Tue, 13 Oct 2020

New package vein with initial version 0.9.0.1
Package: vein
Type: Package
Title: Vehicular Emissions Inventories
Version: 0.9.0.1
Date: 2020-09-23
Authors@R: c( person(given = "Sergio", family = "Ibarra-Espinosa", role = c("aut", "cre", "wdc"), email = "sergio.ibarra@usp.br", comment = c(ORCID = "0000-0002-3162-1905")))
Description: Elaboration of vehicular emissions inventories, consisting in four stages, pre-processing activity data, preparing emissions factors, estimating the emissions and post-processing of emissions in maps and databases. More details in Ibarra-Espinosa et al (2018) <doi:10.5194/gmd-11-2209-2018>. Before using VEIN you need to know the vehicular composition of your study area, in other words, the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to start with the project to download a template to create a structure of directories and scripts.
License: MIT + file LICENSE
URL: https://gitlab.com/ibarraespinosa/vein
BugReports: https://gitlab.com/ibarraespinosa/vein/-/issues
LazyData: no
Depends: R (>= 3.5.0)
Imports: sf, data.table, units, graphics, stats
Suggests: knitr, rmarkdown, testthat, covr, lwgeom, cptcity
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: yes
Config/testthat/parallel: true
Packaged: 2020-10-07 18:00:38 UTC; sergio
VignetteBuilder: knitr
Author: Sergio Ibarra-Espinosa [aut, cre, wdc] (<https://orcid.org/0000-0002-3162-1905>)
Maintainer: Sergio Ibarra-Espinosa <sergio.ibarra@usp.br>
Repository: CRAN
Date/Publication: 2020-10-13 23:50:02 UTC

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New package redist with initial version 2.0.2
Package: redist
Version: 2.0.2
Date: 2020-10-03
Title: Simulation Methods for Legislative Redistricting
Authors@R: c( person("Ben", "Fifield", email = "benfifield@gmail.com", role = c("aut", "cre")), person("Christopher T.", "Kenny", email = "christopherkenny@fas.harvard.edu", role = "aut"), person("Cory", "McCartan", email = "cmccartan@g.harvard.edu", role = "aut"), person("Alexander", "Tarr", email = "atarr@princeton.edu", role = "aut"), person("Michael", "Higgins", email = "mikehiggins@k-state.edu", role = "ctb"), person("Jun", "Kawahara", email = "jkawahara@i.kyoto-u.ac.jp", role = "aut"), person("Kosuke", "Imai", email = "imai@harvard.edu", role = "aut"))
Maintainer: Ben Fifield <benfifield@gmail.com>
Description: Enables researchers to sample redistricting plans from a pre-specified target distribution using Sequential Monte Carlo and Markov Chain Monte Carlo algorithms. The package allows for the implementation of various constraints in the redistricting process such as geographic compactness and population parity requirements. Tools for analysis such as computation of various summary statistics and plotting functionality are also included. The package implements methods described in Fifield, Higgins, Imai and Tarr (2020) <doi: 10.1080/10618600.2020.1739532>, Fifield, Imai, Kawahara, and Kenny (2020) <doi: 10.1080/2330443X.2020.1791773>, and McCartan and Imai (2020) <arXiv: 2008.06131>.
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 0.11.0), spdep, sp, sf, coda, parallel, doParallel, foreach, lwgeom, dplyr, ggplot2, magrittr, readr, servr, sys, tibble, stringr
Suggests: testthat, Rmpi, knitr, rmarkdown, igraph
LinkingTo: Rcpp, RcppArmadillo, RcppEigen, BH
License: GPL (>= 2)
SystemRequirements: gmp, libxml2, python
Packaged: 2020-10-04 16:33:44 UTC; benfifield
NeedsCompilation: yes
BugReports: https://github.com/kosukeimai/redist/issues
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Encoding: UTF-8
Author: Ben Fifield [aut, cre], Christopher T. Kenny [aut], Cory McCartan [aut], Alexander Tarr [aut], Michael Higgins [ctb], Jun Kawahara [aut], Kosuke Imai [aut]
Repository: CRAN
Date/Publication: 2020-10-13 23:50:07 UTC

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Package RcppBigIntAlgos updated to version 0.3.3 with previous version 0.3.1 dated 2020-09-28

Title: Factor Big Integers with the Parallel Quadratic Sieve
Description: Features the multiple polynomial quadratic sieve (MPQS) algorithm for factoring large integers and a vectorized factoring function that returns the complete factorization of an integer. The MPQS is based off of the seminal work of Carl Pomerance (1984) <doi:10.1007/3-540-39757-4_17> along with the modification of multiple polynomials introduced by Peter Montgomery and J. Davis as outlined by Robert D. Silverman (1987) <doi:10.1090/S0025-5718-1987-0866119-8>. Utilizes the C library GMP (GNU Multiple Precision Arithmetic) and 'RcppThread' for sieving multiple polynomials in parallel. The Pollard's rho algorithm for factoring smaller numbers is the same algorithm used by the factorize function in the 'gmp' package.
Author: Joseph Wood [aut, cre], Free Software Foundation, Inc. [cph], Mike Tryczak [ctb]
Maintainer: Joseph Wood <jwood000@gmail.com>

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Package PSPManalysis updated to version 0.3.4 with previous version 0.3.2 dated 2020-09-14

Title: Analysis of Physiologically Structured Population Models
Description: Performs demographic, bifurcation and evolutionary analysis of physiologically structured population models, which is a class of models that consistently translates continuous-time models of individual life history to the population level. A model of individual life history has to be implemented specifying the individual-level functions that determine the life history, such as development and mortality rates and fecundity. M.A. Kirkilionis, O. Diekmann, B. Lisser, M. Nool, B. Sommeijer & A.M. de Roos (2001) <doi:10.1142/S0218202501001264>. O.Diekmann, M.Gyllenberg & J.A.J.Metz (2003) <doi:10.1016/S0040-5809(02)00058-8>. A.M. de Roos (2008) <doi:10.1111/j.1461-0248.2007.01121.x>.
Author: Andre M. de Roos [aut, cre], Ernst Hairer [ctb], Gerhard Wanner [ctb]
Maintainer: Andre M. de Roos <A.M.deRoos@uva.nl>

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New package miic with initial version 1.5.3
Package: miic
Title: Learning Causal or Non-Causal Graphical Models Using Information Theory
Version: 1.5.3
Authors@R: c(person(given = "Vincent", family = "Cabeli", role = c("aut", "cre"), email = "vincent.cabeli@curie.fr"), person(given = "Honghao", family = "Li", role = "aut", email = "honghao.li@curie.fr"), person(given = "Marcel", family = "Ribeiro Dantas", role = "aut", email = "marcel.ribeiro-dantas@curie.fr"), person(given = "Nadir", family = "Sella", role = "aut", email = "nadir.sella@curie.fr"), person(given = "Louis", family = "Verny", role = "aut"), person(given = "Severine", family = "Affeldt", role = "aut"), person(given = "Hervé", family = "Isambert", role = "aut", email = "Herve.Isambert@curie.fr"))
Description: We report an information-theoretic method which learns a large class of causal or non-causal graphical models from purely observational data, while including the effects of unobserved latent variables, commonly found in many datasets. Starting from a complete graph, the method iteratively removes dispensable edges, by uncovering significant information contributions from indirect paths, and assesses edge-specific confidences from randomization of available data. The remaining edges are then oriented based on the signature of causality in observational data. This approach can be applied on a wide range of datasets and provide new biological insights on regulatory networks from single cell expression data, genomic alterations during tumor development and co-evolving residues in protein structures. For more information you can refer to: Cabeli et al. PLoS Comp. Bio. 2020 <doi:10.1371/journal.pcbi.1007866>, Verny et al. PLoS Comp. Bio. 2017 <doi:10.1371/journal.pcbi.1005662>.
License: GPL (>= 2)
URL: https://github.com/miicTeam/miic_R_package
BugReports: https://github.com/miicTeam/miic_R_package/issues
Imports: ppcor, Rcpp, scales, stats,
Suggests: igraph, grDevices, ggplot2 (>= 3.3.0), gridExtra
LinkingTo: Rcpp
SystemRequirements: C++14
LazyData: true
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-10-09 13:30:22 UTC; vcabeli
Author: Vincent Cabeli [aut, cre], Honghao Li [aut], Marcel Ribeiro Dantas [aut], Nadir Sella [aut], Louis Verny [aut], Severine Affeldt [aut], Hervé Isambert [aut]
Maintainer: Vincent Cabeli <vincent.cabeli@curie.fr>
Repository: CRAN
Date/Publication: 2020-10-13 23:50:11 UTC

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Package mexhaz updated to version 1.10 with previous version 1.9 dated 2020-10-03

Title: Mixed Effect Excess Hazard Models
Description: Fit flexible (excess) hazard regression models with the possibility of including non-proportional effects of covariables and of adding a random effect at the cluster level (corresponding to a shared frailty).
Author: Hadrien Charvat, Aurelien Belot
Maintainer: Hadrien Charvat <chadrien@ncc.go.jp>

Diff between mexhaz versions 1.9 dated 2020-10-03 and 1.10 dated 2020-10-13

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Package jipApprox updated to version 0.1.3 with previous version 0.1.2 dated 2019-02-09

Title: Approximate Inclusion Probabilities for Survey Sampling
Description: Approximate joint-inclusion probabilities in Unequal Probability Sampling, or compute Monte Carlo approximations of the first and second-order inclusion probabilities of a general sampling design as in Fattorini (2006) <doi:10.1093/biomet/93.2.269>.
Author: Roberto Sichera [aut, cre]
Maintainer: Roberto Sichera <rob.sichera@gmail.com>

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Package isotree updated to version 0.1.20 with previous version 0.1.19 dated 2020-10-11

