Sat, 10 Apr 2021

Package CME.assistant (with last version 1.1.4) was removed from CRAN

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

2021-03-22 1.1.4
2021-02-26 1.1.3
2020-12-15 1.1.1
2020-11-25 1.1.0

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Package lidaRtRee updated to version 3.0.3 with previous version 3.0.2 dated 2021-04-10

Title: Forest Analysis with Airborne Laser Scanning (LiDAR) Data
Description: Provides functions for forest analysis using airborne laser scanning (LiDAR remote sensing) data: tree detection (method 1 in Eysn et al. (2015) <doi:10.3390/f6051721>) and segmentation; forest parameters estimation and mapping with the area-based approach. It includes complementary steps for forest mapping: co-registration of field plots with LiDAR data (Monnet and Mermin (2014) <doi:10.3390/f5092307>); extraction of both physical (gaps, edges, trees) and statistical features from LiDAR data useful for e.g. habitat suitability modeling (Glad et al. (2020) <doi:10.1002/rse2.117>); model calibration with ground reference, and maps export.
Author: Jean-Matthieu Monnet [aut, cre]
Maintainer: Jean-Matthieu Monnet <jean-matthieu.monnet@inrae.fr>

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Package NMOF updated to version 2.4-1 with previous version 2.4-0 dated 2021-04-01

Title: Numerical Methods and Optimization in Finance
Description: Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments such as bonds and options, for portfolio selection and functions that help with stochastic simulations.
Author: Enrico Schumann [aut, cre] (<https://orcid.org/0000-0001-7601-6576>)
Maintainer: Enrico Schumann <es@enricoschumann.net>

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Package jetpack updated to version 0.5.0 with previous version 0.4.3 dated 2019-07-01

Title: A Friendly Package Manager
Description: Manage project dependencies from your DESCRIPTION file. Create a reproducible virtual environment with minimal additional files in your project. Provides tools to add, remove, and update dependencies as well as install existing dependencies with a single function.
Author: Andrew Kane [aut, cre]
Maintainer: Andrew Kane <andrew@chartkick.com>

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Package geysertimes updated to version 0.1.5 with previous version 0.1.2 dated 2021-01-18

Title: Geyser Data from GeyserTimes.org
Description: Download geyser eruption and observation data from the GeyserTimes site (<https://geysertimes.org>) and optionally store it locally. The vignette shows a simple analysis of downloading, accessing, and summarizing the data.
Author: Stephen Kaluzny [aut, cre]
Maintainer: Stephen Kaluzny <spkaluzny@gmail.com>

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Package nflseedR updated to version 1.0.2 with previous version 1.0.1 dated 2021-03-31

Title: Functions to Efficiently Simulate and Evaluate NFL Seasons
Description: A set of functions to simulate National Football League seasons including the sophisticated tie-breaking procedures.
Author: Lee Sharpe [aut, cph], Sebastian Carl [cre, aut]
Maintainer: Sebastian Carl <mrcaseb@gmail.com>

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Package tidytext updated to version 0.3.1 with previous version 0.3.0 dated 2021-01-06

Title: Text Mining using 'dplyr', 'ggplot2', and Other Tidy Tools
Description: Using tidy data principles can make many text mining tasks easier, more effective, and consistent with tools already in wide use. Much of the infrastructure needed for text mining with tidy data frames already exists in packages like 'dplyr', 'broom', 'tidyr', and 'ggplot2'. In this package, we provide functions and supporting data sets to allow conversion of text to and from tidy formats, and to switch seamlessly between tidy tools and existing text mining packages.
Author: Gabriela De Queiroz [ctb], Colin Fay [ctb] (<https://orcid.org/0000-0001-7343-1846>), Emil Hvitfeldt [ctb], Os Keyes [ctb] (<https://orcid.org/0000-0001-5196-609X>), Kanishka Misra [ctb], Tim Mastny [ctb], Jeff Erickson [ctb], David Robinson [aut], Julia Silge [aut, cre] (<https://orcid.org/0000-0002-3671-836X>)
Maintainer: Julia Silge <julia.silge@gmail.com>

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Package shotGroups updated to version 0.8.1 with previous version 0.8 dated 2021-01-19

