Wed, 16 Nov 2022

Package MagmaClustR (with last version 1.1.0) was removed from CRAN

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

2022-11-01 1.1.0
2022-08-29 1.0.1
2022-06-06 1.0.0

Permanent link
Package shinyHugePlot updated to version 0.2.1 with previous version 0.2.0 dated 2022-10-26

Title: Efficient Plotting of Large-Sized Data
Description: A tool to plot data with large sample size using 'shiny' and 'plotly'. Relatively small samples are chosen from the data using an appropriate algorithm according to a user-defined x range. Jonas Van Der Donckt, Jeroen Van Der Donckt, Emiel Deprost (2022) <https://github.com/predict-idlab/plotly-resampler>.
Author: Junta Tagusari [aut, cre, cph], Jonas Van Der Donckt [cph], Jeroen Van Der Donckt [cph], Emiel Deprost [cph]
Maintainer: Junta Tagusari <j.tagusari@eng.hokudai.ac.jp>

Diff between shinyHugePlot versions 0.2.0 dated 2022-10-26 and 0.2.1 dated 2022-11-16

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Package slider updated to version 0.3.0 with previous version 0.2.2 dated 2021-07-01

Title: Sliding Window Functions
Description: Provides type-stable rolling window functions over any R data type. Cumulative and expanding windows are also supported. For more advanced usage, an index can be used as a secondary vector that defines how sliding windows are to be created.
Author: Davis Vaughan [aut, cre], RStudio [cph, fnd]
Maintainer: Davis Vaughan <davis@rstudio.com>

Diff between slider versions 0.2.2 dated 2021-07-01 and 0.3.0 dated 2022-11-16

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More information about slider at CRAN
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Package pspatreg updated to version 1.0.6 with previous version 1.0.4 dated 2022-07-04

Title: Spatial and Spatio-Temporal Semiparametric Regression Models with Spatial Lags
Description: Estimation and inference of spatial and spatio-temporal semiparametric models including spatial or spatio-temporal non-parametric trends, parametric and non-parametric covariates and, possibly, a spatial lag for the dependent variable and temporal correlation in the noise. The spatio-temporal trend can be decomposed in ANOVA way including main and interaction functional terms. Use of SAP algorithm to estimate the spatial or spatio-temporal trend and non-parametric covariates. The methodology of these models can be found in next references Basile, R. et al. (2014), <doi:10.1016/j.jedc.2014.06.011>; Rodriguez-Alvarez, M.X. et al. (2015) <doi:10.1007/s11222-014-9464-2> and, particularly referred to the focus of the package, Minguez, R., Basile, R. and Durban, M. (2020) <doi:10.1007/s10260-019-00492-8>.
Author: Roman Minguez [aut, cre] , Roberto Basile [aut] , Maria Durban [aut] , Gonzalo Espana-Heredia [aut]
Maintainer: Roman Minguez <roman.minguez@uclm.es>

Diff between pspatreg versions 1.0.4 dated 2022-07-04 and 1.0.6 dated 2022-11-16

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Package pedmut updated to version 0.4.0 with previous version 0.3.0 dated 2021-10-22

Title: Mutation Models for Pedigree Likelihood Computations
Description: A collection of functions for modelling mutations in pedigrees with marker data, as used e.g. in likelihood computations with microsatellite data. Implemented models include proportional and stepwise models, as well as random models for experimental work, and custom models allowing the user to apply any valid mutation matrix. Allele lumping is done following the lumpability criteria of Kemeny and Snell (1976), ISBN:0387901922.
Author: Magnus Dehli Vigeland [aut, cre]
Maintainer: Magnus Dehli Vigeland <m.d.vigeland@medisin.uio.no>

Diff between pedmut versions 0.3.0 dated 2021-10-22 and 0.4.0 dated 2022-11-16

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More information about pedmut at CRAN
Permanent link

Package ordinal updated to version 2022.11-16 with previous version 2019.12-10 dated 2019-12-15

Title: Regression Models for Ordinal Data
Description: Implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature. Multiple random effect terms are allowed and they may be nested, crossed or partially nested/crossed. Restrictions of symmetry and equidistance can be imposed on the thresholds (cut-points/intercepts). Standard model methods are available (summary, anova, drop-methods, step, confint, predict etc.) in addition to profile methods and slice methods for visualizing the likelihood function and checking convergence.
Author: Rune Haubo Bojesen Christensen [aut, cre]
Maintainer: Rune Haubo Bojesen Christensen <rune.haubo@gmail.com>

Diff between ordinal versions 2019.12-10 dated 2019-12-15 and 2022.11-16 dated 2022-11-16

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More information about ordinal at CRAN
Permanent link

Package matchMulti updated to version 1.1.11 with previous version 1.1.10 dated 2022-03-27

Title: Optimal Multilevel Matching using a Network Algorithm
Description: Performs multilevel matches for data with cluster- level treatments and individual-level outcomes using a network optimization algorithm. Functions for checking balance at the cluster and individual levels are also provided, as are methods for permutation-inference-based outcome analysis. Details in Pimentel et al. (2018) <doi:10.1214/17-AOAS1118>. The optmatch package, which is useful for running many of the provided functions, may be downloaded from Github at <https://github.com/markmfredrickson/optmatch> if not available on CRAN.
Author: Luke Keele [aut], Luke Miratrix [aut], Sam Pimentel [aut, cre], Paul Rosenbaum [ctb]
Maintainer: Sam Pimentel <spi@berkeley.edu>

Diff between matchMulti versions 1.1.10 dated 2022-03-27 and 1.1.11 dated 2022-11-16

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More information about matchMulti at CRAN
Permanent link

Package gt updated to version 0.8.0 with previous version 0.7.0 dated 2022-08-25

Title: Easily Create Presentation-Ready Display Tables
Description: Build display tables from tabular data with an easy-to-use set of functions. With its progressive approach, we can construct display tables with a cohesive set of table parts. Table values can be formatted using any of the included formatting functions. Footnotes and cell styles can be precisely added through a location targeting system. The way in which 'gt' handles things for you means that you don't often have to worry about the fine details.
Author: Richard Iannone [aut, cre] , Joe Cheng [aut], Barret Schloerke [aut] , Ellis Hughes [aut] , JooYoung Seo [aut] , RStudio [cph, fnd]
Maintainer: Richard Iannone <rich@rstudio.com>

Diff between gt versions 0.7.0 dated 2022-08-25 and 0.8.0 dated 2022-11-16

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More information about gt at CRAN
Permanent link

Package glmmTMB updated to version 1.1.5 with previous version 1.1.4 dated 2022-07-12

Title: Generalized Linear Mixed Models using Template Model Builder
Description: Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.
Author: Mollie Brooks [aut, cre] , Ben Bolker [aut] , Kasper Kristensen [aut], Martin Maechler [aut] , Arni Magnusson [aut] , Maeve McGillycuddy [ctb], Hans Skaug [aut], Anders Nielsen [aut] , Casper Berg [aut] , Koen van Bentham [aut], Nafis Sadat [ctb] , D [...truncated...]
Maintainer: Mollie Brooks <mollieebrooks@gmail.com>

Diff between glmmTMB versions 1.1.4 dated 2022-07-12 and 1.1.5 dated 2022-11-16

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New package frictionless with initial version 1.0.2
Package: frictionless
Title: Read and Write Frictionless Data Packages
Version: 1.0.2
Description: Read and write Frictionless Data Packages. A 'Data Package' (<https://specs.frictionlessdata.io/data-package/>) is a simple container format and standard to describe and package a collection of (tabular) data. It is typically used to publish FAIR (<https://www.go-fair.org/fair-principles/>) and open datasets.
License: MIT + file LICENSE
URL: https://github.com/frictionlessdata/frictionless-r, https://docs.ropensci.org/frictionless/
BugReports: https://github.com/frictionlessdata/frictionless-r/issues
Imports: assertthat, dplyr, glue, httr, jsonlite, purrr, readr (>= 2.1.0), utils, yaml
Suggests: hms, knitr, lubridate, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2022-11-16 21:03:35 UTC; peter_desmet
Author: Peter Desmet [aut, cre] , Damiano Oldoni [aut] , Research Institute for Nature and Forest [cph] , LifeWatch Belgium [fnd] , Beatriz Milz [rev] , Joao Martins [rev]
Maintainer: Peter Desmet <peter.desmet.work@gmail.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2022-11-16 22:20:06 UTC

More information about frictionless at CRAN
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Package exactextractr updated to version 0.9.1 with previous version 0.9.0 dated 2022-08-23

Title: Fast Extraction from Raster Datasets using Polygons
Description: Provides a replacement for the 'extract' function from the 'raster' package that is suitable for extracting raster values using 'sf' polygons.
Author: Daniel Baston [aut, cre], ISciences, LLC [cph]
Maintainer: Daniel Baston <dbaston@isciences.com>

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Package cbl updated to version 0.1.2 with previous version 0.1.1 dated 2022-06-17

Title: Causal Discovery under a Confounder Blanket
Description: Methods for learning causal relationships among a set of foreground variables X based on signals from a (potentially much larger) set of background variables Z, which are known non-descendants of X. The confounder blanket learner (CBL) uses sparse regression techniques to simultaneously perform many conditional independence tests, with complementary pairs stability selection to guarantee finite sample error control. CBL is sound and complete with respect to a so-called "lazy oracle", and works with both linear and nonlinear systems. For details, see Watson & Silva (2022) <arXiv:2205.05715>.
Author: David Watson [aut, cre]
Maintainer: David Watson <david.s.watson11@gmail.com>

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Package sdamr updated to version 0.2.0 with previous version 0.1.0 dated 2021-09-29

Title: Statistics: Data Analysis and Modelling
Description: Data sets and functions to support the books "Statistics: Data analysis and modelling" by Speekenbrink, M. (2021) <https://mspeekenbrink.github.io/sdam-book/> and "An R companion to Statistics: data analysis and modelling" by Speekenbrink, M. (2021) <https://mspeekenbrink.github.io/sdam-r-companion/>. All datasets analysed in these books are provided in this package. In addition, the package provides functions to compute sample statistics (variance, standard deviation, mode), create raincloud and enhanced Q-Q plots, and expand Anova results into omnibus tests and tests of individual contrasts.
Author: Maarten Speekenbrink [aut, cre]
Maintainer: Maarten Speekenbrink <m.speekenbrink@ucl.ac.uk>

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Package healthyR.ts updated to version 0.2.5 with previous version 0.2.4 dated 2022-11-10

Title: The Time Series Modeling Companion to 'healthyR'
Description: Hospital time series data analysis workflow tools, modeling, and automations. This library provides many useful tools to review common administrative time series hospital data. Some of these include average length of stay, and readmission rates. The aim is to provide a simple and consistent verb framework that takes the guesswork out of everything.
Author: Steven Sanderson [aut, cre], Steven Sanderson [cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>

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Package data.table updated to version 1.14.6 with previous version 1.14.4 dated 2022-10-17

Title: Extension of `data.frame`
Description: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
Author: Matt Dowle [aut, cre], Arun Srinivasan [aut], Jan Gorecki [ctb], Michael Chirico [ctb], Pasha Stetsenko [ctb], Tom Short [ctb], Steve Lianoglou [ctb], Eduard Antonyan [ctb], Markus Bonsch [ctb], Hugh Parsonage [ctb], Scott Ritchie [ctb], Kun Ren [ctb [...truncated...]
Maintainer: Matt Dowle <mattjdowle@gmail.com>

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Package CAISEr updated to version 1.0.17 with previous version 1.0.16 dated 2020-02-04

Title: Comparison of Algorithms with Iterative Sample Size Estimation
Description: Functions for performing experimental comparisons of algorithms using adequate sample sizes for power and accuracy. Implements the methodology originally presented in Campelo and Takahashi (2019) <doi:10.1007/s10732-018-9396-7> for the comparison of two algorithms, and later generalised in Campelo and Wanner (Submitted, 2019) <arxiv:1908.01720>.
Author: Felipe Campelo [aut, cre], Fernanda Takahashi [ctb], Elizabeth Wanner [ctb]
Maintainer: Felipe Campelo <fcampelo@gmail.com>

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Package bayesplot updated to version 1.10.0 with previous version 1.9.0 dated 2022-03-10

Title: Plotting for Bayesian Models
Description: Plotting functions for posterior analysis, MCMC diagnostics, prior and posterior predictive checks, and other visualizations to support the applied Bayesian workflow advocated in Gabry, Simpson, Vehtari, Betancourt, and Gelman (2019) <doi:10.1111/rssa.12378>. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling, particularly (but not exclusively) packages interfacing with 'Stan'.
Author: Jonah Gabry [aut, cre], Tristan Mahr [aut], Paul-Christian Buerkner [ctb], Martin Modrak [ctb], Malcolm Barrett [ctb], Frank Weber [ctb], Eduardo Coronado Sroka [ctb], Teemu Sailynoja [ctb], Aki Vehtari [ctb]
Maintainer: Jonah Gabry <jsg2201@columbia.edu>

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Package ROptEst updated to version 1.3.1 with previous version 1.2.1 dated 2019-04-25

Title: Optimally Robust Estimation
Description: Optimally robust estimation in general smoothly parameterized models using S4 classes and methods.
Author: Matthias Kohl [cre, cph], Mykhailo Pupashenko [ctb] , Gerald Kroisandt [ctb] , Peter Ruckdeschel [aut, cph]
Maintainer: Matthias Kohl <Matthias.Kohl@stamats.de>

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Package iglu updated to version 3.4.2 with previous version 3.3.2 dated 2022-10-19

Title: Interpreting Glucose Data from Continuous Glucose Monitors
Description: Implements a wide range of metrics for measuring glucose control and glucose variability based on continuous glucose monitoring data. The list of implemented metrics is summarized in Rodbard (2009) <doi:10.1089/dia.2009.0015>. Additional visualization tools include time-series plots, lasagna plots and ambulatory glucose profile report.
Author: Steve Broll [aut], David Buchanan [aut], Elizabeth Chun [aut], John Muschelli [aut] , Nathaniel Fernandes [aut], Jung Hoon Seo [aut], Johnathan Shih [aut], Jacek Urbanek [aut], John Schwenck [aut], Marielle Hicban [ctb], Mary Martin [ctb], Pratik Pat [...truncated...]
Maintainer: Irina Gaynanova <irinag@stat.tamu.edu>