Title: Isolation-Based Outlier Detection
Description: Fast and multi-threaded implementation of isolation forest (Liu, Ting, Zhou (2008) <doi:10.1109/ICDM.2008.17>), extended isolation forest (Hariri, Kind, Brunner (2018) <arXiv:1811.02141>), SCiForest (Liu, Ting, Zhou (2010) <doi:10.1007/978-3-642-15883-4_18>), and fair-cut forest (Cortes (2019) <arXiv:1911.06646>), for isolation-based outlier detection, clustered outlier detection, distance or similarity approximation (Cortes (2019) <arXiv:1910.12362>), and imputation of missing values (Cortes (2019) <arXiv:1911.06646>), based on random or guided decision tree splitting. Provides simple heuristics for fitting the model to categorical columns and handling missing data, and offers options for varying between random and guided splits, and for using different splitting criteria.
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

Diff between isotree versions 0.1.19 dated 2020-10-11 and 0.1.20 dated 2020-10-13

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New package hutilscpp with initial version 0.5.1
Package: hutilscpp
Title: Miscellaneous Functions in C++
Version: 0.5.1
Authors@R: person(given = "Hugh", family = "Parsonage", role = c("aut", "cre"), email = "hugh.parsonage@gmail.com")
Description: Provides utility functions that are simply, frequently used, but may require higher performance that what can be obtained from base R. Incidentally provides support for 'reverse geocoding', such as matching a point with its nearest neighbour in another array. Used as a complement to package 'hutils' by sacrificing compilation or installation time for higher running speeds. The name is a portmanteau of the author and 'Rcpp'.
URL: https://github.com/hughparsonage/hutilscpp
BugReports: https://github.com/hughparsonage/hutilscpp/issues
License: GPL-2
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp, data.table, glue, hutils, magrittr, utils
RoxygenNote: 7.1.1
Suggests: bench, parallel, testthat (>= 2.1.0), TeXCheckR, withr, covr
NeedsCompilation: yes
Packaged: 2020-10-04 06:37:26 UTC; hughp
Author: Hugh Parsonage [aut, cre]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-13 23:50:21 UTC

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Package fddm updated to version 0.2-1 with previous version 0.1-1 dated 2020-07-10

Title: Fast Implementation of the Diffusion Decision Model
Description: Provides the probability density function (PDF) of the diffusion decision model (DDM; e.g., Ratcliff & McKoon, 2008, <doi:10.1162/neco.2008.12-06-420>) with across-trial variability in the drift rate. Because the PDF of the DDM contains an infinite sum, it needs to be approximated. 'fddm' implements all published approximations (Navarro & Fuss, 2009, <doi:10.1016/j.jmp.2009.02.003>; Gondan, Blurton, & Kesselmeier, 2014, <doi:10.1016/j.jmp.2014.05.002>) plus new approximations. All approximations are implemented purely in 'C++' providing faster speed than existing packages.
Author: Kendal B. Foster [aut], Henrik Singmann [ctb, cre] (<https://orcid.org/0000-0002-4842-3657>)
Maintainer: Henrik Singmann <singmann@gmail.com>

Diff between fddm versions 0.1-1 dated 2020-07-10 and 0.2-1 dated 2020-10-13

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Package DT updated to version 0.16 with previous version 0.15 dated 2020-08-05

Title: A Wrapper of the JavaScript Library 'DataTables'
Description: Data objects in R can be rendered as HTML tables using the JavaScript library 'DataTables' (typically via R Markdown or Shiny). The 'DataTables' library has been included in this R package. The package name 'DT' is an abbreviation of 'DataTables'.
Author: Yihui Xie [aut, cre], Joe Cheng [aut], Xianying Tan [aut], JJ Allaire [ctb], Maximilian Girlich [ctb], Greg Freedman Ellis [ctb], Johannes Rauh [ctb], jQuery contributors [ctb, cph] (jQuery in htmlwidgets/lib), SpryMedia Limited [ctb, cph] (DataTables in htmlwidgets/lib), Brian Reavis [ctb, cph] (selectize.js in htmlwidgets/lib), Leon Gersen [ctb, cph] (noUiSlider in htmlwidgets/lib), Bartek Szopka [ctb, cph] (jquery.highlight.js in htmlwidgets/lib), RStudio, PBC [cph]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between DT versions 0.15 dated 2020-08-05 and 0.16 dated 2020-10-13

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 R/utils.R                                                                                 |    8 
 inst/doc/DT.html                                                                          |  129 +++++-
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 man/proxy.Rd                                                                              |    6 
 tests/testit/test-datatables.R                                                            |   10 
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Package corrgrapher updated to version 1.0.4 with previous version 1.0.3 dated 2020-10-12

Title: Explore Correlations Between Variables in a Machine Learning Model
Description: When exploring data or models we often examine variables one by one. This analysis is incomplete if the relationship between these variables is not taken into account. The 'corrgrapher' package facilitates simultaneous exploration of the Partial Dependence Profiles and the correlation between variables in the model. The package 'corrgrapher' is a part of the 'DrWhy.AI' universe.
Author: Pawel Morgen [aut, cre], Przemyslaw Biecek [aut]
Maintainer: Pawel Morgen <seriousmorgen@protonmail.com>

Diff between corrgrapher versions 1.0.3 dated 2020-10-12 and 1.0.4 dated 2020-10-13

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Package classifierplots updated to version 1.4.0 with previous version 1.3.3 dated 2017-04-06

Title: Generates a Visualization of Classifier Performance as a Grid of Diagnostic Plots
Description: Generates a visualization of binary classifier performance as a grid of diagnostic plots with just one function call. Includes ROC curves, prediction density, accuracy, precision, recall and calibration plots, all using ggplot2 for easy modification. Debug your binary classifiers faster and easier!
Author: Aaron Defazio [aut, cre], Huw Campbell [aut]
Maintainer: Aaron Defazio <aaron.defazio@gmail.com>

Diff between classifierplots versions 1.3.3 dated 2017-04-06 and 1.4.0 dated 2020-10-13

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Package bspm updated to version 0.3.6 with previous version 0.3.5 dated 2020-08-24

Title: Bridge to System Package Manager
Description: Enables binary package installations on Linux distributions. Provides functions to manage packages via the distribution's package manager. Also provides transparent integration with R's install.packages() and a fallback mechanism. When installed as a system package, interacts with the system's package manager without requiring administrative privileges via an integrated D-Bus service; otherwise, uses sudo. Currently, the following backends are supported: DNF, APT.
Author: Iñaki Ucar [aut, cph, cre] (<https://orcid.org/0000-0001-6403-5550>)
Maintainer: Iñaki Ucar <iucar@fedoraproject.org>

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New package agtboost with initial version 0.9.1
Package: agtboost
Type: Package
Title: Adaptive and Automatic Gradient Boosting Computations
Version: 0.9.1
Date: 2020-09-06
Author: Berent Ånund Strømnes Lunde
Maintainer: Berent Ånund Strømnes Lunde <lundeberent@gmail.com>
Description: Fast and automatic gradient tree boosting designed to avoid manual tuning and cross-validation by utilizing an information theoretic approach. This makes the algorithm adaptive to the dataset at hand; it is completely automatic, and with minimal worries of overfitting. Consequently, the speed-ups relative to state-of-the-art implementations can be in the thousands while mathematical and technical knowledge required on the user are minimized.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6.0)
Imports: methods, Rcpp (>= 1.0.1)
LinkingTo: Rcpp, RcppEigen
RcppModules: aGTBModule
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: yes
Packaged: 2020-10-04 16:29:20 UTC; lunde
Repository: CRAN
Date/Publication: 2020-10-13 23:50:34 UTC

More information about agtboost at CRAN
Permanent link

Package RoBMA updated to version 1.0.5 with previous version 1.0.4 dated 2020-08-07

Title: Robust Bayesian Meta-Analyses
Description: A framework for estimating ensembles of meta-analytic models (assuming either presence or absence of the effect, heterogeneity, and publication bias) and using Bayesian model averaging to combine them. The ensembles use Bayes factors to test for the presence or absence of the individual components (e.g., effect vs. no effect) and model-averages parameter estimates based on posterior model probabilities (Maier, Bartoš & Wagenmakers, 2020, <doi:10.31234/osf.io/u4cns>). The user can define a wide range of non-informative or informative priors for the effect size, heterogeneity, and weight functions. The package provides convenient functions for summary, visualizations, and fit diagnostics.
Author: František Bartoš [aut, cre] (<https://orcid.org/0000-0002-0018-5573>), Maximilian Maier [aut] (<https://orcid.org/0000-0002-9873-6096>), Eric-Jan Wagenmakers [ths] (<https://orcid.org/0000-0003-1596-1034>), Joris Goosen [ctb]
Maintainer: František Bartoš <f.bartos96@gmail.com>

Diff between RoBMA versions 1.0.4 dated 2020-08-07 and 1.0.5 dated 2020-10-13

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More information about RoBMA at CRAN
Permanent link

Package shorts updated to version 1.1.2 with previous version 1.1.1 dated 2020-09-11

Title: Short Sprints
Description: Create short sprint (<6sec) profiles using the split times or the radar gun data. Mono-exponential equation is used to estimate maximal sprinting speed (MSS), relative acceleration (TAU), and other parameters such us maximal acceleration (MAC) and maximal relative power (PMAX). These parameters can be used to predict kinematic and kinetics variables and to compare individuals. The modeling method utilized in this package is based on the works of Chelly SM, Denis C. (2001) <doi: 10.1097/00005768-200102000-00024>, Clark KP, Rieger RH, Bruno RF, Stearne DJ. (2017) <doi: 10.1519/JSC.0000000000002081>, Furusawa K, Hill AV, Parkinson JL (1927) <doi: 10.1098/rspb.1927.0035>, Greene PR. (1986) <doi: 10.1016/0025-5564(86)90063-5>, and Samozino P. (2018) <doi: 10.1007/978-3-319-05633-3_11>.
Author: Mladen Jovanovic [aut, cre], Jason D. Vescovi [dtc]
Maintainer: Mladen Jovanovic <coach.mladen.jovanovic@gmail.com>

