Sun, 18 Apr 2021

New package trackter with initial version 0.1.1
Package: trackter
Title: Automated Kinematic Analysis of Image Data
Version: 0.1.1
Authors@R: person(given="Christopher", family="Kenaley", email = "cpkenaley@gmail.com", role = c("aut", "cre"))
Description: Analysis of shape and contours in regions of interest (ROIs) in image sequences and extracting midline and other kinematic data.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0),
biocViews:
Imports: EBImage, data.table, dplyr, Momocs, raster, zoo, plyr, pastecs, features, jpeg, ggplot2, graphics, stats, utils
Suggests: testthat (>= 3.0.1), covr, knitr, rmarkdown, animation,
SystemRequirements: FFmpeg
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-14 01:40:51 UTC; biology
Author: Christopher Kenaley [aut, cre]
Maintainer: Christopher Kenaley <cpkenaley@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-18 22:10:02 UTC

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Package mistral updated to version 2.2.1 with previous version 2.1.0 dated 2016-04-03

Title: Methods in Structural Reliability
Description: Various reliability analysis methods for rare event inference:1) computing failure probability (probability that the output of a numerical model exceeds a threshold), 2) computing quantile of low or high-order, 3) Wilks formula to compute quantile(s) from a sample or the size of the required i.i.d. sample.
Author: Clement WALTER, Gilles DEFAUX, Bertrand IOOSS, Vincent MOUTOUSSAMY with contributions from Nicolas BOUSQUET, Claire CANNAMELA and Paul LEMAITRE
Maintainer: Bertrand Iooss <biooss@yahoo.fr>

Diff between mistral versions 2.1.0 dated 2016-04-03 and 2.2.1 dated 2021-04-18

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New package CoTiMA with initial version 0.3.9
Package: CoTiMA
Title: Continuous Time Meta-Analysis ('CoTiMA')
Version: 0.3.9
Date: 2021-04-13
Authors@R: c(person("Christian", "Dormann", role = c("aut","cph")), person("Markus", "Homberg", email = "cotima@uni-mainz.de", role = c("ctb", "com", "cre")), person("Christina", "Guthier", role = c("ctb")), person("Manuel", "Voelkle", role = c("ctb")))
Description: The 'CoTiMA' package performs meta-analyses of correlation matrices of repeatedly measured variables taken from studies that used different time intervals. Different time intervals between measurement occasions impose problems for meta-analyses because the effects (e.g. cross-lagged effects) cannot be simply aggregated, for example, by means of common fixed or random effects analysis. However, continuous time math, which is applied in 'CoTiMA', can be used to extrapolate or intrapolate the results from all studies to any desired time lag. By this, effects obtained in studies that used different time intervals can be meta-analyzed. 'CoTiMA' fits models to empirical data using the structural equation model (SEM) package 'ctsem', the effects specified in a SEM are related to parameters that are not directly included in the model (i.e., continuous time parameters; together, they represent the continuous time structural equation model, CTSEM). Statistical model comparisons and significance tests are then performed on the continuous time parameter estimates. 'CoTiMA' also allows analysis of publication bias (Egger's test, PET-PEESE estimates, zcurve analysis etc.) and analysis of statistical power (post hoc power, required sample sizes). See Dormann, C., Guthier, C., & Cortina, J. M. (2019) <doi:10.1177/1094428119847277>. and Guthier, C., Dormann, C., & Voelkle, M. C. (2020) <doi:10.1037/bul0000304>.
License: GPL-3
URL: https://github.com/CoTiMA/CoTiMA
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), OpenMx (>= 2.18.1), ctsem (>= 3.3.11), lavaan (>= 0.6), foreach (>= 1.5.1)
Imports: MBESS (>= 4.6.0), crayon (>= 1.3.4), psych (>= 1.9.12), doParallel (>= 1.0.15), rootSolve (>= 1.8.2), abind (>= 1.4-5), RPushbullet (>= 0.3.3), openxlsx (>= 4.2.2), zcurve (>= 1.0.7), scholar (>= 0.2.0), stringi (>= 1.0.7), MASS
Suggests: R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2021-04-13 15:39:43 UTC; comst
Author: Christian Dormann [aut, cph], Markus Homberg [ctb, com, cre], Christina Guthier [ctb], Manuel Voelkle [ctb]
Maintainer: Markus Homberg <cotima@uni-mainz.de>
Repository: CRAN
Date/Publication: 2021-04-18 22:20:03 UTC

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Package act updated to version 1.0.2 with previous version 1.0.1 dated 2021-02-22

Title: Aligned Corpus Toolkit
Description: The Aligned Corpus Toolkit (act) is designed for linguists that work with time aligned transcription data. It offers functions to import and export various annotation file formats ('ELAN' .eaf, 'EXMARaLDA .exb and 'Praat' .TextGrid files), create print transcripts in the style of conversation analysis, search transcripts (span searches across multiple annotations, search in normalized annotations, make concordances etc.), export and re-import search results (.csv and 'Excel' .xlsx format), create cuts for the search results (print transcripts, audio/video cuts using 'FFmpeg' and video sub titles in 'Subrib title' .srt format), modify the data in a corpus (search/replace, delete, filter etc.), interact with 'Praat' using 'Praat'-scripts, and exchange data with the 'rPraat' package. The package is itself written in R and may be expanded by other users.
Author: Oliver Ehmer [aut, cre]
Maintainer: Oliver Ehmer <oliver.ehmer@romanistik.uni-freiburg.de>

Diff between act versions 1.0.1 dated 2021-02-22 and 1.0.2 dated 2021-04-18

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New package vcrpart with initial version 1.0-4
Package: vcrpart
Title: Tree-Based Varying Coefficient Regression for Generalized Linear and Ordinal Mixed Models
Version: 1.0-4
Date: 2021-04-15
Authors@R: c( person("Reto", "Buergin", role = c("aut", "cre", "cph"), email = "rbuergin@gmx.ch"), person("Gilbert", "Ritschard", role = c("ctb", "ths"), email = "gilbert.ritschard@unige.ch"))
Maintainer: Reto Buergin <rbuergin@gmx.ch>
Description: Recursive partitioning for varying coefficient generalized linear models and ordinal linear mixed models. Special features are coefficient-wise partitioning, non-varying coefficients and partitioning of time-varying variables in longitudinal regression.
License: GPL (>= 2)
Depends: R (>= 3.1.0), parallel, partykit
Imports: stats, grid, graphics, methods, nlme (>= 3.1-123), rpart, formula.tools, numDeriv, ucminf, zoo, sandwich, strucchange
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2021-04-16 10:21:27 UTC; reto
Author: Reto Buergin [aut, cre, cph], Gilbert Ritschard [ctb, ths]
Repository: CRAN
Date/Publication: 2021-04-18 21:40:02 UTC