Title: Analyze Shot Group Data
Description: Analyzes shooting data with respect to group shape, precision, and accuracy. This includes graphical methods, descriptive statistics, and inference tests using standard, but also non-parametric and robust statistical methods. Implements distributions for radial error in bivariate normal variables. Works with files exported by 'OnTarget PC/TDS', 'Silver Mountain' e-target, 'ShotMarker' e-target, or 'Taran', as well as with custom data files in text format. Supports inference from range statistics like extreme spread. Includes a set of web-based graphical user interfaces.
Author: Daniel Wollschlaeger
Maintainer: Daniel Wollschlaeger <dwoll@kuci.org>

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Package bigreadr updated to version 0.2.4 with previous version 0.2.2 dated 2021-02-17

Title: Read Large Text Files
Description: Read large text files by splitting them in smaller files. Package 'bigreadr' also provides some convenient wrappers around fread() and fwrite() from package 'data.table'.
Author: Florian Privé [aut, cre]
Maintainer: Florian Privé <florian.prive.21@gmail.com>

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Package cNORM updated to version 2.0.3 with previous version 2.0.2 dated 2021-01-30

Title: Continuous Norming
Description: Conventional methods for producing standard scores in psychometrics or biometrics are often plagued with "jumps" or "gaps" (i.e., discontinuities) in norm tables and low confidence for assessing extreme scores. The continuous norming method introduced by A. Lenhard et al. (2016, <doi:10.1177/1073191116656437>; 2019, <doi:10.1371/journal.pone.0222279>) and generates continuous test norm scores on the basis of the raw data from standardization samples, without requiring assumptions about the distribution of the raw data: Norm scores are directly established from raw data by modeling the latter ones as a function of both percentile scores and an explanatory variable (e.g., age). The method minimizes bias arising from sampling and measurement error, while handling marked deviations from normality, addressing bottom or ceiling effects and capturing almost all of the variance in the original norm data sample. An online demonstration is available via <https://cnorm.shinyapps.io/cNORM/>.
Author: Wolfgang Lenhard [cre, aut] (<https://orcid.org/0000-0002-8184-6889>), Alexandra Lenhard [aut], Sebastian Gary [aut]
Maintainer: Wolfgang Lenhard <wolfgang.lenhard@uni-wuerzburg.de>

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Package vistime updated to version 1.2.1 with previous version 1.2.0 dated 2021-02-19

Title: Pretty Timelines in R
Description: A library for creating time based charts, like Gantt or timelines. Possible outputs include 'ggplot2' diagrams, 'plotly.js' graphs, 'Highcharts.js' widgets and data.frames. Results can be used in the 'RStudio' viewer pane, in 'RMarkdown' documents or in Shiny apps. In the interactive outputs created by vistime() and hc_vistime(), you can interact with the plot using mouse hover or zoom.
Author: Sandro Raabe [aut, cre]
Maintainer: Sandro Raabe <sa.ra.online@posteo.de>

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Package ingredients updated to version 2.2.0 with previous version 2.0.1 dated 2021-02-05

Title: Effects and Importances of Model Ingredients
Description: Collection of tools for assessment of feature importance and feature effects. Key functions are: feature_importance() for assessment of global level feature importance, ceteris_paribus() for calculation of the what-if plots, partial_dependence() for partial dependence plots, conditional_dependence() for conditional dependence plots, accumulated_dependence() for accumulated local effects plots, aggregate_profiles() and cluster_profiles() for aggregation of ceteris paribus profiles, generic print() and plot() for better usability of selected explainers, generic plotD3() for interactive, D3 based explanations, and generic describe() for explanations in natural language. The package 'ingredients' is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.
Author: Przemyslaw Biecek [aut, cre] (<https://orcid.org/0000-0001-8423-1823>), Hubert Baniecki [aut] (<https://orcid.org/0000-0001-6661-5364>), Adam Izdebski [ctb]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>