Diff between shorts versions 1.1.1 dated 2020-09-11 and 1.1.2 dated 2020-10-13

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Package neonstore updated to version 0.3.1 with previous version 0.3.0 dated 2020-10-06

Title: NEON Data Store
Description: The National Ecological Observatory Network (NEON) provides access to its numerous data products through its REST API, <https://data.neonscience.org/data-api/>. This package provides a high-level user interface for downloading and storing NEON data products. While each of NEON data products consist of hundreds or thousands of individual files. Unlike 'neonUtilities', this package will avoid repeated downloading, provides persistent storage, and improves performance. This package does not provide expose interactions with the individual low-level NEON API endpoints.
Author: Carl Boettiger [aut, cre] (<https://orcid.org/0000-0002-1642-628X>), Quinn Thomas [aut] (<https://orcid.org/0000-0003-1282-7825>), Christine Laney [aut] (<https://orcid.org/0000-0002-4944-2083>), Claire Lunch [aut] (<https://orcid.org/0000-0001-8753-6593>), Noam Ross [ctb] (<https://orcid.org/0000-0002-2136-0000>)
Maintainer: Carl Boettiger <cboettig@gmail.com>

Diff between neonstore versions 0.3.0 dated 2020-10-06 and 0.3.1 dated 2020-10-13

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Permanent link

Package lessR updated to version 3.9.8 with previous version 3.9.7 dated 2020-09-23

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

Diff between lessR versions 3.9.7 dated 2020-09-23 and 3.9.8 dated 2020-10-13

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More information about lessR at CRAN
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Package ff updated to version 4.0.4 with previous version 4.0.2 dated 2020-07-30

Title: Memory-Efficient Storage of Large Data on Disk and Fast Access Functions
Description: The ff package provides data structures that are stored on disk but behave (almost) as if they were in RAM by transparently mapping only a section (pagesize) in main memory - the effective virtual memory consumption per ff object. ff supports R's standard atomic data types 'double', 'logical', 'raw' and 'integer' and non-standard atomic types boolean (1 bit), quad (2 bit unsigned), nibble (4 bit unsigned), byte (1 byte signed with NAs), ubyte (1 byte unsigned), short (2 byte signed with NAs), ushort (2 byte unsigned), single (4 byte float with NAs). For example 'quad' allows efficient storage of genomic data as an 'A','T','G','C' factor. The unsigned types support 'circular' arithmetic. There is also support for close-to-atomic types 'factor', 'ordered', 'POSIXct', 'Date' and custom close-to-atomic types. ff not only has native C-support for vectors, matrices and arrays with flexible dimorder (major column-order, major row-order and generalizations for arrays). There is also a ffdf class not unlike data.frames and import/export filters for csv files. ff objects store raw data in binary flat files in native encoding, and complement this with metadata stored in R as physical and virtual attributes. ff objects have well-defined hybrid copying semantics, which gives rise to certain performance improvements through virtualization. ff objects can be stored and reopened across R sessions. ff files can be shared by multiple ff R objects (using different data en/de-coding schemes) in the same process or from multiple R processes to exploit parallelism. A wide choice of finalizer options allows to work with 'permanent' files as well as creating/removing 'temporary' ff files completely transparent to the user. On certain OS/Filesystem combinations, creating the ff files works without notable delay thanks to using sparse file allocation. Several access optimization techniques such as Hybrid Index Preprocessing and Virtualization are implemented to achieve good performance even with large datasets, for example virtual matrix transpose without touching a single byte on disk. Further, to reduce disk I/O, 'logicals' and non-standard data types get stored native and compact on binary flat files i.e. logicals take up exactly 2 bits to represent TRUE, FALSE and NA. Beyond basic access functions, the ff package also provides compatibility functions that facilitate writing code for ff and ram objects and support for batch processing on ff objects (e.g. as.ram, as.ff, ffapply). ff interfaces closely with functionality from package 'bit': chunked looping, fast bit operations and coercions between different objects that can store subscript information ('bit', 'bitwhich', ff 'boolean', ri range index, hi hybrid index). This allows to work interactively with selections of large datasets and quickly modify selection criteria. Further high-performance enhancements can be made available upon request.
Author: Daniel Adler [aut], Christian Gläser [aut], Oleg Nenadic [aut], Jens Oehlschlägel [aut, cre], Martijn Schuemie [aut], Walter Zucchini [aut]
Maintainer: Jens Oehlschlägel <Jens.Oehlschlaegel@truecluster.com>

Diff between ff versions 4.0.2 dated 2020-07-30 and 4.0.4 dated 2020-10-13

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Package cdcfluview updated to version 0.9.2 with previous version 0.9.1 dated 2020-04-02

Title: Retrieve Flu Season Data from the United States Centers for Disease Control and Prevention ('CDC') 'FluView' Portal
Description: The 'U.S.' Centers for Disease Control and Prevention (CDC) maintain a portal <https://gis.cdc.gov/grasp/fluview/fluportaldashboard.html> for accessing state, regional and national influenza statistics as well as mortality surveillance data. The web interface makes it difficult and time-consuming to select and retrieve influenza data. Tools are provided to access the data provided by the portal's underlying 'API'.
Author: Bob Rudis [aut, cre] (<https://orcid.org/0000-0001-5670-2640>), Craig McGowan [ctb] (<https://orcid.org/0000-0002-6298-0185>), JJ Chen [ctb] (<https://orcid.org/0000-0001-8482-8398>), Sebastian Meyer [ctb] (<https://orcid.org/0000-0002-1791-9449>), James Turtle [ctb] (<https://orcid.org/0000-0003-0735-7769>), Andrew Bates [ctb]
Maintainer: Bob Rudis <bob@rud.is>

Diff between cdcfluview versions 0.9.1 dated 2020-04-02 and 0.9.2 dated 2020-10-13

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Permanent link

New package vfinputs with initial version 0.1.0
Package: vfinputs
Type: Package
Title: Visual Filter Inputs for Shiny
Version: 0.1.0
Date: 2020-09-28
Authors@R: c( person("Rafael", "Henkin", email = "r.henkin@qmul.ac.uk", role = c("cre", "aut"), comment = c(ORCID = "0000-0002-5511-5230")), person("Mike", "Bostock", role = c("cph"), comment = "D3.js library, https://d3js.org") )
Depends: R (>= 3.0.2)
Imports: shiny, htmltools, jsonlite, scales
Suggests: RColorBrewer, testthat
Maintainer: Rafael Henkin <r.henkin@qmul.ac.uk>
Description: A set of visual input controls for Shiny apps to facilitate filtering across multiple outputs.
License: GPL-3
LazyData: TRUE
RoxygenNote: 7.1.1
Encoding: UTF-8
URL: https://github.com/rhenkin/vfinputs
BugReports: https://github.com/rhenkin/vfinputs/issues
NeedsCompilation: no
Packaged: 2020-10-02 09:42:34 UTC; rafael
Author: Rafael Henkin [cre, aut] (<https://orcid.org/0000-0002-5511-5230>), Mike Bostock [cph] (D3.js library, https://d3js.org)
Repository: CRAN
Date/Publication: 2020-10-13 15:20:03 UTC

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New package survivalMPLdc with initial version 0.1.0
Package: survivalMPLdc
Type: Package
Title: Penalised Likelihood for Survival Analysis with Dependent Censoring
Version: 0.1.0
Authors@R: c(person("Jing", "Xu", role = c("aut", "cre"), email = "kenny.xu@duke-nus.edu.sg"), person("Jun", "Ma", role = c("aut"), email = "jun.ma@mq.edu.au"), person("Thomas", "Fung", role = c("aut"), email = "thomas.fung.dr@gmail.com", comment =c(ORCID = "0000-0003-2601-0728")))
Description: Fitting Cox proportional hazard model under dependent right censoring using copula and maximum penalised likelihood methods.
Depends: R (>= 3.5)
License: GPL-3
Imports: copula, stats, methods, splines2, survival, graphics, matrixcalc
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, knitr, rmarkdown
Language: en-GB
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-10-07 07:02:31 UTC; kennyxu1983hotmail.com
Author: Jing Xu [aut, cre], Jun Ma [aut], Thomas Fung [aut] (<https://orcid.org/0000-0003-2601-0728>)
Maintainer: Jing Xu <kenny.xu@duke-nus.edu.sg>
Repository: CRAN
Date/Publication: 2020-10-13 15:10:02 UTC

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Package pagedown updated to version 0.12 with previous version 0.11 dated 2020-09-09

Title: Paginate the HTML Output of R Markdown with CSS for Print
Description: Use the paged media properties in CSS and the JavaScript library 'paged.js' to split the content of an HTML document into discrete pages. Each page can have its page size, page numbers, margin boxes, and running headers, etc. Applications of this package include books, letters, reports, papers, business cards, resumes, and posters.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Romain Lesur [aut, cph] (<https://orcid.org/0000-0002-0721-5595>), Brent Thorne [aut] (<https://orcid.org/0000-0002-1099-3857>), Xianying Tan [aut] (<https://orcid.org/0000-0002-6072-3521>), Christophe Dervieux [ctb] (<https://orcid.org/0000-0003-4474-2498>), Atsushi Yasumoto [ctb] (<https://orcid.org/0000-0002-8335-495X>), RStudio, PBC [cph], Adam Hyde [ctb] (paged.js in resources/js/), Min-Zhong Lu [ctb] (resume.css in resources/css/), Zulko [ctb] (poster-relaxed.css in resources/css/)
Maintainer: Yihui Xie <xie@yihui.name>

Diff between pagedown versions 0.11 dated 2020-09-09 and 0.12 dated 2020-10-13

 DESCRIPTION         |    6 +++---
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Package GLMMadaptive updated to version 0.7-15 with previous version 0.7-0 dated 2020-06-25

