Tue, 24 Nov 2020

New package wikifacts with initial version 0.4.1
Package: wikifacts
Type: Package
Title: Get Facts and Data from Wikipedia and Wikidata
Version: 0.4.1
Authors@R: c(person(given = "Keith", family = "McNulty", role = c("aut", "cre"), email = "keith.mcnulty@gmail.com", comment = c(ORCID = "0000-0002-2332-1654")), person(given = "Petr", family = "Kajzar", role = c("ctb"), email = "petr.kajzar@centrum.cz"))
Description: Query Wikidata and get facts from current and historic Wikipedia main pages.
License: CC0
Encoding: UTF-8
LazyData: true
Imports: curl, magrittr, rvest, utils, xml2
RoxygenNote: 7.1.1
Suggests: covr, testthat
NeedsCompilation: no
Packaged: 2020-11-24 10:48:30 UTC; keithmcnulty
Author: Keith McNulty [aut, cre] (<https://orcid.org/0000-0002-2332-1654>), Petr Kajzar [ctb]
Maintainer: Keith McNulty <keith.mcnulty@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-24 16:20:02 UTC

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Package UKFE updated to version 0.1.1 with previous version 0.1.0 dated 2020-11-23

Title: UK Flood Estimation
Description: Functions to implement the methods of the Flood Estimation Handbook (FEH), associated updates and the revitalised flood hydrograph model (ReFH). Currently the packages uses NRFA peak flow dataset version 9. Aside from FEH functionality, further hydrological functions are available. Most of the methods implemented in this package are described in one or more of the following: "Flood Estimation Handbook", Centre for Ecology & Hydrology (1999, ISBN:0 948540 94 X). "Flood Estimation Handbook Supplementary Report No. 1", Kjeldsen (2007, ISBN:0 903741 15 7). "Regional Frequency Analysis - an approach based on L-moments", Hosking & Wallis (1997, ISBN: 978 0 521 01940 8). "Proposal of the ‘extreme rank plot’ for extreme value analysis: with an emphasis on flood frequency studies", Hammond (2019, <doi:10.2166/nh.2019.157>). "Making better use of local data in flood frequency estimation", Environment Agency (2017, ISBN: 978 1 84911 387 8). "Improving the FEH statistical procedures for flood frequency estimation", Environment Agency (2008, ISBN: 978 1 84432 920 5). "Low flow estimation in the United Kingdom", Institute of Hydrology (1992, ISBN 0 948540 45 1). Wallingford HydroSolutions, (2016, <http://software.hydrosolutions.co.uk/winfap4/Urban-Adjustment-Procedure-Technical-Note.pdf>). Data from the UK National River Flow Archive (<https://nrfa.ceh.ac.uk/>, terms and conditions: <https://nrfa.ceh.ac.uk/costs-terms-and-conditions>.
Author: Anthony Hammond
Maintainer: Anthony Hammond <agqhammond@gmail.com>

Diff between UKFE versions 0.1.0 dated 2020-11-23 and 0.1.1 dated 2020-11-24

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Package scattermore updated to version 0.7 with previous version 0.6 dated 2020-03-06

Title: Scatterplots with More Points
Description: C-based conversion of large scatterplot data to rasters. Speeds up plotting of data with millions of points.
Author: Mirek Kratochvil [aut, cre] (<https://orcid.org/0000-0001-7356-4075>)
Maintainer: Mirek Kratochvil <exa.exa@gmail.com>

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Package microeco updated to version 0.3.1 with previous version 0.3.0 dated 2020-11-15

Title: Microbial Community Ecology Data Analysis
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.
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>

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Package maxLik updated to version 1.4-6 with previous version 1.4-4 dated 2020-09-04

Title: Maximum Likelihood Estimation and Related Tools
Description: Functions for Maximum Likelihood (ML) estimation, non-linear optimization, and related tools. It includes a unified way to call different optimizers, and classes and methods to handle the results from the Maximum Likelihood viewpoint. It also includes a number of convenience tools for testing and developing your own models.
Author: Ott Toomet <otoomet@gmail.com>, Arne Henningsen <arne.henningsen@gmail.com>, with contributions from Spencer Graves and Yves Croissant
Maintainer: Ott Toomet <otoomet@gmail.com>

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Package broman updated to version 0.71-6 with previous version 0.70-4 dated 2020-05-22

Title: Karl Broman's R Code
Description: Miscellaneous R functions, including functions related to graphics (mostly for base graphics), permutation tests, running mean/median, and general utilities.
Author: Karl W Broman [aut, cre] (<https://orcid.org/0000-0002-4914-6671>), Aimee Teo Broman [ctb] (<https://orcid.org/0000-0003-3783-2807>)
Maintainer: Karl W Broman <broman@wisc.edu>

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Package betaper updated to version 1.1-2 with previous version 1.1-1 dated 2020-03-02

Title: Taxonomic Uncertainty on Multivariate Analyses of Ecological Data
Description: Permutational method to incorporate taxonomic uncertainty and some functions to assess its effects on parameters of some widely used multivariate methods in ecology, as explained in Cayuela et al. (2011) <doi:10.1111/j.1600-0587.2009.05899.x>.
Author: Luis Cayuela and Marcelino de la Cruz
Maintainer: Luis Cayuela <luis.cayuela@urjc.es>

Diff between betaper versions 1.1-1 dated 2020-03-02 and 1.1-2 dated 2020-11-24

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Package syuzhet updated to version 1.0.6 with previous version 1.0.4 dated 2017-12-14

Title: Extracts Sentiment and Sentiment-Derived Plot Arcs from Text
Description: Extracts sentiment and sentiment-derived plot arcs from text using a variety of sentiment dictionaries conveniently packaged for consumption by R users. Implemented dictionaries include "syuzhet" (default) developed in the Nebraska Literary Lab "afinn" developed by Finn Årup Nielsen, "bing" developed by Minqing Hu and Bing Liu, and "nrc" developed by Mohammad, Saif M. and Turney, Peter D. Applicable references are available in README.md and in the documentation for the "get_sentiment" function. The package also provides a hack for implementing Stanford's coreNLP sentiment parser. The package provides several methods for plot arc normalization.
Author: Matthew Jockers [aut, cre]
Maintainer: Matthew Jockers <mjockers@gmail.com>