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Package TensorTest2D updated to version 1.0.1 with previous version 1.0.0 dated 2020-11-05

Title: Fitting Second-Order Tensor Data
Description: An implementation of fitting generalized linear models on second-order tensor type data. The functions within this package mainly focus on parameter estimation, including parameter coefficients and standard deviation.
Author: Mark Chen [aut, cre], Sheng-Mao Chang [aut], Wenbin Lu [aut], Jung-Ying Tzeng [aut]
Maintainer: Mark Chen <l501l501l@gmail.com>

Diff between TensorTest2D versions 1.0.0 dated 2020-11-05 and 1.0.1 dated 2021-04-18

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Package SPOT updated to version 2.4.2 with previous version 2.3.0 dated 2021-03-10

Title: Sequential Parameter Optimization Toolbox
Description: A set of tools for model-based optimization and tuning of algorithms. It includes surrogate models, optimizers, and design of experiment approaches. The main interface is spot, which uses sequentially updated surrogate models for the purpose of efficient optimization. The main goal is to ease the burden of objective function evaluations, when a single evaluation requires a significant amount of resources.
Author: Thomas Bartz-Beielstein [aut, cre] (<https://orcid.org/0000-0002-5938-5158>), Joerg Stork [aut] (0000-0002-7471-3498), Martin Zaefferer [aut] (<https://orcid.org/0000-0003-2372-2092>), Margarita Rebolledo [ctb], Christian Lasarczyk [ctb], Frederik Rehbach [aut] (<https://orcid.org/0000-0003-0922-8629>)
Maintainer: Thomas Bartz-Beielstein <tbb@bartzundbartz.de>

Diff between SPOT versions 2.3.0 dated 2021-03-10 and 2.4.2 dated 2021-04-18

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Package sperrorest updated to version 3.0.2 with previous version 3.0.1 dated 2020-05-26

Title: Perform Spatial Error Estimation and Variable Importance in Parallel
Description: Implements spatial error estimation and permutation-based variable importance measures for predictive models using spatial cross-validation and spatial block bootstrap.
Author: Alexander Brenning [aut, cre] (<https://orcid.org/0000-0001-6640-679X>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Tobias Herrmann [aut] (<https://orcid.org/0000-0001-9768-0708>)
Maintainer: Alexander Brenning <alexander.brenning@uni-jena.de>

Diff between sperrorest versions 3.0.1 dated 2020-05-26 and 3.0.2 dated 2021-04-18

 DESCRIPTION                                   |   10 
 MD5                                           |   28 -
 NEWS.md                                       |   14 
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Package spatstat.core updated to version 2.1-2 with previous version 2.0-0 dated 2021-03-23

Title: Core Functionality of the 'spatstat' Family
Description: Functionality for data analysis and modelling of spatial data, mainly spatial point patterns, in the 'spatstat' family of packages. (Excludes analysis of spatial data on a linear network, which is covered by the separate package 'spatstat.linnet'.) Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.
Author: Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut], Kasper Klitgaard Berthelsen [ctb], Achmad Choiruddin [ctb], Jean-Francois Coeurjolly [ctb], Ottmar Cronie [ctb], Tilman Davies [ctb], Julian Gilbey [ctb], Yongtao Guan [ctb], Ute Hahn [ctb], Kassel Hingee [ctb], Abdollah Jalilian [ctb], Marie-Colette van Lieshout [ctb], Greg McSwiggan [ctb], Tuomas Rajala [ctb], Suman Rakshit [ctb], Dominic Schuhmacher [ctb], Rasmus Plenge Waagepetersen [ctb], Hangsheng Wang [ctb]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

Diff between spatstat.core versions 2.0-0 dated 2021-03-23 and 2.1-2 dated 2021-04-18

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More information about spatstat.core at CRAN
Permanent link

Package soilDB updated to version 2.6.1 with previous version 2.5.9 dated 2021-01-26

Title: Soil Database Interface
Description: A collection of functions for reading data from USDA-NCSS soil databases.
Author: Dylan Beaudette [aut], Jay Skovlin [aut], Stephen Roecker [aut], Andrew Brown [aut, cre]
Maintainer: Andrew Brown <andrew.g.brown@usda.gov>

Diff between soilDB versions 2.5.9 dated 2021-01-26 and 2.6.1 dated 2021-04-18

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More information about soilDB at CRAN
Permanent link

Package SGPdata updated to version 25.0-0.0 with previous version 23.0-0.0 dated 2020-01-15

Title: Exemplar Data Sets for Student Growth Percentiles (SGP) Analyses
Description: Data sets utilized by the 'SGP' package as exemplars for users to conduct their own student growth percentiles (SGP) analyses.
Author: Damian W. Betebenner [aut, cre], Adam R. Van Iwaarden [aut], Ben Domingue [aut]
Maintainer: Damian W. Betebenner <dbetebenner@nciea.org>

Diff between SGPdata versions 23.0-0.0 dated 2020-01-15 and 25.0-0.0 dated 2021-04-18

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Package outsider.base updated to version 0.1.4 with previous version 0.1.3 dated 2020-06-14

Title: Base Package for 'Outsider'
Description: Base package for 'outsider' <https://github.com/ropensci/outsider>. The 'outsider' package and its sister packages enable the installation and running of external, command-line software within R. This base package is a key dependency of the user-facing 'outsider' package as it provides the utilities for interfacing between 'Docker' <https://www.docker.com> and R. It is intended that end-users of 'outsider' do not directly work with this base package.
Author: Dom Bennett [aut, cre] (<https://orcid.org/0000-0003-2722-1359>), Hannes Hettling [ctb] (<https://orcid.org/0000-0003-4144-2238>), Daniele Silvestro [ctb] (<https://orcid.org/0000-0003-0100-0961>), Rutger Vos [ctb] (<https://orcid.org/0000-0001-9254-7318>), Alexandre Antonelli [ctb] (<https://orcid.org/0000-0003-1842-9297>), Anna Krystalli [rev]
Maintainer: Dom Bennett <dominic.john.bennett@gmail.com>

Diff between outsider.base versions 0.1.3 dated 2020-06-14 and 0.1.4 dated 2021-04-18

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More information about outsider.base at CRAN
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Package MetabolomicsBasics updated to version 1.2 with previous version 1.1 dated 2018-11-12

Title: Basic Functions to Investigate Metabolomics Data Matrices
Description: A set of functions to investigate raw data from (metabol)omics experiments intended to be used on a raw data matrix, i.e. following peak picking and signal deconvolution. Functions can be used to normalize data, detect biomarkers and perform sample classification.
Author: Jan Lisec [aut, cre]
Maintainer: Jan Lisec <jan.lisec@bam.de>

Diff between MetabolomicsBasics versions 1.1 dated 2018-11-12 and 1.2 dated 2021-04-18