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New package WaterML with initial version 1.9.8
Package: WaterML
Title: Fetch and Analyze Data from 'WaterML' and 'WaterOneFlow' Web Services
Version: 1.9.8
Authors@R: person("Jiri","Kadlec", email="jirikadlec2@gmail.com", role=c("aut", "cre"))
Description: Lets you connect to any of the 'Consortium of Universities for the Advancement of Hydrological Science, Inc.' ('CUAHSI') Water Data Center 'WaterOneFlow' web services and read any 'WaterML' time series data file. To see list of available web services, see <http://hiscentral.cuahsi.org>. All versions of 'WaterML' (1.0, 1.1 and 2.0) and both types of the web service protocol ('SOAP' and 'REST') are supported. The package has six data download functions: GetServices(): show all public web services from the HIS Central Catalog. HISCentral_GetSites() and HISCentral_GetSeriesCatalog(): search for sites or time series from the HIS Central catalog based on geographic bounding box, server, or keyword. GetVariables(): Show a data.frame with all variables on the server. GetSites(): Show a data.frame with all sites on the server. GetSiteInfo(): Show what variables, methods and quality control levels are available at the specific site. GetValues(): Given a site code, variable code, start time and end time, fetch a data.frame of all the observation time series data values. The GetValues() function can also parse 'WaterML' data from a custom URL or from a local file.
License: MIT + file LICENSE
Depends: R (>= 3.0)
Imports: stats, XML, httr
URL: https://github.com/jirikadlec2/waterml
Suggests: knitr, markdown, qpdf, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-09 09:40:28 UTC; Admin
Author: Jiri Kadlec [aut, cre]
Maintainer: Jiri Kadlec <jirikadlec2@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-10 08:10:10 UTC

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New package tukeyGH with initial version 1.0.0
Package: tukeyGH
Title: Tukey's g-and-h Probability Distribution
Version: 1.0.0
Authors@R: c( person('Flavio', 'Santi', email = 'flavio.santi@univr.it', role = c('cre', 'aut'), comment = c(ORCID = "0000-0002-2014-1981")), person('Marco', 'Bee', email = 'marco.bee@unitn.it', role = c('aut'), comment = c(ORCID = "0000-0002-9579-3650")), person('Julien', 'Hambuckers', email = 'jhambuckers@uliege.be', role = c('aut'), comment = c(ORCID = "0000-0003-4567-5477")), person('Luca', 'Trapin', email = 'luca.trapin@unibo.it', role = c('aut'), comment = c(ORCID = "0000-0001-8613-0962")))
Author: Flavio Santi [cre, aut] (<https://orcid.org/0000-0002-2014-1981>), Marco Bee [aut] (<https://orcid.org/0000-0002-9579-3650>), Julien Hambuckers [aut] (<https://orcid.org/0000-0003-4567-5477>), Luca Trapin [aut] (<https://orcid.org/0000-0001-8613-0962>)
Maintainer: Flavio Santi <flavio.santi@univr.it>
URL: https://github.com/f-santi/tukeyGH
BugReports: https://github.com/f-santi/tukeyGH/issues
Description: It provides distribution, density and quantile functions of the Tukey's g-and-h probability distribution, as well as functions for random number generation, parameter estimation and testing.
Depends: R (>= 4.0)
Imports: magrittr (>= 2.0.0), minqa, Rdpack, rootSolve (>= 1.8.2.1)
Suggests: testthat (>= 3.0.0)
License: GPL (>= 3)
LazyData: true
NeedsCompilation: no
Encoding: UTF-8
Repository: CRAN
RdMacros: Rdpack
Packaged: 2021-04-09 09:51:56 UTC; flavio
Date/Publication: 2021-04-10 08:10:02 UTC