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Package stochvol updated to version 3.0.3 with previous version 3.0.2 dated 2020-11-17

Title: Efficient Bayesian Inference for Stochastic Volatility (SV) Models
Description: Efficient algorithms for fully Bayesian estimation of stochastic volatility (SV) models with and without asymmetry (leverage) via Markov chain Monte Carlo (MCMC) methods. Methodological details are given in Kastner and Frühwirth-Schnatter (2014) <doi:10.1016/j.csda.2013.01.002> and Hosszejni and Kastner (2019) <doi:10.1007/978-3-030-30611-3_8>; the most common use cases are described in Kastner (2016) <doi:10.18637/jss.v069.i05> and the package vignette.
Author: Darjus Hosszejni [aut, cre] (<https://orcid.org/0000-0002-3803-691X>), Gregor Kastner [aut] (<https://orcid.org/0000-0002-8237-8271>)
Maintainer: Darjus Hosszejni <darjus.hosszejni@wu.ac.at>

Diff between stochvol versions 3.0.2 dated 2020-11-17 and 3.0.3 dated 2020-11-24

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New package SpatialRegimes with initial version 0.2
Package: SpatialRegimes
Type: Package
Title: Spatial Constrained Clusterwise Regression
Version: 0.2
Date: 2020-11-23
Author: Francesco Vidoli, Roberto Benedetti
Maintainer: Francesco Vidoli <fvidoli@gmail.com>
Description: A collection of functions for estimating spatial regimes, aggregations of neighboring spatial units that are homogeneous in functional terms. The term spatial regime, therefore, should not be understood as a synonym for cluster. More precisely, the term cluster does not presuppose any functional relationship between the variables considered, while the term regime is linked to a regressive relationship underlying the spatial process. For more information, please see Postiglione, P., Andreano, M.S., Benedetti R. (2013) <doi:10.1007/s10614-012-9325-z> , Andreano, M.S., Benedetti, R., and Postiglione, P. (2017) <doi:10.1007/s11135-016-0415-1> , Bille', A.G., Benedetti, R., and Postiglione, P. (2017) <doi:10.1080/17421772.2017.1286373>.
Depends: spdep, quantreg, GWmodel, plm
Imports:
License: GPL (>= 2)
Suggests: R.rsp, utils
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2020-11-23 16:25:28 UTC; Fra
Repository: CRAN
Date/Publication: 2020-11-24 15:40:02 UTC

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Package RobGARCHBoot updated to version 1.1.0 with previous version 1.0.1 dated 2020-05-13

Title: Robust Bootstrap Forecast Densities for GARCH Models
Description: Bootstrap forecast densities for GARCH (Generalized Autoregressive Conditional Heteroskedastic) returns and volatilities using the robust residual-based bootstrap procedure of Trucios, Hotta and Ruiz (2017) <DOI:10.1080/00949655.2017.1359601>.
Author: Carlos Trucios
Maintainer: Carlos Trucios <ctrucios@gmail.com>

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Package jti updated to version 0.5.2 with previous version 0.5.1 dated 2020-11-19

Title: Junction Tree Inference
Description: Minimal and memory efficient implementation of the junction tree algorithm using the Lauritzen-Spiegelhalter scheme; S. L. Lauritzen and D. J. Spiegelhalter (1988) <https://www.jstor.org/stable/2345762?seq=1>.
Author: Mads Lindskou [aut, cre]
Maintainer: Mads Lindskou <mads@math.aau.dk>

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Package jskm updated to version 0.4.2 with previous version 0.4.1 dated 2020-11-01

Title: Kaplan-Meier Plot with 'ggplot2'
Description: The function 'jskm()' creates publication quality Kaplan-Meier plot with at risk tables below. 'svyjskm()' provides plot for weighted Kaplan-Meier estimator.
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>), Zarathu [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

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Package corrr updated to version 0.4.3 with previous version 0.4.2 dated 2020-03-22

Title: Correlations in R
Description: A tool for exploring correlations. It makes it possible to easily perform routine tasks when exploring correlation matrices such as ignoring the diagonal, focusing on the correlations of certain variables against others, or rearranging and visualizing the matrix in terms of the strength of the correlations.
Author: Max Kuhn [aut, cre], Simon Jackson [aut], Jorge Cimentada [aut]
Maintainer: Max Kuhn <max@rstudio.com>

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More information about corrr at CRAN
Permanent link

Package corHMM updated to version 2.5 with previous version 2.4 dated 2020-10-01

Title: Hidden Markov Models of Character Evolution
Description: Fits hidden Markov models of discrete character evolution which allow different transition rate classes on different portions of a phylogeny. Beaulieu et al (2013) <doi:10.1093/sysbio/syt034>.
Author: Jeremy Beaulieu [aut, cre], Brian O'Meara [aut], Jeffrey Oliver [aut], James Boyko [aut]
Maintainer: Jeremy Beaulieu <jmbeauli@uark.edu>

Diff between corHMM versions 2.4 dated 2020-10-01 and 2.5 dated 2020-11-24

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Permanent link

Package yamlet updated to version 0.5.1 with previous version 0.4.8 dated 2020-06-18

Title: Versatile Curation of Table Metadata
Description: A file-based mechanism for documenting datasets. It reads and writes YAML-formatted metadata and applies it as data item attributes. Data and metadata are stored independently but can be coordinated by using similar file paths with different extensions. The 'yamlet' dialect is valid 'YAML', but some conventions are chosen to improve readability. Defaults and conventions can be over-ridden by the user. See ?yamlet and ?decorate.data.frame. See ?read_yamlet ?write_yamlet, and ?io_csv.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

Diff between yamlet versions 0.4.8 dated 2020-06-18 and 0.5.1 dated 2020-11-24

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More information about yamlet at CRAN
Permanent link

Package sparta updated to version 0.6.1 with previous version 0.6.0 dated 2020-11-09

Title: Sparse Tables
Description: Fast Multiplication and Marginalization of Sparse Tables.
Author: Mads Lindskou [aut, cre]
Maintainer: Mads Lindskou <mads@math.aau.dk>

Diff between sparta versions 0.6.0 dated 2020-11-09 and 0.6.1 dated 2020-11-24

 DESCRIPTION           |   10 +--
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 11 files changed, 218 insertions(+), 71 deletions(-)

