Thu, 12 Nov 2020

Package giscoR updated to version 0.2.0 with previous version 0.1.1 dated 2020-10-28

Title: Download Map Data from GISCO API - Eurostat
Description: Tools to download data from the GISCO (Geographic Information System of the Commission) Eurostat database <https://ec.europa.eu/eurostat/web/gisco>. Global and European map data available. This package is in no way officially related to or endorsed by Eurostat.
Author: Diego Hernangómez [aut, cre, cph] (<https://orcid.org/0000-0001-8457-4658>), EuroGraphics [cph] (for the administrative boundaries.), Vincent Arel-Bundock [cph] (<https://orcid.org/0000-0003-2042-7063>, for the gisco_countrycode dataset.)
Maintainer: Diego Hernangómez <diego.hernangomezherrero@gmail.com>

Diff between giscoR versions 0.1.1 dated 2020-10-28 and 0.2.0 dated 2020-11-12

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Package Bergm updated to version 5.0.2 with previous version 5.0.1 dated 2019-11-04

Title: Bayesian Exponential Random Graph Models
Description: Bayesian analysis for exponential random graph models using advanced computational algorithms. More information can be found at: <https://acaimo.github.io/Bergm>.
Author: Alberto Caimo [aut, cre], Lampros Bouranis [aut], Robert Krause [aut] Nial Friel [ctb]
Maintainer: Alberto Caimo <acaimo.stats@gmail.com>

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Package rstudioapi updated to version 0.13 with previous version 0.12 dated 2020-11-10

Title: Safely Access the RStudio API
Description: Access the RStudio API (if available) and provide informative error messages when it's not.
Author: Kevin Ushey [aut, cre], JJ Allaire [aut], Hadley Wickham [aut], Gary Ritchie [aut], RStudio [cph]
Maintainer: Kevin Ushey <kevin@rstudio.com>

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Package permutations updated to version 1.0-9 with previous version 1.0-6 dated 2020-02-07

Title: The Symmetric Group: Permutations of a Finite Set
Description: Manipulates invertible functions from a finite set to itself. Can transform from word form to cycle form and back.
Author: Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>), Paul Egeler [ctb] (<https://orcid.org/0000-0001-6948-9498>)
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

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Package intcensROC updated to version 0.1.2 with previous version 0.1 dated 2018-05-02

Title: AUC Estimation of Interval Censored Survival Data
Description: The kernel of this 'Rcpp' based package is an efficient implementation of the generalized gradient projection method for spline function based constrained maximum likelihood estimator for interval censored survival data (Wu, Yuan; Zhang, Ying. Partially monotone tensor spline estimation of the joint distribution function with bivariate current status data. Ann. Statist. 40, 2012, 1609-1636 <doi:10.1214/12-AOS1016>). The key function computes the density function of the joint distribution of event time and the marker and returns the receiver operating characteristic (ROC) curve for the interval censored survival data as well as area under the curve (AUC).
Author: Jiaxing Lin, Yuan Wu, Xiaofei Wang, Kouros Owzar.
Maintainer: Alexander Sibley <dcibioinformatics@duke.edu>

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Package groupedSurv updated to version 1.0.4.2 with previous version 1.0.4.1 dated 2020-02-02

Title: Efficient Estimation of Grouped Survival Models
Description: These 'Rcpp'-based functions compute the efficient score statistics for grouped time-to-event data (Prentice and Gloeckler, 1978), with the optional inclusion of baseline covariates. Functions for estimating the parameter of interest and nuisance parameters, including baseline hazards, using maximum likelihood are also provided. A parallel set of functions allow for the incorporation of family structure of related individuals (e.g., trios). Note that the current implementation of the frailty model (Ripatti and Palmgren, 2000) is sensitive to departures from model assumptions, and should be considered experimental. For these data, the exact proportional-hazards-model-based likelihood is computed by evaluating multiple variable integration. The integration is accomplished using the 'Cuba' library (Hahn, 2005), and the source files are included in this package. The maximization process is carried out using Brent's algorithm, with the C++ code file from John Burkardt and John Denker (Brent, 2002).
Author: Jiaxing Lin [aut], Alexander Sibley [aut], Tracy Truong [aut], Kouros Owzar [aut], Zhiguo Li [aut], Yu Jiang [ctb], Janice McCarthy [ctb], Andrew Allen [ctb]
Maintainer: Alexander Sibley <dcibioinformatics@duke.edu>

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Package bssm updated to version 1.0.1-1 with previous version 1.0.0 dated 2020-06-09

Title: Bayesian Inference of Non-Gaussian State Space Models
Description: Efficient methods for Bayesian inference of state space models via particle Markov chain Monte Carlo (MCMC) and MCMC based on parallel importance sampling type weighted estimators (Vihola, Helske, and Franks, 2020, <doi:10.1111/sjos.12492>). Gaussian, Poisson, binomial, negative binomial, and Gamma observation densities and basic stochastic volatility models with Gaussian state dynamics, as well as general non-linear Gaussian models and discretised diffusion models are supported.
Author: Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>), Matti Vihola [aut] (<https://orcid.org/0000-0002-8041-7222>)
Maintainer: Jouni Helske <jouni.helske@iki.fi>

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Package thorn updated to version 0.2.0 with previous version 0.1.0 dated 2020-10-22

Title: 'HTMLwidgets' Displaying Some 'WebGL' Shaders
Description: Creates some 'WebGL' shaders. They can be used as the background of a 'Shiny' app. They also can be visualized in the 'RStudio' viewer pane or included in 'Rmd' documents, but this is pretty useless, besides contemplating them.
Author: Stéphane Laurent [aut, cre], Scott Boyle [ctb, cph] ('Hamster.js' library), Mathew Groves [ctb, cph] ('PixiJS' library), Chad Engler [ctb, cph] ('PixiJS' library)
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>

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Package graph3d updated to version 0.2.0 with previous version 0.1.0 dated 2020-08-12

Title: A Wrapper of the JavaScript Library 'vis-graph3d'
Description: Create interactive visualization charts to draw data in three dimensional graphs. The graphs can be included in Shiny apps and R markdown documents, or viewed from the R console and 'RStudio' Viewer. Based on the 'vis.js' Graph3d module and the 'htmlwidgets' R package.
Author: Stéphane Laurent [aut, cre] (R interface), B. V. Almende [aut, cph] (vis.js library), vis.js contributors [aut, cph]
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>

