.
Depends: R (>= 2.10)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: dplyr, rlang
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-20 10:55:41 UTC; u0112219
Author: Pavlos Mamouris [aut, cre], Vahid Nassiri [aut, ctb]
Maintainer: Pavlos Mamouris <pavlos.mamouris@kuleuven.be>
Repository: CRAN
Date/Publication: 2021-04-21 07:40:10 UTC

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Package geneExpressionFromGEO (with last version 0.5) was removed from CRAN

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

2021-04-06 0.5
2021-01-25 0.4
2020-11-17 0.3
2020-11-16 0.2

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Package Rraven updated to version 1.0.13 with previous version 1.0.12 dated 2021-03-09

Title: Connecting R and 'Raven' Sound Analysis Software
Description: A tool to exchange data between R and 'Raven' sound analysis software (Cornell Lab of Ornithology). Functions work on data formats compatible with the R package 'warbleR'.
Author: Marcelo Araya-Salas [aut, cre] (<https://orcid.org/0000-0003-3594-619X>)
Maintainer: Marcelo Araya-Salas <marcelo.araya@ucr.ac.cr>

Diff between Rraven versions 1.0.12 dated 2021-03-09 and 1.0.13 dated 2021-04-21

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Package nandb updated to version 2.0.8 with previous version 2.0.7 dated 2020-05-08

Title: Number and Brightness Image Analysis
Description: Calculation of molecular number and brightness from fluorescence microscopy image series. The software was published in a 2016 paper <doi:10.1093/bioinformatics/btx434>. The seminal paper for the technique is Digman et al. 2008 <doi:10.1529/biophysj.107.114645>. A review of the technique was published in 2017 <doi:10.1016/j.ymeth.2017.12.001>.
Author: Rory Nolan [aut, cre, cph] (<https://orcid.org/0000-0002-5239-4043>), Luis Alvarez [ctb, cph] (<https://orcid.org/0000-0003-1316-1906>), Sergi Padilla-Parra [ctb, ths, cph] (<https://orcid.org/0000-0002-8010-9481>)
Maintainer: Rory Nolan <rorynoolan@gmail.com>

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Package detrendr updated to version 0.6.13 with previous version 0.6.12 dated 2021-02-08

Title: Detrend Images
Description: Detrend fluorescence microscopy image series for fluorescence fluctuation and correlation spectroscopy ('FCS' and 'FFS') analysis. This package contains functionality published in a 2016 paper <doi:10.1093/bioinformatics/btx434> but it has been extended since then with the Robin Hood algorithm and thus contains unpublished work.
Author: Rory Nolan [aut, cre] (<https://orcid.org/0000-0002-5239-4043>), Luis Alvarez [ctb, cph] (<https://orcid.org/0000-0003-1316-1906>), Sergi Padilla-Parra [ctb, ths, cph] (<https://orcid.org/0000-0002-8010-9481>)
Maintainer: Rory Nolan <rorynoolan@gmail.com>

Diff between detrendr versions 0.6.12 dated 2021-02-08 and 0.6.13 dated 2021-04-21

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Package baRulho updated to version 1.0.5 with previous version 1.0.4 dated 2021-03-09

Title: Quantifying Habitat-Induced Acoustic Signal Degradation
Description: Intended to facilitate acoustic analysis of (animal) sound transmission experiments, which typically aim to quantify changes in signal structure when transmitted in a given habitat by broadcasting and re-recording animal sounds at increasing distances. The package offers a workflow with functions to prepare the data set for analysis as well as to calculate and visualize several degradation metrics, including blur ratio, signal-to-noise ratio, excess attenuation and envelope correlation among others (Dabelsteen et al 1993 <doi:10.1121/1.406682>).
Author: Marcelo Araya-Salas [aut, cre]
Maintainer: Marcelo Araya-Salas <marcelo.araya@ucr.ac.cr>

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Package badger updated to version 0.1.0 with previous version 0.0.9 dated 2020-12-05