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Package GENLIB updated to version 1.1.7 with previous version 1.1.6 dated 2022-08-11

Title: Genealogical Data Analysis
Description: Genealogical data analysis including descriptive statistics (e.g., kinship and inbreeding coefficients) and gene-dropping simulations. See: "GENLIB: an R package for the analysis of genealogical data" Gauvin et al. (2015) <doi:10.1186/s12859-015-0581-5>.
Author: Louis Houde [aut], Jean-Francois Lefebvre [aut], Valery Roy-Lagace [aut], Sebastien Lemieux [aut], Michael J. Fromberger [ctb], Jarno van der Kolk [ctb], Mohan Rakesh [ctb], Marie-Helene Roy-Gagnon [cre]
Maintainer: Marie-Helene Roy-Gagnon <mroygagn@uottawa.ca>

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Package xfun updated to version 0.35 with previous version 0.34 dated 2022-10-18

Title: Supporting Functions for Packages Maintained by 'Yihui Xie'
Description: Miscellaneous functions commonly used in other packages maintained by 'Yihui Xie'.
Author: Yihui Xie [aut, cre, cph] , Wush Wu [ctb], Daijiang Li [ctb], Xianying Tan [ctb], Salim Brueggemann [ctb] , Christophe Dervieux [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package sits updated to version 1.2.0 with previous version 1.1.0 dated 2022-07-07

Title: Satellite Image Time Series Analysis for Earth Observation Data Cubes
Description: An end-to-end toolkit for land use and land cover classification using big Earth observation data, based on machine learning methods applied to satellite image data cubes, as described in Simoes et al (2021) <doi:10.3390/rs13132428>. Builds regular data cubes from collections in AWS, Microsoft Planetary Computer, Brazil Data Cube, and Digital Earth Africa using the STAC protocol <https://stacspec.org/> and the 'gdalcubes' R package <doi:10.3390/data4030092>. Supports visualization methods for images and time series and smoothing filters for dealing with noisy time series. Includes functions for quality assessment of training samples using self-organized maps as presented by Santos et al (2021) <doi:10.1016/j.isprsjprs.2021.04.014>. Provides machine learning methods including support vector machines, random forests, extreme gradient boosting, multi-layer perceptrons, temporal convolutional neural networks <doi:10.3390/rs11050523>, residual networks <arxi [...truncated...]
Author: Rolf Simoes [aut], Gilberto Camara [aut, cre], Felipe Souza [aut], Lorena Santos [aut], Pedro Andrade [aut], Karine Ferreira [aut], Alber Sanchez [aut], Gilberto Queiroz [aut]
Maintainer: Gilberto Camara <gilberto.camara.inpe@gmail.com>

Diff between sits versions 1.1.0 dated 2022-07-07 and 1.2.0 dated 2022-11-16

 sits-1.1.0/sits/R/sits_raster_blocks.R                                             |only
 sits-1.1.0/sits/R/sits_smooth_aux_functions.R                                      |only
 sits-1.1.0/sits/R/sits_twdtw.R                                                     |only
 sits-1.1.0/sits/data/samples_modis_4bands.rda                                      |only
 sits-1.1.0/sits/demo/classify_TWDTW.R                                              |only
 sits-1.1.0/sits/inst/extdata/markdown/latex-ms.tex                                 |only
 sits-1.1.0/sits/inst/extdata/markdown/references-sits.bib                          |only
 sits-1.1.0/sits/inst/extdata/plot                                                  |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2013-09-14.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2013-09-30.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2013-10-16.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2013-11-01.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2013-11-17.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2013-12-03.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2013-12-19.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-01-01.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-01-17.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-02-02.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-02-18.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-03-06.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-03-22.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-04-07.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-04-23.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-05-09.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-05-25.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-06-10.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-06-26.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-07-12.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-07-28.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-08-13.jp2 |only
 sits-1.1.0/sits/inst/extdata/raster/mod13q1/TERRA_MODIS_h12v10_NDVI_2014-08-29.jp2 |only
 sits-1.1.0/sits/inst/extdata/samples/samples_amazonia_sentinel2.csv                |only
 sits-1.1.0/sits/inst/extdata/samples/samples_amazonia_sentinel2_small.csv          |only
 sits-1.1.0/sits/inst/extdata/samples/samples_cerrado_cbers.csv                     |only
 sits-1.1.0/sits/inst/extdata/samples/samples_matogrosso.csv                        |only
 sits-1.1.0/sits/inst/extdata/shapefiles/df_bsb                                     |only
 sits-1.1.0/sits/man/check_functions.Rd                                             |only
 sits-1.1.0/sits/man/comparison_functions.Rd                                        |only
 sits-1.1.0/sits/man/config_colors_file.Rd                                          |only
 sits-1.1.0/sits/man/config_file.Rd                                                 |only
 sits-1.1.0/sits/man/config_internals_file.Rd                                       |only
 sits-1.1.0/sits/man/cube_functions.Rd                                              |only
 sits-1.1.0/sits/man/dot-apply_across.Rd                                            |only
 sits-1.1.0/sits/man/dot-apply_capture_expression.Rd                                |only
 sits-1.1.0/sits/man/dot-apply_estimate_block_size.Rd                               |only
 sits-1.1.0/sits/man/dot-apply_find_missing_band.Rd                                 |only
 sits-1.1.0/sits/man/dot-apply_get_all_names.Rd                                     |only
 sits-1.1.0/sits/man/dot-apply_input_bands.Rd                                       |only
 sits-1.1.0/sits/man/dot-apply_input_kernels.Rd                                     |only
 sits-1.1.0/sits/man/dot-apply_missing_band.Rd                                      |only
 sits-1.1.0/sits/man/dot-apply_out_file_name.Rd                                     |only
 sits-1.1.0/sits/man/dot-aws_tiles.Rd                                               |only
 sits-1.1.0/sits/man/dot-config_check_bands.Rd                                      |only
 sits-1.1.0/sits/man/dot-config_colors.Rd                                           |only
 sits-1.1.0/sits/man/dot-config_data_meta_type.Rd                                   |only
 sits-1.1.0/sits/man/dot-config_get.Rd                                              |only
 sits-1.1.0/sits/man/dot-config_gtiff_default_options.Rd                            |only
 sits-1.1.0/sits/man/dot-config_local_file_extension.Rd                             |only
 sits-1.1.0/sits/man/dot-config_metadata_search_strategies.Rd                       |only
 sits-1.1.0/sits/man/dot-config_names.Rd                                            |only
 sits-1.1.0/sits/man/dot-config_new_band.Rd                                         |only
 sits-1.1.0/sits/man/dot-config_new_cloud_band.Rd                                   |only
 sits-1.1.0/sits/man/dot-config_new_collection.Rd                                   |only
 sits-1.1.0/sits/man/dot-config_new_source.Rd                                       |only
 sits-1.1.0/sits/man/dot-config_processing_bloat.Rd                                 |only
 sits-1.1.0/sits/man/dot-config_raster_pkg.Rd                                       |only
 sits-1.1.0/sits/man/dot-config_rstac_limit.Rd                                      |only
 sits-1.1.0/sits/man/dot-config_user_file.Rd                                        |only
 sits-1.1.0/sits/man/dot-create_chunk_file.Rd                                       |only
 sits-1.1.0/sits/man/dot-create_filename.Rd                                         |only
 sits-1.1.0/sits/man/dot-cube_area_freq.Rd                                          |only
 sits-1.1.0/sits/man/dot-cube_band_maximum_value.Rd                                 |only
 sits-1.1.0/sits/man/dot-cube_band_minimum_value.Rd                                 |only
 sits-1.1.0/sits/man/dot-cube_band_missing_value.Rd                                 |only
 sits-1.1.0/sits/man/dot-cube_band_offset_value.Rd                                  |only
 sits-1.1.0/sits/man/dot-cube_band_scale_factor.Rd                                  |only
 sits-1.1.0/sits/man/dot-cube_bands.Rd                                              |only
 sits-1.1.0/sits/man/dot-cube_check.Rd                                              |only
 sits-1.1.0/sits/man/dot-cube_collection.Rd                                         |only
 sits-1.1.0/sits/man/dot-cube_create.Rd                                             |only
 sits-1.1.0/sits/man/dot-cube_crs.Rd                                                |only
 sits-1.1.0/sits/man/dot-cube_derived_create.Rd                                     |only
 sits-1.1.0/sits/man/dot-cube_extract.Rd                                            |only
 sits-1.1.0/sits/man/dot-cube_is_equal.Rd                                           |only
 sits-1.1.0/sits/man/dot-cube_is_regular.Rd                                         |only
 sits-1.1.0/sits/man/dot-cube_labels.Rd                                             |only
 sits-1.1.0/sits/man/dot-cube_params_block.Rd                                       |only
 sits-1.1.0/sits/man/dot-cube_resolution.Rd                                         |only
 sits-1.1.0/sits/man/dot-cube_s3class.Rd                                            |only
 sits-1.1.0/sits/man/dot-cube_size.Rd                                               |only
 sits-1.1.0/sits/man/dot-cube_source.Rd                                             |only
 sits-1.1.0/sits/man/dot-cube_tile_bbox.Rd                                          |only
 sits-1.1.0/sits/man/dot-cube_tiles.Rd                                              |only
 sits-1.1.0/sits/man/dot-cube_token_generator.Rd                                    |only
 sits-1.1.0/sits/man/dot-cube_unique_bands.Rd                                       |only
 sits-1.1.0/sits/man/dot-cube_unique_bbox.Rd                                        |only
 sits-1.1.0/sits/man/dot-cube_unique_tile_size.Rd                                   |only
 sits-1.1.0/sits/man/dot-cube_unique_timeline.Rd                                    |only
 sits-1.1.0/sits/man/dot-cube_xres.Rd                                               |only
 sits-1.1.0/sits/man/dot-cube_yres.Rd                                               |only
 sits-1.1.0/sits/man/dot-find_closest.Rd                                            |only
 sits-1.1.0/sits/man/dot-gc_arrange_images.Rd                                       |only
 sits-1.1.0/sits/man/dot-gc_create_cloud_mask.Rd                                    |only
 sits-1.1.0/sits/man/dot-gc_create_cube_view.Rd                                     |only
 sits-1.1.0/sits/man/dot-gc_create_database_stac.Rd                                 |only
 sits-1.1.0/sits/man/dot-gc_create_pack.Rd                                          |only
 sits-1.1.0/sits/man/dot-gc_create_raster_cube.Rd                                   |only
 sits-1.1.0/sits/man/dot-gc_get_valid_timeline.Rd                                   |only
 sits-1.1.0/sits/man/dot-gc_missing_tiles.Rd                                        |only
 sits-1.1.0/sits/man/dot-gc_regularize.Rd                                           |only
 sits-1.1.0/sits/man/dot-gc_save_raster_cube.Rd                                     |only
 sits-1.1.0/sits/man/dot-mesma_raster_blocks.Rd                                     |only
 sits-1.1.0/sits/man/dot-mesma_raster_blocks_estimate.Rd                            |only
 sits-1.1.0/sits/man/dot-mesma_scale_endmembers.Rd                                  |only
 sits-1.1.0/sits/man/dot-raster_check_bbox.Rd                                       |only
 sits-1.1.0/sits/man/dot-raster_check_block.Rd                                      |only
 sits-1.1.0/sits/man/dot-raster_check_package.Rd                                    |only
 sits-1.1.0/sits/man/dot-raster_colrow.Rd                                           |only
 sits-1.1.0/sits/man/dot-raster_crop.Rd                                             |only
 sits-1.1.0/sits/man/dot-raster_crop_metadata.Rd                                    |only
 sits-1.1.0/sits/man/dot-raster_data_type.Rd                                        |only
 sits-1.1.0/sits/man/dot-raster_extract.Rd                                          |only
 sits-1.1.0/sits/man/dot-raster_freq.Rd                                             |only
 sits-1.1.0/sits/man/dot-raster_gdal_datatype.Rd                                    |only
 sits-1.1.0/sits/man/dot-raster_gdal_datatypes.Rd                                   |only
 sits-1.1.0/sits/man/dot-raster_get_values.Rd                                       |only
 sits-1.1.0/sits/man/dot-raster_merge.Rd                                            |only
 sits-1.1.0/sits/man/dot-raster_new_rast.Rd                                         |only
 sits-1.1.0/sits/man/dot-raster_open_rast.Rd                                        |only
 sits-1.1.0/sits/man/dot-raster_open_stack.Rd                                       |only
 sits-1.1.0/sits/man/dot-raster_params_file.Rd                                      |only
 sits-1.1.0/sits/man/dot-raster_properties.Rd                                       |only
 sits-1.1.0/sits/man/dot-raster_rast.Rd                                             |only
 sits-1.1.0/sits/man/dot-raster_read_stack.Rd                                       |only
 sits-1.1.0/sits/man/dot-raster_resampling.Rd                                       |only
 sits-1.1.0/sits/man/dot-raster_set_values.Rd                                       |only
 sits-1.1.0/sits/man/dot-raster_supported_packages.Rd                               |only
 sits-1.1.0/sits/man/dot-raster_write_rast.Rd                                       |only
 sits-1.1.0/sits/man/dot-sits_accuracy_area_assess.Rd                               |only
 sits-1.1.0/sits/man/dot-sits_accuracy_pred_ref.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_avg_polygon.Rd                                        |only
 sits-1.1.0/sits/man/dot-sits_bbox_intersect.Rd                                     |only
 sits-1.1.0/sits/man/dot-sits_bbox_to_sf.Rd                                         |only
 sits-1.1.0/sits/man/dot-sits_classify_check_params.Rd                              |only
 sits-1.1.0/sits/man/dot-sits_classify_multicores.Rd                                |only
 sits-1.1.0/sits/man/dot-sits_cluster_dendro_bestcut.Rd                             |only
 sits-1.1.0/sits/man/dot-sits_cluster_dendrogram.Rd                                 |only
 sits-1.1.0/sits/man/dot-sits_cluster_validity.Rd                                   |only
 sits-1.1.0/sits/man/dot-sits_coords_to_bbox_wgs84.Rd                               |only
 sits-1.1.0/sits/man/dot-sits_create_folds.Rd                                       |only
 sits-1.1.0/sits/man/dot-sits_csv_check.Rd                                          |only
 sits-1.1.0/sits/man/dot-sits_distances.Rd                                          |only
 sits-1.1.0/sits/man/dot-sits_distances_classify.Rd                                 |only
 sits-1.1.0/sits/man/dot-sits_distances_sample.Rd                                   |only
 sits-1.1.0/sits/man/dot-sits_fast_apply.Rd                                         |only
 sits-1.1.0/sits/man/dot-sits_filter_intersecting_tiles.Rd                          |only
 sits-1.1.0/sits/man/dot-sits_function_factory.Rd                                   |only
 sits-1.1.0/sits/man/dot-sits_get_data_check.Rd                                     |only
 sits-1.1.0/sits/man/dot-sits_get_samples_from_csv.Rd                               |only
 sits-1.1.0/sits/man/dot-sits_get_samples_from_sf.Rd                                |only
 sits-1.1.0/sits/man/dot-sits_get_samples_from_shp.Rd                               |only
 sits-1.1.0/sits/man/dot-sits_get_top_values.Rd                                     |only
 sits-1.1.0/sits/man/dot-sits_get_ts.Rd                                             |only
 sits-1.1.0/sits/man/dot-sits_mass_ginv.Rd                                          |only
 sits-1.1.0/sits/man/dot-sits_ml_model_samples.Rd                                   |only
 sits-1.1.0/sits/man/dot-sits_ml_normalization_param.Rd                             |only
 sits-1.1.0/sits/man/dot-sits_ml_normalize_data.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_ml_normalize_matrix.Rd                                |only
 sits-1.1.0/sits/man/dot-sits_oversample_smote.Rd                                   |only
 sits-1.1.0/sits/man/dot-sits_parallel_is_open.Rd                                   |only
 sits-1.1.0/sits/man/dot-sits_parallel_map.Rd                                       |only
 sits-1.1.0/sits/man/dot-sits_parallel_reset_node.Rd                                |only
 sits-1.1.0/sits/man/dot-sits_parallel_start.Rd                                     |only
 sits-1.1.0/sits/man/dot-sits_parallel_stop.Rd                                      |only
 sits-1.1.0/sits/man/dot-sits_parse_roi_cube.Rd                                     |only
 sits-1.1.0/sits/man/dot-sits_parse_roi_cube.ll.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_parse_roi_cube.sf.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_parse_roi_cube.xy.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_plot_allyears.Rd                                      |only
 sits-1.1.0/sits/man/dot-sits_plot_dendrogram.Rd                                    |only
 sits-1.1.0/sits/man/dot-sits_plot_ggplot_series.Rd                                 |only
 sits-1.1.0/sits/man/dot-sits_plot_ggplot_series_na.Rd                              |only
 sits-1.1.0/sits/man/dot-sits_plot_ggplot_series_no_na.Rd                           |only
 sits-1.1.0/sits/man/dot-sits_plot_ggplot_together.Rd                               |only
 sits-1.1.0/sits/man/dot-sits_plot_resample_class.Rd                                |only
 sits-1.1.0/sits/man/dot-sits_plot_title.Rd                                         |only
 sits-1.1.0/sits/man/dot-sits_plot_together.Rd                                      |only
 sits-1.1.0/sits/man/dot-sits_plot_twdtw_alignments.Rd                              |only
 sits-1.1.0/sits/man/dot-sits_plot_twdtw_class.Rd                                   |only
 sits-1.1.0/sits/man/dot-sits_proj_format_crs.Rd                                    |only
 sits-1.1.0/sits/man/dot-sits_proj_from_latlong.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_proj_to_latlong.Rd                                    |only
 sits-1.1.0/sits/man/dot-sits_raster_block_list.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_raster_blocks.Rd                                      |only
 sits-1.1.0/sits/man/dot-sits_raster_blocks_estimate.Rd                             |only
 sits-1.1.0/sits/man/dot-sits_raster_data_get_ts.Rd                                 |only
 sits-1.1.0/sits/man/dot-sits_raster_data_preprocess.Rd                             |only
 sits-1.1.0/sits/man/dot-sits_raster_data_read.Rd                                   |only
 sits-1.1.0/sits/man/dot-sits_raster_sub_image.Rd                                   |only
 sits-1.1.0/sits/man/dot-sits_raster_sub_image_default.Rd                           |only
 sits-1.1.0/sits/man/dot-sits_raster_sub_image_from_bbox.Rd                         |only
 sits-1.1.0/sits/man/dot-sits_raster_sub_image_from_block.Rd                        |only
 sits-1.1.0/sits/man/dot-sits_raster_sub_image_intersects.Rd                        |only
 sits-1.1.0/sits/man/dot-sits_roi_bbox.Rd                                           |only
 sits-1.1.0/sits/man/dot-sits_roi_bbox.ll.Rd                                        |only
 sits-1.1.0/sits/man/dot-sits_roi_bbox.sf.Rd                                        |only
 sits-1.1.0/sits/man/dot-sits_roi_bbox.xy.Rd                                        |only
 sits-1.1.0/sits/man/dot-sits_roi_sf_to_geojson.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_samples_split.Rd                                      |only
 sits-1.1.0/sits/man/dot-sits_sf_point_to_tibble.Rd                                 |only
 sits-1.1.0/sits/man/dot-sits_sf_polygon_to_tibble.Rd                               |only
 sits-1.1.0/sits/man/dot-sits_sf_to_tibble.Rd                                       |only
 sits-1.1.0/sits/man/dot-sits_sgolay_coef.Rd                                        |only
 sits-1.1.0/sits/man/dot-sits_shp_check_validity.Rd                                 |only
 sits-1.1.0/sits/man/dot-sits_smote.Rd                                              |only
 sits-1.1.0/sits/man/dot-sits_som_bayes_estimate.Rd                                 |only
 sits-1.1.0/sits/man/dot-sits_som_label_neurons.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_som_paint_neurons.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_tibble.Rd                                             |only
 sits-1.1.0/sits/man/dot-sits_tibble_align_dates.Rd                                 |only
 sits-1.1.0/sits/man/dot-sits_tibble_bands_check.Rd                                 |only
 sits-1.1.0/sits/man/dot-sits_tibble_prediction.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_tibble_prune.Rd                                       |only
 sits-1.1.0/sits/man/dot-sits_tibble_test.Rd                                        |only
 sits-1.1.0/sits/man/dot-sits_timeline_check.Rd                                     |only
 sits-1.1.0/sits/man/dot-sits_timeline_check_cube.Rd                                |only
 sits-1.1.0/sits/man/dot-sits_timeline_class_info.Rd                                |only
 sits-1.1.0/sits/man/dot-sits_timeline_dist_indexes.Rd                              |only
 sits-1.1.0/sits/man/dot-sits_timeline_during.Rd                                    |only
 sits-1.1.0/sits/man/dot-sits_timeline_format.Rd                                    |only
 sits-1.1.0/sits/man/dot-sits_timeline_idx_from_dates.Rd                            |only
 sits-1.1.0/sits/man/dot-sits_timeline_match.Rd                                     |only
 sits-1.1.0/sits/man/dot-sits_timeline_match_indexes.Rd                             |only
 sits-1.1.0/sits/man/dot-sits_timeline_valid_date.Rd                                |only
 sits-1.1.0/sits/man/dot-sits_transform_samples.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_twdtw_breaks.Rd                                       |only
 sits-1.1.0/sits/man/dot-sits_twdtw_from_tibble.Rd                                  |only
 sits-1.1.0/sits/man/dot-sits_twdtw_matches_to_prediction.Rd                        |only
 sits-1.1.0/sits/man/dot-smth_block_filename.Rd                                     |only
 sits-1.1.0/sits/man/dot-smth_estimate_block_size.Rd                                |only
 sits-1.1.0/sits/man/dot-stac_add_gdal_vsi.Rd                                       |only
 sits-1.1.0/sits/man/dot-stac_format_datetime.Rd                                    |only
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 sits-1.2.0/sits/NEWS.md                                                            |   40 
 sits-1.2.0/sits/R/RcppExports.R                                                    |   92 
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 sits-1.2.0/sits/man/sits_apply.Rd                                                  |   25 
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 sits-1.2.0/sits/man/sits_labels.Rd                                                 |    4 
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 sits-1.2.0/sits/man/sits_resnet.Rd                                                 |    6 
 sits-1.2.0/sits/man/sits_rfor.Rd                                                   |    9 
 sits-1.2.0/sits/man/sits_run_examples.Rd                                           |    2 
 sits-1.2.0/sits/man/sits_select.Rd                                                 |   15 
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 sits-1.2.0/sits/man/sits_smooth.Rd                                                 |   61 
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 sits-1.2.0/sits/man/sits_to_xlsx.Rd                                                |    2 
 sits-1.2.0/sits/man/sits_train.Rd                                                  |    5 
 sits-1.2.0/sits/man/sits_tuning.Rd                                                 |    6 
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Package MKinfer updated to version 0.9 with previous version 0.8 dated 2022-11-06