 DESCRIPTION                     |   11 ++++----
 MD5                             |   51 ++++++++++++++++++++++------------------
 NAMESPACE                       |    5 +++
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New package LSTS with initial version 2.0
Package: LSTS
Title: Locally Stationary Time Series
Version: 2.0
Authors@R: c( person("Ricardo", "Olea", role = c("aut", "cph"), email = "raolea@uc.cl"), person("Wilfredo", "Palma", role = c("aut", "cph"), email = "wpalma@uc.cl"), person("Pilar", "Rubio", role = c("aut"), email = "parubio@puc.cl"), person("Mauricio", "Vargas", role = c("aut", "cre"), email = "mavargas11@uc.cl", comment = c(ORCID = "0000-0003-1017-7574")), person(family = "National Oceanic and Atmospheric Administration (NOAA)", role = c("dtc")) )
Description: A set of functions that allow stationary analysis and locally stationary time series analysis. The principal references are Dahlhaus (1997) <doi:10.1214/aos/1034276620>, Dahlhaus and Giraitis (1998) <doi:10.1111/1467-9892.00114>, Brockwell, et al. (2002) <isbn:978-3-319-29854-2>, Ljung and Box (1978) <doi:10.1093/biomet/65.2.297>, Palma (2007) <isbn:978-0-470-11402-5>, Palma, et al. (2011) <doi:10.1002/for.1259>, and Palma and Olea (2010) <doi:10.1214/10-AOS812>.
URL: https://pacha.dev/LSTS/
BugReports: https://github.com/pachamaltese/LSTS/issues/
Imports: stats, Rdpack, ggplot2, scales, patchwork
RdMacros: Rdpack
Depends: R (>= 3.6.0)
License: Apache License (>= 2)
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2021-04-07 18:52:37 UTC; pacha
Author: Ricardo Olea [aut, cph], Wilfredo Palma [aut, cph], Pilar Rubio [aut], Mauricio Vargas [aut, cre] (<https://orcid.org/0000-0003-1017-7574>), National Oceanic and Atmospheric Administration (NOAA) [dtc]
Maintainer: Mauricio Vargas <mavargas11@uc.cl>
Repository: CRAN
Date/Publication: 2021-04-18 21:50:18 UTC

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New package KODAMA with initial version 1.6
Package: KODAMA
Version: 1.6
Date: 2021-04-16
Authors@R: c(person("Stefano", "Cacciatore", role = c("aut", "trl", "cre"),email = "tkcaccia@gmail.com", comment = c(ORCID = "0000-0001-7052-7156")), person("Leonardo", "Tenori", role = "aut",email = "tenori@cerm.unifi.it", comment = c(ORCID = "0000-0001-6438-059X")))
Maintainer: Stefano Cacciatore <tkcaccia@gmail.com>
Title: Knowledge Discovery by Accuracy Maximization
Description: An unsupervised and semi-supervised learning algorithm that performs feature extraction from noisy and high-dimensional data. It facilitates identification of patterns representing underlying groups on all samples in a data set. Based on Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA. (2017) Bioinformatics <doi:10.1093/bioinformatics/btw705> and Cacciatore S, Luchinat C, Tenori L. (2014) Proc Natl Acad Sci USA <doi:10.1073/pnas.1220873111>.
Depends: R (>= 2.10.0), stats
Imports: Rcpp (>= 0.12.4)
LinkingTo: Rcpp, RcppArmadillo
Suggests: rgl, knitr, rmarkdown
VignetteBuilder: knitr
SuggestsNote: No suggestions
License: GPL (>= 2)
Packaged: 2021-04-16 11:10:21 UTC; stefano
NeedsCompilation: yes
Repository: CRAN
Author: Stefano Cacciatore [aut, trl, cre] (<https://orcid.org/0000-0001-7052-7156>), Leonardo Tenori [aut] (<https://orcid.org/0000-0001-6438-059X>)
Date/Publication: 2021-04-18 22:00:13 UTC

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Package ffscrapr updated to version 1.4.1 with previous version 1.4.0 dated 2021-04-13

Title: API Client for Fantasy Football League Platforms
Description: Helps access various Fantasy Football APIs by handling authentication and rate-limiting, forming appropriate calls, and returning tidy dataframes which can be easily connected to other data sources.
Author: Tan Ho [aut, cre], Tony ElHabr [ctb], Joe Sydlowski [ctb]
Maintainer: Tan Ho <tan@tanho.ca>

Diff between ffscrapr versions 1.4.0 dated 2021-04-13 and 1.4.1 dated 2021-04-18

 DESCRIPTION                             |    7 +-
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Package climate updated to version 1.0.0 with previous version 0.9.9 dated 2021-01-08

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

Diff between climate versions 0.9.9 dated 2021-01-08 and 1.0.0 dated 2021-04-18

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 climate-1.0.0/climate/R/test_url.R                   |    2 
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 47 files changed, 357 insertions(+), 311 deletions(-)

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New package chronosphere with initial version 0.4.1
Package: chronosphere
Title: Earth System History Variables
Version: 0.4.1
Author: Adam T. Kocsis, Nussaibah B. Raja
Collate: zzz.R classes.R data.R colours.R reconstruction.R utility.R platemodel.R fetching.R info.R XArray-base.R XArray-combine.R XArray-xattrib.R XArray-subset.R XArray-apply.R RasterArray-base.R RasterArray-cast.R RasterArray-combine.R RasterArray-groupgen.R RasterArray-raster.R RasterArray-subset.R RasterArray-xattrib.R SpatialStack-base.R SpatialStack-sp.R SpatialStack-subset.R SpatialArray-base.R SpatialArray-sp.R SpatialArray-cast.R SpatialArray-combine.R SpatialArray-subset.R inter.R plotting.R
Maintainer: Adam T. Kocsis <adam.t.kocsis@gmail.com>
Description: The purpose of the 'chronosphere' project is to facilitate spatially explicit analyses of (paleo)environmental/ecological research. The package serves as a gateway to plate tectonic reconstructions, deep time global climate model results as well as fossil occurrence datasets such as the Paleobiology Database <https://paleobiodb.org/> and the PaleoReefs Database <https://www.paleo-reefs.pal.uni-erlangen.de/>. Environmental data stored on a remote server can be downloaded and imported directly to the R environment. Query functions to the GPlates <https://www.gplates.org/> desktop application or the GPlates Web Service <https://gws.gplates.org/> allow users to reconstruct coordinates, static plates, and Spatial objects. A wrapper class 'RasterArray' is implemented around the 'RasterLayer' class, allowing the organization of spatially explicit raster data in n-dimensional arrays. The project is developed under the umbrella of the DFG (Deutsche Forschungsgemeinschaft) Research Unit TERSANE2 (For 2332, TEmperature Related Stressors in ANcient Extinctions).
License: CC BY 4.0
Date: 2021-04-16
BugReports: https://github.com/chronosphere-portal/r_package/issues
Encoding: UTF-8
LazyData: false
Depends: R (>= 3.5.0), raster, sp
Imports: graphics, methods, grDevices, utils
NeedsCompilation: no
VignetteBuilder: knitr
Suggests: jpeg, knitr, ncdf4, rgdal, rmarkdown
Packaged: 2021-04-16 13:17:09 UTC; root
Repository: CRAN
Date/Publication: 2021-04-18 21:50:07 UTC