Title: Badge for R Package
Description: Query information and generate badge for using in README and GitHub Pages.
Author: Guangchuang Yu [aut, cre] (<https://orcid.org/0000-0002-6485-8781>), Gregor de Cillia [ctb], Dirk Eddelbuettel [ctb], Maëlle Salmon [ctb], Robrecht Cannoodt [ctb] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Alexander Rossell Hayes [ctb] (<https://orcid.org/0000-0001-9412-0457>, rossellhayes)
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package collector (with last version 0.1.3) was removed from CRAN

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2020-02-17 0.1.3

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

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2019-01-02 1.0

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Package spread (with last version 2019.8.5) was removed from CRAN

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2019-08-20 2019.8.5

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Package rainette (with last version 0.1.2) was removed from CRAN

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2021-01-20 0.1.2
2020-05-09 0.1.1
2020-03-25 0.1

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

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2018-11-14 1.0

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Package tempcyclesdata (with last version 1.0.1) was removed from CRAN

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

2016-01-03 1.0.1
2016-01-01 1.0.0

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Package onlineretail (with last version 0.1.1) was removed from CRAN

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2021-01-26 0.1.1
2020-11-20 0.1.0

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

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2019-10-07 1.0.0

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Package alineR (with last version 1.1.4) was removed from CRAN

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2017-09-14 1.1.4
2016-04-01 1.1.3
2015-11-30 1.1.2
2015-08-06 1.1.1
2015-07-27 1.1
2015-07-10 1.0

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Package redist (with last version 3.0.1) was removed from CRAN

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2021-04-07 3.0.1
2020-10-13 2.0.2

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Package fhidata (with last version 2019.8.27) was removed from CRAN

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2019-08-29 2019.8.27
2019-06-24 2019.6.24
2019-05-21 2019.5.19
2019-04-04 2019.4.2

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

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2018-12-18 0.1.0

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Package dataverse (with last version 0.3.8) was removed from CRAN

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2021-04-14 0.3.8
2021-03-08 0.3.7

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Package DEPONS2R (with last version 1.0.0) was removed from CRAN

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2020-10-26 1.0.0

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

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2019-10-30 1.0

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Package iriR (with last version 0.2.1) was removed from CRAN

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2021-01-06 0.2.1
2020-11-09 0.1.0

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Package HCmodelSets (with last version 1.1.1) was removed from CRAN

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2020-04-20 1.1.1
2019-12-16 1.1
2018-12-17 1.0.2
2018-12-13 1.0.1
2018-12-11 1.0.0
2018-11-27 0.2.1
2018-07-05 0.1.1

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Package tvm updated to version 0.5.0 with previous version 0.4.0 dated 2019-03-06

Title: Time Value of Money Functions
Description: Functions for managing cashflows and interest rate curves.
Author: Juan Manuel Truppia
Maintainer: Juan Manuel Truppia <jmtruppia@gmail.com>

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Package rsvg updated to version 2.1.1 with previous version 2.1 dated 2020-05-19

Title: Render SVG Images into PDF, PNG, PostScript, or Bitmap Arrays
Description: Renders vector-based svg images into high-quality custom-size bitmap arrays using 'librsvg2'. The resulting bitmap can be written to e.g. png, jpeg or webp format. In addition, the package can convert images directly to various formats such as pdf or postscript.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package reticulate updated to version 1.19 with previous version 1.18 dated 2020-10-25

Title: Interface to 'Python'
Description: Interface to 'Python' modules, classes, and functions. When calling into 'Python', R data types are automatically converted to their equivalent 'Python' types. When values are returned from 'Python' to R they are converted back to R types. Compatible with all versions of 'Python' >= 2.7.
Author: Kevin Ushey [aut, cre], JJ Allaire [aut], RStudio [cph, fnd], Yuan Tang [aut, cph] (<https://orcid.org/0000-0001-5243-233X>), Dirk Eddelbuettel [ctb, cph], Bryan Lewis [ctb, cph], Sigrid Keydana [ctb], Ryan Hafen [ctb, cph], Marcus Geelnard [ctb, cph] (TinyThread library, http://tinythreadpp.bitsnbites.eu/)
Maintainer: Kevin Ushey <kevin@rstudio.com>

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Package PeerPerformance updated to version 2.2.3 with previous version 2.2.2 dated 2020-04-21