More information about sparta at CRAN
Permanent link

Package MediaNews updated to version 0.2.0 with previous version 0.1.0 dated 2020-02-09

Title: Media News Extraction for Text Analysis
Description: Extract textual data from different media channels through its source, based on users choice of keywords. These data can be used to perform text analysis to identify patterns in respective media reporting. The media channels used in this package are print media from India. The data (or news) used are publicly available to consumers.
Author: Vatsal Aima
Maintainer: Vatsal Aima <vaima75@hotmail.com>

Diff between MediaNews versions 0.1.0 dated 2020-02-09 and 0.2.0 dated 2020-11-24

 DESCRIPTION              |   14 +++++------
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 8 files changed, 59 insertions(+), 67 deletions(-)

More information about MediaNews at CRAN
Permanent link

Package insight updated to version 0.11.0 with previous version 0.10.0 dated 2020-10-22

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>), Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Mattan S. Ben-Shachar [aut, ctb] (<https://orcid.org/0000-0002-4287-4801>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between insight versions 0.10.0 dated 2020-10-22 and 0.11.0 dated 2020-11-24

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Package fhircrackr updated to version 0.2.1 with previous version 0.2.0 dated 2020-10-19

Title: Handling HL7 FHIR Resources in R
Description: Useful tools for conveniently downloading FHIR resources in xml format and converting them to R data frames. The package uses FHIR-search to download bundles from a FHIR server, provides functions to save and read xml-files containing such bundles and allows flattening the bundles to data.frames using XPath expressions.
Author: Thomas Peschel [aut, cre], Julia Gantner [aut] (<https://orcid.org/0000-0003-1568-5893>), Jens Przybilla [aut], Frank Meineke [aut] (<https://orcid.org/0000-0002-9256-7543>)
Maintainer: Thomas Peschel <tpeschel@imise.uni-leipzig.de>

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Package diversitree updated to version 0.9-15 with previous version 0.9-14 dated 2020-09-04

Title: Comparative 'Phylogenetic' Analyses of Diversification
Description: Contains a number of comparative 'phylogenetic' methods, mostly focusing on analysing diversification and character evolution. Contains implementations of 'BiSSE' (Binary State 'Speciation' and Extinction) and its unresolved tree extensions, 'MuSSE' (Multiple State 'Speciation' and Extinction), 'QuaSSE', 'GeoSSE', and 'BiSSE-ness' Other included methods include Markov models of discrete and continuous trait evolution and constant rate 'speciation' and extinction.
Author: Richard G. FitzJohn [aut, cre], Emma Goldberg [aut], Karen Magnuson-Ford [aut], Roger Sidje [aut]
Maintainer: Richard G. FitzJohn <rich.fitzjohn@gmail.com>

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Package clam updated to version 2.3.7 with previous version 2.3.5 dated 2020-08-10

Title: Classical Age-Depth Modelling of Cores from Deposits
Description: Performs 'classical' age-depth modelling of dated sediment deposits - prior to applying more sophisticated techniques such as Bayesian age-depth modelling. Any radiocarbon dated depths are calibrated. Age-depth models are constructed by sampling repeatedly from the dated levels, each time drawing age-depth curves. Model types include linear interpolation, linear or polynomial regression, and a range of splines. See Blaauw (2010). <doi:10.1016/j.quageo.2010.01.002>.
Author: Maarten Blaauw [aut, cre], J. Andres Christen [ctb], Judith Esquivel Vazquez [ctb], Simon Goring [ctb]
Maintainer: Maarten Blaauw <maarten.blaauw@qub.ac.uk>

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Package anticlust updated to version 0.5.6 with previous version 0.5.3 dated 2020-09-25

Title: Subset Partitioning via Anticlustering
Description: The method of anticlustering partitions a pool of elements into groups (i.e., anticlusters) in such a way that the between-group similarity is maximized and -- at the same time -- the within-group heterogeneity is maximized. This reverses the logic of cluster analysis that strives for high within-group homogeneity and low similarity of the different groups. Computationally, anticlustering is accomplished by maximizing instead of minimizing a clustering objective function, such as the intra-cluster variance (used in k-means clustering) or the sum of pairwise distances within clusters. The function anticlustering() implements exact and heuristic anticlustering algorithms as described in Papenberg and Klau (2020; <doi:10.1037/met0000301>). The exact approach requires that the GNU linear programming kit (<https://www.gnu.org/software/glpk/glpk.html>) is available and the R package 'Rglpk' (<https://cran.R-project.org/package=Rglpk>) is installed. Some other functions are available to solve classical clustering problems. The function balanced_clustering() applies a cluster analysis under size constraints, i.e., creates equal-sized clusters. The function matching() can be used for (unrestricted, bipartite, or K-partite) matching. The function wce() can be used optimally solve the (weighted) cluster editing problem, also known as correlation clustering, clique partitioning problem or transitivity clustering.
Author: Martin Papenberg [aut, cre] (<https://orcid.org/0000-0002-9900-4268>), Meik Michalke [ctb] (centroid based clustering algorithm), Gunnar W. Klau [ths], Juliane V. Tkotz [ctb] (package logo)
Maintainer: Martin Papenberg <martin.papenberg@hhu.de>

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Package ivx updated to version 1.1.0 with previous version 1.0.0 dated 2019-05-04

Title: Robust Econometric Inference
Description: Drawing statistical inference on the coefficients of a short- or long-horizon predictive regression with persistent regressors by using the IVX method of Magdalinos and Phillips (2009) <doi:10.1017/S0266466608090154> and Kostakis, Magdalinos and Stamatogiannis (2015) <doi:10.1093/rfs/hhu139>.
Author: Kostas Vasilopoulos [cre, aut], Efthymios Pavlidis [aut]
Maintainer: Kostas Vasilopoulos <k.vasilopoulo@gmail.com>

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Package chickn updated to version 1.2.3 with previous version 1.2.2 dated 2020-11-12

Title: 'Compressive' Hierarchical Kernel Clustering Toolbox
Description: Routines for efficient cluster analysis of large scale data. This package implements the 'CHICKN' clustering algorithm (see 'Permiakova' 'et' 'al.' (2020) "'CHICKN': Extraction of 'peptide' 'chromatographic' 'elution' profiles from large scale mass 'spectrometry' data by means of 'Wasserstein' 'compressive' hierarchical cluster analysis"). Functions for data compression, hierarchical clustering and post processing are provided.
Author: Olga Permiakova [aut, cre], Romain Guibert [aut], Thomas Burger [aut]
Maintainer: Olga Permiakova <olga.permiakova@gmail.com>