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New package bigalgebra with initial version 1.0.0
Package: bigalgebra
Title: 'BLAS' and 'LAPACK' Routines for Native R Matrices and 'big.matrix' Objects
Version: 1.0.0
Date: 2021-04-13
Depends: bigmemory (>= 4.0.0)
Imports: methods
LinkingTo: bigmemory, BH, Rcpp
Authors@R: c( person(given = "Frederic", family= "Bertrand", role = c("cre", "ctb"), email = "frederic.bertrand@utt.fr", comment = c(ORCID = "0000-0002-0837-8281")), person(given = "Michael J.", family= "Kane", role = c("aut")), person(given = "Bryan", family= "Lewis", role = c("aut")), person(given = "John W.", family= "Emerson", role = c("aut")))
Author: Frederic Bertrand [cre, ctb] (<https://orcid.org/0000-0002-0837-8281>), Michael J. Kane [aut], Bryan Lewis [aut], John W. Emerson [aut]
Maintainer: Frederic Bertrand <frederic.bertrand@utt.fr>
Description: Provides arithmetic functions for R matrix and 'big.matrix' objects as well as functions for QR factorization, Cholesky factorization, General eigenvalue, and Singular value decomposition (SVD). A method matrix multiplication and an arithmetic method -for matrix addition, matrix difference- allows for mixed type operation -a matrix class object and a big.matrix class object- and pure type operation for two big.matrix class objects.
License: LGPL-3 | Apache License 2.0
Encoding: UTF-8
Copyright: (C) 2014 Michael J. Kane, Bryan Lewis, and John W. Emerson
LazyLoad: yes
NeedsCompilation: yes
URL: https://fbertran.github.io/bigalgebra/, https://github.com/fbertran/bigalgebra/
BugReports: https://github.com/fbertran/bigalgebra/issues/
Packaged: 2021-04-16 10:43:31 UTC; fbertran
Repository: CRAN
Date/Publication: 2021-04-18 22:00:07 UTC

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New package ausplotsR with initial version 1.2.4
Package: ausplotsR
Title: TERN AusPlots Analysis Package
Version: 1.2.4
Date: 2021-4-15
Authors@R: c( person("Greg", "Guerin", email = "ggueri01@gmail.com", role = c("aut", "cre")), person("Tom", "Saleeba", role = "aut"), person("Samantha", "Munroe", role = "aut"), person("Bernardo", "Blanco-Martin", role="aut"), person("Irene", "Martín-Forés", role = "aut"), person("Andrew", "Tokmakoff", role = "aut"))
Maintainer: Greg Guerin <ggueri01@gmail.com>
Depends: R (>= 3.1.0), vegan, maps, mapdata
Suggests: knitr, rmarkdown
Imports: plyr, R.utils, simba, httr, jsonlite, sp, maptools, ggplot2, gtools, jose, betapart, curl
Description: Extraction, preparation, visualisation and analysis of TERN AusPlots ecosystem monitoring data. Direct access to plot-based data on vegetation and soils across Australia, including physical sample barcode numbers. Simple function calls extract the data and merge them into species occurrence matrices for downstream analysis, or calculate things like basal area and fractional cover. TERN AusPlots is a national field plot-based ecosystem surveillance monitoring method and dataset for Australia. The data have been collected across a national network of plots and transects by the Terrestrial Ecosystem Research Network (TERN - <https://www.tern.org.au>), an Australian Government NCRIS-enabled project, and its Ecosystem Surveillance platform (<https://www.tern.org.au/tern-observatory/tern-ecosystem-surveillance/>).
License: GPL-3
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-16 08:00:51 UTC; GregG
Author: Greg Guerin [aut, cre], Tom Saleeba [aut], Samantha Munroe [aut], Bernardo Blanco-Martin [aut], Irene Martín-Forés [aut], Andrew Tokmakoff [aut]
Repository: CRAN
Date/Publication: 2021-04-18 22:00:10 UTC

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Package spsur updated to version 1.0.1.8 with previous version 1.0.1.7 dated 2021-04-09

Title: Spatial Seemingly Unrelated Regression Models
Description: A collection of functions to test and estimate Seemingly Unrelated Regression (usually called SUR) models, with spatial structure, by maximum likelihood and three-stage least squares. The package estimates the most common spatial specifications, that is, SUR with Spatial Lag of X regressors (called SUR-SLX), SUR with Spatial Lag Model (called SUR-SLM), SUR with Spatial Error Model (called SUR-SEM), SUR with Spatial Durbin Model (called SUR-SDM), SUR with Spatial Durbin Error Model (called SUR-SDEM), SUR with Spatial Autoregressive terms and Spatial Autoregressive Disturbances (called SUR-SARAR), SUR-SARAR with Spatial Lag of X regressors (called SUR-GNM) and SUR with Spatially Independent Model (called SUR-SIM). The methodology of these models can be found in next references Mur, J., Lopez, F., and Herrera, M. (2010) <doi:10.1080/17421772.2010.516443> Lopez, F.A., Mur, J., and Angulo, A. (2014) <doi:10.1007/s00168-014-0624-2>.
Author: Ana Angulo [aut], Fernando A Lopez [aut], Roman Minguez [aut, cre], Jesus Mur [aut]
Maintainer: Roman Minguez <roman.minguez@uclm.es>

Diff between spsur versions 1.0.1.7 dated 2021-04-09 and 1.0.1.8 dated 2021-04-18

 DESCRIPTION                       |    8 
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 NAMESPACE                         |    2 
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 R/lr_betas.R                      |    1 
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 29 files changed, 6514 insertions(+), 6533 deletions(-)

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Package PAMA updated to version 1.0.1 with previous version 1.0.0 dated 2021-04-14

Title: Rank Aggregation with Partition Mallows Model
Description: Rank aggregation aims to achieve a better ranking list given multiple observations. 'PAMA' implements Partition-Mallows model for rank aggregation where the rankers' quality are different. Both Bayesian inference and Maximum likelihood estimation (MLE) are provided. It can handle partial list as well. When covariates information is available, this package can make inference by incorporating the covariate information. More information can be found in the paper "Integrated Partition-Mallows Model and Its Inference for Rank Aggregation".
Author: Wanchuang Zhu [cre, aut]
Maintainer: Wanchuang Zhu <andy.chou.sub@gmail.com>