Title: Inferential Statistics
Description: Computation of various confidence intervals (Altman et al. (2000), ISBN:978-0-727-91375-3; Hedderich and Sachs (2018), ISBN:978-3-662-56657-2) including bootstrapped versions (Davison and Hinkley (1997), ISBN:978-0-511-80284-3) as well as Hsu (Hedderich and Sachs (2018), ISBN:978-3-662-56657-2), permutation (Janssen (1997), <doi:10.1016/S0167-7152(97)00043-6>), bootstrap (Davison and Hinkley (1997), ISBN:978-0-511-80284-3) and multiple imputation (Barnard and Rubin (1999), <doi:10.1093/biomet/86.4.948>) t-test. Graphical visualization by volcano plots.
Author: Matthias Kohl [aut, cre]
Maintainer: Matthias Kohl <Matthias.Kohl@stamats.de>

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Package mixsqp updated to version 0.3-48 with previous version 0.3-43 dated 2020-05-14

Title: Sequential Quadratic Programming for Fast Maximum-Likelihood Estimation of Mixture Proportions
Description: Provides an optimization method based on sequential quadratic programming (SQP) for maximum likelihood estimation of the mixture proportions in a finite mixture model where the component densities are known. The algorithm is expected to obtain solutions that are at least as accurate as the state-of-the-art MOSEK interior-point solver (called by function "KWDual" in the 'REBayes' package), and they are expected to arrive at solutions more quickly when the number of samples is large and the number of mixture components is not too large. This implements the "mix-SQP" algorithm, with some improvements, described in Y. Kim, P. Carbonetto, M. Stephens & M. Anitescu (2020) <DOI:10.1080/10618600.2019.1689985>.
Author: Youngseok Kim [aut], Peter Carbonetto [aut, cre], Mihai Anitescu [aut], Matthew Stephens [aut], Jason Willwerscheid [ctb], Jean Morrison [ctb]
Maintainer: Peter Carbonetto <peter.carbonetto@gmail.com>

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Package FuzzyClass updated to version 0.1.3 with previous version 0.1.2 dated 2022-08-25

Title: Fuzzy and Non-Fuzzy Classifiers
Description: It provides classifiers which can be used for discrete variables and for continuous variables based on the Naive Bayes and Fuzzy Naive Bayes hypothesis. Those methods were developed by researchers belong to the 'Laboratory of Technologies for Virtual Teaching and Statistics (LabTEVE)' (<http://www.de.ufpb.br/~labteve/>) and 'Laboratory of Applied Statistics to Image Processing and Geoprocessing (LEAPIG)' (<http://www.de.ufpb.br/~leapig/>) at 'Federal University of Paraiba, Brazil'. They considered some statistical distributions and their papers were published in the scientific literature, as for instance, the Gaussian classifier using fuzzy parameters, proposed by 'Moraes, Ferreira and Machado' (2021) <doi:10.1007/s40815-020-00936-4>.
Author: Jodavid Ferreira [aut, cre] , Ronei Moraes [ctb] , Arthur Ricardo [ctb]
Maintainer: Jodavid Ferreira <jodavid@protonmail.com>

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Package spOccupancy updated to version 0.5.0 with previous version 0.4.0 dated 2022-07-13

Title: Single-Species, Multi-Species, and Integrated Spatial Occupancy Models
Description: Fits single-species, multi-species, and integrated non-spatial and spatial occupancy models using Markov Chain Monte Carlo (MCMC). Models are fit using Polya-Gamma data augmentation detailed in Polson, Scott, and Windle (2013) <doi:10.1080/01621459.2013.829001>. Spatial models are fit using either Gaussian processes or Nearest Neighbor Gaussian Processes (NNGP) for large spatial datasets. Details on NNGP models are given in Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091> and Finley, Datta, and Banerjee (2020) <arXiv:2001.09111>. Provides functionality for data integration of multiple single-species occupancy data sets using a joint likelihood framework. Details on data integration are given in Miller, Pacifici, Sanderlin, and Reich (2019) <doi:10.1111/2041-210X.13110>. Details on single-species and multi-species models are found in MacKenzie, Nichols, Lachman, Droege, Royle, and Langtimm (2002) <doi:10.1890/0012-9658(2002)083[2 [...truncated...]
Author: Jeffrey Doser [aut, cre], Andrew Finley [aut], Marc Kery [ctb]
Maintainer: Jeffrey Doser <doserjef@msu.edu>

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Package rbi.helpers updated to version 0.3.3 with previous version 0.3.2 dated 2020-06-18

Title: 'RBi' Helper Functions
Description: Contains a collection of helper functions to use with 'RBi', the R interface to 'LibBi', described in Murray et al. (2015) <doi:10.18637/jss.v067.i10>. It contains functions to adapt the proposal distribution and number of particles in particle Markov-Chain Monte Carlo, as well as calculating the Deviance Information Criterion (DIC) and converting between times in 'LibBi' results and R time/dates.
Author: Sebastian Funk <sebastian.funk@lshtm.ac.uk>
Maintainer: Sebastian Funk <sebastian.funk@lshtm.ac.uk>