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Package textrecipes updated to version 0.4.0 with previous version 0.3.0 dated 2020-07-08

Title: Extra 'Recipes' for Text Processing
Description: Converting text to numerical features requires specifically created procedures, which are implemented as steps according to the 'recipes' package. These steps allows for tokenization, filtering, counting (tf and tfidf) and feature hashing.
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>

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New package SCORNET with initial version 0.1.0
Package: SCORNET
Title: Semi-Supervised Calibration of Risk with Noisy Event Times
Version: 0.1.0
Authors@R: person(given = "Yuri", family = "Ahuja", role = c("aut", "cre"), email = "Yuri_Ahuja@hms.harvard.edu")
Description: A consistent, semi-supervised, non-parametric survival curve estimator optimized for efficient use of Electronic Health Record (EHR) data with a limited number of current status labels. See van der Laan and Robins (1997) <doi:10.2307/2670119>.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.1.1
Imports: Matrix, survival, pracma, foreach, doParallel, parallel, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
URL: https://github.com/celehs/SCORNET
BugReports: https://github.com/celehs/SCORNET/issues
NeedsCompilation: yes
Packaged: 2020-11-08 17:12:17 UTC; yuriahuja
Author: Yuri Ahuja [aut, cre]
Maintainer: Yuri Ahuja <Yuri_Ahuja@hms.harvard.edu>
Repository: CRAN
Date/Publication: 2020-11-12 18:20:02 UTC

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New package PSS.Health with initial version 0.1.4
Package: PSS.Health
Type: Package
Title: Power and Sample Size for Health Researchers
Version: 0.1.4
Date: 2020-11-06
Language: pt
Authors@R: c(person(given = "Rogério", family = "Borges", role = c("aut", "cre"), email = "roborges@hcpa.edu.br", comment = c(ORCID = "orcid.org/0000-0002-2548-1889")), person(given = "Guilherme", family = "Azambuja", role = c("aut"), email = "gsazambuja@gmail.com", comment = c(ORCID = "orcid.org/0000-0001-6246-4538")), person(given = "Aline", family = "Mancuso", role = c("aut"), email = "amancuso@hcpa.edu.br", comment = c(ORCID = "orcid.org/0000-0001-6033-8335")), person(given = "Vanessa", family = "Leotti", role = c("aut"), email = "vleotti@hcpa.edu.br", comment = c(ORCID = "orcid.org/0000-0003-3860-9367")), person(given = "Vânia", family = "Hirakata", role = c("aut"), email = "vhirakata@hcpa.edu.br", comment = c(ORCID = "orcid.org/0000-0003-4645-2080")), person(given = "Suzi", family = "Camey", role = c("aut"), email = "scamey@hcpa.edu.br", comment = c(ORCID = "orcid.org/0000-0002-5564-081X")), person(given = "Stela", family = "Castro", role = c("aut"), email = "stelacastro@hcpa.edu.br", comment = c(ORCID = "orcid.org/0000-0001-5862-6709")), person(given = "Hospital de Clínicas de Porto Alegre", role = c("fnd")) )
Description: Power and Sample Size for Health Researchers is a Shiny application that brings together a series of functions related to sample size and power calculations for common analysis in the healthcare field. There are functionalities to calculate the sample size to estimate or test hypotheses for means, proportions, association, Pearson's correlation coefficient, regression coefficients (linear, logistic and Cox), Cronbach's alpha, interobserver agreement, intraclass correlation coefficients, limit of agreement on Bland-Altman plots, area under the curve, sensitivity and specificity incorporating the prevalence of disease.
Imports: DT, easypower, EnvStats, ICC.Sample.Size, kappaSize, MESS, plotly, powerMediation, powerSurvEpi, presize, pROC, pwr, pwr2, shiny, shinycssloaders, shinyFeedback, shinythemes, shinyhelper, tidyverse, TrialSize, WebPower, writexl
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 7.1.0
Contact: 'mailto:l-bioestatistica@hcpa.edu.br'
NeedsCompilation: no
Packaged: 2020-11-08 23:09:38 UTC; roger
Author: Rogério Borges [aut, cre] (<https://orcid.org/0000-0002-2548-1889>), Guilherme Azambuja [aut] (<https://orcid.org/0000-0001-6246-4538>), Aline Mancuso [aut] (<https://orcid.org/0000-0001-6033-8335>), Vanessa Leotti [aut] (<https://orcid.org/0000-0003-3860-9367>), Vânia Hirakata [aut] (<https://orcid.org/0000-0003-4645-2080>), Suzi Camey [aut] (<https://orcid.org/0000-0002-5564-081X>), Stela Castro [aut] (<https://orcid.org/0000-0001-5862-6709>), Hospital de Clínicas de Porto Alegre [fnd]
Maintainer: Rogério Borges <roborges@hcpa.edu.br>
Repository: CRAN
Date/Publication: 2020-11-12 18:40:03 UTC

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New package MCMChybridGP with initial version 5.4
Package: MCMChybridGP
Version: 5.4
Title: Hybrid Markov Chain Monte Carlo using Gaussian Processes
Author: Mark J. Fielding <mark.fielding@gmx.com>
Maintainer: Mark J. Fielding <mark.fielding@gmx.com>
Depends: MASS
Description: Hybrid Markov chain Monte Carlo (MCMC) to simulate from a multimodal target distribution. A Gaussian process approximation makes this possible when derivatives are unknown. The Package serves to minimize the number of function evaluations in Bayesian calibration of computer models using parallel tempering. It allows replacement of the true target distribution in high temperature chains, or complete replacement of the target. Methods used are described in, "Efficient MCMC schemes for computationally expensive posterior distributions", Fielding et al. (2011) <doi:10.1198/TECH.2010.09195>. The research presented in this work was carried out as part of the Singapore-Delft Water Alliance Multi-Objective Multi-Reservoir Management research programme (R-264-001-272).
License: GPL-2
LazyLoad: yes
Packaged: 2020-11-09 20:50:35 UTC; mark
Repository: CRAN
Date/Publication: 2020-11-12 18:50:02 UTC
NeedsCompilation: yes