Diff between PAMA versions 1.0.0 dated 2021-04-14 and 1.0.1 dated 2021-04-18

 DESCRIPTION     |    8 ++++----
 MD5             |   22 +++++++++++-----------
 R/NBANFL.R      |    9 ++++++++-
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 R/PAMA.PL.R     |    2 +-
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 12 files changed, 51 insertions(+), 35 deletions(-)

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New package latticeDensity with initial version 1.2.6
Package: latticeDensity
Title: Density Estimation and Nonparametric Regression on Irregular Regions
Version: 1.2.6
Date: 2021-04-14
Author: Ronald Barry <rpbarry@alaska.edu>
Maintainer: Ronald Barry <rpbarry@alaska.edu>
Depends: R (>= 3.5.0), spatstat (>= 2.0-0), spatstat.geom
Imports: splancs, spdep, spam, stats, utils, graphics, grDevices, sp, spatialreg, sf
LazyData: true
Suggests: knitr, devtools, roxygen2, testthat, rmarkdown, rgdal
Encoding: UTF-8
Description: Functions that compute the lattice-based density estimator of Barry and McIntyre, which accounts for point processes in two-dimensional regions with irregular boundaries and holes. The package also implements two-dimensional non-parametric regression for similar regions.
License: GPL-2
URL: www.r-project.org
Packaged: 2021-04-18 02:48:41 UTC; ronaldbarry
Repository: CRAN
Date/Publication: 2021-04-18 16:20:02 UTC
VignetteBuilder: knitr
NeedsCompilation: no

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New package ForestTools with initial version 0.2.4
Package: ForestTools
Title: Analyzing Remotely Sensed Forest Data
Version: 0.2.4
Date: 2021-04-12
Author: Andrew Plowright, Jean-Romain Roussel
Maintainer: Andrew Plowright <andrew.plowright@alumni.ubc.ca>
Description: Provides tools for analyzing remotely sensed forest data, including functions for detecting treetops from canopy models, outlining tree crowns, calculating textural metrics and generating spatial statistics.
Depends: R (>= 4.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: APfun, doParallel, foreach, imager, methods, parallel, plyr, progress, raster, Rcpp, rgeos, sp
Suggests: testthat, knitr, rmarkdown
URL: https://github.com/andrew-plowright/ForestTools
BugReports: https://github.com/andrew-plowright/ForestTools/issues
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-04-17 04:32:19 UTC; andre
Repository: CRAN
Date/Publication: 2021-04-18 16:30:05 UTC

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Permanent link

New package bRacatus with initial version 1.0.3
Package: bRacatus
Title: A Method to Estimate the Accuracy and Biogeographical Status of Georeferenced Biological Data
Version: 1.0.3
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 = "aut"), person("Patrick","Weigelt",email = "weigelt.patrick@gmail.com", role = "ctb"), person("Sam","Levin",email = "sam.levin@idiv.de", role = "ctb"), person("Carsten","Meyer",email = "carsten.meyer@idiv.de", role = "ths"))
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
License: GPL (>= 2)
Encoding: UTF-8
URL: https://github.com/EduardoArle/bRacatus
BugReports: https://github.com/EduardoArle/bRacatus/issues
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-17 16:26:24 UTC; ca13kute
Author: Eduardo Arlé [aut, cre], Alexander Zizka [aut], Patrick Weigelt [ctb], Sam Levin [ctb], Carsten Meyer [ths]
Maintainer: Eduardo Arlé <eduardo.arle@idiv.de>
Repository: CRAN
Date/Publication: 2021-04-18 16:30:02 UTC

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Package jrvFinance updated to version 1.4.2 with previous version 1.4.1 dated 2019-03-15

Title: Basic Finance; NPV/IRR/Annuities/Bond-Pricing; Black Scholes
Description: Implements the basic financial analysis functions similar to (but not identical to) what is available in most spreadsheet software. This includes finding the IRR and NPV of regularly spaced cash flows and annuities. Bond pricing and YTM calculations are included. In addition, Black Scholes option pricing and Greeks are also provided.
Author: Jayanth Varma [aut, cre]
Maintainer: Jayanth Varma <jrvarma@iima.ac.in>

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Package spinifex updated to version 0.2.8 with previous version 0.2.7 dated 2020-11-18

Title: Manual Tours, Manual Control of Dynamic Projections of Numeric Multivariate Data
Description: Data visualization tours animates linear projection of multivariate data as its basis (ie. orientation) changes. The 'spinifex' packages generates paths for manual tours by manipulating the contribution of a single variable at a time ['Cook' & 'Buja' (1997) <doi:10.2307/1390747>]. Other types of tours, such as grand (random walk) and guided (optimizing some objective function) are available in the 'tourr' package ['Wickham' 'et' 'al.' (2011) <doi:10.18637/jss.v040.i02>]. 'spinifex' builds on 'tourr' and can render tours with 'gganimate' and 'plotly' graphics, and allows for exporting as an .html widget and as an .gif, respectively. This work is fully discussed at ['Spyrison' & 'Cook' (2020) <doi:10.32614/RJ-2020-027>.
Author: Nicholas Spyrison [aut, cre], Dianne Cook [aut, ths]
Maintainer: Nicholas Spyrison <spyrison@gmail.com>

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Package rMVP updated to version 1.0.6 with previous version 1.0.5 dated 2021-03-02

Title: Memory-Efficient, Visualize-Enhanced, Parallel-Accelerated GWAS Tool
Description: A memory-efficient, visualize-enhanced, parallel-accelerated Genome-Wide Association Study (GWAS) tool. It can (1) effectively process large data, (2) rapidly evaluate population structure, (3) efficiently estimate variance components several algorithms, (4) implement parallel-accelerated association tests of markers three methods, (5) globally efficient design on GWAS process computing, (6) enhance visualization of related information. 'rMVP' contains three models GLM (Alkes Price (2006) <DOI:10.1038/ng1847>), MLM (Jianming Yu (2006) <DOI:10.1038/ng1702>) and FarmCPU (Xiaolei Liu (2016) <doi:10.1371/journal.pgen.1005767>); variance components estimation methods EMMAX (Hyunmin Kang (2008) <DOI:10.1534/genetics.107.080101>;), FaSTLMM (method: Christoph Lippert (2011) <DOI:10.1038/nmeth.1681>, R implementation from 'GAPIT2': You Tang and Xiaolei Liu (2016) <DOI:10.1371/journal.pone.0107684> and 'SUPER': Qishan Wang and Feng Tian (2014) <DOI:10.1371/journal.pone.0107684>), and HE regression (Xiang Zhou (2017) <DOI:10.1214/17-AOAS1052>).
Author: Lilin Yin [aut], Haohao Zhang [aut], Zhenshuang Tang [aut], Jingya Xu [aut], Dong Yin [aut], Zhiwu Zhang [aut], Xiaohui Yuan [aut], Mengjin Zhu [aut], Shuhong Zhao [aut], Xinyun Li [aut], Qishan Wang [ctb], Feng Tian [ctb], Hyunmin Kang [ctb], Xiang Zhou [ctb], Xiaolei Liu [cre, aut, cph]
Maintainer: Xiaolei Liu <xiaoleiliu@mail.hzau.edu.cn>