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Package miesmuschel updated to version 0.0.2 with previous version 0.0.1 dated 2022-11-09

Title: Mixed Integer Evolution Strategies
Description: Evolutionary black box optimization algorithms building on the 'bbotk' package. 'miesmuschel' offers both ready-to-use optimization algorithms, as well as their fundamental building blocks that can be used to manually construct specialized optimization loops. The Mixed Integer Evolution Strategies as described by Li et al. (2013) <doi:10.1162/EVCO_a_00059> can be implemented, as well as the multi-objective optimization algorithms NSGA-II by Deb, Pratap, Agarwal, and Meyarivan (2002) <doi:10.1109/4235.996017>.
Author: Martin Binder [aut, cre], Lennart Schneider [ctb] , Susanne Dandl [ctb] , Andreas Hofheinz [ctb]
Maintainer: Martin Binder <mlr.developer@mb706.com>

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Package NetMix updated to version 0.2.0.1 with previous version 0.2.0 dated 2021-03-01

Title: Dynamic Mixed-Membership Network Regression Model
Description: Stochastic collapsed variational inference on mixed-membership stochastic blockmodel for networks, incorporating node-level predictors of mixed-membership vectors, as well as dyad-level predictors. For networks observed over time, the model defines a hidden Markov process that allows the effects of node-level predictors to evolve in discrete, historical periods. In addition, the package offers a variety of utilities for exploring results of estimation, including tools for conducting posterior predictive checks of goodness-of-fit and several plotting functions. The package implements methods described in Olivella, Pratt and Imai (2019) 'Dynamic Stochastic Blockmodel Regression for Social Networks: Application to International Conflicts', available at <https://www.santiagoolivella.info/pdfs/socnet.pdf>.
Author: Santiago Olivella [aut, cre], Adeline Lo [aut, cre], Tyler Pratt [aut, cre], Kosuke Imai [aut, cre]
Maintainer: Santiago Olivella <olivella@unc.edu>

Diff between NetMix versions 0.2.0 dated 2021-03-01 and 0.2.0.1 dated 2022-11-16

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Package neonUtilities updated to version 2.2.0 with previous version 2.1.4 dated 2022-04-14

Title: Utilities for Working with NEON Data
Description: NEON data packages can be accessed through the NEON Data Portal <https://www.neonscience.org> or through the NEON Data API (see <https://data.neonscience.org/data-api> for documentation). Data delivered from the Data Portal are provided as monthly zip files packaged within a parent zip file, while individual files can be accessed from the API. This package provides tools that aid in discovering, downloading, and reformatting data prior to use in analyses. This includes downloading data via the API, merging data tables by type, and converting formats. For more information, see the readme file at <https://github.com/NEONScience/NEON-utilities>.
Author: Claire Lunch [aut, cre, ctb], Christine Laney [aut, ctb], Nathan Mietkiewicz [aut, ctb], Eric Sokol [aut, ctb], Kaelin Cawley [aut, ctb], NEON [aut]
Maintainer: Claire Lunch <clunch@battelleecology.org>

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Package fclust updated to version 2.1.1.1 with previous version 2.1.1 dated 2019-09-17

Title: Fuzzy Clustering
Description: Algorithms for fuzzy clustering, cluster validity indices and plots for cluster validity and visualizing fuzzy clustering results.
Author: Paolo Giordani, Maria Brigida Ferraro, Alessio Serafini
Maintainer: Paolo Giordani <paolo.giordani@uniroma1.it>

Diff between fclust versions 2.1.1 dated 2019-09-17 and 2.1.1.1 dated 2022-11-16

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Package wavethresh updated to version 4.7.2 with previous version 4.7.1 dated 2022-11-09

Title: Wavelets Statistics and Transforms
Description: Performs 1, 2 and 3D real and complex-valued wavelet transforms, nondecimated transforms, wavelet packet transforms, nondecimated wavelet packet transforms, multiple wavelet transforms, complex-valued wavelet transforms, wavelet shrinkage for various kinds of data, locally stationary wavelet time series, nonstationary multiscale transfer function modeling, density estimation.
Author: Guy Nason [aut, cre], Stuart Barber [ctb], Tim Downie [ctb], Piotr Frylewicz [ctb], Arne Kovac [ctb], Todd Ogden [ctb], Bernard Silverman [ctb]
Maintainer: Guy Nason <g.nason@imperial.ac.uk>

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Package TidyDensity updated to version 1.2.4 with previous version 1.2.3 dated 2022-10-04

Title: Functions for Tidy Analysis and Generation of Random Data
Description: To make it easy to generate random numbers based upon the underlying stats distribution functions. All data is returned in a tidy and structured format making working with the data simple and straight forward. Given that the data is returned in a tidy 'tibble' it lends itself to working with the rest of the 'tidyverse'.
Author: Steven Sanderson [aut, cre], Steven Sanderson [cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>

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Package shar updated to version 2.0.2 with previous version 2.0.1 dated 2022-11-01

Title: Species-Habitat Associations
Description: Analyse species-habitat associations in R. Therefore, information about the location of the species (as a point pattern) is needed together with environmental conditions (as a categorical raster). To test for significance habitat associations, one of the two components is randomized. Methods are mainly based on Plotkin et al. (2000) <doi:10.1006/jtbi.2000.2158> and Harms et al. (2001) <doi:10.1111/j.1365-2745.2001.00615.x>.
Author: Maximilian H.K. Hesselbarth [aut, cre] , Marco Sciaini [aut] , Zeke Marshall [ctb] , Thomas Etherington [ctb]
Maintainer: Maximilian H.K. Hesselbarth <mhk.hesselbarth@gmail.com>

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Package pkgload updated to version 1.3.2 with previous version 1.3.1 dated 2022-10-28

Title: Simulate Package Installation and Attach
Description: Simulates the process of installing a package and then attaching it. This is a key part of the 'devtools' package as it allows you to rapidly iterate while developing a package.
Author: Hadley Wickham [aut], Winston Chang [aut], Jim Hester [aut], Lionel Henry [aut, cre], RStudio [cph, fnd], R Core team [ctb]
Maintainer: Lionel Henry <lionel@rstudio.com>

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Package nanonext updated to version 0.7.1 with previous version 0.7.0 dated 2022-11-07

Title: NNG (Nanomsg Next Gen) Lightweight Messaging Library
Description: R binding for NNG (Nanomsg Next Gen), a successor to ZeroMQ. NNG is a socket library providing high-performance scalability protocols, implementing a cross-platform standard for messaging and communications. Serves as a concurrency framework for building distributed applications, utilising 'aio' objects which resolve automatically upon completion of asynchronous operations.
Author: Charlie Gao [aut, cre] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

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Package mrds updated to version 2.2.8 with previous version 2.2.7 dated 2022-08-20

Title: Mark-Recapture Distance Sampling
Description: Animal abundance estimation via conventional, multiple covariate and mark-recapture distance sampling (CDS/MCDS/MRDS). Detection function fitting is performed via maximum likelihood. Also included are diagnostics and plotting for fitted detection functions. Abundance estimation is via a Horvitz-Thompson-like estimator.
Author: Jeff Laake <jeff.laake@noaa.gov>, David Borchers <dlb@st-and.ac.uk>, Len Thomas <len.thomas@st-and.ac.uk>, David Miller <dave@ninepointeightone.net> and Jon Bishop
Maintainer: Laura Marshall <lhm@st-andrews.ac.uk>

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Package hce updated to version 0.0.8 with previous version 0.0.2 dated 2022-09-26

Title: Design and Analysis of Hierarchical Composite Endpoints
Description: Simulate and analyze hierarchical composite endpoints. Win odds is the main analysis method. See Gasparyan SB et al (2022) <doi:10.1007/s43441-022-00420-1>.
Author: Samvel B. Gasparyan [aut, cre]
Maintainer: Samvel B. Gasparyan <gasparyan.co@gmail.com>

Diff between hce versions 0.0.2 dated 2022-09-26 and 0.0.8 dated 2022-11-16

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Permanent link

Package GET updated to version 0.3-2 with previous version 0.3-1 dated 2022-08-17

Title: Global Envelopes
Description: Implementation of global envelopes for a set of general d-dimensional vectors T in various applications. A 100(1-alpha)% global envelope is a band bounded by two vectors such that the probability that T falls outside this envelope in any of the d points is equal to alpha. Global means that the probability is controlled simultaneously for all the d elements of the vectors. The global envelopes can be used for graphical Monte Carlo and permutation tests where the test statistic is a multivariate vector or function (e.g. goodness-of-fit testing for point patterns and random sets, functional analysis of variance, functional general linear model, n-sample test of correspondence of distribution functions), for central regions of functional or multivariate data (e.g. outlier detection, functional boxplot) and for global confidence and prediction bands (e.g. confidence band in polynomial regression, Bayesian posterior prediction). See Myllymäki and Mrkvička (2020) <arXiv:1911.06583>, Myl [...truncated...]
Author: Mari Myllymaeki [aut, cre], Tomas Mrkvička [aut], Jiri Dvorak [ctb], Pavel Grabarnik [ctb], Ute Hahn [ctb], Mikko Kuronen [ctb], Michael Rost [ctb], Henri Seijo [ctb]
Maintainer: Mari Myllymaeki <mari.myllymaki@luke.fi>

Diff between GET versions 0.3-1 dated 2022-08-17 and 0.3-2 dated 2022-11-16

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More information about GET at CRAN
Permanent link

Package eha updated to version 2.10.1 with previous version 2.10.0 dated 2022-04-17

Title: Event History Analysis
Description: Parametric proportional hazards fitting with left truncation and right censoring for common families of distributions, piecewise constant hazards, and discrete models. Parametric accelerated failure time models for left truncated and right censored data. Proportional hazards models for tabular and register data. Sampling of risk sets in Cox regression, selections in the Lexis diagram, bootstrapping. Broström (2012) <doi:10.1201/9781315373942>.
Author: Goeran Brostroem [aut, cre], Jianming Jin [ctb]
Maintainer: Goeran Brostroem <goran.brostrom@umu.se>

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Package biodosetools updated to version 3.6.1 with previous version 3.6.0 dated 2022-01-27

Title: An R Shiny Application for Biological Dosimetry
Description: A tool to perform all different statistical tests and calculations needed by Biological Dosimetry Laboratories.
Author: Alfredo Hernandez [aut, cre] , David Endesfelder [aut], Pere Puig [aut]
Maintainer: Alfredo Hernandez <aldomann.designs@gmail.com>

Diff between biodosetools versions 3.6.0 dated 2022-01-27 and 3.6.1 dated 2022-11-16

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Permanent link

New package vol2birdR with initial version 0.2.0
Package: vol2birdR
Title: Vertical Profiles of Biological Signals in Weather Radar Data
Version: 0.2.0
Date: 2022-11-15
Description: 'R' implementation of the 'vol2bird' software for generating vertical profiles of birds and other biological signals in weather radar data. See Dokter et al. (2011) <doi:10.1098/rsif.2010.0116> for a paper describing the methodology.
License: LGPL (>= 3)
URL: https://github.com/adokter/vol2birdR/, https://adriaandokter.com/vol2bird/
BugReports: https://github.com/adokter/vol2birdR/issues
Imports: assertthat, methods, pkgbuild, Rcpp (>= 1.0.4), rlang, utils, withr
LinkingTo: Rcpp, RcppGSL
VignetteBuilder: knitr
SystemRequirements: GNU make, GSL, HDF5, PROJ
NeedsCompilation: yes
RcppModules: RaveIO, PolarVolume, Vol2Bird, Vol2BirdConfig
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Copyright: file COPYRIGHTS
Encoding: UTF-8
Packaged: 2022-11-15 22:59:37 UTC; amd427
Author: Anders Henja [aut], Adriaan M. Dokter [aut, cre] , Jurriaan H. Spaaks [ctb], Lourens Veen [ctb], Iwan Holleman [ctb], Hidde Leijnse [ctb], John H. Merritt [ctb], Bart Kelley [ctb], Daniel Michelson [ctb], Mark Couture [ctb], GloBAM [fnd]
Maintainer: Adriaan M. Dokter <amd427@cornell.edu>
Repository: CRAN
Date/Publication: 2022-11-16 14:40:02 UTC

More information about vol2birdR at CRAN
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Package vapour updated to version 0.9.2 with previous version 0.9.0 dated 2022-11-07

Title: Access to the 'Geospatial Data Abstraction Library' ('GDAL')
Description: Provides low-level access to 'GDAL' functionality. 'GDAL' is the 'Geospatial Data Abstraction Library' a translator for raster and vector geospatial data formats that presents a single raster abstract data model and single vector abstract data model to the calling application for all supported formats <https://gdal.org/>. This package is focussed on providing exactly and only what GDAL does, to enable developing further tools.
Author: Michael Sumner [aut, cre] , Simon Wotherspoon [ctb] , Mark Padgham [ctb] ), Edzer Pebesma [ctb] , Roger Bivand [ctb] , Jim Hester [ctb, cph] , Timothy Keitt [ctb] , Jeroen Ooms [ctb] , Dale Maschette [ctb] , Joseph Stachelek [ctb], Even Rouault [ctb] [...truncated...]
Maintainer: Michael Sumner <mdsumner@gmail.com>

Diff between vapour versions 0.9.0 dated 2022-11-07 and 0.9.2 dated 2022-11-16

 vapour-0.9.0/vapour/man/vapour_read_names.Rd                   |only
 vapour-0.9.2/vapour/DESCRIPTION                                |   11 
 vapour-0.9.2/vapour/MD5                                        |   65 
 vapour-0.9.2/vapour/NAMESPACE                                  |    1 
 vapour-0.9.2/vapour/NEWS.md                                    |   15 
 vapour-0.9.2/vapour/R/RcppExports.R                            |  374 +--
 vapour-0.9.2/vapour/R/vapour-package.R                         |   96 
 vapour-0.9.2/vapour/R/vapour_input_attributes.R                |   15 
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 vapour-0.9.2/vapour/R/zzz.R                                    |    6 
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 vapour-0.9.2/vapour/configure.ac                               |   17 
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 vapour-0.9.2/vapour/inst/include/gdalmiscutils/gdalmiscutils.h |   41 
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 vapour-0.9.2/vapour/vignettes/feature-access.Rmd               |    4 
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 35 files changed, 1375 insertions(+), 1231 deletions(-)