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New package rwa with initial version 0.0.3
Package: rwa
Type: Package
Title: Perform a Relative Weights Analysis
Version: 0.0.3
Author: Martin Chan <martinchan53@gmail.com>
Maintainer: Martin Chan <martinchan53@gmail.com>
Description: Perform a Relative Weights Analysis (RWA) (a.k.a. Key Drivers Analysis) as per the method described in Tonidandel & LeBreton (2015) <DOI:10.1007/s10869-014-9351-z>, with its original roots in Johnson (2000) <DOI:10.1207/S15327906MBR3501_1>. In essence, RWA decomposes the total variance predicted in a regression model into weights that accurately reflect the proportional contribution of the predictor variables, which addresses the issue of multi-collinearity. In typical scenarios, RWA returns similar results to Shapley regression, but with a significant advantage on computational performance.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/martinctc/rwa
BugReports: https://github.com/martinctc/rwa/issues
RoxygenNote: 7.1.1
Imports: dplyr, magrittr, stats, tidyr, ggplot2
NeedsCompilation: no
Packaged: 2020-11-22 17:05:48 UTC; Martin Chan
Repository: CRAN
Date/Publication: 2020-11-24 12:10:02 UTC

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Package rosetta updated to version 0.3.1 with previous version 0.3.0 dated 2020-11-12

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 monoClust updated to version 1.2.0 with previous version 1.1.0 dated 2020-11-17

Title: Perform Monothetic Clustering with Extensions to Circular Data
Description: Implementation of the Monothetic Clustering algorithm (Chavent, 1998 <doi:10.1016/S0167-8655(98)00087-7>) on continuous data sets. A lot of extensions are included in the package, including applying Monothetic clustering on data sets with circular variables, visualizations with the results, and permutation and cross-validation based tests to support the decision on the number of clusters.
Author: Tan Tran [aut, cre] (<https://orcid.org/0000-0001-9881-6339>), Brian McGuire [aut], Mark Greenwood [aut] (<https://orcid.org/0000-0001-6933-1201>)
Maintainer: Tan Tran <vinhtantran@gmail.com>

Diff between monoClust versions 1.1.0 dated 2020-11-17 and 1.2.0 dated 2020-11-24

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New package mixcure with initial version 2.0
Encoding: UTF-8
Package: mixcure
Title: Mixture Cure Models
Version: 2.0
Authors@R: person("Yingwei", "Peng", role = c("aut", "cre"), email = "yingwei.peng@queensu.ca")
Description: Implementation of parametric and semiparametric mixture cure models based on existing R packages. See details of the models in Peng and Yu (2020) <ISBN: 9780367145576>.
Depends: R (>= 3.5.0), survival
Imports: boot, flexsurv, survey, gam, timereg
License: GPL-3
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-11-17 03:10:05 UTC; Yingwei
Author: Yingwei Peng [aut, cre]
Maintainer: Yingwei Peng <yingwei.peng@queensu.ca>
Repository: CRAN
Date/Publication: 2020-11-24 12:20:02 UTC

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New package migrate with initial version 0.1.0
Package: migrate
Type: Package
Title: Create Credit State Migration (Transition) Matrices
Version: 0.1.0
Authors@R: c(person(given = "Michael", family = "Thomas", role = c("aut", "cre"), email = "mthomas@ketchbrookanalytics.com"), person(given = "Brad", family = "Lindblad", role = "ctb", email = "bradley.lindblad@gmail.com"))
Description: Tools to help convert credit risk data at two time points into traditional credit state migration (aka, "transition") matrices. At a higher level, 'migrate' is intended to help an analyst understand how risk moved in their credit portfolio over a time interval. References to this methodology include: 1. Schuermann, T. (2008) <doi:10.1002/9780470061596.risk0409>. 2. Perederiy, V. (2017) <arXiv:1708.00062>.
License: MIT + file LICENSE
URL: https://github.com/mthomas-ketchbrook/migrate
BugReports: https://github.com/mthomas-ketchbrook/migrate/issues
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 2.1.0), knitr, rmarkdown
Depends: R (>= 3.1)
Imports: dplyr (>= 1.0.2), tidyr (>= 1.1.0), crayon (>= 1.3.4), stringr (>= 1.4.0), tibble (>= 3.0.1), rlang, utils, magrittr
VignetteBuilder: knitr
Language: en-US
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-22 23:33:20 UTC; 18602
Author: Michael Thomas [aut, cre], Brad Lindblad [ctb]
Maintainer: Michael Thomas <mthomas@ketchbrookanalytics.com>
Repository: CRAN
Date/Publication: 2020-11-24 12:40:03 UTC

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New package ennet with initial version 0.1.0
Package: ennet
Type: Package
Title: Utilities to Extract and Analyse Text Data from the Emergency Nutrition Network Forum
Version: 0.1.0
Authors@R: person(given = "Ernest", family = "Guevarra", email = "ernest@guevarra.io", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4887-4415"))
Description: The Emergency Nutrition Network or en-net forum is the go to online forum for field practitioners requiring prompt technical advice for operational challenges for which answers are not readily accessible in current guidelines. The questions and the corresponding answers raised within en-net can provide insight into what the key topics of discussion are within the nutrition sector. This package provides utility functions for the extraction, processing and analysis of text data from the online forum.
License: GPL-3
Depends: R (>= 2.10)
Imports: magrittr, rvest, xml2, tibble, dplyr, stringr, lubridate
Suggests: knitr, rmarkdown, DiagrammeR, testthat, spelling
Encoding: UTF-8
Language: en-GB
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/katilingban/ennet
BugReports: https://github.com/katilingban/ennet/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-22 18:25:45 UTC; ernest
Author: Ernest Guevarra [aut, cre] (<https://orcid.org/0000-0002-4887-4415>)
Maintainer: Ernest Guevarra <ernest@guevarra.io>
Repository: CRAN
Date/Publication: 2020-11-24 12:20:05 UTC

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Package covid19br updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-29