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Package rdnb updated to version 0.1-4 with previous version 0.1-3 dated 2019-04-10

Title: R Interface to the 'Deutsche Nationalbibliothek (German National Library) API'
Description: A wrapper for the 'Deutsche Nationalbibliothek (German National Library) API', available at <https://www.dnb.de>. The German National Library is the German central archival library, collecting, archiving, bibliographically classifying all German and German-language publications, foreign publications about Germany, translations of German works, and the works of German-speaking emigrants published abroad between 1933 and 1945.
Author: Christian Graul [aut, cre]
Maintainer: Christian Graul <christian.graul@gmail.com>

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Package IDSA updated to version 2.1 with previous version 1.2 dated 2021-01-28

Title: An Interactive Detector for Spatial Associations
Description: Method of interactive detector for spatial associations (IDSA) as described in Yongze Song (2021) <doi:10.1080/13658816.2021.1882680>. IDSA is used to quantify the power of interactive determinant (PID) between a spatial response variable and explanatory variables. IDSA is developed based on methods of spatial heterogeneity.
Author: Yongze Song [aut, cre] (<https://orcid.org/0000-0003-3420-9622>)
Maintainer: Yongze Song <yongze.song@postgrad.curtin.edu.au>

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Package mistat updated to version 2.0.3 with previous version 1.0-5 dated 2018-01-08

Title: Data Sets, Functions and Examples from the Book: "Modern Industrial Statistics" by Kenett, Zacks and Amberti
Description: Provide all the data sets and statistical analysis applications used in "Modern Industrial Statistics: with applications in R, MINITAB and JMP" by R.S. Kenett and S. Zacks with contributions by D. Amberti, John Wiley and Sons, 2021, which is a third revised and expanded revision of "Modern Industrial Statistics: Design and Control of Quality and Reliability", R. Kenett and S. Zacks, Duxbury/Wadsworth Publishing, 1998.
Author: Daniele Amberti
Maintainer: Daniele Amberti <daniele.amberti@gmail.com>

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Package Rvmmin updated to version 2018-4.17.1 with previous version 2018-4.17 dated 2018-04-17

Title: Variable Metric Nonlinear Function Minimization
Description: Variable metric nonlinear function minimization with bounds constraints.
Author: John C. Nash [aut, cre]
Maintainer: John C. Nash <nashjc@uottawa.ca>

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Package ramcmc updated to version 0.1.1 with previous version 0.1.0-1.1 dated 2020-10-14

Title: Robust Adaptive Metropolis Algorithm
Description: Function for adapting the shape of the random walk Metropolis proposal as specified by robust adaptive Metropolis algorithm by Vihola (2012) <DOI:10.1007/s11222-011-9269-5>. The package also includes fast functions for rank-one Cholesky update and downdate. These functions can be used directly from R or the corresponding C++ header files can be easily linked to other R packages.
Author: Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>)
Maintainer: Jouni Helske <jouni.helske@iki.fi>

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Package withr updated to version 2.4.2 with previous version 2.4.1 dated 2021-01-26

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

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Package Rdimtools updated to version 1.0.6 with previous version 1.0.4 dated 2020-09-07

Title: Dimension Reduction and Estimation Methods
Description: We provide linear and nonlinear dimension reduction techniques. Intrinsic dimension estimation methods for exploratory analysis are also provided. For more details on the package, see the paper by You (2020) <arXiv:2005.11107>.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>), Changhee Suh [ctb]
Maintainer: Kisung You <kyoustat@gmail.com>

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Package mgcv updated to version 1.8-35 with previous version 1.8-34 dated 2021-02-16

Title: Mixed GAM Computation Vehicle with Automatic Smoothness Estimation
Description: Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) <doi:10.1201/9781315370279> for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.
Author: Simon Wood <simon.wood@r-project.org>
Maintainer: Simon Wood <simon.wood@r-project.org>

Diff between mgcv versions 1.8-34 dated 2021-02-16 and 1.8-35 dated 2021-04-18

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Package mc2d updated to version 0.1-19 with previous version 0.1-18 dated 2017-03-06

Title: Tools for Two-Dimensional Monte-Carlo Simulations
Description: A complete framework to build and study Two-Dimensional Monte-Carlo simulations, aka Second-Order Monte-Carlo simulations. Also includes various distributions (pert, triangular, Bernoulli, empirical discrete and continuous).
Author: Regis Pouillot [aut, cre], Marie-Laure Delignette-Muller [ctb], Jean-Baptiste Denis [ctb]
Maintainer: Regis Pouillot <rpouillot@yahoo.fr>

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

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

2020-10-01 1.0.0

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Package tibble updated to version 3.1.1 with previous version 3.1.0 dated 2021-02-25

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

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Package filesstrings updated to version 3.2.2 with previous version 3.2.1 dated 2020-10-18

Title: Handy File and String Manipulation
Description: This started out as a package for file and string manipulation. Since then, the 'fs' and 'strex' packages emerged, offering functionality previously given by this package (but it's done better in these new ones). Those packages have hence almost pushed 'filesstrings' into extinction. However, it still has a small number of unique, handy file manipulation functions which can be seen in the vignette. One example is a function to remove spaces from all file names in a directory.
Author: Rory Nolan [aut, cre, cph] (<https://orcid.org/0000-0002-5239-4043>), Sergi Padilla-Parra [ths] (<https://orcid.org/0000-0002-8010-9481>)
Maintainer: Rory Nolan <rorynoolan@gmail.com>

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Package cvCovEst updated to version 0.3.5 with previous version 0.3.4 dated 2021-03-06

Title: Cross-Validated Covariance Matrix Estimation
Description: An efficient cross-validated approach for covariance matrix estimation, particularly useful in high-dimensional settings. This method relies upon the theory of loss-based estimator selection to identify the optimal estimator of the covariance matrix from among a prespecified set of candidates.
Author: Philippe Boileau [aut, cre, cph] (<https://orcid.org/0000-0002-4850-2507>), Nima Hejazi [aut] (<https://orcid.org/0000-0002-7127-2789>), Brian Collica [aut], Jamarcus Liu [ctb], Mark van der Laan [ctb, ths] (<https://orcid.org/0000-0003-1432-5511>), Sandrine Dudoit [ctb, ths] (<https://orcid.org/0000-0002-6069-8629>)
Maintainer: Philippe Boileau <philippe_boileau@berkeley.edu>

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Package autoplotly updated to version 0.1.4 with previous version 0.1.3 dated 2021-04-16