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Package ursa updated to version 3.9.8 with previous version 3.9.7 dated 2022-09-11

Title: Non-Interactive Spatial Tools for Raster Processing and Visualization
Description: S3 classes and methods for manipulation with georeferenced raster data: reading/writing, processing, multi-panel visualization. SWU.
Author: Nikita Platonov [aut, cre]
Maintainer: Nikita Platonov <platonov@sevin.ru>

Diff between ursa versions 3.9.7 dated 2022-09-11 and 3.9.8 dated 2022-11-16

 DESCRIPTION                |    6 +++---
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 18 files changed, 87 insertions(+), 59 deletions(-)

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New package tibblify with initial version 0.3.0
Package: tibblify
Title: Rectangle Nested Lists
Version: 0.3.0
Description: A tool to rectangle a nested list, that is to convert it into a tibble. This is done automatically or according to a given specification. A common use case is for nested lists coming from parsing JSON files or the JSON response of REST APIs. It is supported by the 'vctrs' package and therefore offers a wide support of vector types.
License: GPL-3
URL: https://github.com/mgirlich/tibblify, https://mgirlich.github.io/tibblify/
BugReports: https://github.com/mgirlich/tibblify/issues
Depends: R (>= 3.4.0)
Imports: cli (>= 3.3.0), lifecycle (>= 1.0.1), purrr (>= 0.3.4), rlang (>= 1.0.4), tibble (>= 3.1.8), tidyselect (>= 1.2.0), vctrs (>= 0.5.0), withr (>= 2.5.0)
Suggests: covr (>= 3.6.1), jsonlite (>= 1.8.0), knitr (>= 1.40), rmarkdown (>= 2.16), spelling (>= 2.2), testthat (>= 3.1.4)
LinkingTo: vctrs (>= 0.5.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: yes
SystemRequirements: C++11
Packaged: 2022-11-14 07:13:35 UTC; mgirlich
Author: Maximilian Girlich [aut, cre, cph], Kirill Mueller [ctb]
Maintainer: Maximilian Girlich <maximilian.girlich@outlook.com>
Repository: CRAN
Date/Publication: 2022-11-16 14:40:09 UTC

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Package snSMART updated to version 0.2.2 with previous version 0.2.1 dated 2022-10-06

Title: Small N Sequential Multiple Assignment Randomized Trial Methods
Description: Consolidated data simulation, sample size calculation and analysis functions for several snSMART (small sample sequential, multiple assignment, randomized trial) designs under one library. See Wei, B., Braun, T.M., Tamura, R.N. and Kidwell, K.M. "A Bayesian analysis of small n sequential multiple assignment randomized trials (snSMARTs)." (2018) Statistics in medicine, 37(26), pp.3723-3732 <doi:10.1002/sim.7900>.
Author: Sidi Wang [aut], Kelley Kidwell [aut], Michael Kleinsasser [cre]
Maintainer: Michael Kleinsasser <mkleinsa@umich.edu>

Diff between snSMART versions 0.2.1 dated 2022-10-06 and 0.2.2 dated 2022-11-16

 DESCRIPTION               |   42 +++---
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 21 files changed, 591 insertions(+), 350 deletions(-)

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Package SmallCountRounding updated to version 1.0.3 with previous version 1.0.2 dated 2022-10-12

Title: Small Count Rounding of Tabular Data
Description: A statistical disclosure control tool to protect frequency tables in cases where small values are sensitive. The function PLSrounding() performs small count rounding of necessary inner cells so that all small frequencies of cross-classifications to be published (publishable cells) are rounded. This is equivalent to changing micro data since frequencies of unique combinations are changed. Thus, additivity and consistency are guaranteed. The methodology is described in Langsrud and Heldal (2018) <https://www.researchgate.net/publication/327768398_An_Algorithm_for_Small_Count_Rounding_of_Tabular_Data>.
Author: Oyvind Langsrud [aut, cre], Johan Heldal [aut]
Maintainer: Oyvind Langsrud <oyl@ssb.no>

Diff between SmallCountRounding versions 1.0.2 dated 2022-10-12 and 1.0.3 dated 2022-11-16

 DESCRIPTION                                      |    8 
 MD5                                              |    8 
 NEWS.md                                          |    5 
 R/RoundViaDummy.R                                |    3 
 inst/doc/Introduction_to_SmallCountRounding.html |  656 +++++++++++++++++++----
 5 files changed, 583 insertions(+), 97 deletions(-)

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New package quadraticSD with initial version 0.1.0
Package: quadraticSD
Title: Visualizing the SD using a Quadratic Curve
Version: 0.1.0
Maintainer: Siddhanta Phuyal <siddhantaphuyal7159@gmail.com>
Description: Given a dataset, the user is invited to utilize the Empirical Cumulative Distribution Function (ECDF) to guess interactively the mean and the mean deviation. Thereafter, using the quadratic curve the user can guess the Root Mean Squared Deviation (RMSD) and visualize the standard deviation (SD). For details, see Sarkar and Rashid (2019)<doi:10.3126/njs.v3i0.25574>, Have You Seen the Standard Deviaton?, Nepalese Journal of Statistics, Vol. 3, 1-10.
License: GPL-3
Encoding: UTF-8
Imports: shiny, ggplot2
NeedsCompilation: no
Packaged: 2022-11-16 00:17:42 UTC; siddh
Author: Siddhanta Phuyal [aut, cre], Mamunur Rashid [aut], Jyotirmoy Sarkar [aut]
Repository: CRAN
Date/Publication: 2022-11-16 14:40:13 UTC

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New package mrfse with initial version 0.4.1
Package: mrfse
Title: Markov Random Field Structure Estimator
Version: 0.4.1
Date: 2022-11-10
Description: Three algorithms for estimating a Markov random field structure.Two of them are an exact version and a simulated annealing version of a penalized maximum conditional likelihood method similar to the Bayesian Information Criterion. These algorithm are described in Frondana (2016) <doi:10.11606/T.45.2018.tde-02022018-151123>.The third one is a greedy algorithm, described in Bresler (2015) <doi:10.1145/2746539.2746631).
License: GPL (>= 3)
NeedsCompilation: yes
LinkingTo: Rcpp
Imports: Rcpp
Depends: gtools, Rfast
Packaged: 2022-11-10 21:46:57 UTC; root
Author: Rodrigo Carvalho [aut, cre], Florencia Leonardi [rev, ths]
Maintainer: Rodrigo Carvalho <rodrigorsdc@gmail.com>
Repository: CRAN
Date/Publication: 2022-11-16 14:40:15 UTC

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New package MeshAgreement with initial version 0.1.2
Package: MeshAgreement
Title: Agreement Measures for 3D Meshes
Version: 0.1.2
Date: 2022-11-14
Depends: R (>= 3.5)
Imports: stats, Rvcg, cgalMeshes
Suggests: knitr, shiny, DT, bs4Dash, sortable, rgl, Boov
VignetteBuilder: knitr
LazyData: yes
Description: Calculates distance-based and volume-overlap-based agreement measures for triangular 3D meshes. These include the Hausdorff distance, the average surface distance, the Dice similarity coefficient, and the Jaccard similarity coefficient as documented in Stockinger et al. (2021) <doi:10.1186/s13014-021-01965-5>. Overall agreement for a set of meshes is calculated as the aggregate agreement for all pairwise comparisons. Based on algorithms provided by the 'VCGLIB' <http://vcg.isti.cnr.it/vcglib/> and 'CGAL' <https://www.cgal.org/> libraries. Includes web-based graphical user interface.
License: GPL (>= 2)
URL: https://github.com/dwoll/MeshAgreement/
NeedsCompilation: no
Packaged: 2022-11-14 19:18:55 UTC; Daniel
Author: Daniel Wollschlaeger [aut, cre], Heiko Karle [aut]
Maintainer: Daniel Wollschlaeger <wollschlaeger@uni-mainz.de>
Repository: CRAN
Date/Publication: 2022-11-16 14:40:28 UTC

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New package Kcop with initial version 1.0.0
Package: Kcop
Title: Smooth Test for Equality of Copulas and Clustering Multivariate
Version: 1.0.0
Description: Implements approaches of non-parametric smooth test to compare simultaneously K(K>1) copulas and non-parametric clustering of multivariate populations with arbitrary sizes. See Yves I. Ngounou Bakam and Denys Pommeret (2022) <arXiv:2112.05623> and Yves I. Ngounou Bakam and Denys Pommeret (2022) <arXiv:2211.06338>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: false
Depends: R (>= 2.10)
Imports: base, copula,dplyr, gtools, orthopolynom, stats
NeedsCompilation: no
Packaged: 2022-11-16 08:52:37 UTC; yves
Author: Yves Ismael Ngounou Bakam [aut, cre], Denys Pommeret [aut]
Maintainer: Yves Ismael Ngounou Bakam <yvesngounou20@gmail.com>
Repository: CRAN
Date/Publication: 2022-11-16 15:00:20 UTC

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Package jmatrix updated to version 1.1 with previous version 1.0 dated 2022-11-01

Title: Read from/Write to Disk Matrices with any Data Type in a Binary Format
Description: A mainly instrumental package meant to allow other packages whose core is written in 'C++' to read, write and manipulate matrices in a binary format so that the memory used for them is no more than strictly needed. Its functionality is already inside 'parallelpam' and 'scellpam', so if you have installed any of these, you do not need to install 'jmatrix'. Using just the needed memory is not always true with 'R' matrices or vectors, since by default they are of double type. Trials like the 'float' package have been done, but to use them you have to coerce a matrix already loaded in 'R' memory to a float matrix, and then you can delete it. The problem comes when your computer has not memory enough to hold the matrix in the first place, so you are forced to load it by chunks. This is the problem this package tries to address (with partial success, but this is a difficult problem since 'R' is not a strictly typed language, which is anyway quite hard to get in an interpreted language). This [...truncated...]
Author: Juan Domingo [aut, cre] , Guillermo Ayala [ctb] , Spanish Ministry of Science and Innovation, MCIN/AEI <doi:10.13039/501100011033> [fnd]
Maintainer: Juan Domingo <Juan.Domingo@uv.es>

Diff between jmatrix versions 1.0 dated 2022-11-01 and 1.1 dated 2022-11-16

 DESCRIPTION            |    6 +-
 MD5                    |   14 ++---
 inst/doc/jmatrix.html  |  135 +++++++++++++++++++++++--------------------------
 inst/include/jmatrix.h |   20 +++++++
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 src/jmatrixaux.cpp     |   38 +++++++++++++
 src/matinfo.cpp        |   20 +++----
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 8 files changed, 194 insertions(+), 107 deletions(-)

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Package hpa updated to version 1.3.0 with previous version 1.2.1 dated 2021-07-04

Title: Distributions Hermite Polynomial Approximation
Description: Multivariate conditional and marginal densities, moments, cumulative distribution functions as well as binary choice and sample selection models based on Hermite polynomial approximation which was proposed and described by A. Gallant and D. W. Nychka (1987) <doi:10.2307/1913241>.
Author: Potanin Bogdan
Maintainer: Potanin Bogdan <bogdanpotanin@gmail.com>

Diff between hpa versions 1.2.1 dated 2021-07-04 and 1.3.0 dated 2022-11-16

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 NAMESPACE                 |    2 
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 src/hpaSelection.cpp      |   31 -
 src/hpaValidation.cpp     |    3 
 src/normalMoments.cpp     |   21 
 src/polynomialIndex.cpp   |    1 
 src/spline.cpp            |   20 
 18 files changed, 1644 insertions(+), 321 deletions(-)

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New package irtpwr with initial version 1.0.0
Package: irtpwr
Title: Power Analysis for IRT Models Using the Wald, LR, Score, and Gradient Statistics
Version: 1.0.0
Description: Implementation of analytical and sampling-based power analyses for the Wald, likelihood ratio (LR), score, and gradient tests. Can be applied to item response theory (IRT) models that are fitted using marginal maximum likelihood estimation. The methods are described in our paper (Zimmer et al. (2022) <doi:10.1007/s11336-022-09883-5>).
License: GPL (>= 3)
URL: https://github.com/flxzimmer/irtpwr
BugReports: https://github.com/flxzimmer/irtpwr/issues
Encoding: UTF-8
Suggests: testthat, knitr, rmarkdown
Imports: mirt, Deriv, digest, spatstat.random, ggplot2, methods
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-11-16 13:10:38 UTC; fzimmer
Author: Felix Zimmer [aut, cre] , Rudolf Debelak [aut]
Maintainer: Felix Zimmer <felix.zimmer@mail.de>
Repository: CRAN
Date/Publication: 2022-11-16 15:00:14 UTC

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Package extremeStat updated to version 1.5.3 with previous version 1.5.2 dated 2022-08-23

Title: Extreme Value Statistics and Quantile Estimation
Description: Fit, plot and compare several (extreme value) distribution functions. Compute (truncated) distribution quantile estimates and plot return periods on a linear scale. On the fitting method, see Asquith (2011): Distributional Analysis with L-moment Statistics [...] ISBN 1463508417.
Author: Berry Boessenkool
Maintainer: Berry Boessenkool <berry-b@gmx.de>

Diff between extremeStat versions 1.5.2 dated 2022-08-23 and 1.5.3 dated 2022-11-16

 DESCRIPTION                    |    8 ++--
 MD5                            |    6 +--
 inst/doc/extremeStat.html      |   70 +++++++++++++++++++++--------------------
 tests/testthat/test-quantile.R |    4 +-
 4 files changed, 46 insertions(+), 42 deletions(-)

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Package dataquieR updated to version 1.0.13 with previous version 1.0.12 dated 2022-11-11