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New package lidaRtRee with initial version 3.0.2
Package: lidaRtRee
Version: 3.0.2
Title: Forest Analysis with Airborne Laser Scanning (LiDAR) Data
Date: 2021-04-01
Author: Jean-Matthieu Monnet [aut, cre]
Maintainer: Jean-Matthieu Monnet <jean-matthieu.monnet@inrae.fr>
Description: Provides functions for forest analysis using airborne laser scanning (LiDAR remote sensing) data: tree detection (method 1 in Eysn et al. (2015) <doi:10.3390/f6051721>) and segmentation; forest parameters estimation and mapping with the area-based approach. It includes complementary steps for forest mapping: co-registration of field plots with LiDAR data (Monnet and Mermin (2014) <doi:10.3390/f5092307>); extraction of both physical (gaps, edges, trees) and statistical features from LiDAR data useful for e.g. habitat suitability modeling (Glad et al. (2020) <doi:10.1002/rse2.117>); model calibration with ground reference, and maps export.
URL: https://gitlab.irstea.fr/jean-matthieu.monnet/lidaRtRee
BugReports: https://gitlab.irstea.fr/jean-matthieu.monnet/lidaRtRee/-/issues
Depends: R (>= 3.5.0)
Imports: graphics, stats, methods, grDevices, sp, raster, imager, leaps, gvlma, car, reldist, lidR (>= 3.1.0)
License: GPL-3
LazyData: TRUE
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-09 10:40:34 UTC; jean-matthieu
Repository: CRAN
Date/Publication: 2021-04-10 08:10:06 UTC

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Package broom.helpers updated to version 1.3.0 with previous version 1.2.1 dated 2021-02-26

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

Diff between broom.helpers versions 1.2.1 dated 2021-02-26 and 1.3.0 dated 2021-04-10

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New package SBCK with initial version 0.3.1
Package: SBCK
Title: Statistical Bias Correction Kit
Version: 0.3.1
Date: 2021-03-31
Authors@R: c( person("Yoann" , "Robin", email = "yoann.robin.k@gmail.com" , role = c("aut", "cre")), person("Mathieu", "Vrac" , email = "mathieu.vrac@lsce.ipsl.fr", role = c("cph")) )
Description: Implementation of several recent multivariate bias correction methods with a unified interface to facilitate their use. A description and comparison between methods can be found in François et al, (2020) <doi:10.5194/esd-11-537-2020>.
URL: https://github.com/yrobink/SBCK
Depends: R (>= 3.3)
License: GPL-3
Encoding: UTF-8
LazyData: false
NeedsCompilation: yes
Imports: Rcpp, methods, R6, ROOPSD
LinkingTo: Rcpp, RcppEigen
RcppModules: SBCK_cpp
Packaged: 2021-04-09 08:45:45 UTC; yrobin
Author: Yoann Robin [aut, cre], Mathieu Vrac [cph]
Maintainer: Yoann Robin <yoann.robin.k@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-10 08:00:08 UTC

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New package RUVIIIC with initial version 1.0.18
Package: RUVIIIC
Title: RUV-III-C
Version: 1.0.18
Date: 2021-04-09
Author: Rohan Shah [aut, cre], Sean Peters [ctb], Qing Zhong [ctb], Children's Medical Research Institute [cph]
Authors@R: c(person("Rohan", "Shah", role = c("aut", "cre"), email = "rshah@cmri.org.au"), person("Sean", "Peters", role = "ctb"), person("Qing", "Zhong", role = "ctb"), person("Children's Medical Research Institute", role = "cph"))
Maintainer: Rohan Shah <rshah@cmri.org.au>
Description: Variations of Remove Unwanted Variation-III (RUV-III) known as RUV-III-C (RUV-III Complete). RUV-III performs normalisation using negative control variables and replication. RUV-III-C extends this method to cases where the data contains missing values, by applying RUV-III to complete subsets of the data. Originally designed for SWATH-MS proteomics datasets. Poulos et al. (2020) <doi:10.1038/s41467-020-17641-3>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyLoad: yes
LazyData: yes
SystemRequirements: C++11
LinkingTo: Rcpp, RcppEigen, RSpectra, RcppProgress
Suggests: ruv, testthat
Depends: R (>= 3.5), RSpectra, progress
Collate: 'RcppExports.R' 'RUVIII_C.R' 'RUVIII_C_Varying.R' 'data.R' 'roxygen.R' 'threads.R'
NeedsCompilation: yes
Packaged: 2021-04-09 05:25:26 UTC; rshah
Repository: CRAN
Date/Publication: 2021-04-10 08:00:11 UTC