Title: Brazilian COVID-19 Pandemic Data
Description: Set of functions to import COVID-19 pandemic data into R. The Brazilian COVID-19 data, obtained from the official Brazilian repository at <https://covid.saude.gov.br/>, is available at country, region, state, and city-levels. The package also downloads the world-level COVID-19 data from the John Hopkins University's repository.
Author: Fabio Demarqui [aut, cre], Cristiano Santos [aut], Matheus Costa [ctb]
Maintainer: Fabio Demarqui <fndemarqui@est.ufmg.br>

Diff between covid19br versions 0.1.0 dated 2020-09-29 and 0.1.1 dated 2020-11-24

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Package BAT updated to version 2.4.0 with previous version 2.3.0 dated 2020-10-28

Title: Biodiversity Assessment Tools
Description: Includes algorithms to assess alpha and beta diversity in all their dimensions (taxon, phylogenetic and functional diversity), whether communities are completely sampled or not. It allows performing a number of analyses based on either species identities or phylogenetic/functional trees or functional kernel n-dimensional hypervolumes depicting species relationships.
Author: Pedro Cardoso, Stefano Mammola, Francois Rigal, Jose Carlos Carvalho
Maintainer: Pedro Cardoso <pedro.cardoso@helsinki.fi>

Diff between BAT versions 2.3.0 dated 2020-10-28 and 2.4.0 dated 2020-11-24

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New package LPsmooth with initial version 0.1.3
Package: LPsmooth
Type: Package
Title: LP Smoothed Inference and Graphics
Version: 0.1.3
Author: Xiangyu Zhang <zhan6004@umn.edu>, Sara Algeri <salgeri@umn.edu>
Maintainer: Xiangyu Zhang <zhan6004@umn.edu>
Description: Classical tests of goodness-of-fit aim to validate the conformity of a postulated model to the data under study. In their standard formulation, however, they do not allow exploring how the hypothesized model deviates from the truth nor do they provide any insight into how the rejected model could be improved to better fit the data. To overcome these shortcomings, we establish a comprehensive framework for goodness-of-fit which naturally integrates modeling, estimation, inference and graphics. In this package, the deviance tests and comparison density plots are performed to conduct the LP smoothed inference, where the letter L denotes nonparametric methods based on quantiles and P stands for polynomials. Simulations methods are used to perform variance estimation, inference and post-selection adjustments. Algeri S. and Zhang X. (2020) <arXiv:2005.13011>.
Imports: LPGraph,LPBkg,truncnorm,nloptr,Hmisc,orthopolynom,polynom
License: GPL-3
LazyData: True
NeedsCompilation: no
Packaged: 2020-11-23 16:14:06 UTC; zxysmacbook
Repository: CRAN
Date/Publication: 2020-11-24 11:30:05 UTC

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New package eBsc with initial version 4.12
Package: eBsc
Type: Package
Title: "Empirical Bayes Smoothing Splines with Correlated Errors"
Version: 4.12
Date: 2020-11-08
Author: Francisco Rosales, Tatyana Krivobokova, Paulo Serra.
Description: Presents a statistical method that uses a recursive algorithm for signal extraction. The method handles a non-parametric estimation for the correlation of the errors. See "Serra", "Krivobokova" and "Rosales" (2018) <arXiv:1812.06948> for details.
License: GPL-2
Imports: Brobdingnag, parallel, nlme, Matrix, MASS, splines, Rcpp
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Maintainer: John Barrera <johnkevinbarrera@gmail.com>
Packaged: 2020-11-24 06:58:41 UTC; john
Repository: CRAN
Date/Publication: 2020-11-24 11:30:02 UTC

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Package tipitaka updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-22

Title: Data and Tools for Analyzing the Pali Canon
Description: Provides access to the complete Pali Canon, or Tipitaka, the canonical scripture for Theravadin Buddhists worldwide. Based on the Chattha Sangayana Tipitaka version 4 (Vipassana Research Institute, 1990).
Author: Dan Zigmond [aut, cre]
Maintainer: Dan Zigmond <djz@shmonk.com>

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Package starnet updated to version 0.0.6 with previous version 0.0.5 dated 2020-11-09

Title: Stacked Elastic Net
Description: Implements stacked elastic net regression (Rauschenberger 2020, <doi:10.1093/bioinformatics/btaa535>). The elastic net generalises ridge and lasso regularisation (Zou 2005, <doi:10.1111/j.1467-9868.2005.00503.x>). Instead of fixing or tuning the mixing parameter alpha, we combine multiple alpha by stacked generalisation (Wolpert 1992 <doi:10.1016/S0893-6080(05)80023-1>).
Author: Armin Rauschenberger [aut, cre]
Maintainer: Armin Rauschenberger <armin.rauschenberger@uni.lu>

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Package SDMtune updated to version 1.1.3 with previous version 1.1.2 dated 2020-10-02

Title: Species Distribution Model Selection
Description: User-friendly framework that enables the training and the evaluation of species distribution models (SDMs). The package implements functions for data driven variable selection and model tuning and includes numerous utilities to display the results. All the functions used to select variables or to tune model hyperparameters have an interactive real-time chart displayed in the 'RStudio' viewer pane during their execution.
Author: Sergio Vignali [aut, cre] (<https://orcid.org/0000-0002-3390-5442>), Arnaud Barras [aut] (<https://orcid.org/0000-0003-0850-6965>), Veronika Braunisch [aut] (<https://orcid.org/0000-0001-7035-4662>), Conservation Biology - University of Bern [fnd]
Maintainer: Sergio Vignali <sergio.vignali@iee.unibe.ch>

Diff between SDMtune versions 1.1.2 dated 2020-10-02 and 1.1.3 dated 2020-11-24

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Package otrimle updated to version 1.6 with previous version 1.3 dated 2019-09-24

Title: Robust Model-Based Clustering
Description: Performs robust cluster analysis allowing for outliers and noise that cannot be fitted by any cluster. The data are modelled by a mixture of Gaussian distributions and a noise component, which is an improper uniform distribution covering the whole Euclidean space. Parameters are estimated by (pseudo) maximum likelihood. This is fitted by a EM-type algorithm. See Coretto and Hennig (2016) <doi:10.1080/01621459.2015.1100996>, and Coretto and Hennig (2017) <https://jmlr.org/papers/v18/16-382.html>.
Author: Pietro Coretto [aut, cre], Christian Hennig [aut]
Maintainer: Pietro Coretto <pcoretto@unisa.it>