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New package microeco with initial version 0.2.1
Package: microeco
Type: Package
Title: Microbial Community Ecology Data Analysis
Version: 0.2.1
Authors@R: c(person("Chi", "Liu", role = c("aut", "cre"), email = "liuchi0426@126.com"), person("Minjie", "Yao", role = "aut", email = "yaomj@fafu.edu.cn"), person("Xiangzhen", "Li", role = "aut", email = "lixz@cib.ac.cn"), person("Paul J.", "McMurdie", role = "ctb", email = "joey711@gmail.com"), person("Yang", "Cao", role = "ctb", email = "yiluheihei@gmail.com"), person("James Robert", "White", role = "ctb", email = "whitej@umd.edu"), person("Stilianos", "Louca", role = "cph", email = "slouca@uoregon.edu"), person("Nhu H.", "Nguyen", role = "cph", email = "nhnguyen@umn.edu") )
Author: Chi Liu [aut, cre], Minjie Yao [aut], Xiangzhen Li [aut], Paul J. McMurdie [ctb], Yang Cao [ctb], James Robert White [ctb], Stilianos Louca [cph], Nhu H. Nguyen [cph]
Maintainer: Chi Liu <liuchi0426@126.com>
Description: A series of statistical and plotting approaches in microbial community ecology based on the R6 class. The classes are designed for data preprocessing, taxa abundance plotting, alpha diversity statistics, beta diversity statistics, differential abundance test and indicator taxon analysis, environmental data analysis, null model analysis, network analysis and functional analysis.
Depends: R (>= 3.5.0)
Imports: R6, stats, ape, vegan, rlang, data.table, magrittr, dplyr, tibble, reshape2, scales, grid, ggplot2, boot, agricolae, VGAM, GUniFrac, picante, randomForest, MASS, RColorBrewer, pheatmap, ggpubr, gridExtra, ggrepel, ggdendro, Rcpp
Suggests: igraph, WGCNA, tidytree, mice
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
License: GPL-3
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-11-08 15:40:50 UTC; Chi
Repository: CRAN
Date/Publication: 2020-11-12 17:20:02 UTC
RoxygenNote: 7.1.0

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Package lmeInfo updated to version 0.1.2 with previous version 0.1.1 dated 2020-05-10

Title: Information Matrices for 'lmeStruct' and 'glsStruct' Objects
Description: Provides analytic derivatives and information matrices for fitted linear mixed effects (lme) models and generalized least squares (gls) models estimated using lme() (from package 'nlme') and gls() (from package 'nlme'), respectively. The package includes functions for estimating the sampling variance-covariance of variance component parameters using the inverse Fisher information. The variance components include the parameters of the random effects structure (for lme models), the variance structure, and the correlation structure. The expected and average forms of the Fisher information matrix are used in the calculations, and models estimated by full maximum likelihood or restricted maximum likelihood are supported. The package also includes a function for estimating standardized mean difference effect sizes (Pustejovsky, Hedges, and Shadish (2014) <DOI:10.3102/1076998614547577>) based on fitted lme or gls models.
Author: James Pustejovsky [aut] (<https://orcid.org/0000-0003-0591-9465>), Man Chen [aut, cre]
Maintainer: Man Chen <manchen9005@gmail.com>

Diff between lmeInfo versions 0.1.1 dated 2020-05-10 and 0.1.2 dated 2020-11-12

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 lmeInfo-0.1.2/lmeInfo/NAMESPACE                                                |    5 
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 lmeInfo-0.1.2/lmeInfo/tests/testthat/test-two-level-models.R                   |   23 ++
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New package chickn with initial version 1.2.2
Package: chickn
Type: Package
Title: Compressed Hierarchical Clustering Toolbox
Version: 1.2.2
Date: 2020-11-08
Authors@R: c(person("Olga","Permiakova", role = c("aut", "cre"), email = "olga.permiakova@gmail.com"), person("Thomas","Burger",role = "aut",email = "thomas.burger@cea.fr"))
Maintainer: Olga Permiakova <olga.permiakova@gmail.com>
Description: Routines for efficient cluster analysis of large scale data. The package implements the 'CHICKN' clustering algorithm, which clusters the data into K groups by relying on the compressed data version. The package provides functions for data compression, hierarchical clustering and result post processing. The used data compression procedure is based on the sketching learning N. 'Keriven', N. 'Tremblay', Y. 'Traonmilin', R. 'Gribonval' (2017) <arXiv:1606.02838v2> and 'Nystrom' kernel approximation S. Wang, A. 'Gittens', M. W. 'Mahoney' (2019) <arXiv:1706.02803v4>. Hierarchical clustering relies on the 'Compressive' K means algorithm N. 'Keriven', A. 'Bourrier', R. 'Gribonval', P. Perez (2017) <arXiv:1610.08738v4>.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.5)
Imports: Rcpp, bigstatsr (>= 1.2.3), RcppParallel, mvnfast, zipfR, MASS, pracma, nloptr, foreach, doRNG, parallel, doParallel, Rdpack
LinkingTo: Rcpp, RcppArmadillo, RcppParallel, bigstatsr (>= 1.2.3), rmio
SystemRequirements: C++11
RoxygenNote: 7.1.1
RdMacros: Rdpack
NeedsCompilation: yes
Packaged: 2020-11-08 16:26:04 UTC; satrix
Author: Olga Permiakova [aut, cre], Thomas Burger [aut]
Repository: CRAN
Date/Publication: 2020-11-12 17:20:07 UTC

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Package abtest updated to version 0.2.2 with previous version 0.2.1 dated 2020-04-23

Title: Bayesian A/B Testing
Description: Provides functions for Bayesian A/B testing including prior elicitation options based on Kass and Vaidyanathan (1992) <doi:10.1111/j.2517-6161.1992.tb01868.x>.
Author: Quentin F. Gronau [aut, cre], Akash Raj [ctb], Eric-Jan Wagenmakers [ths]
Maintainer: Quentin F. Gronau <Quentin.F.Gronau@gmail.com>

Diff between abtest versions 0.2.1 dated 2020-04-23 and 0.2.2 dated 2020-11-12

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Package tidyCpp updated to version 0.0.2 with previous version 0.0.1 dated 2020-10-10