Title: Generalized Linear Mixed Models using Adaptive Gaussian Quadrature
Description: Fits generalized linear mixed models for a single grouping factor under maximum likelihood approximating the integrals over the random effects with an adaptive Gaussian quadrature rule; Jose C. Pinheiro and Douglas M. Bates (1995) <doi:10.1080/10618600.1995.10474663>.
Author: Dimitris Rizopoulos [aut, cre] (<https://orcid.org/0000-0001-9397-0900>)
Maintainer: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>

Diff between GLMMadaptive versions 0.7-0 dated 2020-06-25 and 0.7-15 dated 2020-10-13

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New package SE.EQ with initial version 1.0
Package: SE.EQ
Type: Package
Title: SE-Test for Equivalence
Version: 1.0
Date: 2020-10-06
Author: Thomas Hoffelder
Maintainer: Thomas Hoffelder <thomas.hoffelder@boehringer-ingelheim.com>
Description: Implements the SE-test for equivalence according to Hoffelder et al. (2015) <DOI:10.1080/10543406.2014.920344>. The SE-test for equivalence is a multivariate two-sample equivalence test. Distance measure of the test is the sum of standardized differences between the expected values or in other words: the sum of effect sizes (SE) of all components of the two multivariate samples. The test is an asymptotically valid test for normally distributed data (see Hoffelder et al.,2015). The function SE.EQ() implements the SE-test for equivalence according to Hoffelder et al. (2015). The function SE.EQ.dissolution.profiles() implements a variant of the SE-test for equivalence for similarity analyses of dissolution profiles as mentioned in Suarez-Sharp et al.(2020) <DOI:10.1208/s12248-020-00458-9>). The equivalence margin used in SE.EQ.dissolution.profiles() is analogically defined as for the T2EQ approach according to Hoffelder (2019) <DOI:10.1002/bimj.201700257>) by means of a systematic shift in location of 10 [\% of label claim] of both dissolution profile populations. SE.EQ.dissolution.profiles() checks whether the weighted mean of the differences of the expected values of both dissolution profile populations is statistically significantly smaller than 10 [\% of label claim]. The weights are built up by the inverse variances.
Imports: MASS
License: GPL-3
NeedsCompilation: no
Packaged: 2020-10-06 11:04:08 UTC; hoffelde
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2020-10-13 14:10:05 UTC

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New package giscoR with initial version 0.1.0
Package: giscoR
Type: Package
Title: Download Geospatial Data from GISCO API - Eurostat
Version: 0.1.0
Authors@R: c( person("Diego", "Hernangómez", role=c("aut", "cre"), email="diego.hernangomezherrero@gmail.com", comment=c(ORCID="0000-0001-8457-4658")))
Description: Tools to download data from the GISCO (Geographic Information System of the Commission) Eurostat database <https://ec.europa.eu/eurostat/web/gisco>. This package is in no way officially related to or endorsed by Eurostat.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
BugReports: https://github.com/dieghernan/giscoR/issues
URL: https://dieghernan.github.io/giscoR/, https://github.com/dieghernan/giscoR
Depends: R (>= 3.3.0)
Imports: sf (>= 0.9), countrycode (>= 1.2.0), geojsonsf (>= 2.0)
Suggests: cartography (>= 2.0.0), colorspace, eurostat, lwgeom, tinytest, knitr, rmarkdown
Date: 2020-10-05
VignetteBuilder: knitr
SystemRequirements: GDAL (>= 2.0.1), GEOS (>= 3.4.0), PROJ.4 (>= 4.8.0)
NeedsCompilation: no
Packaged: 2020-10-06 12:02:04 UTC; rstudio-user
Author: Diego Hernangómez [aut, cre] (<https://orcid.org/0000-0001-8457-4658>)
Maintainer: Diego Hernangómez <diego.hernangomezherrero@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-13 14:30:02 UTC

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New package fxTWAPLS with initial version 0.0.2
Package: fxTWAPLS
Title: An Improved Version of WA-PLS
Version: 0.0.2
Authors@R: c( person(given = "Mengmeng", family = "Liu", role = c("aut"), email = "m.liu18@imperial.ac.uk", comment = c(ORCID = "0000-0001-6250-0148")), person(given = "Roberto", family = "Villegas-Diaz", role = c("aut", "cre"), email = "r.villegas-diaz@reading.ac.uk", comment = c(ORCID = "0000-0001-5036-8661")), person("SPECIAL Research Group @ University of Reading", role = c("cph")))
Description: The goal of this package is to provide an improved version of WA-PLS (Weighted Averaging Partial Least Squares) by including the tolerances of taxa and the frequency of the sampled climate variable. This package also provides a way of leave-out cross-validation that removes both the test site and sites that are both geographically close and climatically close for each cycle, to avoid the risk of pseudo-replication.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/special-uor/fxTWAPLS, https://special-uor.github.io/fxTWAPLS/, https://research.reading.ac.uk/palaeoclimate/
BugReports: https://github.com/special-uor/fxTWAPLS/issues
Imports: doParallel, foreach, geosphere, ggplot2, MASS, matrixStats, parallel, tictoc
Suggests: badger, hexSticker, knitr, kableExtra, pkgdown, rmarkdown, scales, testthat
Depends: R (>= 3.6)
RoxygenNote: 7.1.1
Language: en-GB
NeedsCompilation: no
Packaged: 2020-10-06 14:05:41 UTC; roberto.villegas-diaz
Author: Mengmeng Liu [aut] (<https://orcid.org/0000-0001-6250-0148>), Roberto Villegas-Diaz [aut, cre] (<https://orcid.org/0000-0001-5036-8661>), SPECIAL Research Group @ University of Reading [cph]
Maintainer: Roberto Villegas-Diaz <r.villegas-diaz@reading.ac.uk>
Repository: CRAN
Date/Publication: 2020-10-13 14:50:03 UTC

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New package ecochange with initial version 1.3
Package: ecochange
Type: Package
Title: Integrating Ecological Remote Sensing Data to Derive EBV Metrics
Version: 1.3
Date: 2020-10-06
Authors@R: c(person(given = "Wilson", family = "Lara Henao", role = c("aut", "cre"), email = "wilarhen@temple.edu"), person(given = "Victor", family = "Gutierrez-Velez", role = "aut"))
Maintainer: Wilson Lara Henao <wilarhen@temple.edu>
Description: Essential Biodiversity Variables (EBV) are state variables with dimensions on time, space, and biological organization that can document biodiversity change. Freely available remote sensing products (RSP) are downloaded and integrated with data for national or regional domains to derive EBV metrics related to horizontal ecosystem extent, forest fragmentation, species distribution ranges, among others. To process the spatial data, the users must provide at least a region of interest (polygon or geographic administrative unit). Downloadable RSP include Global Surface Water (Peckel et al., 2016) <doi:10.1038/nature20584>, Forest Change (Hansen et al., 2013) <doi:10.1126/science.1244693>, and Continuous Tree Cover data (Sexton et al., 2013) <doi:10.1080/17538947.2013.786146>.
License: GPL-3
Depends: R (>= 3.5.0), raster, rgeos
Imports: readr,rgdal,parallel,curl,gdalUtils,ggplot2,graphics,rvest,stats,landscapemetrics,sp,tibble,utils,xml2,dplyr,sf,R.utils,httr,getPass,methods,rasterVis,viridis,rlang,forcats,lattice
Encoding: latin1
LazyData: TRUE
NeedsCompilation: no
Packaged: 2020-10-06 22:13:33 UTC; wilar
Author: Wilson Lara Henao [aut, cre], Victor Gutierrez-Velez [aut]
Repository: CRAN
Date/Publication: 2020-10-13 15:00:02 UTC

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Package corto updated to version 1.1.2 with previous version 1.1.0 dated 2020-06-27

Title: Inference of Gene Regulatory Networks
Description: We present 'corto' (Correlation Tool), a simple package to infer gene regulatory networks and visualize master regulators from gene expression data using DPI (Data Processing Inequality) and bootstrapping to recover edges. An initial step is performed to calculate all significant edges between a list of source nodes (centroids) and target genes. Then all triplets containing two centroids and one target are tested in a DPI step which removes edges. A bootstrapping process then calculates the robustness of the network, eventually re-adding edges previously removed by DPI. The algorithm has been optimized to run outside a computing cluster, using a fast correlation implementation. The package finally provides functions to calculate network enrichment analysis from RNA-Seq and ATAC-Seq signatures as described in the article by Giorgi lab (2020) <doi:10.1093/bioinformatics/btaa223>.
Author: Federico M. Giorgi [aut, cre], Daniele Mercatelli [ctb], Gonzalo Lopez-Garcia [ctb]
Maintainer: Federico M. Giorgi <federico.giorgi@gmail.com>

Diff between corto versions 1.1.0 dated 2020-06-27 and 1.1.2 dated 2020-10-13

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 11 files changed, 116 insertions(+), 27 deletions(-)

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New package RRBoost with initial version 0.1
Package: RRBoost
Type: Package
Title: A Robust Boosting Algorithm
Version: 0.1
Date: 2020-09-28
Authors@R: c(person("Xiaomeng", "Ju", role=c("aut", "cre"), email="xiaomeng.ju@stat.ubc.ca"), person("Matias", "Salibian-Barrera", role = c("aut"), email = "matias@stat.ubc.ca") )
Description: An implementation of robust boosting algorithms for regression in R. This includes the RRBoost method proposed in the paper "Robust Boosting for Regression Problems" (Ju X and Salibian-Barrera M. 2020) <doi:10.1016/j.csda.2020.107065> (to appear in Computational Statistics and Data Science). It also implements previously proposed boosting algorithms in the simulation section of the paper: L2Boost, LADBoost, MBoost (Friedman, J. H. (2001) <doi:10.1214/aos/1013203451>) and Robloss (Lutz et al. (2008) <doi:10.1016/j.csda.2007.11.006>).
Depends: R (>= 3.5.0)
Imports: stats, rpart, RobStatTM
License: GPL (>= 3)
LazyData: True
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-10-05 16:10:45 UTC; JasmineJu
Author: Xiaomeng Ju [aut, cre], Matias Salibian-Barrera [aut]
Maintainer: Xiaomeng Ju <xiaomeng.ju@stat.ubc.ca>
Repository: CRAN
Date/Publication: 2020-10-13 13:10:06 UTC