Diff between otrimle versions 1.3 dated 2019-09-24 and 1.6 dated 2020-11-24

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Package BlockFeST updated to version 1.8 with previous version 1.6 dated 2018-05-06

Title: Bayesian Calculation of Region-Specific Fixation Index to Detect Local Adaptation
Description: An R implementation of an extension of the 'BayeScan' software (Foll, 2008) <DOI:10.1534/genetics.108.092221> for codominant markers, adding the option to group individual SNPs into pre-defined blocks. A typical application of this new approach is the identification of genomic regions, genes, or gene sets containing one or more SNPs that evolved under directional selection.
Author: Bastian Pfeifer
Maintainer: Bastian Pfeifer <bastianxpfeifer@gmail.com>

Diff between BlockFeST versions 1.6 dated 2018-05-06 and 1.8 dated 2020-11-24

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Package smurf updated to version 1.0.7 with previous version 1.0.6 dated 2020-05-16

Title: Sparse Multi-Type Regularized Feature Modeling
Description: Implementation of the SMuRF algorithm of Devriendt et al. (2018) <arXiv:1810.03136> to fit generalized linear models (GLMs) with multiple types of predictors via regularized maximum likelihood.
Author: Tom Reynkens [aut, cre] (<https://orcid.org/0000-0002-5516-5107>), Sander Devriendt [aut], Katrien Antonio [aut]
Maintainer: Tom Reynkens <tomreynkens@hotmail.com>

Diff between smurf versions 1.0.6 dated 2020-05-16 and 1.0.7 dated 2020-11-24

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Package cubelyr updated to version 1.0.1 with previous version 1.0.0 dated 2020-02-29

Title: A Data Cube 'dplyr' Backend
Description: An implementation of a data cube extracted out of 'dplyr' for backward compatibility.
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

Diff between cubelyr versions 1.0.0 dated 2020-02-29 and 1.0.1 dated 2020-11-24

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Package survParamSim updated to version 0.1.3 with previous version 0.1.2 dated 2020-06-18

Title: Parametric Survival Simulation with Parameter Uncertainty
Description: Perform survival simulation with parametric survival model generated from 'survreg' function in 'survival' package. In each simulation coefficients are resampled from variance-covariance matrix of parameter estimates to capture uncertainty in model parameters. Prediction intervals of Kaplan-Meier estimates and hazard ratio of treatment effect can be further calculated using simulated survival data.
Author: Kenta Yoshida [aut, cre] (<https://orcid.org/0000-0003-4967-3831>), Laurent Claret [aut]
Maintainer: Kenta Yoshida <6.kurabupasu@gmail.com>

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Package SubtypeDrug updated to version 0.1.3 with previous version 0.1.2 dated 2020-09-24

Title: Prioritization of Candidate Cancer Subtype Specific Drugs
Description: A systematic biology tool was developed to prioritize cancer subtype-specific drugs by integrating genetic perturbation, drug action, biological pathway, and cancer subtype. The capabilities of this tool include inferring patient-specific subpathway activity profiles in the context of gene expression profiles with subtype labels, calculating differentially expressed subpathways based on cultured human cells treated with drugs in the 'cMap' (connectivity map) database, prioritizing cancer subtype specific drugs according to drug-disease reverse association score based on subpathway, and visualization of results (Castelo (2013) <doi:10.1186/1471-2105-14-7>; Han et al (2019) <doi:10.1093/bioinformatics/btz894>; Lamb and Justin (2006) <DOI:10.1126/science.1132939>).
Author: Xudong Han, Junwei Han, Chonghui Liu
Maintainer: Junwei Han <hanjunwei1981@163.com>

Diff between SubtypeDrug versions 0.1.2 dated 2020-09-24 and 0.1.3 dated 2020-11-24

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More information about SubtypeDrug at CRAN
Permanent link

New package gwasforest with initial version 1.0.0
Package: gwasforest
Title: Make Forest Plot with GWAS Data
Version: 1.0.0
Authors@R: c( person("Yili", "Xu", email = "yilixu@usc.edu", role = c("aut", "cre")), person("Anqi", "Wang", email = "wanganqi@usc.edu", role = c("aut")))
Description: Extract and reform data from GWAS (genome-wide association study) results, and then make a single integrated forest plot containing multiple windows of which each shows the result of individual SNPs (or other items of interest).
URL: https://github.com/yilixu/gwasforest
BugReports: https://github.com/yilixu/gwasforest/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: colorspace, data.table, dplyr, ggplot2, ggrepel, glue, utils
NeedsCompilation: no
Packaged: 2020-11-22 11:06:46 UTC; yilixu
Author: Yili Xu [aut, cre], Anqi Wang [aut]
Maintainer: Yili Xu <yilixu@usc.edu>
Repository: CRAN
Date/Publication: 2020-11-24 08:30:03 UTC

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Package finbif updated to version 0.3.1 with previous version 0.3.0 dated 2020-04-23

Title: Interface for the 'Finnish Biodiversity Information Facility' API
Description: A programmatic interface to the 'Finnish Biodiversity Information Facility' ('FinBIF') API (<https://api.laji.fi>). 'FinBIF' aggregates Finnish biodiversity data from multiple sources in a single open access portal for researchers, citizen scientists, industry and government. 'FinBIF' allows users of biodiversity information to find, access, combine and visualise data on Finnish plants, animals and microorganisms. The 'finbif' package makes the publicly available data in 'FinBIF' easily accessible to programmers. Biodiversity information is available on taxonomy and taxon occurrence. Occurrence data can be filtered by taxon, time, location and other variables. The data accessed are conveniently preformatted for subsequent analyses.
Author: LUOMUS - Finnish Museum of Natural History [cph], William Morris [aut, cre] (<https://orcid.org/0000-0002-8686-4154>)
Maintainer: William Morris <willi@mmorris.email>