Title: Tidy C++ Header-Only Definitions for Parts of the C API of R
Description: Core parts of the C API of R are wrapped in a C++ namespace via a set of inline functions giving a tidier representation of the underlying data structures and functionality using a header-only implementation without additional dependencies.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between tidyCpp versions 0.0.1 dated 2020-10-10 and 0.0.2 dated 2020-11-12

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Package incidence2 updated to version 0.2.2 with previous version 0.2.1 dated 2020-10-16

Title: Compute, Handle and Plot Incidence of Dated Events
Description: Provides functions and classes to compute, handle and visualise incidence from dated events for a defined time interval. Dates can be provided in various standard formats. The class 'incidence2' is used to store computed incidence and can be easily manipulated, subsetted, and plotted. This package is part of the RECON (<https://www.repidemicsconsortium.org/>) toolkit for outbreak analysis.
Author: Tim Taylor [aut, cre] (<https://orcid.org/0000-0002-8587-7113>), Thibaut Jombart [aut], Zhian N. Kamvar [aut] (<https://orcid.org/0000-0003-1458-7108>), Rich FitzJohn [aut], Jun Cai [ctb] (<https://orcid.org/0000-0001-9495-1226>), Sangeeta Bhatia [ctb], Jakob Schumacher [ctb], Juliet R.C. Pulliam [ctb] (<https://orcid.org/0000-0003-3314-8223>)
Maintainer: Tim Taylor <tim.taylor@hiddenelephants.co.uk>

Diff between incidence2 versions 0.2.1 dated 2020-10-16 and 0.2.2 dated 2020-11-12

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Package CGPfunctions updated to version 0.6.3 with previous version 0.6.2 dated 2020-07-16

Title: Powell Miscellaneous Functions for Teaching and Learning Statistics
Description: Miscellaneous functions useful for teaching statistics as well as actually practicing the art. They typically are not new methods but rather wrappers around either base R or other packages.
Author: Chuck Powell [aut, cre] (<https://orcid.org/0000-0002-3606-2188>)
Maintainer: Chuck Powell <ibecav@gmail.com>

Diff between CGPfunctions versions 0.6.2 dated 2020-07-16 and 0.6.3 dated 2020-11-12

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Package gfilmm updated to version 1.0.0 with previous version 0.1.0 dated 2020-11-05

Title: Generalized Fiducial Inference for Normal Linear Mixed Models
Description: Simulation of the generalized fiducial distribution for normal linear mixed models with interval data. Fiducial inference is somehow similar to Bayesian inference, in the sense that it is based on a distribution that represents the uncertainty about the parameters, like the posterior distribution in Bayesian statistics. It does not require a prior distribution, and it yields results close to frequentist results. Reference: Cisewski and Hannig (2012) <doi:10.1214/12-AOS1030>.
Author: Stéphane Laurent [aut, cre], Jessi Cisewski [aut, ctb] (author of the original Matlab code, <https://orcid.org/0000-0002-9656-2272>)
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>

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Package textshaping updated to version 0.2.0 with previous version 0.1.2 dated 2020-10-08

Title: Bindings to the 'HarfBuzz' and 'Fribidi' Libraries for Text Shaping
Description: Provides access to the text shaping functionality in the 'HarfBuzz' library and the bidirectional algorithm in the 'Fribidi' library. 'textshaping' is a low-level utility package mainly for graphic devices that expands upon the font tool-set provided by the 'systemfonts' package.
Author: Thomas Lin Pedersen [cre, aut] (<https://orcid.org/0000-0002-5147-4711>), RStudio [cph]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@rstudio.com>

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Package rNeighborQTL updated to version 1.1.1 with previous version 1.1.0 dated 2020-07-28

Title: Interval Mapping for Quantitative Trait Loci Underlying Neighbor Effects
Description: To enable quantitative trait loci mapping of neighbor effects, this package extends a single-marker regression to interval mapping. The theoretical background of the method is described in Sato et al. (2020) <doi:10.1101/2020.05.20.089474>.
Author: Yasuhiro Sato [aut, cre] (<https://orcid.org/0000-0002-6466-723X>), Kazuya Takeda [aut], Atsushi J. Nagano [aut] (<https://orcid.org/0000-0001-7891-5049>)
Maintainer: Yasuhiro Sato <sato.yasuhiro.36c@kyoto-u.jp>

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Package gert updated to version 1.0.2 with previous version 1.0.1 dated 2020-10-14

Title: Simple Git Client for R
Description: Simple git client for R based on 'libgit2' with support for SSH and HTTPS remotes. All functions in 'gert' use basic R data types (such as vectors and data-frames) for their arguments and return values. User credentials are shared with command line 'git' through the git-credential store and ssh keys stored on disk or ssh-agent. On Linux, a somewhat recent version of 'libgit2' is required; we provide a 'PPA' for older Ubuntu 'LTS' versions.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>), Jennifer Bryan [ctb] (<https://orcid.org/0000-0002-6983-2759>)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package dplyr.teradata updated to version 0.4.1 with previous version 0.3.2 dated 2019-05-10

Title: A 'Teradata' Backend for 'dplyr'
Description: A 'Teradata' backend for 'dplyr'. It makes it possible to operate 'Teradata' database <https://www.teradata.com/products-and-services/teradata-database/> in the same way as manipulating data frames with 'dplyr'.
Author: Koji Makiyama [cre, aut], Jim Hester [ctb]
Maintainer: Koji Makiyama <hoxo.smile@gmail.com>

Diff between dplyr.teradata versions 0.3.2 dated 2019-05-10 and 0.4.1 dated 2020-11-12

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Package PTXQC updated to version 1.0.7 with previous version 1.0.5 dated 2020-06-09