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New package PCL with initial version 1.0
Package: PCL
Title: Proximal Causal Learning
Version: 1.0
Date: 2021-04-04
Authors@R: c(person(given = "Andrew", family = "Ying", role = c("aut", "cre"), email = "aying9339@gmail.com"), person(given = "Yifan", family = "Cui", role = "ctb"), person(given = "AmirEmad", family = "Ghassami", role = "ctb"))
Maintainer: Andrew Ying <aying9339@gmail.com>
Description: We fit causal models using proxies. We implement two stage proximal least squares estimator. E.J. Tchetgen Tchetgen, A. Ying, Y. Cui, X. Shi, and W. Miao. (2020). An Introduction to Proximal Causal Learning. arXiv e-prints, arXiv-2009 <arXiv:2009.10982>.
License: GPL (>= 2)
Depends: R (>= 4.0)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-09 00:59:22 UTC; andrewying
Author: Andrew Ying [aut, cre], Yifan Cui [ctb], AmirEmad Ghassami [ctb]
Repository: CRAN
Date/Publication: 2021-04-10 07:50:10 UTC

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New package MedLEA with initial version 1.0.1
Package: MedLEA
Title: Morphological and Structural Features of Medicinal Leaves
Version: 1.0.1
Authors@R: c(person(given = "Jayani P. G.", family = "Lakshika", role = c("aut", "cph"), email = "jayanilakshika76@gmail.com"), person(given = "Thiyanga S.", family = "Talagala", role = c("aut", "ths", "cre", "cph"), email="ttalagala@sjp.ac.lk", comment = c(ORCID = "0000-0002-0656-9789")))
Description: Contains a dataset of morphological and structural features of 'Medicinal LEAves (MedLEA)'. The features of each species is recorded by manually viewing the medicinal plant repository available at (<http://www.instituteofayurveda.org/plants/>). You can also download repository of leaf images of 1099 medicinal plants in Sri Lanka.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: tidyverse, patchwork, tm, wordcloud2
Encoding: UTF-8
LazyData: true
Suggests: rmarkdown, knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-09 05:09:02 UTC; thiyangashaminitalagala
Author: Jayani P. G. Lakshika [aut, cph], Thiyanga S. Talagala [aut, ths, cre, cph] (<https://orcid.org/0000-0002-0656-9789>)
Maintainer: Thiyanga S. Talagala <ttalagala@sjp.ac.lk>
Repository: CRAN
Date/Publication: 2021-04-10 07:50:12 UTC

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New package garchmodels with initial version 0.1.0
Package: garchmodels
Title: The Tidymodels Extension for GARCH Models
Version: 0.1.0
Authors@R: c( person("Alberto", "Almuiña", email = "albertogonzalezalmuinha@gmail.com", role = c("aut", "cre")) )
Description: Garch framework for use with the 'tidymodels' ecosystem. It includes both univariate and multivariate methods from the 'rugarch' and 'rmgarch' packages. These models include DCC-Garch, Copula Garch and Go-GARCH among others.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), parsnip, rugarch, rmgarch
Imports: rlang (>= 0.1.2), magrittr, purrr, dplyr, stringr, tibble, tidyr, dials
Suggests: tidymodels, tidyverse, modeltime, timetk, lubridate, knitr, rmarkdown, roxygen2, testthat (>= 3.0.0), covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-08 20:53:30 UTC; Usuario
Author: Alberto Almuiña [aut, cre]
Maintainer: Alberto Almuiña <albertogonzalezalmuinha@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-10 07:50:02 UTC

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New package equatags with initial version 0.1.0
Package: equatags
Title: Equations to 'XML'
Version: 0.1.0
Authors@R: c( person("David", "Gohel", role = c("aut", "cre"), email = "david.gohel@ardata.fr"), person(given = "ArData", role = "cph") )
Description: Provides function transform_mathjax() to transform equations defined using 'MathML', 'LaTeX' or 'ASCIIMathML' notation into format 'SVG' or 'Office Open XML Math'. The 'XML' result can then be included in 'HTML', 'Microsoft Word' documents or 'Microsoft PowerPoint' presentations by using a 'Markdown' document or the R package 'officer'.
BugReports: https://github.com/ardata-fr/equatags/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: rappdirs, xml2, xslt, locatexec
SystemRequirements: Node.js
NeedsCompilation: no
Packaged: 2021-04-09 07:05:23 UTC; davidgohel
Author: David Gohel [aut, cre], ArData [cph]
Maintainer: David Gohel <david.gohel@ardata.fr>
Repository: CRAN
Date/Publication: 2021-04-10 08:00:02 UTC