Title: Data Quality in Epidemiological Research
Description: Data quality assessments guided by a 'data quality framework introduced by Schmidt and colleagues, 2021' <doi:10.1186/s12874-021-01252-7> target the data quality dimensions integrity, completeness, consistency, and accuracy. The scope of applicable functions rests on the availability of extensive metadata which can be provided in spreadsheet tables. Either standardized (e.g. as 'html5' reports) or individually tailored reports can be generated. For an introduction into the specification of corresponding metadata, please refer to the 'package website' <https://dataquality.ship-med.uni-greifswald.de/Annotation_of_Metadata.html>.
Author: University Medicine Greifswald [cph], Elisa Kasbohm [aut] , Joany Marino [aut] , Adrian Richter [aut] , Carsten Oliver Schmidt [aut] , Stephan Struckmann [aut, cre] , German Research Foundation [fnd], European Union’s Horizon 2020 programme [fnd]
Maintainer: Stephan Struckmann <stephan.struckmann@uni-greifswald.de>

Diff between dataquieR versions 1.0.12 dated 2022-11-11 and 1.0.13 dated 2022-11-16

 DESCRIPTION                     |    6 ++--
 MD5                             |    8 ++---
 NEWS.md                         |    4 ++
 R/acc_margins.R                 |    2 -
 inst/doc/DQ-report-example.html |   58 ++++++++++++++++++++--------------------
 5 files changed, 41 insertions(+), 37 deletions(-)

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New package dartR.data with initial version 1.0.2
Package: dartR.data
Title: Auxiliary Data Package for Our Main Package 'dartR'
Version: 1.0.2
Description: Data package for 'dartR'. Provides data sets to run examples in 'dartR'. This was necessary due to the size limit imposed by 'CRAN'. The data in 'dartR.data' is needed to run the examples provided in the 'dartR' functions. All available data sets are either based on actual data (but reduced in size) and/or simulated data sets to allow the fast execution of examples and demonstration of the functions.
Depends: R (>= 3.5), adegenet (>= 2.0.0)
License: GPL (>= 3)
LazyData: true
Encoding: UTF-8
NeedsCompilation: no
URL: https://github.com/green-striped-gecko/dartR.data
BugReports: https://groups.google.com/g/dartr?pli=1
Packaged: 2022-11-16 02:42:11 UTC; s425824
Author: Bernd Gruber [aut, cre], Arthur Georges [aut], Jose L. Mijangos [aut], Carlo Pacioni [aut], Oliver Berry [ctb]
Maintainer: Bernd Gruber <bernd.gruber@canberra.edu.au>
Repository: CRAN
Date/Publication: 2022-11-16 14:50:02 UTC

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New package custom.gauss.quad with initial version 1.0.0
Package: custom.gauss.quad
Title: Custom Made Gauss Quadrature Nodes and Weights
Version: 1.0.0
Maintainer: Paul Kabaila <p.kabaila@latrobe.edu.au>
Description: Use the high-precision arithmetic provided by the R package 'Rmpfr' to compute a custom-made Gauss quadrature nodes and weights, with up to 33 nodes, using a moment-based method via moment determinants. Paul Kabaila (2022) <arXiv:2211.04729>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rmpfr
NeedsCompilation: no
Packaged: 2022-11-16 02:47:08 UTC; Kabaila
Author: Paul Kabaila [aut, cre]
Repository: CRAN
Date/Publication: 2022-11-16 14:50:05 UTC

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New package cipheR with initial version 1.0.0
Package: cipheR
Title: Encryption and Decryption with Text Ciphers
Version: 1.0.0
Description: Encrypts and decrypts using basic ciphers. None of these should be used in place of real encryption using state of the art tools. The ciphers included use methods described in the ciphers's Wikipedia and cryptography hobby websites.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2022-11-16 02:37:08 UTC; guslipkin
Author: Gus Lipkin [aut, cre]
Maintainer: Gus Lipkin <gus.lipkin@gmail.com>
Repository: CRAN
Date/Publication: 2022-11-16 14:50:08 UTC

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New package casebase with initial version 0.10.3
Package: casebase
Title: Fitting Flexible Smooth-in-Time Hazards and Risk Functions via Logistic and Multinomial Regression
Version: 0.10.3
Date: 2022-11-09
Description: Fit flexible and fully parametric hazard regression models to survival data with single event type or multiple competing causes via logistic and multinomial regression. Our formulation allows for arbitrary functional forms of time and its interactions with other predictors for time-dependent hazards and hazard ratios. From the fitted hazard model, we provide functions to readily calculate and plot cumulative incidence and survival curves for a given covariate profile. This approach accommodates any log-linear hazard function of prognostic time, treatment, and covariates, and readily allows for non-proportionality. We also provide a plot method for visualizing incidence density via population time plots. Based on the case-base sampling approach of Hanley and Miettinen (2009) <DOI:10.2202/1557-4679.1125>, Saarela and Arjas (2015) <DOI:10.1111/sjos.12125>, and Saarela (2015) <DOI:10.1007/s10985-015-9352-x>.
Depends: R (>= 3.5.0)
Imports: data.table, ggplot2, methods, mgcv, stats, survival, VGAM
License: MIT + file LICENSE
LazyData: TRUE
Suggests: colorspace, covr, eha, glmnet, knitr, progress, rmarkdown, splines, testthat (>= 3.0.0), visreg
VignetteBuilder: knitr
URL: https://sahirbhatnagar.com/casebase/
BugReports: https://github.com/sahirbhatnagar/casebase/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-11-13 17:55:05 UTC; sahirbhatnagar
Author: Sahir Bhatnagar [aut, cre] , Maxime Turgeon [aut] , Jesse Islam [aut] , Olli Saarela [aut] , James Hanley [aut]
Maintainer: Sahir Bhatnagar <sahir.bhatnagar@gmail.com>
Repository: CRAN
Date/Publication: 2022-11-16 14:30:08 UTC

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Package ttbary updated to version 0.3-1 with previous version 0.3-0 dated 2022-08-15

Title: Barycenter Methods for Spatial Point Patterns
Description: Computes a point pattern in R^2 or on a graph that is representative of a collection of many data patterns. The result is an approximate barycenter (also known as Fréchet mean or prototype) based on a transport-transform metric. Possible choices include Optimal SubPattern Assignment (OSPA) and Spike Time metrics. Details can be found in Müller, Schuhmacher and Mateu (2020) <doi:10.1007/s11222-020-09932-y>.
Author: Raoul Mueller [aut], Dominic Schuhmacher [aut, cre]
Maintainer: Dominic Schuhmacher <dominic.schuhmacher@mathematik.uni-goettingen.de>

Diff between ttbary versions 0.3-0 dated 2022-08-15 and 0.3-1 dated 2022-11-16

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Package matlab2r updated to version 1.3.0 with previous version 1.2.0 dated 2022-08-17

Title: Translation Layer from MATLAB to R
Description: Allows users familiar with MATLAB to use MATLAB-named functions in R. Several basic MATLAB functions are written in this package to mimic the behavior of their original counterparts, with more to come as this package grows.
Author: Waldir Leoncio [aut, cre]
Maintainer: Waldir Leoncio <w.l.netto@medisin.uio.no>

Diff between matlab2r versions 1.2.0 dated 2022-08-17 and 1.3.0 dated 2022-11-16

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Package HDiR updated to version 1.1.3 with previous version 1.1.2 dated 2022-08-06

Title: Directional Highest Density Regions
Description: We provide an R tool for computation and nonparametric plug-in estimation of Highest Density Regions (HDRs) and general level sets in the directional setting. Concretely, circular and spherical HDRs can be reconstructed from a data sample following Saavedra-Nieves and Crujeiras (2021) <doi:10.1007/s11634-021-00457-4>. This library also contains two real datasets in the circular and spherical settings. The first one concerns a problem from animal orientation studies and the second one is related to earthquakes occurrences.
Author: Paula Saavedra-Nieves [aut, cre], Rosa M Crujeiras [aut], Andres Prieto [ctb], Felicita Scapini [dtc]
Maintainer: Paula Saavedra-Nieves <paula.saavedra@usc.es>

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Package crunch updated to version 1.30.1 with previous version 1.30.0 dated 2022-05-02

Title: Crunch.io Data Tools
Description: The Crunch.io service <https://crunch.io/> provides a cloud-based data store and analytic engine, as well as an intuitive web interface. Using this package, analysts can interact with and manipulate Crunch datasets from within R. Importantly, this allows technical researchers to collaborate naturally with team members, managers, and clients who prefer a point-and-click interface.
Author: Greg Freedman Ellis [aut, cre], Jonathan Keane [aut], Mike Malecki [aut], Neal Richardson [aut], Gordon Shotwell [aut]
Maintainer: Greg Freedman Ellis <greg@crunch.io>

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Package ardl.nardl updated to version 1.0.2 with previous version 1.0.1 dated 2022-11-04

Title: Linear and Nonlinear Autoregressive Distributed Lag Models
Description: Estimate the linear and nonlinear autoregressive distributed lag (ARDL & NARDL) models and the corresponding error correction models, and test for longrun and short-run asymmetric. The Pesaran, Shin & Smith (2001) (<doi:10.1002/jae.616>) bounds test for level relationships is also provided. The 'ardl.nardl' package also performs short-run and longrun symmetric restrictions available at Shin et al. (2014) <doi:10.1007/978-1-4899-8008-3_9> and their corresponding tests.
Author: Eric I. Otoakhia [aut, cre]
Maintainer: Eric I. Otoakhia <otoakhiai@gmail.com>

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Package era (with last version 0.4.0) was removed from CRAN

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

2022-03-09 0.4.0
2021-01-29 0.3.1

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Package deBInfer (with last version 0.4.3) was removed from CRAN

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

2022-04-21 0.4.3
2018-04-18 0.4.2
2016-09-14 0.4.1

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Package workflows updated to version 1.1.2 with previous version 1.1.0 dated 2022-09-26

Title: Modeling Workflows
Description: Managing both a 'parsnip' model and a preprocessor, such as a model formula or recipe from 'recipes', can often be challenging. The goal of 'workflows' is to streamline this process by bundling the model alongside the preprocessor, all within the same object.
Author: Davis Vaughan [aut], Simon Couch [aut, cre] , RStudio [cph, fnd]
Maintainer: Simon Couch <simonpatrickcouch@gmail.com>

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Package tidyquant updated to version 1.0.6 with previous version 1.0.5 dated 2022-09-08

Title: Tidy Quantitative Financial Analysis
Description: Bringing business and financial analysis to the 'tidyverse'. The 'tidyquant' package provides a convenient wrapper to various 'xts', 'zoo', 'quantmod', 'TTR' and 'PerformanceAnalytics' package functions and returns the objects in the tidy 'tibble' format. The main advantage is being able to use quantitative functions with the 'tidyverse' functions including 'purrr', 'dplyr', 'tidyr', 'ggplot2', 'lubridate', etc. See the 'tidyquant' website for more information, documentation and examples.
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>

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Package surveillance updated to version 1.20.3 with previous version 1.20.1 dated 2022-07-19

Title: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena
Description: Statistical methods for the modeling and monitoring of time series of counts, proportions and categorical data, as well as for the modeling of continuous-time point processes of epidemic phenomena. The monitoring methods focus on aberration detection in count data time series from public health surveillance of communicable diseases, but applications could just as well originate from environmetrics, reliability engineering, econometrics, or social sciences. The package implements many typical outbreak detection procedures such as the (improved) Farrington algorithm, or the negative binomial GLR-CUSUM method of Hoehle and Paul (2008) <doi:10.1016/j.csda.2008.02.015>. A novel CUSUM approach combining logistic and multinomial logistic modeling is also included. The package contains several real-world data sets, the ability to simulate outbreak data, and to visualize the results of the monitoring in a temporal, spatial or spatio-temporal fashion. A recent overview of the available mon [...truncated...]
Author: Michael Hoehle [aut, ths] , Sebastian Meyer [aut, cre] , Michaela Paul [aut], Leonhard Held [ctb, ths], Howard Burkom [ctb], Thais Correa [ctb], Mathias Hofmann [ctb], Christian Lang [ctb], Juliane Manitz [ctb], Andrea Riebler [ctb], Daniel Sabanes B [...truncated...]
Maintainer: Sebastian Meyer <seb.meyer@fau.de>

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Package SpatialBSS updated to version 0.13-0 with previous version 0.12-0 dated 2021-10-07

Title: Blind Source Separation for Multivariate Spatial Data
Description: Blind source separation for multivariate spatial data based on simultaneous/joint diagonalization of (robust) local covariance matrices. This package is an implementation of the methods described in Bachoc, Genton, Nordhausen, Ruiz-Gazen and Virta (2020) <doi:10.1093/biomet/asz079>.
Author: Christoph Muehlmann [aut, cre] , Mika Sipil<e4> [aut] , Klaus Nordhausen [aut] , Sara Taskinen [aut] , Joni Virta [aut]
Maintainer: Christoph Muehlmann <christoph.muehlmann@tuwien.ac.at>

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Package sensobol updated to version 1.1.2 with previous version 1.1.1 dated 2022-04-26

Title: Computation of Variance-Based Sensitivity Indices
Description: It allows to rapidly compute, bootstrap and plot up to fourth-order Sobol'-based sensitivity indices using several state-of-the-art first and total-order estimators. Sobol' indices can be computed either for models that yield a scalar as a model output or for systems of differential equations. The package also provides a suit of benchmark tests functions and several options to obtain publication-ready figures of the model output uncertainty and sensitivity-related analysis. An overview of the package can be found in Puy et al. (2022) <doi:10.18637/jss.v102.i05>.
Author: Arnald Puy [aut, cre] , Bertrand Ioos [ctb] , Gilles Pujol [ctb] , RStudio [cph]
Maintainer: Arnald Puy <arnald.puy@pm.me>

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Package SAMtool updated to version 1.4.1 with previous version 1.4.0 dated 2022-06-07

Title: Stock Assessment Methods Toolkit
Description: Simulation tools for closed-loop simulation are provided for the 'MSEtool' operating model to inform data-rich fisheries. 'SAMtool' provides a conditioning model, assessment models of varying complexity with standardized reporting, model-based management procedures, and diagnostic tools for evaluating assessments inside closed-loop simulation.
Author: Quang Huynh [aut, cre], Tom Carruthers [aut], Adrian Hordyk [aut]
Maintainer: Quang Huynh <quang@bluematterscience.com>

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Package rust updated to version 1.4.0 with previous version 1.3.13 dated 2021-10-31