Diff between finbif versions 0.3.0 dated 2020-04-23 and 0.3.1 dated 2020-11-24

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 finbif-0.3.1/finbif/R/variables.R                                                            |    6 
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 finbif-0.3.1/finbif/data/finland_map.rda                                                     |binary
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 finbif-0.3.1/finbif/man/filters.Rd                                                           |    6 
 finbif-0.3.1/finbif/man/finbif-package.Rd                                                    |    2 
 finbif-0.3.1/finbif/man/variables.Rd                                                         |    6 
 finbif-0.3.1/finbif/tests/testthat/test-finbif_occurrence.R                                  |   14 
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New package aRbs with initial version 0.0.1
Package: aRbs
Title: Find Arbitrage Opportunities for Sports Matches
Version: 0.0.1
Authors@R: person("Andrew", "Little", email = "andrewlittlebristol@gmail.com", role = c("aut", "cre"))
Maintainer: Andrew Little <andrewlittlebristol@gmail.com>
Description: Money doesn't grow on trees. Arbitrage opportunities do. Find the best arbitrage opportunities (arbs) in sports matches through <https://www.oddschecker.com/>. This package allows the user to input the URLs of <https://www.oddschecker.com/> subdomains in order to find any opportunities for arbitrage. The majority of the functionality is implemented using the function \code{get_arbs()}. This function first finds all subdomains of the URL entered, then filters to only include those that look like event betting pages. Next, odds are scraped from the various bookmakers listed for that event, before returning combinations of bookmakers, odds or outcomes that could be used for arbitrage. Bets placed subsequently are done so at bettor's risk and we take no responsibility for losses that may occur from use of this package. Odds subject to instantaneous changes.
License: GPL-2
Imports: data.table, crayon, dplyr, progress, stringr, xml2, rvest, purrr, stats
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-11-21 17:24:14 UTC; alittle
Author: Andrew Little [aut, cre]
Repository: CRAN
Date/Publication: 2020-11-24 08:30:06 UTC

More information about aRbs at CRAN
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Package SpatialVx updated to version 0.7-1 with previous version 0.7 dated 2020-09-01

Title: Spatial Forecast Verification
Description: Spatial forecast verification refers to verifying weather forecasts when the verification set (forecast and observations) is on a spatial field, usually a high-resolution gridded spatial field. Most of the functions here require the forecast and observed fields to be gridded and on the same grid. For a thorough review of most of the methods in this package, please see Gilleland et al. (2009) <doi: 10.1175/2009WAF2222269.1>.
Author: Eric Gilleland <EricG@ucar.edu>
Maintainer: Eric Gilleland <EricG@ucar.edu>

Diff between SpatialVx versions 0.7 dated 2020-09-01 and 0.7-1 dated 2020-11-24

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More information about SpatialVx at CRAN
Permanent link

Package rstanemax updated to version 0.1.3 with previous version 0.1.2 dated 2020-06-18

Title: Emax Model Analysis with 'Stan'
Description: Perform sigmoidal Emax model fit using 'Stan' in a formula notation, without writing 'Stan' model code.
Author: Kenta Yoshida [aut, cre] (<https://orcid.org/0000-0003-4967-3831>), Trustees of Columbia University [cph] (src/init.cpp, tools/make_cc.R, R/stanmodels.R)
Maintainer: Kenta Yoshida <6.kurabupasu@gmail.com>

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More information about rstanemax at CRAN
Permanent link

Package prioritizr updated to version 5.0.3 with previous version 5.0.2 dated 2020-07-30

Title: Systematic Conservation Prioritization in R
Description: Conservation prioritization using integer programming techniques. To solve large-scale problems, users should install the 'gurobi' optimizer (available from <https://www.gurobi.com/>).
Author: Jeffrey O Hanson [aut] (<https://orcid.org/0000-0002-4716-6134>), Richard Schuster [aut, cre] (<https://orcid.org/0000-0003-3191-7869>), Nina Morrell [aut], Matthew Strimas-Mackey [aut] (<https://orcid.org/0000-0001-8929-7776>), Matthew E Watts [aut], Peter Arcese [aut] (<https://orcid.org/0000-0002-8097-482X>), Joseph Bennett [aut] (<https://orcid.org/0000-0002-3901-9513>), Hugh P Possingham [aut] (<https://orcid.org/0000-0001-7755-996X>)
Maintainer: Richard Schuster <richard.schuster@glel.carleton.ca>

Diff between prioritizr versions 5.0.2 dated 2020-07-30 and 5.0.3 dated 2020-11-24

 DESCRIPTION                                                |   32 
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 R/misc.R                                                   |   84 
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 R/number_of_total_units.R                                  |  128 
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 R/objectives.R                                             |  192 
 R/package.R                                                |  170 
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 R/portfolios.R                                             |  216 
 R/pproto.R                                                 |  150 
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 R/print.R                                                  |  216 
 R/problem.R                                                | 2010 
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 R/sf.R                                                     |   12 
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 R/solve.R                                                  |  770 
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 R/tbl_df.R                                                 |  148 
 R/waiver.R                                                 |   62 
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 R/zzz.R                                                    |   62 
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Package nonmemica updated to version 0.9.7 with previous version 0.9.6 dated 2020-10-21

Title: Create and Evaluate NONMEM Models in a Project Context
Description: Systematically creates and modifies NONMEM(R) control streams. Harvests NONMEM output, builds run logs, creates derivative data, generates diagnostics. NONMEM (ICON Development Solutions <http://www.iconplc.com/>) is software for nonlinear mixed effects modeling. See 'package?nonmemica'.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

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New package gwer with initial version 2.1
Package: gwer
Type: Package
Title: Geographically Weighted Elliptical Regression
Version: 2.1
Date: 2020-11-23
Author: Yuri A. Araujo, Francisco Jose A. Cysneiros and Audrey H. M. A. Cysneiros
Maintainer: Yuri A. Araujo <yada1@de.ufpe.br>
Description: Computes a elliptical regression model or a geographically weighted regression model with elliptical errors using Fisher's score algorithm. Provides diagnostic measures, residuals and analysis of variance. Cysneiros, F. J. A., Paula, G. A., and Galea, M. (2007) <doi:10.1016/j.spl.2007.01.012>.
Depends: R (>= 2.14), sp (>= 0.8-3), stats
Imports: maptools (>= 0.7-32), Matrix, methods, spData (>= 0.2.6.2), spdep, spgwr, utils, assertthat, glogis, graphics
Suggests: rgdal, parallel
NeedsCompilation: no
License: GPL (>= 2)
RoxygenNote: 7.1.1
Encoding: UTF-8
LazyData: true
Packaged: 2020-11-24 05:01:09 UTC; LoD_B
Repository: CRAN
Date/Publication: 2020-11-24 07:40:02 UTC