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New package elasdics with initial version 0.1.1
Package: elasdics
Title: Elastic Analysis of Sparse, Dense and Irregular Curves
Version: 0.1.1
Author: Lisa Steyer <lisa.steyer@hu-berlin.de>
Maintainer: Lisa Steyer <lisa.steyer@hu-berlin.de>
Description: Provides functions to align curves and to compute mean curves based on the elastic distance defined in the square-root-velocity framework. For more details on this framework see Srivastava and Klassen (2016, <doi:10.1007/978-1-4939-4020-2>).
License: GPL-3
Encoding: UTF-8
Imports: splines, stats, numDeriv
Suggests: testthat, covr
NeedsCompilation: no
Packaged: 2021-04-09 08:33:22 UTC; User
Repository: CRAN
Date/Publication: 2021-04-10 08:00:05 UTC

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New package basecamb with initial version 0.9.0
Package: basecamb
Title: Utilities for Streamlined Data Import, Imputation and Modelling
Version: 0.9.0
Authors@R: c(person(given = "J. Peter", family = "Marquardt", role = c("aut"), email = "peter@kmarquardt.de", comment = c(ORCID = "0000-0002-5596-1357")), person(given = "Till D.", family = "Best", role = c("aut", "cre"), email = "till-best@gmx.de", comment = c(ORCID = "0000-0001-7323-827X")))
Description: Provides functions streamlining the data analysis workflow: Outsourcing data import, renaming and type casting to a *.csv. Manipulating imputed datasets and fitting models on them. Summarizing models.
Depends: R (>= 4.0.0)
Imports: assertive.types, mice, Hmisc
License: GPL (>= 3)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-08 22:32:09 UTC; Till-
Author: J. Peter Marquardt [aut] (<https://orcid.org/0000-0002-5596-1357>), Till D. Best [aut, cre] (<https://orcid.org/0000-0001-7323-827X>)
Maintainer: Till D. Best <till-best@gmx.de>
Repository: CRAN
Date/Publication: 2021-04-10 07:50:07 UTC

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Package DealGPL570 (with last version 0.2.0) was removed from CRAN

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

2019-12-11 0.2.0
2019-11-12 0.0.1

Permanent link
Package SoupX (with last version 1.5.0) was removed from CRAN

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

2021-01-13 1.5.0
2020-10-15 1.4.8
2020-05-26 1.4.5

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Package sigora (with last version 3.0.5) was removed from CRAN

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

2019-08-23 3.0.5
2018-09-28 3.0.1
2016-05-10 2.0.1

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Package RxODE updated to version 1.0.8 with previous version 1.0.7 dated 2021-04-08

Title: Facilities for Simulating from ODE-Based Models
Description: Facilities for running simulations from ordinary differential equation ('ODE') models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The 'VODE' and 'LSODA' are in the public domain. The information is available in the inst/COPYRIGHTS.
Author: Matthew L. Fidler [aut] (<https://orcid.org/0000-0001-8538-6691>), Melissa Hallow [aut], Wenping Wang [aut, cre], Zufar Mulyukov [ctb], Alan Hindmarsh [ctb], Awad H. Al-Mohy [ctb], Matt Dowle [ctb], Cleve Moler [ctb], David Cooley [ctb], Daniel C. Dillon [ctb], Drew Schmidt [ctb], Arun Srinivasan [ctb], Ernst Hairer [ctb], Gerhard Wanner [ctb], Goro Fuji [ctb], Hadley Wickham [ctb], Jack Dongarra [ctb], Linda Petzold [ctb], Martin Maechler [ctb], Matteo Fasiolo [ctb], Morwenn [ctb], Nicholas J. Higham [ctb], Roger B. Sidje [ctb], Simon Frost [ctb], Kevin Ushey [ctb], Yu Feng [ctb]
Maintainer: Wenping Wang <wwang8198@gmail.com>