Title: Automatic Generation of Interactive Visualizations for Statistical Results
Description: Functionalities to automatically generate interactive visualizations for statistical results supported by 'ggfortify', such as time series, PCA, clustering and survival analysis, with 'plotly.js' <https://plotly.com/> and 'ggplot2' style. The generated visualizations can also be easily extended using 'ggplot2' and 'plotly' syntax while staying interactive.
Author: Yuan Tang [aut, cre] (<https://orcid.org/0000-0001-5243-233X>)
Maintainer: Yuan Tang <terrytangyuan@gmail.com>

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Package geysertimes (with last version 0.1.5) was removed from CRAN

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

2021-04-10 0.1.5
2021-01-18 0.1.2

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Package EFDR updated to version 1.2 with previous version 1.0 dated 2019-05-20

Title: Wavelet-Based Enhanced FDR for Detecting Signals from Complete or Incomplete Spatially Aggregated Data
Description: Enhanced False Discovery Rate (EFDR) is a tool to detect anomalies in an image. The image is first transformed into the wavelet domain in order to decorrelate any noise components, following which the coefficients at each resolution are standardised. Statistical tests (in a multiple hypothesis testing setting) are then carried out to find the anomalies. The power of EFDR exceeds that of standard FDR, which would carry out tests on every wavelet coefficient: EFDR choose which wavelets to test based on a criterion described in Shen et al. (2002). The package also provides elementary tools to interpolate spatially irregular data onto a grid of the required size. The work is based on Shen, X., Huang, H.-C., and Cressie, N. 'Nonparametric hypothesis testing for a spatial signal.' Journal of the American Statistical Association 97.460 (2002): 1122-1140.
Author: Andrew Zammit-Mangion [aut, cre], Hsin-Cheng Huang [aut]
Maintainer: Andrew Zammit-Mangion <andrewzm@gmail.com>

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Package yorkr updated to version 0.0.21 with previous version 0.0.20 dated 2021-04-09

Title: Analyze Cricket Performances Based on Data from Cricsheet
Description: Analyzing performances of cricketers and cricket teams based on 'yaml' match data from Cricsheet <https://cricsheet.org/>.
Author: Tinniam V Ganesh
Maintainer: Tinniam V Ganesh <tvganesh.85@gmail.com>

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Package ubiquity updated to version 1.0.4 with previous version 1.0.3 dated 2020-09-13

Title: PKPD, PBPK, and Systems Pharmacology Modeling Tools
Description: Complete work flow for the analysis of pharmacokinetic pharmacodynamic (PKPD), physiologically-based pharmacokinetic (PBPK) and systems pharmacology models including: creation of ordinary differential equation-based models, pooled parameter estimation, individual/population based simulations, rule-based simulations for clinical trial design and modeling assays, deployment with a customizable 'Shiny' app, and non-compartmental analysis. System-specific analysis templates can be generated and each element includes integrated reporting with 'PowerPoint' and 'Word'.
Author: John Harrold [aut, cre] (<https://orcid.org/0000-0003-2052-4373>)
Maintainer: John Harrold <john.m.harrold@gmail.com>

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Package strex updated to version 1.4.2 with previous version 1.4.1 dated 2020-10-17

Title: Extra String Manipulation Functions
Description: There are some things that I wish were easier with the 'stringr' or 'stringi' packages. The foremost of these is the extraction of numbers from strings. 'stringr' and 'stringi' make you figure out the regular expression for yourself; 'strex' takes care of this for you. There are many other handy functionalities in 'strex'. Contributions to this package are encouraged: it is intended as a miscellany of string manipulation functions that cannot be found in 'stringi' or 'stringr'.
Author: Rory Nolan [aut, cre] (<https://orcid.org/0000-0002-5239-4043>)
Maintainer: Rory Nolan <rorynoolan@gmail.com>

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Package sparsevar updated to version 0.1.0 with previous version 0.0.11 dated 2019-08-19

Title: Sparse VAR/VECM Models Estimation
Description: A wrapper for sparse VAR/VECM time series models estimation using penalties like ENET (Elastic Net), SCAD (Smoothly Clipped Absolute Deviation) and MCP (Minimax Concave Penalty). Based on the work of Sumanta Basu and George Michailidis <doi:10.1214/15-AOS1315>.
Author: Simone Vazzoler [aut, cre]
Maintainer: Simone Vazzoler <svazzole@gmail.com>

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 sparsevar-0.1.0/sparsevar/DESCRIPTION                                                                         |   18 
 sparsevar-0.1.0/sparsevar/MD5                                                                                 |   90 +-
 sparsevar-0.1.0/sparsevar/NEWS.md                                                                             |   10 
 sparsevar-0.1.0/sparsevar/R/createSparseMatrix.R                                                              |   72 -
 sparsevar-0.1.0/sparsevar/R/fitVAR.R                                                                          |  250 ++---
 sparsevar-0.1.0/sparsevar/R/fitVARX.R                                                                         |   50 -
 sparsevar-0.1.0/sparsevar/R/fitVECM.R                                                                         |  106 +-
 sparsevar-0.1.0/sparsevar/R/impulseResponse.R                                                                 |  439 ++++------
 sparsevar-0.1.0/sparsevar/R/mcSimulations.R                                                                   |   82 -
 sparsevar-0.1.0/sparsevar/R/plotIRF.R                                                                         |  137 +--
 sparsevar-0.1.0/sparsevar/R/plotMatrix.R                                                                      |  126 +-
 sparsevar-0.1.0/sparsevar/R/simulateVAR.R                                                                     |   76 -
 sparsevar-0.1.0/sparsevar/R/simulateVARX.R                                                                    |  144 +--
 sparsevar-0.1.0/sparsevar/R/sparsevar.R                                                                       |   16 
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 sparsevar-0.1.0/sparsevar/R/twoStepOLS.R                                                                      |   63 -
 sparsevar-0.1.0/sparsevar/R/utils.R                                                                           |   62 -
 sparsevar-0.1.0/sparsevar/R/utilsVAR.R                                                                        |  153 +--
 sparsevar-0.1.0/sparsevar/README.md                                                                           |    9 
 sparsevar-0.1.0/sparsevar/build/vignette.rds                                                                  |binary
 sparsevar-0.1.0/sparsevar/inst/doc/using.R                                                                    |   22 
 sparsevar-0.1.0/sparsevar/inst/doc/using.Rmd                                                                  |    2 
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 sparsevar-0.1.0/sparsevar/man/checkImpulseZero.Rd                                                             |    2 
 sparsevar-0.1.0/sparsevar/man/computeForecasts.Rd                                                             |    4 
 sparsevar-0.1.0/sparsevar/man/createSparseMatrix.Rd                                                           |   30 
 sparsevar-0.1.0/sparsevar/man/errorBandsIRF.Rd                                                                |    2 
 sparsevar-0.1.0/sparsevar/man/fitVAR.Rd                                                                       |   24 
 sparsevar-0.1.0/sparsevar/man/fitVARX.Rd                                                                      |    2 
 sparsevar-0.1.0/sparsevar/man/fitVECM.Rd                                                                      |    4 
 sparsevar-0.1.0/sparsevar/man/informCrit.Rd                                                                   |    2 
 sparsevar-0.1.0/sparsevar/man/mcSimulations.Rd                                                                |   19 
 sparsevar-0.1.0/sparsevar/man/multiplot.Rd                                                                    |    2 
 sparsevar-0.1.0/sparsevar/man/plotIRFGrid.Rd                                                                  |    4 
 sparsevar-0.1.0/sparsevar/man/plotMatrix.Rd                                                                   |    2 
 sparsevar-0.1.0/sparsevar/man/plotVAR.Rd                                                                      |    2 
 sparsevar-0.1.0/sparsevar/man/plotVECM.Rd                                                                     |    2 
 sparsevar-0.1.0/sparsevar/man/simulateVARX.Rd                                                                 |    8 
 sparsevar-0.1.0/sparsevar/man/sparsevar.Rd                                                                    |    5 
 sparsevar-0.1.0/sparsevar/vignettes/using.Rmd                                                                 |    2 
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Package RaSEn updated to version 2.1.0 with previous version 2.0.0 dated 2021-01-15