More information about gwer at CRAN
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Package extRemes updated to version 2.1 with previous version 2.0-12 dated 2020-05-03

Title: Extreme Value Analysis
Description: General functions for performing extreme value analysis. In particular, allows for inclusion of covariates into the parameters of the extreme-value distributions, as well as estimation through MLE, L-moments, generalized (penalized) MLE (GMLE), as well as Bayes. Inference methods include parametric normal approximation, profile-likelihood, Bayes, and bootstrapping. Some bivariate functionality and dependence checking (e.g., auto-tail dependence function plot, extremal index estimation) is also included. For a tutorial, see Gilleland and Katz (2016) <doi: 10.18637/jss.v072.i08> and for bootstrapping, please see Gilleland (2020) <doi: 10.1175/JTECH-D-20-0070.1>.
Author: Eric Gilleland
Maintainer: Eric Gilleland <ericg@ucar.edu>

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Package broom.helpers updated to version 1.1.0 with previous version 1.0.0 dated 2020-09-18

Title: Helpers for Model Coefficients Tibbles
Description: Provides suite of functions to work with regression model 'broom::tidy()' tibbles. The suite includes functions to group regression model terms by variable, insert reference and header rows for categorical variables, add variable labels, and more.
Author: Joseph Larmarange [aut, cre] (<https://orcid.org/0000-0001-7097-700X>), Daniel D. Sjoberg [aut] (<https://orcid.org/0000-0003-0862-2018>)
Maintainer: Joseph Larmarange <joseph@larmarange.net>

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Package boostmtree updated to version 1.5.0 with previous version 1.4.1 dated 2019-11-21

Title: Boosted Multivariate Trees for Longitudinal Data
Description: Implements Friedman's gradient descent boosting algorithm for modeling longitudinal response using multivariate tree base learners. Longitudinal response could be continuous, binary, nominal or ordinal. A time-covariate interaction effect is modeled using penalized B-splines (P-splines) with estimated adaptive smoothing parameter. Although the package is design for longitudinal data, it can handle cross-sectional data as well. Implementation details are provided in Pande et al. (2017), Mach Learn <DOI:10.1007/s10994-016-5597-1>.
Author: Hemant Ishwaran <hemant.ishwaran@gmail.com>, Amol Pande <amoljpande@gmail.com>
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>

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Package baytrends updated to version 2.0.2 with previous version 1.2.1 dated 2020-03-31

Title: Long Term Water Quality Trend Analysis
Description: Enable users to evaluate long-term trends using a Generalized Additive Modeling (GAM) approach. The model development includes selecting a GAM structure to describe nonlinear seasonally-varying changes over time, incorporation of hydrologic variability via either a river flow or salinity, the use of an intervention to deal with method or laboratory changes suspected to impact data values, and representation of left- and interval-censored data. The approach has been applied to water quality data in the Chesapeake Bay, a major estuary on the east coast of the United States to provide insights to a range of management- and research-focused questions. Methodology described in Murphy (2019) <doi:10.1016/j.envsoft.2019.03.027>.
Author: Rebecca Murphy, Elgin Perry, Jennifer Keisman, Jon Harcum, Erik W Leppo
Maintainer: Erik W Leppo <Erik.Leppo@tetratech.com>

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 baytrends-2.0.2/baytrends/NEWS                                                                  |  218 ++++
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 baytrends-2.0.2/baytrends/R/detrended.flow.R                                                    |    3 
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More information about baytrends at CRAN
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Package fastmatrix updated to version 0.3 with previous version 0.2-3571 dated 2020-10-10

Title: Fast Computation of some Matrices Useful in Statistics
Description: Small set of functions to fast computation of some matrices and operations useful in statistics.
Author: Felipe Osorio [aut, cre] (<https://orcid.org/0000-0002-4675-5201>), Alonso Ogueda [aut]
Maintainer: Felipe Osorio <felipe.osorios@usm.cl>

Diff between fastmatrix versions 0.2-3571 dated 2020-10-10 and 0.3 dated 2020-11-24

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 fastmatrix-0.3/fastmatrix/R/norms.R                     |    4 
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 fastmatrix-0.3/fastmatrix/inst/CITATION                 |    4 
 fastmatrix-0.3/fastmatrix/inst/include/fastmatrix.h     |   34 +
 fastmatrix-0.3/fastmatrix/inst/include/fastmatrix_API.h |  188 ++++++++++
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 fastmatrix-0.3/fastmatrix/src/sherman_morrison.c        |   35 +
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 fastmatrix-0.3/fastmatrix/src/utils.c                   |   24 -
 35 files changed, 791 insertions(+), 238 deletions(-)

More information about fastmatrix at CRAN
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Package funGp updated to version 0.2.1 with previous version 0.2.0 dated 2020-11-17

Title: Gaussian Process Models for Scalar and Functional Inputs
Description: Construction and smart selection of Gaussian process models with emphasis on treatment of functional inputs. This package offers: (i) flexible modeling of functional-input regression problems through the fairly general Gaussian process model; (ii) built-in dimension reduction for functional inputs; (iii) heuristic optimization of the structural parameters of the model (e.g., active inputs, kernel function, type of distance). Metamodeling background is provided in Betancourt et al. (2020) <doi:10.1016/j.ress.2020.106870>. The algorithm for structural parameter optimization is described in <https://hal.archives-ouvertes.fr/hal-02532713>.
Author: Jose Betancourt [cre, aut], François Bachoc [aut], Thierry Klein [aut], Deborah Idier [ctb], Jeremy Rohmer [ctb]
Maintainer: Jose Betancourt <djbetancourt@uninorte.edu.co>

Diff between funGp versions 0.2.0 dated 2020-11-17 and 0.2.1 dated 2020-11-24

 DESCRIPTION          |    8 ++++----
 MD5                  |    8 ++++----
 NEWS.md              |    9 +++++++--
 R/3_ant_admin.R      |    3 +--
 man/get_active_in.Rd |    3 +--
 5 files changed, 17 insertions(+), 14 deletions(-)

More information about funGp at CRAN
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