Title: Ratio-of-Uniforms Simulation with Transformation
Description: Uses the generalized ratio-of-uniforms (RU) method to simulate from univariate and (low-dimensional) multivariate continuous distributions. The user specifies the log-density, up to an additive constant. The RU algorithm is applied after relocation of mode of the density to zero, and the user can choose a tuning parameter r. For details see Wakefield, Gelfand and Smith (1991) <DOI:10.1007/BF01889987>, Efficient generation of random variates via the ratio-of-uniforms method, Statistics and Computing (1991) 1, 129-133. A Box-Cox variable transformation can be used to make the input density suitable for the RU method and to improve efficiency. In the multivariate case rotation of axes can also be used to improve efficiency. From version 1.2.0 the 'Rcpp' package <https://cran.r-project.org/package=Rcpp> can be used to improve efficiency.
Author: Paul J. Northrop [aut, cre, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

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Package PDtoolkit updated to version 1.0.0 with previous version 0.4.0 dated 2022-06-06

Title: Collection of Tools for PD Rating Model Development and Validation
Description: The goal of this package is to cover the most common steps in probability of default (PD) rating model development and validation. The main procedures available are those that refer to univariate, bivariate, multivariate analysis, calibration and validation. Along with accompanied 'monobin' and 'monobinShiny' packages, 'PDtoolkit' provides functions which are suitable for different data transformation and modeling tasks such as: imputations, monotonic binning of numeric risk factors, binning of categorical risk factors, weights of evidence (WoE) and information value (IV) calculations, WoE coding (replacement of risk factors modalities with WoE values), risk factor clustering, area under curve (AUC) calculation and others. Additionally, package provides set of validation functions for testing homogeneity, heterogeneity, discriminatory and predictive power of the model.
Author: Andrija Djurovic [aut, cre]
Maintainer: Andrija Djurovic <djandrija@gmail.com>

Diff between PDtoolkit versions 0.4.0 dated 2022-06-06 and 1.0.0 dated 2022-11-16

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Package modeltime updated to version 1.2.4 with previous version 1.2.3 dated 2022-10-18

Title: The Tidymodels Extension for Time Series Modeling
Description: The time series forecasting framework for use with the 'tidymodels' ecosystem. Models include ARIMA, Exponential Smoothing, and additional time series models from the 'forecast' and 'prophet' packages. Refer to "Forecasting Principles & Practice, Second edition" (<https://otexts.com/fpp2/>). Refer to "Prophet: forecasting at scale" (<https://research.facebook.com/blog/2017/02/prophet-forecasting-at-scale/>.).
Author: Matt Dancho [aut, cre], Business Science [cph]
Maintainer: Matt Dancho <mdancho@business-science.io>

Diff between modeltime versions 1.2.3 dated 2022-10-18 and 1.2.4 dated 2022-11-16

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Package mlr3fselect updated to version 0.8.0 with previous version 0.7.2 dated 2022-08-25

Title: Feature Selection for 'mlr3'
Description: Implements methods for feature selection with 'mlr3', e.g. random search and sequential selection. Various termination criteria can be set and combined. The class 'AutoFSelector' provides a convenient way to perform nested resampling in combination with 'mlr3'.
Author: Marc Becker [aut, cre] , Patrick Schratz [aut] , Michel Lang [aut] , Bernd Bischl [aut]
Maintainer: Marc Becker <marcbecker@posteo.de>

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Package MatchIt updated to version 4.5.0 with previous version 4.4.0 dated 2022-05-18

Title: Nonparametric Preprocessing for Parametric Causal Inference
Description: Selects matched samples of the original treated and control groups with similar covariate distributions -- can be used to match exactly on covariates, to match on propensity scores, or perform a variety of other matching procedures. The package also implements a series of recommendations offered in Ho, Imai, King, and Stuart (2007) <DOI:10.1093/pan/mpl013>. (The 'gurobi' package, which is not on CRAN, is optional and comes with an installation of the Gurobi Optimizer, available at <https://www.gurobi.com>.)
Author: Daniel Ho [aut] , Kosuke Imai [aut] , Gary King [aut] , Elizabeth Stuart [aut] , Alex Whitworth [ctb], Noah Greifer [cre, aut]
Maintainer: Noah Greifer <noah.greifer@gmail.com>

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Package marmap updated to version 1.0.8 with previous version 1.0.7 dated 2022-11-12

Title: Import, Plot and Analyze Bathymetric and Topographic Data
Description: Import xyz data from the NOAA (National Oceanic and Atmospheric Administration, <https://www.noaa.gov>), GEBCO (General Bathymetric Chart of the Oceans, <https://www.gebco.net>) and other sources, plot xyz data to prepare publication-ready figures, analyze xyz data to extract transects, get depth / altitude based on geographical coordinates, or calculate z-constrained least-cost paths.
Author: Eric Pante, Benoit Simon-Bouhet, and Jean-Olivier Irisson
Maintainer: Benoit Simon-Bouhet <besibo@gmail.com>

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Package markdown updated to version 1.4 with previous version 1.3 dated 2022-10-29

Title: Render Markdown with 'commonmark'
Description: Render Markdown to full HTML documents with the 'commonmark' package. Markdown is a plain-text formatting syntax that can be converted to 'XHTML' or other formats. See <https://en.wikipedia.org/wiki/Markdown> for more information about Markdown.
Author: JJ Allaire [aut], Jeffrey Horner [aut], Yihui Xie [aut, cre] , Henrik Bengtsson [ctb], Jim Hester [ctb], Yixuan Qiu [ctb], Kohske Takahashi [ctb], Adam November [ctb], Nacho Caballero [ctb], Jeroen Ooms [ctb], Thomas Leeper [ctb], Joe Cheng [ctb], An [...truncated...]
Maintainer: Yihui Xie <xie@yihui.name>

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Package ibdreg updated to version 0.3.8 with previous version 0.3.6 dated 2021-09-05

Title: Regression Methods for IBD Linkage with Covariates
Description: Method to test genetic linkage with covariates by regression methods with response IBD sharing for relative pairs. Account for correlations of IBD statistics and covariates for relative pairs within the same pedigree.
Author: Jason P. Sinnwell and Daniel J. Schaid
Maintainer: Jason P. Sinnwell <Sinnwell.Jason@mayo.edu>

Diff between ibdreg versions 0.3.6 dated 2021-09-05 and 0.3.8 dated 2022-11-16

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Package healthyR.ai updated to version 0.0.10 with previous version 0.0.9 dated 2022-10-04

Title: The Machine Learning and AI Modeling Companion to 'healthyR'
Description: Hospital machine learning and ai data analysis workflow tools, modeling, and automations. This library provides many useful tools to review common administrative hospital data. Some of these include predicting length of stay, and readmits. The aim is to provide a simple and consistent verb framework that takes the guesswork out of everything.
Author: Steven Sanderson [aut, cre, cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>

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Package ggpubr updated to version 0.5.0 with previous version 0.4.0 dated 2020-06-27

Title: 'ggplot2' Based Publication Ready Plots
Description: The 'ggplot2' package is excellent and flexible for elegant data visualization in R. However the default generated plots requires some formatting before we can send them for publication. Furthermore, to customize a 'ggplot', the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills. 'ggpubr' provides some easy-to-use functions for creating and customizing 'ggplot2'- based publication ready plots.
Author: Alboukadel Kassambara [aut, cre]
Maintainer: Alboukadel Kassambara <alboukadel.kassambara@gmail.com>

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Package distr updated to version 2.9.1 with previous version 2.9.0 dated 2022-11-12

Title: Object Oriented Implementation of Distributions
Description: S4-classes and methods for distributions.
Author: Florian Camphausen [ctb] , Matthias Kohl [aut, cph], Peter Ruckdeschel [cre, cph], Thomas Stabla [ctb] , R Core Team [ctb, cph]
Maintainer: Peter Ruckdeschel <peter.ruckdeschel@uni-oldenburg.de>

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Package CORElearn updated to version 1.57.2 with previous version 1.57.1 dated 2022-11-06

Title: Classification, Regression and Feature Evaluation
Description: A suite of machine learning algorithms written in C++ with the R interface contains several learning techniques for classification and regression. Predictive models include e.g., classification and regression trees with optional constructive induction and models in the leaves, random forests, kNN, naive Bayes, and locally weighted regression. All predictions obtained with these models can be explained and visualized with the 'ExplainPrediction' package. This package is especially strong in feature evaluation where it contains several variants of Relief algorithm and many impurity based attribute evaluation functions, e.g., Gini, information gain, MDL, and DKM. These methods can be used for feature selection or discretization of numeric attributes. The OrdEval algorithm and its visualization is used for evaluation of data sets with ordinal features and class, enabling analysis according to the Kano model of customer satisfaction. Several algorithms support parallel multithreaded executi [...truncated...]
Author: Marko Robnik-Sikonja and Petr Savicky
Maintainer: "Marko Robnik-Sikonja" <marko.robnik@fri.uni-lj.si>

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Package cgam updated to version 1.20 with previous version 1.19 dated 2022-10-04

Title: Constrained Generalized Additive Model
Description: A constrained generalized additive model is fitted by the cgam routine. Given a set of predictors, each of which may have a shape or order restrictions, the maximum likelihood estimator for the constrained generalized additive model is found using an iteratively re-weighted cone projection algorithm. The ShapeSelect routine chooses a subset of predictor variables and describes the component relationships with the response. For each predictor, the user needs only specify a set of possible shape or order restrictions. A model selection method chooses the shapes and orderings of the relationships as well as the variables. The cone information criterion (CIC) is used to select the best combination of variables and shapes. A genetic algorithm may be used when the set of possible models is large. In addition, the cgam routine implements a two-dimensional isotonic regression using warped-plane splines without additivity assumptions. It can also fit a convex or concave regression surface with [...truncated...]
Author: Mary Meyer [aut], Xiyue Liao [aut, cre]
Maintainer: Xiyue Liao <xiyue.liao@csulb.edu>

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Package bnclassify updated to version 0.4.7 with previous version 0.4.6 dated 2021-10-29

Title: Learning Discrete Bayesian Network Classifiers from Data
Description: State-of-the art algorithms for learning discrete Bayesian network classifiers from data, including a number of those described in Bielza & Larranaga (2014) <doi:10.1145/2576868>, with functions for prediction, model evaluation and inspection.
Author: Mihaljevic Bojan [aut, cre], Bielza Concha [aut], Larranaga Pedro [aut], Wickham Hadley [ctb]
Maintainer: Mihaljevic Bojan <boki.mihaljevic@gmail.com>

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Package asremlPlus updated to version 4.3.40 with previous version 4.3.36 dated 2022-08-17

Title: Augments 'ASReml-R' in Fitting Mixed Models and Packages Generally in Exploring Prediction Differences
Description: Assists in automating the selection of terms to include in mixed models when 'asreml' is used to fit the models. Also used to display, in tables and graphs, predictions obtained using any model fitting function and to explore differences between predictions. The content falls into the following natural groupings: (i) Data, (ii) Object manipulation functions, (iii) Model modification functions, (iv) Model testing functions, (v) Model diagnostics functions, (vi) Prediction production and presentation functions, (vii) Response transformation functions, and (viii) Miscellaneous functions (for further details see 'asremlPlus-package' in help). A history of the fitting of a sequence of models is kept in a data frame. Procedures are available for choosing models that conform to the hierarchy or marginality principle and for displaying predictions for significant terms in tables and graphs. The 'asreml' package provides a computationally efficient algorithm for fitting mixed models using Resi [...truncated...]
Author: Chris Brien [aut, cre]
Maintainer: Chris Brien <chris.brien@adelaide.edu.au>

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Package ACDm updated to version 1.0.4.2 with previous version 1.0.4.1 dated 2022-07-08

Title: Tools for Autoregressive Conditional Duration Models
Description: Package for Autoregressive Conditional Duration (ACD, Engle and Russell, 1998) models. Creates trade, price or volume durations from transactions (tic) data, performs diurnal adjustments, fits various ACD models and tests them.
Author: Markus Belfrage
Maintainer: Markus Belfrage <markus.belfrage@gmail.com>

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New package taboolaR with initial version 0.1.0
Package: taboolaR
Title: Get Data from 'Taboola' via the 'Windsor.ai' API
Version: 0.1.0
Description: Collect your data on digital marketing campaigns from 'Taboola' using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.
License: GPL-3
URL: https://windsor.ai/
Depends: R (>= 3.5.0)
Imports: jsonlite (>= 1.7.2)
Suggests: knitr, rmarkdown, dplyr, ggplot2, tidyr, curl
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2022-11-14 16:05:34 UTC; pablo
Author: Pablo Sanchez [cre, aut], Windsor.ai [cph]
Maintainer: Pablo Sanchez <pablosama@outlook.es>
Repository: CRAN
Date/Publication: 2022-11-16 11:50:02 UTC

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Package schtools updated to version 0.3.1 with previous version 0.3.0 dated 2022-10-05

Title: Schloss Lab Tools for Reproducible Microbiome Research
Description: A collection of useful functions and example code created and used by the Schloss Lab for reproducible microbiome research. Perform common tasks like read files created by mothur <https://mothur.org/>, tidy up your microbiome data, and format R Markdown documents for publication. See the website <http://www.schlosslab.org/schtools/> for more information, documentation, and examples.
Author: Kelly Sovacool [aut, cre] , Nick Lesniak [aut] , Patrick Schloss [aut], Sarah Lucas [ctb] , Courtney Armour [ctb] , Jacqueline Moltzau [ctb] , Andrew Hannah [ctb], Nielson Baxter [ctb], Alyxandria Schubert [ctb], Kathryn Iverson [ctb]
Maintainer: Kelly Sovacool <sovacool@umich.edu>

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Package proverbs updated to version 0.2.0 with previous version 0.1.0 dated 2022-02-01

Title: Print a Daily Bible Proverb to Console
Description: A simple package to grab a Bible proverb corresponding to the day of the month.
Author: Brad Lindblad [aut, cre, cph]
Maintainer: Brad Lindblad <me@bradlindblad.com>

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Package NMdata updated to version 0.0.14 with previous version 0.0.13 dated 2022-09-07