Diff between RxODE versions 1.0.7 dated 2021-04-08 and 1.0.8 dated 2021-04-10

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Package noaaoceans updated to version 0.3.0 with previous version 0.2.0 dated 2019-12-01

Title: Collect Ocean Data from NOAA
Description: Provides a small set of tools for collecting data from National Oceanic and Atmospheric Administration (NOAA) data sources. The functions provided in the package are wrappers around NOAA's existing APIs which is found at <https://api.tidesandcurrents.noaa.gov/api/prod/>.
Author: Sean Warlick [aut, cre]
Maintainer: Sean Warlick <warlick.sean@gmail.com>

Diff between noaaoceans versions 0.2.0 dated 2019-12-01 and 0.3.0 dated 2021-04-10

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 noaaoceans-0.3.0/noaaoceans/DESCRIPTION                                                                        |   11 
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 noaaoceans-0.3.0/noaaoceans/NAMESPACE                                                                          |    2 
 noaaoceans-0.3.0/noaaoceans/NEWS.md                                                                            |    9 
 noaaoceans-0.3.0/noaaoceans/R/noaaoceans.R                                                                     |    2 
 noaaoceans-0.3.0/noaaoceans/R/query_coops_data.R                                                               |    8 
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 noaaoceans-0.3.0/noaaoceans/R/query_meta_data.R                                                                |only
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 noaaoceans-0.3.0/noaaoceans/inst/doc/getting_started.html                                                      |  363 +++++-----
 noaaoceans-0.3.0/noaaoceans/man/coops_station_inventory.Rd                                                     |   39 -
 noaaoceans-0.3.0/noaaoceans/man/noaaoceans.Rd                                                                  |    3 
 noaaoceans-0.3.0/noaaoceans/man/query_coops_data.Rd                                                            |   24 
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Package disaggR updated to version 0.2.0.2 with previous version 0.1.11 dated 2020-12-09

Title: Two-Steps Benchmarks for Time Series Disaggregation
Description: The twoStepsBenchmark() and threeRuleSmooth() functions allow you to disaggregate a low-frequency time-serie with time-series of higher frequency, using the French National Accounts methodology. The aggregated sum of the resulting time-serie is strictly equal to the low-frequency serie within the benchmarking window. Typically, the low-frequency serie is an annual one, unknown for the last year, and the high frequency one is either quarterly or mensual. See "Methodology of quarterly national accounts", Insee Méthodes N°126, by Insee (2012, ISBN:978-2-11-068613-8).
Author: Arnaud Feldmann [aut, cre] (<https://orcid.org/0000-0003-0109-7505>), Franck Arnaud [ctb] (barplot base graphics method for the mts class), Institut national de la statistique et des études économiques [cph] (https://www.insee.fr/)
Maintainer: Arnaud Feldmann <arnaud.feldmann@insee.fr>

Diff between disaggR versions 0.1.11 dated 2020-12-09 and 0.2.0.2 dated 2021-04-10

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 disaggR-0.2.0.2/disaggR/DESCRIPTION                                                                     |   43 
 disaggR-0.2.0.2/disaggR/LICENSE                                                                         |    2 
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 disaggR-0.2.0.2/disaggR/NEWS.md                                                                         |   14 
 disaggR-0.2.0.2/disaggR/R/bflSmooth.R                                                                   |   53 
 disaggR-0.2.0.2/disaggR/R/data.R                                                                        |   42 
 disaggR-0.2.0.2/disaggR/R/disaggR.R                                                                     |   23 
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 disaggR-0.2.0.2/disaggR/R/utils.R                                                                       |   60 
 disaggR-0.2.0.2/disaggR/README.md                                                                       |   41 
 disaggR-0.2.0.2/disaggR/inst                                                                            |only
 disaggR-0.2.0.2/disaggR/man/bflSmooth.Rd                                                                |   26 
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 disaggR-0.2.0.2/disaggR/man/rho.Rd                                                                      |   47 
 disaggR-0.2.0.2/disaggR/man/se.Rd                                                                       |   41 
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 disaggR-0.2.0.2/disaggR/tests/figs/deps.txt                                                             |    6 
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Package DescTools updated to version 0.99.41 with previous version 0.99.40 dated 2021-02-03