Title: Quality Report Generation for MaxQuant and mzTab Results
Description: Generates Proteomics (PTX) quality control (QC) reports for shotgun LC-MS data analyzed with the MaxQuant software suite (from .txt files) or mzTab files (ideally from OpenMS 'QualityControl' tool). Reports are customizable (target thresholds, subsetting) and available in HTML or PDF format. Published in J. Proteome Res., Proteomics Quality Control: Quality Control Software for MaxQuant Results (2015) <doi:10.1021/acs.jproteome.5b00780>.
Author: Chris Bielow [aut, cre], Juliane Schmachtenberg [ctb], Swenja Wagner [ctb], Patricia Scheil [ctb], Tom Waschischek [ctb], Guido Mastrobuoni [dtc, rev]
Maintainer: Chris Bielow <chris.bielow@bsc.fu-berlin.de>

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New package CTP with initial version 2.0.0
Package: CTP
Type: Package
Title: Closed Testing Procedure (CTP)
Description: This is a package for constructing hypothesis trees based on the closure principle and analysing Closed Testing Procedures (CTP) using adjusted p-values. For reference, see Marcus, R., Peritz, E, and Gabriel, K.R. (1976) <doi:10.2307/2335748> and Bauer, P (1991) <doi:10.1002/sim.4780100609>.
Version: 2.0.0
Authors@R: c( person("Paul", "Jordan", email = "paul.jordan@roche.com", role = c("aut", "cre")), person("Herpers", "Matthias", role = "aut") )
Depends: clinfun, diagram, stats
Imports: dplyr, magrittr, MASS, survival, shape, Gmisc, grid
Suggests: knitr
License: GPL (>= 2)
LazyLoad: yes
Encoding: UTF-8
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-07 18:15:33 UTC; jordanp
Author: Paul Jordan [aut, cre], Herpers Matthias [aut]
Maintainer: Paul Jordan <paul.jordan@roche.com>
Repository: CRAN
Date/Publication: 2020-11-12 10:10:02 UTC

More information about CTP at CRAN
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Package s2dv updated to version 0.1.0 with previous version 0.0.1 dated 2020-03-08

Title: A Set of Common Tools for Seasonal to Decadal Verification
Description: The advanced version of package 's2dverification'. It is intended for 'seasonal to decadal' (s2d) climate forecast verification, but it can also be used in other kinds of forecasts or general climate analysis. This package is specially designed for the comparison between the experimental and observational datasets. The functionality of the included functions covers from data retrieval, data post-processing, skill scores against observation, to visualization. Compared to 's2dverification', 's2dv' is more compatible with the package 'startR', able to use multiple cores for computation and handle multi-dimensional arrays with a higher flexibility.
Author: BSC-CNS [aut, cph], An-Chi Ho [aut, cre], Nuria Perez-Zanon [aut], Roberto Bilbao [ctb], Carlos Delgado [ctb], Andrea Manrique [ctb], Deborah Verfaillie [ctb]
Maintainer: An-Chi Ho <an.ho@bsc.es>

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New package rsetse with initial version 0.4.0
Package: rsetse
Title: Strain Elevation Tension Spring Embedding
Version: 0.4.0
Authors@R: c(person(given = "Jonathan", family = "Bourne", role = c("aut", "cre"), email = "jonathan.s.bourne@gmail.com", comment = c(ORCID = "0000-0003-2616-3716")) )
Description: An R implementation for the Strain Elevation and Tension embedding algorithm from Bourne (2020) <doi:10.1007/s41109-020-00329-4>. The package embeds graphs and networks using the Strain Elevation and Tension embedding (SETSe) algorithm. SETSe represents the network as a physical system, where edges are elastic, and nodes exert a force either up or down based on node features. SETSe positions the nodes vertically such that the tension in the edges of a node is equal and opposite to the force it exerts for all nodes in the network. The resultant structure can then be analysed by looking at the node elevation and the edge strain and tension. This algorithm works on weighted and unweighted networks as well as networks with or without explicit node features. Edge elasticity can be created from existing edge weights or kept as a constant.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dplyr, Matrix, rlang, igraph, purrr, tibble, minpack.lm, magrittr, methods, stats
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, tidyr, ggplot2, ggraph
VignetteBuilder: knitr
URL: https://github.com/JonnoB/rSETSe
BugReports: https://github.com/JonnoB/rSETSe/issues
NeedsCompilation: no
Packaged: 2020-11-07 11:50:04 UTC; jonno
Author: Jonathan Bourne [aut, cre] (<https://orcid.org/0000-0003-2616-3716>)
Maintainer: Jonathan Bourne <jonathan.s.bourne@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-12 09:30:02 UTC

More information about rsetse at CRAN
Permanent link

New package rmoo with initial version 0.1.5
Package: rmoo
Title: 'Non-Dominated Genetic Algorithms' Family
Version: 0.1.5
Authors@R: c(person(given = "Francisco", family = "Benitez", role = c("aut", "cre"), email = "benitezfj94@gmail.com"), person(given = "Diego", family = "Pinto Roa", role = "aut", email = "dpinto@pol.una.py", comment = c(ORCID = "0000-0003-2479-9876")))
Description: A multiobjective optimization package based on K. Deb's algorithm and inspired in 'GA' package by Luca Scrucca (2017) <DOI:10.32614/RJ-2017-008>. The 'rmoo' package is a framework for multi- and many-objective optimization, allowing to work with representation of real numbers, permutations and binaries, offering a high range of configurations.
License: GPL (>= 2)
Encoding: UTF-8
Language: es
LazyData: true
RoxygenNote: 7.1.1
Collate: 'associate.R' 'crowding_distance.R' 'generate_reference_points.R' 'geneticoperator.R' 'get_fixed_rowsum_integer_matrix.R' 'miscfun.R' 'niching.R' 'non_dominated_fronts.R' 'numberOrNAOrMatrix-class.R' 'nsga-class.R' 'nsga.R' 'nsga2-class.R' 'nsga2.R' 'nsga3-class.R' 'nsga3.R' 'nsgaControl.R' 'rmoo.R' 'performance_metrics.R' 'sharing.R' 'update_points.R' 'zzz.R'
Imports: stats, utils, ecr, rgl, graphics, methods, grDevices
URL: https://github.com/benitezfj/rmoo
BugReports: https://github.com/benitezfj/rmoo/issues
Suggests: testthat, covr
NeedsCompilation: no
Packaged: 2020-11-07 22:52:04 UTC; Fran
Author: Francisco Benitez [aut, cre], Diego Pinto Roa [aut] (<https://orcid.org/0000-0003-2479-9876>)
Maintainer: Francisco Benitez <benitezfj94@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-12 10:00:07 UTC