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New package rapsimng with initial version 0.1.0
Package: rapsimng
Type: Package
Title: APSIM Next Generation
Version: 0.1.0
Authors@R: person("Bangyou", "Zheng", email = "bangyou.zheng@csiro.au", role = c("aut", "cre"))
Description: The Agricultural Production Systems sIMulator ('APSIM') is a widely used to simulate the agricultural systems for multiple crops. This package is designed to create, modify and run 'apsimx' files in the 'APSIM' Next Generation <https://www.apsim.info/>.
License: MIT + file LICENSE
URL: https://rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng
BugReports: https://github.com/byzheng/rapsimng/issues
Encoding: UTF-8
LazyData: true
Imports: jsonlite, xml2, tibble, magrittr, tidyr, dplyr, rlang
RoxygenNote: 7.1.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-10-06 04:52:56 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <bangyou.zheng@csiro.au>
Repository: CRAN
Date/Publication: 2020-10-13 14:00:02 UTC

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New package MMDCopula with initial version 0.1.0
Package: MMDCopula
Type: Package
Title: Robust Estimation of Copulas by Maximum Mean Discrepancy
Version: 0.1.0
Description: Provides functions for the robust estimation of parametric families of copulas using minimization of the Maximum Mean Discrepancy, following the article Alquier, Chérief-Abdellatif, Derumigny and Fermanian (2020) <arXiv:2010.00408>.
Authors@R: c( person("Alexis", "Derumigny",, email = "a.f.f.derumigny@utwente.nl", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-6163-8097")), person("Pierre", "Alquier",, email = "pierre.alquier.stat@gmail.com", role = "aut", comment = c(ORCID = "0000-0003-4249-7337")), person("Jean-David", "Fermanian",, email = "Jean-David.Fermanian@ensae.fr", role = "aut", comment = c(ORCID = "0000-0001-5960-5555")), person("Badr-Eddine", "Chérief-Abdellatif",, email = "badr.eddine.cherief.abdellatif@gmail.com", role = "aut") )
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.6.0)
Imports: VineCopula, cubature, pcaPP, randtoolbox,
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
BugReports: https://github.com/AlexisDerumigny/MMDCopula/issues
NeedsCompilation: no
Packaged: 2020-10-06 07:36:00 UTC; Alexis
Author: Alexis Derumigny [aut, cre] (<https://orcid.org/0000-0002-6163-8097>), Pierre Alquier [aut] (<https://orcid.org/0000-0003-4249-7337>), Jean-David Fermanian [aut] (<https://orcid.org/0000-0001-5960-5555>), Badr-Eddine Chérief-Abdellatif [aut]
Maintainer: Alexis Derumigny <a.f.f.derumigny@utwente.nl>
Repository: CRAN
Date/Publication: 2020-10-13 14:00:06 UTC

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New package gsisdecoder with initial version 0.0.1
Package: gsisdecoder
Title: High Efficient Functions to Decode NFL Player IDs
Version: 0.0.1
Authors@R: person(given = "Sebastian", family = "Carl", role = c("aut", "cre"), email = "mrcaseb@gmail.com")
Description: A set of high efficient functions to decode identifiers of National Football League players.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
LinkingTo: Rcpp
Imports: Rcpp
URL: https://github.com/mrcaseb/gsisdecoder
BugReports: https://github.com/mrcaseb/gsisdecoder/issues
Suggests: testthat, covr
NeedsCompilation: yes
Packaged: 2020-10-05 20:07:29 UTC; S.Carl
Author: Sebastian Carl [aut, cre]
Maintainer: Sebastian Carl <mrcaseb@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-13 13:50:03 UTC

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New package dadjoke with initial version 1.0
Package: dadjoke
Title: Displays a Dad Joke
Version: 1.0
Authors@R: person("Shambhavi", "Priyam", email = "priyam@coll.mpg.de", role = c("aut", "cre"))
Maintainer: Shambhavi Priyam <priyam@coll.mpg.de>
Description: Displays a terrible joke, the kind only dads crack.
Depends: R (>= 3.0.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-10-06 00:36:26 UTC; priyam
Author: Shambhavi Priyam [aut, cre]
Repository: CRAN
Date/Publication: 2020-10-13 13:50:06 UTC

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New package CompModels with initial version 0.1.0
Package: CompModels
Title: Pseudo Computer Models for Optimization
Version: 0.1.0
Authors@R: person(given = "Tony", family = "Pourmohamad", role = c("aut", "cre"), email = "tpourmohamad@gmail.com")
Description: A suite of computer model test functions that can be used to test and evaluate algorithms for Bayesian (also known as sequential) optimization. Some of the functions have known functional forms, however, most are intended to serve as black-box functions where evaluation requires running computer code that reveals little about the functional forms of the objective and/or constraints. The primary goal of the package is to provide users (especially those who do not have access to real computer models) a source of reproducible and shareable examples that can be used for benchmarking algorithms. The package is a living repository, and so more functions will be added over time. For function suggestions, please do contact the author of the package.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-10-06 06:11:52 UTC; pourmoht
Author: Tony Pourmohamad [aut, cre]
Maintainer: Tony Pourmohamad <tpourmohamad@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-13 14:00:09 UTC

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Package callr updated to version 3.5.1 with previous version 3.5.0 dated 2020-10-08

Title: Call R from R
Description: It is sometimes useful to perform a computation in a separate R process, without affecting the current R process at all. This packages does exactly that.
Author: Gábor Csárdi [aut, cre, cph] (<https://orcid.org/0000-0001-7098-9676>), Winston Chang [aut], RStudio [cph, fnd], Mango Solutions [cph, fnd]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between callr versions 3.5.0 dated 2020-10-08 and 3.5.1 dated 2020-10-13

 DESCRIPTION                              |    6 -
 MD5                                      |   10 +-
 NEWS.md                                  |    5 +
 R/r-session.R                            |  112 +++++++++++++++++++++++++++----
 R/script.R                               |    2 
 tests/testthat/test-r-session-messages.R |   33 +++++++++
 6 files changed, 146 insertions(+), 22 deletions(-)

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New package BeastJar with initial version 1.10.5
Package: BeastJar
Type: Package
Title: JAR Dependency for MCMC Using 'BEAST'
Version: 1.10.5
Authors@R: c( person("Marc A.", "Suchard", email = "msuchard@ucla.edu", role = c("aut","cre","cph")), person("Andrew", "Rambaut", role = "cph"), person("Alexei J.", "Drummond", role = "cph") )
Description: Provides JAR to perform Markov chain Monte Carlo (MCMC) inference using the popular Bayesian Evolutionary Analysis by Sampling Trees 'BEAST' software library of Suchard et al (2018) <doi:10.1093/ve/vey016>. 'BEAST' supports auto-tuning Metropolis-Hastings, slice, Hamiltonian Monte Carlo and Sequential Monte Carlo sampling for a large variety of composable standard and phylogenetic statistical models using high performance computing. By placing the 'BEAST' JAR in this package, we offer an efficient distribution system for 'BEAST' use by other R packages using CRAN.
License: Apache License 2.0
Encoding: UTF-8
LazyData: true
Imports: rJava
URL: https://github.com/beast-dev/BeastJar
Copyright: See file COPYRIGHTS
RoxygenNote: 7.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2020-10-06 01:03:35 UTC; msuchard
Author: Marc A. Suchard [aut, cre, cph], Andrew Rambaut [cph], Alexei J. Drummond [cph]
Maintainer: Marc A. Suchard <msuchard@ucla.edu>
Repository: CRAN
Date/Publication: 2020-10-13 13:50:08 UTC

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New package sdmpredictors with initial version 0.2.9
Package: sdmpredictors
Type: Package
Title: Species Distribution Modelling Predictor Datasets
Version: 0.2.9
Date: 2020-10-09
Depends: R (>= 3.2.5), raster (>= 2.5-8), rgdal (>= 1.1-10)
Imports: R.utils (>= 2.4.0), stats, utils, RCurl
Authors@R: c( person("Samuel", "Bosch", email = "mail@samuelbosch.com", role = c("aut")), person("Lennert", "Tyberghein", email = "lennert.tyberghein@vliz.be", role = c("ctb")), person("Olivier", "De Clerck", email = "olivier.declerck@ugent.be", role = c("ctb")), person("Salvador", "Fernandez", email = "salvador.fernandez@vliz.be", role = c("ctb", "cre")), person("Lennert", "Schepers", email = "lennert.schepers@vliz.be", role = c("ctb")))
Description: Terrestrial and marine predictors for species distribution modelling from multiple sources, including WorldClim <https://www.worldclim.org/>,, ENVIREM <https://envirem.github.io/>, Bio-ORACLE <https://bio-oracle.org/> and MARSPEC <http://www.marspec.org/>.
License: MIT + file LICENSE
URL: https://www.samuelbosch.com/p/sdmpredictors.html
BugReports: https://github.com/lifewatch/sdmpredictors/issues
LazyData: true
Suggests: ggplot2, reshape2, testthat, knitr, rmarkdown
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-10-09 14:59:23 UTC; salvadorf
Author: Samuel Bosch [aut], Lennert Tyberghein [ctb], Olivier De Clerck [ctb], Salvador Fernandez [ctb, cre], Lennert Schepers [ctb]
Maintainer: Salvador Fernandez <salvador.fernandez@vliz.be>
Repository: CRAN
Date/Publication: 2020-10-13 12:50:02 UTC