Title: Luck-Corrected Peer Performance Analysis in R
Description: Provides functions to perform the peer performance analysis of funds' returns as described in Ardia and Boudt (2018) <doi:10.1016/j.jbankfin.2017.10.014>.
Author: David Ardia [aut, cre] (<https://orcid.org/0000-0003-2823-782X>), Kris Boudt [aut], Nabil Bouamara [ctb]
Maintainer: David Ardia <david.ardia.ch@gmail.com>

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Package landmap updated to version 0.0.9 with previous version 0.0.7 dated 2021-01-29

Title: Automated Spatial Prediction using Ensemble Machine Learning
Description: Functions and tools for spatial interpolation and/or prediction of environmental variables (points to grids) based on using Ensemble Machine Learning with geographical distances. Package also provides access to Global Environmental Layers (<https://www.OpenLandMap.org>) produced by the OpenGeoHub.org foundation and collaborators. Some functions have been migrated and adopted from the Global Soil Information Facilities package.
Author: Tomislav Hengl [aut, cre]
Maintainer: Tomislav Hengl <tom.hengl@opengeohub.org>

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Package GA updated to version 3.2.1 with previous version 3.2 dated 2019-01-10

Title: Genetic Algorithms
Description: Flexible general-purpose toolbox implementing genetic algorithms (GAs) for stochastic optimisation. Binary, real-valued, and permutation representations are available to optimize a fitness function, i.e. a function provided by users depending on their objective function. Several genetic operators are available and can be combined to explore the best settings for the current task. Furthermore, users can define new genetic operators and easily evaluate their performances. Local search using general-purpose optimisation algorithms can be applied stochastically to exploit interesting regions. GAs can be run sequentially or in parallel, using an explicit master-slave parallelisation or a coarse-grain islands approach.
Author: Luca Scrucca [aut, cre] (<https://orcid.org/0000-0003-3826-0484>)
Maintainer: Luca Scrucca <luca.scrucca@unipg.it>

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Package FORTLS updated to version 1.0.2 with previous version 1.0.1 dated 2021-03-02

Title: Automatic Processing of TLS Point Cloud Data for Forestry Purposes
Description: Process automation of Terrestrial Laser Scanner (TLS) point cloud data derived from single scans. 'FORTLS' enables (i) detection of trees and estimation of diameter at breast height (dbh), (ii) estimation of some stand variables (e.g. density, basal area, mean and dominant height), (iii) computation of metrics related to important forest attributes estimated in Forest Inventories (FIs) at stand level and (iv) optimization of plot design for combining TLS data and field measured data. Documentation about 'FORTLS' is described in Molina-Valero et al. (2020, <doi:10.3390/IECF2020-08066>).
Author: Juan Alberto Molina-Valero [aut, cph, cre], María José Ginzo Villamayor [aut, com], Manuel Antonio Novo Pérez [aut, com], Adela Martínez-Calvo [aut, com], Juan Gabriel Álvarez-González [aut, ths], Fernando Montes [aut], César Pérez-Cruzado [aut, ths]
Maintainer: Juan Alberto Molina-Valero <juanalberto.molina.valero@usc.es>

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Package flashlight updated to version 0.8.0 with previous version 0.7.5 dated 2021-02-13

Title: Shed Light on Black Box Machine Learning Models
Description: Shed light on black box machine learning models by the help of model performance, variable importance, global surrogate models, ICE profiles, partial dependence (Friedman J. H. (2001) <doi:10.1214/aos/1013203451>), accumulated local effects (Apley D. W. (2016) <arXiv:1612.08468>), further effects plots, scatter plots, interaction strength, and variable contribution breakdown (approximate SHAP) for single observations (Gosiewska and Biecek (2019) <arxiv:1903.11420>). All tools are implemented to work with case weights and allow for stratified analysis. Furthermore, multiple flashlights can be combined and analyzed together.
Author: Michael Mayer [aut, cre, cph]
Maintainer: Michael Mayer <mayermichael79@gmail.com>

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More information about flashlight at CRAN
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Package AdMit updated to version 2.1.6 with previous version 2.1.5 dated 2020-04-20

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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More information about AdMit at CRAN
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