Title: Preparation, Checking and Post-Processing Data for PK/PD Modeling
Description: Efficient tools for preparation, checking and post-processing of data in PK/PD (pharmacokinetics/pharmacodynamics) modeling, with focus on use of Nonmem. Helps with trivial but tedious tasks and tries to identify errors to save time on debugging. Implemented in 'data.table', but easily integrated with 'base' and 'tidyverse'.
Author: Philip Delff [aut, cre]
Maintainer: Philip Delff <philip@delff.dk>

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New package loedata with initial version 1.0.1
Package: loedata
Title: Data Sets from "Lectures on Econometrics" by Chirok Han
Version: 1.0.1
Description: Data sets for Chirok Han (2022, ISBN:979-11-303-1497-6, "Lectures on Econometrics"). Students, teachers, and self-learners will find the data sets essential for replicating the results in the book.
Depends: R (>= 3.0)
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-11-15 02:36:42 UTC; hanch
Author: Chirok Han [aut, cre, cph]
Maintainer: Chirok Han <chirokhan@korea.ac.kr>
Repository: CRAN
Date/Publication: 2022-11-16 12:00:05 UTC

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New package dsmmR with initial version 0.0.96
Package: dsmmR
Title: Estimation and Simulation of Drifting Semi-Markov Models
Version: 0.0.96
Date: 2022-11-15
Description: Performs parametric and non-parametric estimation and simulation of Drifting semi-Markov processes. The definition of parametric and non-parametric model specifications is also possible. Furthermore, three different types of Drifting semi-Markov models are considered. These models differ in the number of transition matrices and sojourn time distributions used for the computation of a number of semi-Markov kernels, which in turn characterize the Drifting semi-Markov kernel. For the parametric model estimation and specification, several discrete distributions are considered for the sojourn times: Uniform, Poisson, Geometric, Discrete Weibull and Negative Binomial. The non-parametric model specification makes no assumptions about the shape of the sojourn time distributions. Semi-Markov models are described in: Barbu, V.S., Limnios, N. (2008) <doi:10.1007/978-0-387-73173-5>. Drifting Markov models are described in: Vergne, N. (2008) <doi:10.2202/1544-6115.1326>. Reliability ind [...truncated...]
License: GPL
Imports: DiscreteWeibull
Suggests: utils, knitr, rmarkdown
Encoding: UTF-8
NeedsCompilation: yes
Author: Vlad Stefan Barbu [aut] , Ioannis Mavrogiannis [aut, cre], Nicolas Vergne [aut]
Maintainer: Ioannis Mavrogiannis <mavrogiannis.ioa@gmail.com>
Depends: R (>= 2.10)
Packaged: 2022-11-15 06:17:25 UTC; ioann
Repository: CRAN
Date/Publication: 2022-11-16 12:00:08 UTC

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Package tidyBdE updated to version 0.3.1 with previous version 0.3.0 dated 2022-10-07

Title: Download Data from Bank of Spain
Description: Tools to download data series from 'Banco de España' ('BdE') on 'tibble' format. 'Banco de España' is the national central bank and, within the framework of the Single Supervisory Mechanism ('SSM'), the supervisor of the Spanish banking system along with the European Central Bank. This package is in no way sponsored endorsed or administered by 'Banco de España'.
Author: Diego H. Herrero [aut, cre, cph]
Maintainer: Diego H. Herrero <dev.dieghernan@gmail.com>

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Package inti updated to version 0.5.8 with previous version 0.5.7 dated 2022-08-09

Title: Tools and Statistical Procedures in Plant Science
Description: The 'inti' package is part of the 'inkaverse' project for developing different procedures and tools used in plant science and experimental designs. The mean aim of the package is to support researchers during the planning of experiments and data collection (tarpuy()), data analysis and graphics (yupana()) , and technical writing. Learn more about the 'inkaverse' project at <https://inkaverse.com/>.
Author: Flavio Lozano-Isla [aut, cre] , QuipoLab [ctb], Inkaverse [cph]
Maintainer: Flavio Lozano-Isla <flavjack@gmail.com>

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Package IBrokers updated to version 0.10-2 with previous version 0.10-1 dated 2022-04-10

Title: R API to Interactive Brokers Trader Workstation
Description: Provides native R access to Interactive Brokers Trader Workstation API.
Author: Jeffrey A. Ryan [aut, cph], Joshua M. Ulrich [cre, aut], J.W. de Roode [ctb]
Maintainer: Joshua M. Ulrich <josh.m.ulrich@gmail.com>

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Package Greg updated to version 2.0.1 with previous version 2.0.0 dated 2022-10-13

Title: Regression Helper Functions
Description: Methods for manipulating regression models and for describing these in a style adapted for medical journals. Contains functions for generating an HTML table with crude and adjusted estimates, plotting hazard ratio, plotting model estimates and confidence intervals using forest plots, extending this to comparing multiple models in a single forest plots. In addition to the descriptive methods, there are functions for the robust covariance matrix provided by the 'sandwich' package, a function for adding non-linearities to a model, and a wrapper around the 'Epi' package's Lexis() functions for time-splitting a dataset when modeling non-proportional hazards in Cox regressions.
Author: Max Gordon [aut, cre], Reinhard Seifert [aut]
Maintainer: Max Gordon <max@gforge.se>

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Package CSHShydRology updated to version 1.3.0 with previous version 1.2.10 dated 2022-10-18

Title: Canadian Hydrological Analyses
Description: A collection of user-submitted functions to aid in the analysis of hydrological data, particularly for users in Canada. The functions focus on the use of Canadian data sets, and are suited to Canadian hydrology, such as the important cold region hydrological processes and will work with Canadian hydrological models. The functions are grouped into several themes, currently including Statistical hydrology, Basic data manipulations, Visualization, and Spatial hydrology. Functions developed by the Floodnet project are also included. CSHShydRology has been developed with the assistance of the Canadian Society for Hydrological Sciences (CSHS) which is an affiliated society of the Canadian Water Resources Association (CWRA). As of version 1.2.6, functions now fail gracefully when attempting to download data from a url which is unavailable.
Author: Kevin Shook [cre, aut], Paul Whitfield [aut], Robert Chlumsky [aut], Daniel Moore [aut], Martin Durocher [aut], Matthew Lemieux [ctb], Jason Chiang [ctb], Joel Trubilowicz [ctb], SJ Kim [ctb]
Maintainer: Kevin Shook <kevin.shook@usask.ca>

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Package vctrs updated to version 0.5.1 with previous version 0.5.0 dated 2022-10-21

Title: Vector Helpers
Description: Defines new notions of prototype and size that are used to provide tools for consistent and well-founded type-coercion and size-recycling, and are in turn connected to ideas of type- and size-stability useful for analysing function interfaces.
Author: Hadley Wickham [aut], Lionel Henry [aut, cre], Davis Vaughan [aut], data.table team [cph] and their contribution to R's order), RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>

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Package topmodel updated to version 0.7.5 with previous version 0.7.4 dated 2022-05-05

Title: Implementation of the Hydrological Model TOPMODEL in R
Description: Set of hydrological functions including an R implementation of the hydrological model TOPMODEL, which is based on the 1995 FORTRAN version by Keith Beven. From version 0.7.0, the package is put into maintenance mode.
Author: Wouter Buytaert
Maintainer: Wouter Buytaert <w.buytaert@imperial.ac.uk>

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Package pct updated to version 0.9.5 with previous version 0.9.3 dated 2021-11-02

Title: Propensity to Cycle Tool
Description: Functions and example data to teach and increase the reproducibility of the methods and code underlying the Propensity to Cycle Tool (PCT), a research project and web application hosted at <https://www.pct.bike/>. For an academic paper on the methods, see Lovelace et al (2017) <doi:10.5198/jtlu.2016.862>.
Author: Robin Lovelace [aut, cre] , Layik Hama [aut] , Nathanael Sheehan [ctb]
Maintainer: Robin Lovelace <rob00x@gmail.com>

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Package ParallelDSM updated to version 0.3.7 with previous version 0.3.6 dated 2022-11-02

Title: Parallel Digital Soil Mapping using Machine Learning
Description: Parallel computing, multi-core CPU is used to efficiently compute and process multi-dimensional soil data.This package includes the parallelized 'Quantile Regression Forests' algorithm for Digital Soil Mapping and is mainly dependent on the package 'quantregForest' and 'snowfall'. Detailed references to the R package and the web site are described in the methods, as detailed in the method documentation.
Author: Xiaodong Song [aut], Peicong Tang [aut, cre], Wentao Zhu [aut], Gaoqiang Ge [aut], Jun Zhu [aut], Ganlin Zhang [aut]
Maintainer: Peicong Tang <peicongtang0409@163.com>

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Package glinvci updated to version 1.1.20 with previous version 1.1.18 dated 2022-03-16

Title: Phylogenetic Comparative Methods with Uncertainty Estimates
Description: A framework for analytically computing the asymptotic confidence intervals and maximum-likelihood estimates of a class of continuous-time Gaussian branching processes defined by Mitov V, Bartoszek K, Asimomitis G, Stadler T (2019) <doi:10.1016/j.tpb.2019.11.005>. The class of model includes the widely used Ornstein-Uhlenbeck and Brownian motion branching processes. The framework is designed to be flexible enough so that the users can easily specify their own sub-models, or re-parameterizations, and obtain the maximum-likelihood estimates and confidence intervals of their own custom models.
Author: Hao Chi Kiang [cre, aut]
Maintainer: Hao Chi Kiang <hello@hckiang.com>

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Package deepregression updated to version 0.3 with previous version 0.2 dated 2022-09-21

Title: Fitting Deep Distributional Regression
Description: Allows for the specification of semi-structured deep distributional regression models which are fitted in a neural network as proposed by Ruegamer et al. (2021) <arXiv:2104.02705>. Predictors can be modeled using structured (penalized) linear effects, structured non-linear effects or using an unstructured deep network model.
Author: David Ruegamer [aut, cre], Florian Pfisterer [ctb], Philipp Baumann [ctb], Chris Kolb [ctb], Lucas Kook [ctb]
Maintainer: David Ruegamer <david.ruegamer@gmail.com>

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Package CDatanet updated to version 2.0.3 with previous version 2.0.2 dated 2022-11-14

Title: Modeling Count Data with Peer Effects
Description: Likelihood-based estimation and data generation from a class of models used to estimate peer effects on count data by controlling for the network endogeneity. This class includes count data models with social interactions (Houndetoungan 2022; <doi:10.2139/ssrn.3721250>), spatial tobit models (Xu and Lee 2015; <doi:10.1016/j.jeconom.2015.05.004>), and spatial linear-in-means models (Lee 2004; <doi:10.1111/j.1468-0262.2004.00558.x>).
Author: Elysee Aristide Houndetoungan [cre, aut]
Maintainer: Elysee Aristide Houndetoungan <ariel92and@gmail.com>

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Package twn updated to version 0.2.3 with previous version 0.2.2 dated 2022-04-28

Title: Taxa Waterbeheer Nederland voor R
Description: The TWN-list (Taxa Waterbeheer Nederland) is the Dutch standard for naming taxons in Dutch Watermanagement. This package makes it easier to use the TWN-list for ecological analyses. It consists of two parts. First it makes the TWN-list itself available in R. Second, it has a few functions that make it easy to perform some basic and often recurring tasks for checking and consulting taxonomic data from the TWN-list.
Author: Johan van Tent [aut, cre]
Maintainer: Johan van Tent <tentvanjohan@hotmail.com>

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Package RaceID updated to version 0.2.8 with previous version 0.2.7 dated 2022-11-01

Title: Identification of Cell Types and Inference of Lineage Trees from Single-Cell RNA-Seq Data
Description: Application of 'RaceID' allows inference of cell types and prediction of lineage trees by he StemID2 algorithm. Herman, J.S., Sagar, Grün D. (2018) <DOI:10.1038/nmeth.4662>.
Author: Dominic Gruen <dominic.gruen@gmail.com>
Maintainer: Dominic Gruen <dominic.gruen@gmail.com>

Diff between RaceID versions 0.2.7 dated 2022-11-01 and 0.2.8 dated 2022-11-16

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Package ggpie updated to version 0.2.5 with previous version 0.2.4 dated 2022-10-21

Title: Pie, Donut and Rose Pie Plots
Description: Create pie, donut and rose pie plot with 'ggplot2'.
Author: Yabing Song [aut, cre]
Maintainer: Yabing Song <songyb0519@gmail.com>

Diff between ggpie versions 0.2.4 dated 2022-10-21 and 0.2.5 dated 2022-11-16

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Package crosstalkr updated to version 0.9.0 with previous version 0.8.0 dated 2022-09-16

Title: Analysis of Graph-Structured Data with a Focus on Protein-Protein Interaction Networks
Description: Provides a general framework for the identification of nodes that are functionally related to a set of seeds in graph structured data. In addition to being optimized for use with generic graphs, we also provides support to analyze protein-protein interactions networks from online repositories. For more details on core method, refer to Nibbe et al. (2010) <doi:10.1371/journal.pcbi.1000639>.
Author: Davis Weaver [aut, cre]
Maintainer: Davis Weaver <davis.weaver@case.edu>

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New package robusTest with initial version 1.0.0
Package: robusTest
Title: Calibrated Correlation, Two-Sample Tests
Version: 1.0.0
Description: Implementation of corrected two-sample tests. A corrected version of the Pearson and Kendall correlation tests, the Mann-Whitney (Wilcoxon) rank sum test, the Mann-Whitney (Wilcoxon) signed rank test and a variance test are implemented. The package also proposes a test for the median. All these corrected tests are asymptotically calibrated meaning that the probability of rejection under the null hypothesis is asymptotically equal to the level of the test. The package also proposes a test for independence between two continuous variables of Kolmogorov-Smirnov's type. This test is exact.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
LinkingTo: Rcpp
Imports: Rcpp, stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2022-11-14 13:19:47 UTC; obouaziz
Author: Olivier Bouaziz [aut, cre]
Maintainer: Olivier Bouaziz <olivier.bouaziz@parisdescartes.fr>
Repository: CRAN
Date/Publication: 2022-11-16 06:30:02 UTC

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