Title: Random Subspace Ensemble Classification and Variable Screening
Description: We propose a general ensemble classification framework, RaSE algorithm, for the sparse classification problem. In RaSE algorithm, for each weak learner, some random subspaces are generated and the optimal one is chosen to train the model on the basis of some criterion. To be adapted to the problem, a novel criterion, ratio information criterion (RIC) is put up with based on Kullback-Leibler divergence. Besides minimizing RIC, multiple criteria can be applied, for instance, minimizing extended Bayesian information criterion (eBIC), minimizing training error, minimizing the validation error, minimizing the cross-validation error, minimizing leave-one-out error. There are various choices of base classifier, for instance, linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbour, logistic regression, decision trees, random forest, support vector machines. RaSE algorithm can also be applied to do feature ranking, providing us the importance of each feature based on the selected percentage in multiple subspaces. RaSE framework can be extended to the general prediction framework, including both classification and regression. We can use the selected percentages of variables for variable screening. The latest version added the variable screening function for both regression and classification problems.
Author: Ye Tian [aut, cre] and Yang Feng [aut]
Maintainer: Ye Tian <ye.t@columbia.edu>

Diff between RaSEn versions 2.0.0 dated 2021-01-15 and 2.1.0 dated 2021-04-18

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Package modesto updated to version 0.1.3 with previous version 0.1.2 dated 2019-01-04

Title: Modeling and Analysis of Stochastic Systems
Description: Compute important quantities when we consider stochastic systems that are observed continuously. Such as, Cost model, Limiting distribution, Transition matrix, Transition distribution and Occupancy matrix. The methods are described, for example, Ross S. (2014), Introduction to Probability Models. Eleven Edition. Academic Press.
Author: Carlos Alberto Cardozo Delgado
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>

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Package mlr3proba updated to version 0.4.0 with previous version 0.3.2 dated 2021-03-15

Title: Probabilistic Supervised Learning for 'mlr3'
Description: Provides extensions for probabilistic supervised learning for 'mlr3'. This includes extending the regression task to probabilistic and interval regression, adding a survival task, and other specialized models, predictions, and measures. mlr3extralearners is available from <https://github.com/mlr-org/mlr3extralearners>.
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>), Franz Kiraly [aut], Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Nurul Ain Toha [ctb], Andreas Bender [ctb] (<https://orcid.org/0000-0001-5628-8611>)
Maintainer: Raphael Sonabend <raphaelsonabend@gmail.com>

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 mlr3proba-0.4.0/mlr3proba/MD5                                                      |  120 ++++------
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 mlr3proba-0.4.0/mlr3proba/NEWS.md                                                  |    9 
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 mlr3proba-0.4.0/mlr3proba/R/pecs.R                                                 |   68 ++++-
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 mlr3proba-0.4.0/mlr3proba/R/zzz.R                                                  |   37 ---
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Package gratia updated to version 0.6.0 with previous version 0.5.1 dated 2021-01-23

Title: Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'
Description: Graceful 'ggplot'-based graphics and utility functions for working with generalized additive models (GAMs) fitted using the 'mgcv' package. Provides a reimplementation of the plot() method for GAMs that 'mgcv' provides, as well as 'tidyverse' compatible representations of estimated smooths.
Author: Gavin L. Simpson [aut, cre] (<https://orcid.org/0000-0002-9084-8413>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>)
Maintainer: Gavin L. Simpson <ucfagls@gmail.com>

Diff between gratia versions 0.5.1 dated 2021-01-23 and 0.6.0 dated 2021-04-18

 DESCRIPTION                                                                                   |   12 
 MD5                                                                                           |  269 
 NAMESPACE                                                                                     |   29 
 NEWS.md                                                                                       |   81 
 R/add-methods.R                                                                               |   86 
 R/compare-smooths.R                                                                           |only
 R/derivatives.R                                                                               |   39 
 R/diagnose.R                                                                                  |  364 
 R/draw-methods.R                                                                              |   80 
 R/edf.R                                                                                       |only
 R/evaluate_smooth.R                                                                           |    4 
 R/evaluate_smooth2.R                                                                          |    9 
 R/family-utils.R                                                                              |  222 
 R/penalty.R                                                                                   |   36 
 R/posterior-samples.R                                                                         |   42 
 R/utililties.R                                                                                |    2 
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 build/partial.rdb                                                                             |binary
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 man/add_constant.Rd                                                                           |   18 
 man/appraise.Rd                                                                               |   24 
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 man/derivatives.Rd                                                                            |   13 
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 man/draw.derivatives.Rd                                                                       |   26 
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 man/draw.gam.Rd                                                                               |   24 
 man/draw.mgcv_smooth.Rd                                                                       |    2 
 man/draw.penalty_df.Rd                                                                        |    2 
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 man/link.Rd                                                                                   |   49 
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 man/qq_plot.Rd                                                                                |   26 
 man/smooth_estimates.Rd                                                                       |    3 
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 man/worm_plot.Rd                                                                              |only
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 tests/figs/test-derivatives-methods                                                           |only
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 tests/figs/worm-plot-methods                                                                  |only
 tests/testthat/test-derivatives.R                                                             |   61 
 tests/testthat/test-draw-methods.R                                                            |   22 
 tests/testthat/test-evaluate-smooth-methods.R                                                 |    8 
 tests/testthat/test-family-utils.R                                                            |  123 
 tests/testthat/test-qq-plot.R                                                                 |   26 
 tests/testthat/test-simulate-methods.R                                                        |    1 
 tests/testthat/test-worm-plot.R                                                               |only
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