Title: Tools for Descriptive Statistics
Description: A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.
Author: Andri Signorell [aut, cre], Ken Aho [ctb], Andreas Alfons [ctb], Nanina Anderegg [ctb], Tomas Aragon [ctb], Chandima Arachchige [ctb], Antti Arppe [ctb], Adrian Baddeley [ctb], Kamil Barton [ctb], Ben Bolker [ctb], Hans W. Borchers [ctb], Frederico Caeiro [ctb], Stephane Champely [ctb], Daniel Chessel [ctb], Leanne Chhay [ctb], Nicholas Cooper [ctb], Clint Cummins [ctb], Michael Dewey [ctb], Harold C. Doran [ctb], Stephane Dray [ctb], Charles Dupont [ctb], Dirk Eddelbuettel [ctb], Claus Ekstrom [ctb], Martin Elff [ctb], Jeff Enos [ctb], Richard W. Farebrother [ctb], John Fox [ctb], Romain Francois [ctb], Michael Friendly [ctb], Tal Galili [ctb], Matthias Gamer [ctb], Joseph L. Gastwirth [ctb], Vilmantas Gegzna [ctb], Yulia R. Gel [ctb], Sereina Graber [ctb], Juergen Gross [ctb], Gabor Grothendieck [ctb], Frank E. Harrell Jr [ctb], Richard Heiberger [ctb], Michael Hoehle [ctb], Christian W. Hoffmann [ctb], Soeren Hojsgaard [ctb], Torsten Hothorn [ctb], Markus Huerzeler [ctb], Wallace W. Hui [ctb], Pete Hurd [ctb], Rob J. Hyndman [ctb], Christopher Jackson [ctb], Matthias Kohl [ctb], Mikko Korpela [ctb], Max Kuhn [ctb], Detlew Labes [ctb], Friederich Leisch [ctb], Jim Lemon [ctb], Dong Li [ctb], Martin Maechler [ctb], Arni Magnusson [ctb], Ben Mainwaring [ctb], Daniel Malter [ctb], George Marsaglia [ctb], John Marsaglia [ctb], Alina Matei [ctb], David Meyer [ctb], Weiwen Miao [ctb], Giovanni Millo [ctb], Yongyi Min [ctb], David Mitchell [ctb], Franziska Mueller [ctb], Markus Naepflin [ctb], Daniel Navarro [ctb], Henric Nilsson [ctb], Klaus Nordhausen [ctb], Derek Ogle [ctb], Hong Ooi [ctb], Nick Parsons [ctb], Sandrine Pavoine [ctb], Tony Plate [ctb], Luke Prendergast [ctb], Roland Rapold [ctb], William Revelle [ctb], Tyler Rinker [ctb], Brian D. Ripley [ctb], Caroline Rodriguez [ctb], Nathan Russell [ctb], Nick Sabbe [ctb], Ralph Scherer [ctb], Venkatraman E. Seshan [ctb], Michael Smithson [ctb], Greg Snow [ctb], Karline Soetaert [ctb], Werner A. Stahel [ctb], Alec Stephenson [ctb], Mark Stevenson [ctb], Ralf Stubner [ctb], Matthias Templ [ctb], Duncan Temple Lang [ctb], Terry Therneau [ctb], Yves Tille [ctb], Luis Torgo [ctb], Adrian Trapletti [ctb], Joshua Ulrich [ctb], Kevin Ushey [ctb], Jeremy VanDerWal [ctb], Bill Venables [ctb], John Verzani [ctb], Pablo J. Villacorta Iglesias [ctb], Gregory R. Warnes [ctb], Stefan Wellek [ctb], Hadley Wickham [ctb], Rand R. Wilcox [ctb], Peter Wolf [ctb], Daniel Wollschlaeger [ctb], Joseph Wood [ctb], Ying Wu [ctb], Thomas Yee [ctb], Achim Zeileis [ctb]
Maintainer: Andri Signorell <andri@signorell.net>

Diff between DescTools versions 0.99.40 dated 2021-02-03 and 0.99.41 dated 2021-04-10

 DESCRIPTION              |   10 -
 MD5                      |   54 ++++-----
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 tests/misc.R             |   14 ++
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Permanent link


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