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New package rmangal with initial version 2.0.2
Package: rmangal
Type: Package
Title: 'Mangal' Client
Version: 2.0.2
Authors@R: c( person(given = "Steve", family = "Vissault", comment = c(ORCID = "0000-0002-0866-4376"), email = "s.vissault@yahoo.fr", role = c("aut", "cre")), person(given = "Kevin", family = "Cazelles", comment = c(ORCID = "0000-0001-6619-9874"), email = "kcazelle@uoguelph.ca", role = c("aut","ctb")), person(given = "Gabriel", family = "Bergeron", email = "gabriel.bergeron3@usherbrooke.ca", role = c("aut","ctb")), person(given = "Benjamin", family = "Mercier", email = "Benjamin.B.Mercier@usherbrooke.ca", role = c("aut","ctb")), person(given = "Clément", family = "Violet", email = "Clement.Violet@etudiant.univ-brest.fr", role = c("aut","ctb")), person(given = "Dominique", family = "Gravel", email = "dominique.gravel@usherbrooke.ca", role = c("aut")), person(given = "Timothée", family = "Poisot", email = "timothee.poisot@umontreal.ca", role = c("aut")), person(given = "Thomas Lin", family = "Pedersen", role = "rev", comment = c(ORCID = "0000-0002-5147-4711")), person(given = "Anna Willoughby", role = "rev", comment = c(ORCID = "0000-0002-0504-0605")) )
Description: An interface to the 'Mangal' database - a collection of ecological networks. This package includes functions to work with the 'Mangal RESTful API' methods (<https://mangal.io/doc/api/>).
URL: https://docs.ropensci.org/rmangal/, https://mangal.io, https://github.com/ropensci/rmangal
BugReports: https://github.com/ropensci/rmangal/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: httr (>= 1.3.1), igraph, jsonlite (>= 1.5), memoise, purrr
RoxygenNote: 7.1.1
Suggests: ggraph (>= 2.0.0), knitr, magrittr, mapview, rmarkdown, sf, spelling, taxize, tidygraph, testthat, tibble, USAboundaries, webshot,
VignetteBuilder: knitr
X-schema.org-applicationCategory: ecologicalNetworks
X-schema.org-keywords: ecology, networks, food webs, interactions, data publications, open access
X-schema.org-isPartOf: https://ropensci.org
NeedsCompilation: no
Packaged: 2020-10-12 16:25:20 UTC; steve
Author: Steve Vissault [aut, cre] (<https://orcid.org/0000-0002-0866-4376>), Kevin Cazelles [aut, ctb] (<https://orcid.org/0000-0001-6619-9874>), Gabriel Bergeron [aut, ctb], Benjamin Mercier [aut, ctb], Clément Violet [aut, ctb], Dominique Gravel [aut], Timothée Poisot [aut], Thomas Lin Pedersen [rev] (<https://orcid.org/0000-0002-5147-4711>), Anna Willoughby [rev] (<https://orcid.org/0000-0002-0504-0605>)
Maintainer: Steve Vissault <s.vissault@yahoo.fr>
Repository: CRAN
Date/Publication: 2020-10-13 12:30:02 UTC

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Package rgdal updated to version 1.5-18 with previous version 1.5-17 dated 2020-10-08

Title: Bindings for the 'Geospatial' Data Abstraction Library
Description: Provides bindings to the 'Geospatial' Data Abstraction Library ('GDAL') (>= 1.11.4) and access to projection/transformation operations from the 'PROJ' library. Use is made of classes defined in the 'sp' package. Raster and vector map data can be imported into R, and raster and vector 'sp' objects exported. The 'GDAL' and 'PROJ' libraries are external to the package, and, when installing the package from source, must be correctly installed first; it is important that 'GDAL' < 3 be matched with 'PROJ' < 6. From 'rgdal' 1.5-8, installed with to 'GDAL' >=3, 'PROJ' >=6 and 'sp' >= 1.4, coordinate reference systems use 'WKT2_2019' strings, not 'PROJ' strings. 'Windows' and 'macOS' binaries (including 'GDAL', 'PROJ' and their dependencies) are provided on 'CRAN'.
Author: Roger Bivand [cre, aut] (<https://orcid.org/0000-0003-2392-6140>), Tim Keitt [aut], Barry Rowlingson [aut, ctb], Edzer Pebesma [ctb], Michael Sumner [ctb], Robert Hijmans [ctb], Even Rouault [cph, ctb], Frank Warmerdam [cph, ctb], Jeroen Ooms [ctb], Colin Rundel [ctb]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

Diff between rgdal versions 1.5-17 dated 2020-10-08 and 1.5-18 dated 2020-10-13

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Package plm updated to version 2.2-5 with previous version 2.2-4 dated 2020-08-31

Title: Linear Models for Panel Data
Description: A set of estimators and tests for panel data econometrics, as described in Baltagi (2013) Econometric Analysis of Panel Data, ISBN-13:978-1-118-67232-7, Hsiao (2014) Analysis of Panel Data <doi:10.1017/CBO9781139839327> and Croissant and Millo (2018), Panel Data Econometrics with R, ISBN:978-1-118-94918-4.
Author: Yves Croissant [aut, cre], Giovanni Millo [aut], Kevin Tappe [aut], Ott Toomet [ctb], Christian Kleiber [ctb], Achim Zeileis [ctb], Arne Henningsen [ctb], Liviu Andronic [ctb], Nina Schoenfelder [ctb]
Maintainer: Yves Croissant <yves.croissant@univ-reunion.fr>

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Package PlackettLuce updated to version 0.3.1 with previous version 0.2-9 dated 2019-09-16

Title: Plackett-Luce Models for Rankings
Description: Functions to prepare rankings data and fit the Plackett-Luce model jointly attributed to Plackett (1975) <doi:10.2307/2346567> and Luce (1959, ISBN:0486441369). The standard Plackett-Luce model is generalized to accommodate ties of any order in the ranking. Partial rankings, in which only a subset of items are ranked in each ranking, are also accommodated in the implementation. Disconnected/weakly connected networks implied by the rankings may be handled by adding pseudo-rankings with a hypothetical item. Optionally, a multivariate normal prior may be set on the log-worth parameters and ranker reliabilities may be incorporated as proposed by Raman and Joachims (2014) <doi:10.1145/2623330.2623654>. Maximum a posteriori estimation is used when priors are set. Methods are provided to estimate standard errors or quasi-standard errors for inference as well as to fit Plackett-Luce trees. See the package website or vignette for further details.
Author: Heather Turner [aut, cre] (<https://orcid.org/0000-0002-1256-3375>), Ioannis Kosmidis [aut] (<https://orcid.org/0000-0003-1556-0302>), David Firth [aut] (<https://orcid.org/0000-0003-0302-2312>), Jacob van Etten [ctb] (<https://orcid.org/0000-0001-7554-2558>)
Maintainer: Heather Turner <ht@heatherturner.net>

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New package MODIStsp with initial version 2.0.4
Package: MODIStsp
Title: A Tool for Automating Download and Preprocessing of MODIS Land Products Data
Type: Package
Version: 2.0.4
Authors@R: c(person("Lorenzo", "Busetto", email = "lbusett@gmail.com", role = c("aut", "cre"), comment = c(ORCID = '0000-0001-9634-6038')), person("Luigi", "Ranghetti", email = "ranghetti.l@irea.cnr.it", role = c("aut"), comment = c(ORCID = '0000-0001-6207-5188')), person("Leah", "Wasser", role = "rev", comment = "Leah Wasser reviewed the package for rOpenSci, see https://github.com/ropensci/software-review/issues/184"), person("Jeff", "Hanson", role = "rev", comment = "Jeff Hanson reviewed the package for rOpenSci, see https://github.com/ropensci/software-review/issues/184"))
Description: Allows automating the creation of time series of rasters derived from MODIS Satellite Land Products data. It performs several typical preprocessing steps such as download, mosaicking, reprojection and resize of data acquired on a specified time period. All processing parameters can be set using a user-friendly GUI. Users can select which layers of the original MODIS HDF files they want to process, which additional Quality Indicators should be extracted from aggregated MODIS Quality Assurance layers and, in the case of Surface Reflectance products , which Spectral Indexes should be computed from the original reflectance bands. For each output layer, outputs are saved as single-band raster files corresponding to each available acquisition date. Virtual files allowing access to the entire time series as a single file are also created. Command-line execution exploiting a previously saved processing options file is also possible, allowing to automatically update time series related to a MODIS product whenever a new image is available.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: assertthat, bitops (>= 1.0-6), data.table (>= 1.9.6), gdalUtilities, httr (>= 1.4.2), jsonlite, geojsonio, parallel, raster (>= 3.3.13), sf (>= 0.9.3), stringr (>= 1.0.0), xts (>= 0.9-7), xml2 (>= 1.2.0),
Suggests: testthat, spelling, knitr, rmarkdown, png, grid, httptest, geojsonlint, leaflet, shiny, shinydashboard, shinyFiles, shinyalert, shinyjs, rappdirs, leafem (>= 0.1.3), mapedit (>= 0.6.0), rgdal, magrittr, formatR
SystemRequirements:
URL: https://github.com/ropensci/MODIStsp/, https://docs.ropensci.org/MODIStsp/
BugReports: https://github.com/ropensci/MODIStsp/issues
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2020-10-12 15:55:52 UTC; LB_laptop
Author: Lorenzo Busetto [aut, cre] (<https://orcid.org/0000-0001-9634-6038>), Luigi Ranghetti [aut] (<https://orcid.org/0000-0001-6207-5188>), Leah Wasser [rev] (Leah Wasser reviewed the package for rOpenSci, see https://github.com/ropensci/software-review/issues/184), Jeff Hanson [rev] (Jeff Hanson reviewed the package for rOpenSci, see https://github.com/ropensci/software-review/issues/184)
Maintainer: Lorenzo Busetto <lbusett@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-13 12:40:07 UTC