More information about rmoo at CRAN
Permanent link

Package pkgndep updated to version 1.0.1 with previous version 1.0.0 dated 2020-05-21

Title: Check the Heaviness of Package Dependencies
Description: It checks the heaviness of the packages that user's package depends on. For each package listed in the "Depends", "Imports" and "Suggests" fields in the DESCRIPTION file, it opens a new R session, loads the package and counts the number of namespaces that are loaded. The summary of the dependencies is visualized by a customized heatmap. Examples of dependency analysis can be found at <https://jokergoo.github.io/pkgndep/stat/>.
Author: Zuguang Gu
Maintainer: Zuguang Gu <z.gu@dkfz.de>

Diff between pkgndep versions 1.0.0 dated 2020-05-21 and 1.0.1 dated 2020-11-12

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Permanent link

Package MODIS updated to version 1.2.3 with previous version 1.2.2 dated 2020-06-24

Title: Acquisition and Processing of MODIS Products
Description: Download and processing functionalities for the Moderate Resolution Imaging Spectroradiometer (MODIS). The package provides automated access to the global online data archives LP DAAC (<https://lpdaac.usgs.gov/>), LAADS (<https://ladsweb.modaps.eosdis.nasa.gov/>) and NSIDC (<https://nsidc.org/>) as well as processing capabilities such as file conversion, mosaicking, subsetting and time series filtering.
Author: Matteo Mattiuzzi [aut], Florian Detsch [cre, aut]
Maintainer: Florian Detsch <fdetsch@web.de>

Diff between MODIS versions 1.2.2 dated 2020-06-24 and 1.2.3 dated 2020-11-12

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New package intensegRid with initial version 0.1.0
Package: intensegRid
Type: Package
Title: R Wrapper for the Carbon Intensity API
Version: 0.1.0
Author: Kasia Kulma <katarzyna.kulma@gmail.com>
Maintainer: Kasia Kulma <katarzyna.kulma@gmail.com>
Description: Electricity is not made equal and it vary in its carbon footprint (or carbon intensity) depending on its source. This package enables to access and query data provided by the Carbon Intensity API (<https://carbonintensity.org.uk/>). National Grid’s Carbon Intensity API provides an indicative trend of regional carbon intensity of the electricity system in Great Britain.
License: CC0
Encoding: UTF-8
LazyData: TRUE
URL: https://github.com/KKulma/intensegRid, https://kkulma.github.io/intensegRid/articles/intro-to-carbon-intensity.html
BugReports: https://github.com/KKulma/intensegRid/issues
RoxygenNote: 7.1.0
Depends: R (>= 2.10)
Imports: dplyr, httr, jsonlite, lubridate, magrittr, tidyr, tibble, rlang, purrr
Suggests: knitr, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-07 20:04:25 UTC; kkulma
Repository: CRAN
Date/Publication: 2020-11-12 10:00:11 UTC

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New package codebreaker with initial version 0.0.2
Package: codebreaker
Title: Retro Logic Game
Version: 0.0.2
Authors@R: person(given = "Roland", family = "Krasser", role = c("aut", "cre"), email = "roland.krasser@gmail.com")
Description: Logic game in the style of the early 1980s home computers that can be played in the R console. This game is inspired by Mastermind, a game that became popular in the 1970s. Can you break the code?
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/rolkra/codebreaker
Imports: beepr, cli
RoxygenNote: 7.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-11-07 18:59:27 UTC; rolkra
Author: Roland Krasser [aut, cre]
Maintainer: Roland Krasser <roland.krasser@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-12 09:50:02 UTC

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New package altfuelr with initial version 0.1.0
Package: altfuelr
Title: Provides an Interface to the NREL Alternate Fuels Locator
Version: 0.1.0
Authors@R: person(given = "Christopher", family = "Burch", role = c("aut", "cre"), email = "christopher.m.burch@gmail.com", comment = c(ORCID = "0000-0001-6934-3325"))
Description: Provides a number of functions to access the National Energy Research Laboratory Alternate Fuel Locator API <https://developer.nrel.gov/docs/transportation/alt-fuel-stations-v1/>. The Alternate Fuel Locator shows the location of alternate fuel stations in the United States and Canada. This package also includes the data from the US Department of Energy Alternate Fuel database as a data set.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.1.0)
Imports: httr, jsonlite, purrr, lubridate, dplyr, magrittr, stringr
NeedsCompilation: no
Packaged: 2020-11-07 15:52:19 UTC; chris
Author: Christopher Burch [aut, cre] (<https://orcid.org/0000-0001-6934-3325>)
Maintainer: Christopher Burch <christopher.m.burch@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-12 09:40:02 UTC

More information about altfuelr at CRAN
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Package rosetta updated to version 0.3.0 with previous version 0.2.0 dated 2019-11-27

Title: Parallel Use of Statistical Packages in Teaching
Description: When teaching statistics, it can often be desirable to uncouple the content from specific software packages. To ease such efforts, the Rosetta Stats website (<https://rosettastats.com>) allows comparing analyses in different packages. This package is the companion to the Rosetta Stats website, aiming to provide functions that produce output that is similar to output from other statistical packages, thereby facilitating 'software-agnostic' teaching of statistics.
Author: Gjalt-Jorn Peters [aut, cre] (<https://orcid.org/0000-0002-0336-9589>), Ron Pat-El [ctb] (<https://orcid.org/0000-0002-4742-0163>), Peter Verboon [ctb] (<https://orcid.org/0000-0001-8656-0890>), Melissa Gordon Wolf [ctb] (<https://orcid.org/0000-0001-7677-0659>)
Maintainer: Gjalt-Jorn Peters <gjalt-jorn@userfriendlyscience.com>

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Package QUALYPSO updated to version 1.2 with previous version 1.1 dated 2019-06-19

Title: Partitioning Uncertainty Components of an Incomplete Ensemble of Climate Projections
Description: These functions use data augmentation and Bayesian techniques for the assessment of single-member and incomplete ensembles of climate projections. It provides unbiased estimates of climate change responses of all simulation chains and of all uncertainty variables. It additionally propagates uncertainty due to missing information in the estimates. - Evin, G., B. Hingray, J. Blanchet, N. Eckert, S. Morin, and D. Verfaillie. (2019) <doi:10.1175/JCLI-D-18-0606.1>.
Author: Guillaume Evin [aut, cre]
Maintainer: Guillaume Evin <guillaume.evin@inrae.fr>