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New package easyr with initial version 0.5-2
Package: easyr
Type: Package
Title: Helpful Functions from Oliver Wyman Actuarial Consulting
Version: 0.5-2
Authors@R: c( person( "Oliver Wyman", "Actuarial Consulting", email = "rajesh.sahasrabuddhe@oliverwyman.com", role = c("aut", "cph") ), person( "Bryce", "Chamberlain", email = "bryce.chamberlain@oliverwyman.com", role = c("aut", "cre") ), person( "Scott", "Sobel", email = "scott.sobel@oliverwyman.com", role = c("ctb") ), person( "Rajesh", "Sahasrabuddhe", email = "rajesh.sahasrabuddhe@oliverwyman.com", role = c("ctb") ) )
Maintainer: Bryce Chamberlain <bryce.chamberlain@oliverwyman.com>
Description: Makes difficult operations easy. Includes these types of functions: shorthand, type conversion, data wrangling, and work flow. Also includes some helpful data objects: NA strings, U.S. state list, color blind charting colors. Built and shared by Oliver Wyman Actuarial Consulting. Accepting proposed contributions through GitHub.
License: GPL (>= 2)
LazyData: true
URL: https://github.com/oliver-wyman-actuarial/easyr
BugReports: https://github.com/oliver-wyman-actuarial/easyr/issues
Depends: R (>= 3.4.0)
Imports: data.table, digest, dplyr, foreign, glue, Hmisc, lubridate, stringr, openssl, readxl, rlang, rprojroot, XML
RoxygenNote: 6.1.1
Suggests: pdftools, qs, rstudioapi, testthat
NeedsCompilation: no
Packaged: 2020-10-09 15:24:51 UTC; bryce.chamberlain
Author: Oliver Wyman Actuarial Consulting [aut, cph], Bryce Chamberlain [aut, cre], Scott Sobel [ctb], Rajesh Sahasrabuddhe [ctb]
Repository: CRAN
Date/Publication: 2020-10-13 12:40:02 UTC

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New package cora with initial version 0.1.0
Package: cora
Title: Cora Data for Entity Resolution
Version: 0.1.0
Authors@R: c(person("Rebecca", "Steorts", email= "beka@stat.duke.edu", role=c("aut", "cre")), person("Andee", "Kaplan", email= "andrea.kaplan@duke.edu", role="aut"), person("Srini", "Sunil", email="srinivas.sunil@duke.edu", role="aut"))
Description: Duplicated publication data (pre-processed and formatted) for entity resolution. This data set contains a total of 1879 records. The following variables are included in the data set: id, title, book title, authors, address, date, year, editor, journal, volume, pages, publisher, institution, type, tech, note. The data set has a respective gold data set that provides information on which records match based on id.
URL: https://github.com/resteorts/cora
BugReports: https://github.com/resteorts/cora/issues
Depends: R (>= 3.4.0)
License: CC0
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1.9000
NeedsCompilation: no
Packaged: 2020-10-05 10:57:07 UTC; rebeccasteorts
Author: Rebecca Steorts [aut, cre], Andee Kaplan [aut], Srini Sunil [aut]
Maintainer: Rebecca Steorts <beka@stat.duke.edu>
Repository: CRAN
Date/Publication: 2020-10-13 12:50:06 UTC

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New package bRacatus with initial version 1.0.0
Package: bRacatus
Title: Estimating the Accuracy and the Status of Point Occurrence Records
Version: 1.0.0
Language: en-GB
Authors@R: c(person("Eduardo", "Arlé", email = "eduardo.arle@idiv.de", role = c("aut", "cre")), person("Alexander","Zizka",email = "alexaner.zizka@idiv.de", role = "ctb"))
Description: Automated assessment of accuracy and geographical status of georeferenced biological data. The methods rely on reference regions, namely checklists and range maps. Includes functions to obtain data from the Global Biodiversity Information Facility <https://www.gbif.org/> and from the Global Inventory of Floras and Traits <https://gift.uni-goettingen.de/home>. Alternatively, the user can input their own data. Furthermore, provides easy visualisation of the data and the results through the plotting functions. Especially suited for large datasets. The reference for the methodology is: Arlé et al. (under review).
Depends: R (>= 3.5.0)
Imports: data.table, geojsonio, graphics, grDevices, jsonlite, maptools, methods, plotfunctions, raster, rgbif, rgeos, rworldmap, sp, stats, testthat
License: GPL (>= 2)
Encoding: UTF-8
URL: https://github.com/EduardoArle/bRacatus
BugReports: https://github.com/EduardoArle/bRacatus/issues
LazyData: true
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-10-05 12:25:04 UTC; ca13kute
Author: Eduardo Arlé [aut, cre], Alexander Zizka [ctb]
Maintainer: Eduardo Arlé <eduardo.arle@idiv.de>
Repository: CRAN
Date/Publication: 2020-10-13 13:00:14 UTC

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Package IRTBEMM updated to version 1.0.6 with previous version 1.0.5 dated 2020-09-23

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

Diff between IRTBEMM versions 1.0.5 dated 2020-09-23 and 1.0.6 dated 2020-10-13

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Package hett updated to version 0.3-3 with previous version 0.3-2 dated 2018-06-12

Title: Heteroscedastic t-Regression
Description: Functions for the fitting and summarizing of heteroscedastic t-regression.
Author: Julian Taylor <julian.taylor@adelaide.edu.au>
Maintainer: Julian Taylor <julian.taylor@adelaide.edu.au>

Diff between hett versions 0.3-2 dated 2018-06-12 and 0.3-3 dated 2020-10-13

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Package vtable updated to version 1.2.6 with previous version 1.2.1 dated 2020-06-20

Title: Variable Table for Variable Documentation
Description: Automatically generates HTML variable documentation including variable names, labels, classes, value labels (if applicable), value ranges, and summary statistics. See the vignette "vtable" for a package overview.
Author: Nick Huntington-Klein [aut, cre]
Maintainer: Nick Huntington-Klein <nhuntington-klein@seattleu.edu>

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Package SNPassoc updated to version 2.0-1 with previous version 2.0-0 dated 2020-09-07

Title: SNPs-Based Whole Genome Association Studies
Description: Functions to perform most of the common analysis in genome association studies are implemented. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). Permutation test and related tests (sum statistic and truncated product) are also implemented. Max-statistic and genetic risk-allele score exact distributions are also possible to be estimated. The methods are described in Gonzalez JR et al. (2007) <doi: 10.1093/bioinformatics/btm025>.
Author: Juan R Gonzalez and Victor Moreno
Maintainer: Juan R Gonzalez <juanr.gonzalez@isglobal.org>

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Package parzer updated to version 0.3.0 with previous version 0.2.0 dated 2020-10-07

Title: Parse Messy Geographic Coordinates
Description: Parse geographic coordinates from various formats to decimal degree numeric values. Parse coordinates into their parts (degree, minutes, seconds); calculate hemisphere from coordinates; pull out individually degrees, minutes, or seconds; add and subtract degrees, minutes, and seconds. C++ code herein originally inspired from code written by Jeffrey D. Bogan, but then completely re-written.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Alban Sagouis [ctb], Jeffrey Bogan [ctb] (C++ code originally from Jeffrey Bogan, but completely re-written), Julien Brun [rev] (Julien Brun reviewed the package, see https://github.com/ropensci/onboarding/issues/341), Maria Munafó [rev] (Maria Munafó reviewed the package, see https://github.com/ropensci/onboarding/issues/341), rOpenSci [fnd] (https://ropensci.org)
Maintainer: Scott Chamberlain <sckott@protonmail.com>

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Package lqr updated to version 3.31 with previous version 2.11 dated 2020-05-02

Title: Robust Linear Quantile Regression
Description: It fits a robust linear quantile regression model using a new family of zero-quantile distributions for the error term. Missing values and censored observations can be handled as well. This family of distribution includes skewed versions of the Normal, Student's t, Laplace, Slash and Contaminated Normal distribution. It also performs logistic quantile regression for bounded responses as shown in Galarza et.al.(2020) <doi:10.1007/s13571-020-00231-0>. It provides estimates and full inference. It also provides envelopes plots for assessing the fit and confidences bands when several quantiles are provided simultaneously.
Author: Christian E. Galarza, Luis Benites, Marcelo Bourguignon, Victor H. Lachos
Maintainer: Christian E. Galarza <cgalarza88@gmail.com>

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Package dbnR updated to version 0.5.3 with previous version 0.5.2 dated 2020-10-08

Title: Dynamic Bayesian Network Learning and Inference
Description: Learning and inference over dynamic Bayesian networks of arbitrary Markovian order. Extends some of the functionality offered by the 'bnlearn' package to learn the networks from data and perform exact inference. It offers two structure learning algorithms for dynamic Bayesian networks and the possibility to perform forecasts of arbitrary length. A tool for visualizing the structure of the net is also provided via the 'visNetwork' package.
Author: David Quesada [aut, cre], Gabriel Valverde [ctb]
Maintainer: David Quesada <dkesada@gmail.com>

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Package cmsafvis updated to version 1.0.1 with previous version 1.0.0 dated 2020-10-06

Title: Visualize CM SAF NetCDF Data
Description: The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (<http://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The 'cmsafvis' R-package provides a collection of R-operators for the analysis and visualization of CM SAF NetCDF data. CM SAF climate data records are provided for free via (<https://wui.cmsaf.eu>). Detailed information and test data are provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox>).
Author: Steffen Kothe [aut, cre]
Maintainer: Steffen Kothe <Steffen.Kothe@dwd.de>

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Package bootstrapFP updated to version 0.4.4 with previous version 0.4.3 dated 2019-02-24

Title: Bootstrap Algorithms for Finite Population Inference
Description: Finite Population bootstrap algorithms to estimate the variance of the Horvitz-Thompson estimator for single-stage sampling. For a survey of bootstrap methods for finite populations, see Mashreghi et Al. (2016) <doi:10.1214/16-SS113>.
Author: Roberto Sichera [aut, cre]
Maintainer: Roberto Sichera <rob.sichera@gmail.com>

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Package MANOVA.RM updated to version 0.4.2 with previous version 0.3.4 dated 2019-08-28