Diff between QUALYPSO versions 1.1 dated 2019-06-19 and 1.2 dated 2020-11-12

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Package pavo updated to version 2.5.0 with previous version 2.4.0 dated 2020-02-08

Title: Perceptual Analysis, Visualization and Organization of Spectral Colour Data
Description: A cohesive framework for parsing, analyzing and organizing colour from spectral data.
Author: Thomas White [aut, cre] (<https://orcid.org/0000-0002-3976-1734>), Rafael Maia [aut] (<https://orcid.org/0000-0002-7563-9795>), Hugo Gruson [aut] (<https://orcid.org/0000-0002-4094-1476>), John Endler [aut], Chad Eliason [aut], Pierre-Paul Bitton [aut] (<https://orcid.org/0000-0001-5984-2331>)
Maintainer: Thomas White <thomas.white026@gmail.com>

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Package metagam updated to version 0.2.0 with previous version 0.1.2 dated 2020-06-22

Title: Meta-Analysis of Generalized Additive Models
Description: Meta-analysis of generalized additive models and generalized additive mixed models. A typical use case is when data cannot be shared across locations, and an overall meta-analytic fit is sought. 'metagam' provides functionality for removing individual participant data from models computed using the 'mgcv' and 'gamm4' packages such that the model objects can be shared without exposing individual data. Furthermore, methods for meta-analysing these fits are provided. The implemented methods are described in Sorensen et al. (2020), <arXiv:2002.02627>, extending previous works by Schwartz and Zanobetti (2000) and Crippa et al. (2018) <doi:10.6000/1929-6029.2018.07.02.1>.
Author: Oystein Sorensen [aut, cre] (<https://orcid.org/0000-0003-0724-3542>), Andreas M. Brandmaier [aut] (<https://orcid.org/0000-0001-8765-6982>), Athanasia Mo Mowinckel [aut] (<https://orcid.org/0000-0002-5756-0223>)
Maintainer: Oystein Sorensen <oystein.sorensen@psykologi.uio.no>

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Package fastai updated to version 2.0.1 with previous version 2.0.0 dated 2020-11-11

Title: Interface to 'fastai'
Description: The 'fastai' <https://docs.fast.ai/index.html> library simplifies training fast and accurate neural networks using modern best practices. It is based on research in to deep learning best practices undertaken at 'fast.ai', including 'out of the box' support for vision, text, tabular, audio, time series, and collaborative filtering models.
Author: Turgut Abdullayev [ctb, cre, cph, aut]
Maintainer: Turgut Abdullayev <turqut.a.314@gmail.com>

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Package lefko3 updated to version 3.1.0 with previous version 3.0.0 dated 2020-10-21

Title: Historical and Ahistorical Population Projection Matrix Analysis
Description: Creates matrix population models for use in population ecological analyses. Specializes on the construction of historical matrices, which are 2d matrices comprising 3 time intervals of demographic information. Estimates both raw and function-based forms of historical and standard ahistorical matrices. Methodology based on Ehrlen (2000) <doi:10.1890/0012-9658(2000)081[1675:TDOPPD]2.0.CO;2>.
Author: Richard P. Shefferson [aut, cre] (<https://orcid.org/0000-0002-5234-3131>), Johan Ehrlen [aut] (<https://orcid.org/0000-0001-8539-8967>)
Maintainer: Richard P. Shefferson <cdorm@g.ecc.u-tokyo.ac.jp>

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Package Compositional updated to version 4.2 with previous version 4.1 dated 2020-09-19

Title: Compositional Data Analysis
Description: Regression, classification, contour plots, hypothesis testing and fitting of distributions for compositional data are some of the functions included. The standard textbook for such data is John Aitchison's (1986) "The statistical analysis of compositional data". Relevant papers include a) Tsagris M.T., Preston S. and Wood A.T.A. (2011) A data-based power transformation for compositional data. Fourth International International Workshop on Compositional Data Analysis. b) Tsagris M. (2014). The k-NN algorithm for compositional data: a revised approach with and without zero values present. Journal of Data Science, 12(3):519--534. c) Tsagris M. (2015). A novel, divergence based, regression for compositional data. Proceedings of the 28th Panhellenic Statistics Conference, 15-18 April 2015, Athens, Greece, 430--444. d) Tsagris M. (2015). Regression analysis with compositional data containing zero values. Chilean Journal of Statistics, 6(2):47--57. e) Tsagris M., Preston S. and Wood A.T.A. (2016). Improved supervised classification for compositional data using the alpha-transformation. Journal of Classification, 33(2):243--261. <doi:10.1007/s00357-016-9207-5>. f) Tsagris M., Preston S. and Wood A.T.A. (2017). Nonparametric hypothesis testing for equality of means on the simplex. Journal of Statistical Computation and Simulation, 87(2): 406--422. <doi:10.1080/00949655.2016.1216554> g) Tsagris M. and Stewart C. (2018). A Dirichlet regression model for compositional data with zeros. Lobachevskii Journal of Mathematics, 39(3): 398--412. <doi:10.1134/S1995080218030198>. h) Alenazi A. (2019). Regression for compositional data with compositional data as predictor variables with or without zero values. Journal of Data Science, 17(1): 219--238. <doi:10.6339/JDS.201901_17(1).0010>. i) Tsagris M. and Stewart C. (2020). A folded model for compositional data analysis. Australian and New Zealand Journal of Statistics, 62(2):249--277. <doi:10.1111/anzs.12289>. j) Tsagris M., Alenazi A. and Stewart C. (2020). The alpha-k-NN regression for compositional data. <arXiv:2002.05137>. We further include functions for percentages (or proportions).
Author: Michail Tsagris [aut, cre], Giorgos Athineou [aut], Abdulaziz Alenazi [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package blavaan updated to version 0.3-12 with previous version 0.3-10 dated 2020-08-03