Title: Resampling-Based Analysis of Multivariate Data and Repeated Measures Designs
Description: Implemented are various tests for semi-parametric repeated measures and general MANOVA designs that do neither assume multivariate normality nor covariance homogeneity, i.e., the procedures are applicable for a wide range of general multivariate factorial designs. In addition to asymptotic inference methods, novel bootstrap and permutation approaches are implemented as well. These provide more accurate results in case of small to moderate sample sizes. Furthermore, post-hoc comparisons are provided for the multivariate analyses. Friedrich, S., Konietschke, F. and Pauly, M. (2018) <arXiv:1801.08002>.
Author: Sarah Friedrich, Frank Konietschke, Markus Pauly
Maintainer: Sarah Friedrich <sarah.friedrich@med.uni-goettingen.de>

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Package kyotil updated to version 2020.10-12 with previous version 2020.8-22 dated 2020-08-26

Title: Utility Functions for Statistical Analysis Report Generation and Monte Carlo Studies
Description: Helper functions for creating formatted summary of regression models, writing publication-ready tables to latex files, and running Monte Carlo experiments.
Author: Youyi Fong [cre], Krisztian Sebestyen [aut], Jason Becker [ctb], Bendix Carstensen [ctb], Daryl Morris [ctb], Josh Pasek [ctb], Dennis Chao [ctb], Andri Signorell [ctb], Sue Li [ctb], Jonathan Bartlett [ctb], Christophe Dutang [ctb]
Maintainer: Youyi Fong <youyifong@gmail.com>

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Package splitTools updated to version 0.3.1 with previous version 0.3.0 dated 2020-09-19

Title: Tools for Data Splitting
Description: Fast, lightweight toolkit for data splitting. Data sets can be partitioned into disjoint groups (e.g. into training, validation, and test) or into (repeated) k-folds for subsequent cross-validation. Besides basic splits, the package supports stratified, grouped as well as blocked splitting. Furthermore, cross-validation folds for time series data can be created. See e.g. Hastie et al. (2001) <doi:10.1007/978-0-387-84858-7> for the basic background on data partitioning and cross-validation.
Author: Michael Mayer [aut, cre]
Maintainer: Michael Mayer <mayermichael79@gmail.com>

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Package wk updated to version 0.3.3 with previous version 0.3.2 dated 2020-08-03

Title: Lightweight Well-Known Geometry Parsing
Description: Provides a minimal R and C++ API for parsing well-known binary and well-known text representation of geometries to and from R-native formats. Well-known binary is compact and fast to parse; well-known text is human-readable and is useful for writing tests. These formats are only useful in R if the information they contain can be accessed in R, for which high-performance functions are provided here.
Author: Dewey Dunnington [aut, cre] (<https://orcid.org/0000-0002-9415-4582>), Edzer Pebesma [aut] (<https://orcid.org/0000-0001-8049-7069>)
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

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Package wdpar updated to version 1.0.4 with previous version 1.0.3 dated 2020-07-30

Title: Interface to the World Database on Protected Areas
Description: Fetch and clean data from the World Database on Protected Areas (WDPA). Data is obtained from Protected Planet <https://www.protectedplanet.net/en>.
Author: Jeffrey O Hanson [aut, cre]
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>

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Package RcmdrPlugin.EZR updated to version 1.53 with previous version 1.52 dated 2020-08-31

Title: R Commander Plug-in for the EZR (Easy R) Package
Description: EZR (Easy R) adds a variety of statistical functions, including survival analyses, ROC analyses, metaanalyses, sample size calculation, and so on, to the R commander. EZR enables point-and-click easy access to statistical functions, especially for medical statistics. EZR is platform-independent and runs on Windows, Mac OS X, and UNIX. Its complete manual is available only in Japanese (Chugai Igakusha, ISBN: 978-4-498-10901-8 or Nankodo, ISBN: 978-4-524-26158-1), but an report that introduced the investigation of EZR was published in Bone Marrow Transplantation (Nature Publishing Group) as an Open article. This report can be used as a simple manual. It can be freely downloaded from the journal website as shown below. This report has been cited in more than 3,000 scientific articles.
Author: Yoshinobu Kanda
Maintainer: Yoshinobu Kanda <ycanda-tky@umin.ac.jp>

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Package rbace updated to version 0.2.2 with previous version 0.2.0 dated 2020-09-10

Title: 'Bielefeld' Academic Search Engine ('BASE') Client
Description: Interface to the API for the 'Bielefeld' Academic Search Engine ('BASE') (<https://www.base-search.net/>). 'BASE' is a search engine for more than 150 million scholarly documents from more than 7000 sources. Methods are provided for searching for documents, as well as getting information on higher level groupings of documents: collections and repositories within collections. Search includes faceting, so you can get a high level overview of number of documents across a given variable (e.g., year). 'BASE' asks users to respect a rate limit, but does not enforce it themselves; we enforce that rate limit.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package modelplotr updated to version 1.1.0 with previous version 1.0.0 dated 2019-04-24

Title: Plots to Evaluate the Business Performance of Predictive Models
Description: Plots to assess the quality of predictive models from a business perspective. Using these plots, it can be shown how implementation of the model will impact business targets like response on a campaign or return on investment. Different scopes can be selected: compare models, compare datasets or compare target class values and various plot customization and highlighting options are available. targets like response on a campaign. Different scopes can be selected: compare models, compare datasets or compare target class values and various plot customization and highlighting options are available.
Author: Jurriaan Nagelkerke [aut, cre], Pieter Marcus [aut]
Maintainer: Jurriaan Nagelkerke <jurriaan.nagelkerke@gmail.com>

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Package cleanNLP updated to version 3.0.3 with previous version 3.0.2 dated 2020-03-08

Title: A Tidy Data Model for Natural Language Processing
Description: Provides a set of fast tools for converting a textual corpus into a set of normalized tables. Users may make use of the 'udpipe' back end with no external dependencies, or two Python back ends with 'spaCy' <https://spacy.io> or 'CoreNLP' <https://stanfordnlp.github.io/CoreNLP/>. Exposed annotation tasks include tokenization, part of speech tagging, named entity recognition, and dependency parsing.
Author: Taylor B. Arnold [aut, cre]
Maintainer: Taylor B. Arnold <taylor.arnold@acm.org>

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Package bookdown updated to version 0.21 with previous version 0.20 dated 2020-06-23

Title: Authoring Books and Technical Documents with R Markdown
Description: Output formats and utilities for authoring books and technical documents with R Markdown.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), JJ Allaire [ctb], Albert Kim [ctb], Alessandro Samuel-Rosa [ctb], Andrzej Oles [ctb], Atsushi Yasumoto [ctb] (<https://orcid.org/0000-0002-8335-495X>), Aust Frederik [ctb] (<https://orcid.org/0000-0003-4900-788X>), Bastiaan Quast [ctb], Ben Marwick [ctb], Chester Ismay [ctb], Christophe Dervieux [ctb], Clifton Franklund [ctb], Daniel Emaasit [ctb], David Shuman [ctb], Dean Attali [ctb], Drew Tyre [ctb], Ellis Valentiner [ctb], Frans van Dunne [ctb], Hadley Wickham [ctb], Jeff Allen [ctb], Jennifer Bryan [ctb], Jonathan McPhers [ctb], JooYoung Seo [ctb] (<https://orcid.org/0000-0002-4064-6012>), Joyce Robbins [ctb], Junwen Huang [ctb], Kevin Cheung [ctb], Kevin Ushey [ctb], Kim Seonghyun [ctb], Kirill Muller [ctb], Luciano Selzer [ctb], Matthew Lincoln [ctb], Maximilian Held [ctb], Michael Sachs [ctb], Michal Bojanowski [ctb], Nathan Werth [ctb], Noam Ross [ctb], Peter Hickey [ctb], Romain Lesur [ctb] (<https://orcid.org/0000-0002-0721-5595>), Sahir Bhatnagar [ctb], Steve Simpson [ctb], Thierry Onkelinx [ctb] (<https://orcid.org/0000-0001-8804-4216>), Vincent Fulco [ctb], Yixuan Qiu [ctb], Zhuoer Dong [ctb], RStudio, PBC [cph], Bartek Szopka [ctb] (The jQuery Highlight plugin), Zeno Rocha [cph] (clipboard.js library), jQuery Foundation [cph] (jQuery library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/resources/AUTHORS), MathQuill contributors [ctb] (The MathQuill library; authors listed in inst/resources/AUTHORS), FriendCode Inc [cph, ctb] (The gitbook style, with modifications)
Maintainer: Yihui Xie <xie@yihui.name>

Diff between bookdown versions 0.20 dated 2020-06-23 and 0.21 dated 2020-10-13

 DESCRIPTION                                    |   12 +-
 MD5                                            |   43 +++++-----
 NAMESPACE                                      |    1 
 R/ebook.R                                      |   22 +++--
 R/gitbook.R                                    |    1 
 R/html.R                                       |   23 +++--
 R/latex.R                                      |    4 
 R/render.R                                     |   33 +++++---
 R/utils.R                                      |  101 ++++++++++++++++++++++++-
 R/word.R                                       |    9 +-
 README.md                                      |    2 
 inst/resources/gitbook/css/plugin-bookdown.css |    2 
 inst/resources/gitbook/js/plugin-sharing.js    |    2 
 inst/rmarkdown                                 |only
 man/calibre.Rd                                 |    2 
 man/fence_theorems.Rd                          |only
 man/html_document2.Rd                          |   18 ++--
 man/kindlegen.Rd                               |   10 +-
 man/render_book.Rd                             |   19 +++-
 man/serve_book.Rd                              |    2 
 tests/rmd/_bookdown.yml                        |only
 tests/rmd/custom-environments.Rmd              |only
 tests/rmd/number-sections.Rmd                  |only
 tests/test-rmd.R                               |   36 +++++++-
 tests/testit/test-utils.R                      |   54 +++++++++++++
 25 files changed, 306 insertions(+), 90 deletions(-)

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