Title: Bayesian Latent Variable Analysis
Description: Fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models.
Author: Edgar Merkle [aut, cre] (<https://orcid.org/0000-0001-7158-0653>), Yves Rosseel [aut], Ben Goodrich [aut], Mauricio Garnier-Villarreal [ctb] (<https://orcid.org/0000-0002-2951-6647>, R/blav_compare.R, R/ctr_bayes_fit.R), Terrence D. Jorgensen [ctb] (<https://orcid.org/0000-0001-5111-6773>, R/ctr_bayes_fit.R, R/ctr_ppmc.R), Huub Hoofs [ctb] (R/ctr_bayes_fit.R), Rens van de Schoot [ctb] (R/ctr_bayes_fit.R)
Maintainer: Edgar Merkle <merklee@missouri.edu>

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Package themis updated to version 0.1.3 with previous version 0.1.2 dated 2020-08-14

Title: Extra Recipes Steps for Dealing with Unbalanced Data
Description: A dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets. A dataset can be balanced by increasing the number of minority cases using SMOTE 2011 <arXiv:1106.1813>, BorderlineSMOTE 2005 <doi:10.1007/11538059_91> and ADASYN 2008 <https://ieeexplore.ieee.org/document/4633969>. Or by decreasing the number of majority cases using NearMiss 2003 <https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf> or Tomek link removal 1976 <https://ieeexplore.ieee.org/document/4309452>.
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>

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Package spatstat.data updated to version 1.5-2 with previous version 1.4-3 dated 2020-01-26

Title: Datasets for 'spatstat'
Description: Contains all the datasets for the 'spatstat' package.
Author: Adrian Baddeley [aut, cre] (<https://orcid.org/0000-0001-9499-8382>), Rolf Turner [aut] (<https://orcid.org/0000-0001-5521-5218>), Ege Rubak [aut] (<https://orcid.org/0000-0002-6675-533X>)
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package poorman updated to version 0.2.3 with previous version 0.2.2 dated 2020-10-11

Title: A Poor Man's Dependency Free Recreation of 'dplyr'
Description: A replication of key functionality from 'dplyr' and the wider 'tidyverse' using only 'base'.
Author: Nathan Eastwood [aut, cre]
Maintainer: Nathan Eastwood <nathan.eastwood@icloud.com>

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Package svars updated to version 1.3.4 with previous version 1.3.3 dated 2020-01-09

Title: Data-Driven Identification of SVAR Models
Description: Implements data-driven identification methods for structural vector autoregressive (SVAR) models. Based on an existing VAR model object (provided by e.g. VAR() from the 'vars' package), the structural impact matrix is obtained via data-driven identification techniques (i.e. changes in volatility (Rigobon, R. (2003) <doi:10.1162/003465303772815727>), patterns of GARCH (Normadin, M., Phaneuf, L. (2004) <doi:10.1016/j.jmoneco.2003.11.002>), independent component analysis (Matteson, D. S, Tsay, R. S., (2013) <doi:10.1080/01621459.2016.1150851>), least dependent innovations (Herwartz, H., Ploedt, M., (2016) <doi:10.1016/j.jimonfin.2015.11.001>), smooth transition in variances (Luetkepohl, H., Netsunajev, A. (2017) <doi:10.1016/j.jedc.2017.09.001>) or non-Gaussian maximum likelihood (Lanne, M., Meitz, M., Saikkonen, P. (2017) <doi:10.1016/j.jeconom.2016.06.002>)).
Author: Alexander Lange [aut, cre], Bernhard Dalheimer [aut], Helmut Herwartz [aut], Simone Maxand [aut], Hannes Riebl [ctb]
Maintainer: Alexander Lange <alexander.lange@uni-goettingen.de>

Diff between svars versions 1.3.3 dated 2020-01-09 and 1.3.4 dated 2020-11-12

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Package mlflow updated to version 1.12.0 with previous version 1.10.0 dated 2020-07-21

Title: Interface to 'MLflow'
Description: R interface to 'MLflow', open source platform for the complete machine learning life cycle, see <https://mlflow.org/>. This package supports installing 'MLflow', tracking experiments, creating and running projects, and saving and serving models.
Author: Matei Zaharia [aut, cre], Javier Luraschi [aut], Kevin Kuo [aut] (<https://orcid.org/0000-0001-7803-7901>), RStudio [cph]
Maintainer: Matei Zaharia <matei@databricks.com>

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Package Mercator updated to version 0.11.5 with previous version 0.11.2 dated 2020-08-24

Title: Clustering and Visualizing Distance Matrices
Description: Defines the classes used to explore, cluster and visualize distance matrices, especially those arising from binary data.
Author: Kevin R. Coombes, Caitlin E. Coombes
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package lazytrade updated to version 0.4.2 with previous version 0.4.1 dated 2020-10-22

Title: Learn Computer and Data Science using Algorithmic Trading
Description: Provide sets of functions and methods to learn and practice data science using idea of algorithmic trading. Main goal is to process information within "Decision Support System" to come up with analysis or predictions. There are several utilities such as dynamic and adaptive risk management using reinforcement learning and even functions to generate predictions of price changes using pattern recognition deep regression learning. Summary of Methods used: Awesome H2O tutorials: <https://github.com/h2oai/awesome-h2o>, Market Type research of Van Tharp Institute: <https://www.vantharp.com/>, Reinforcement Learning R package: <https://CRAN.R-project.org/package=ReinforcementLearning>.
Author: Vladimir Zhbanko
Maintainer: Vladimir Zhbanko <vladimir.zhbanko@gmail.com>

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Package DAMisc updated to version 1.6.2 with previous version 1.6.1 dated 2020-09-11

Title: Dave Armstrong's Miscellaneous Functions
Description: Miscellaneous set of functions I use in my teaching either at the University of Western Ontario or the Inter-university Consortium for Political and Social Research (ICPSR) Summer Program in Quantitative Methods. Broadly, the functions help with presentation and interpretation of LMs and GLMs, but also implement some new tools like Alternating Least Squares Optimal Scaling for dependent variables, a Bayesian analog to the ALSOS algorithm. There are also tools to help understand interactions in both LMs and binary GLMs.
Author: Dave Armstrong [aut, cre]
Maintainer: Dave Armstrong <dave@quantoid.net>

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