Sat, 03 Apr 2021

Package SMARTbayesR updated to version 1.0.2 with previous version 1.0.1 dated 2020-11-09

Title: Bayesian Set of Best Dynamic Treatment Regimes and Sample Size in SMARTs
Description: Permits determination of a set of optimal dynamic treatment regimes and sample size for a SMART design in the Bayesian setting. Please see Artman (2020) <arXiv:2008.02341>.
Author: William Artman [aut, cre]
Maintainer: William Artman <William_Artman@URMC.Rochester.edu>

Diff between SMARTbayesR versions 1.0.1 dated 2020-11-09 and 1.0.2 dated 2021-04-03

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More information about SMARTbayesR at CRAN
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Package movecost updated to version 0.6 with previous version 0.5 dated 2020-06-05

Title: Calculation of Accumulated Cost Surface and Least-Cost Paths Related to Human Movement Across the Landscape
Description: Provides the facility to calculate non-isotropic accumulated cost surface and least-cost paths using a number of human-movement-related cost functions that can be selected by the user. It just requires a Digital Terrain Model, a start location and (optionally) destination locations. See Alberti (2019) <doi:10.1016/j.softx.2019.100331>.
Author: Gianmarco Alberti [aut, cre]
Maintainer: Gianmarco Alberti <gianmarcoalberti@gmail.com>

Diff between movecost versions 0.5 dated 2020-06-05 and 0.6 dated 2021-04-03

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Package FITSio updated to version 2.1-6 with previous version 2.1-5 dated 2021-03-23

Title: FITS (Flexible Image Transport System) Utilities
Description: Utilities to read and write files in the FITS (Flexible Image Transport System) format, a standard format in astronomy (see e.g. <https://en.wikipedia.org/wiki/FITS> for more information). Present low-level routines allow: reading, parsing, and modifying FITS headers; reading FITS images (multi-dimensional arrays); reading FITS binary and ASCII tables; and writing FITS images (multi-dimensional arrays). Higher-level functions allow: reading files composed of one or more headers and a single (perhaps multidimensional) image or single table; reading tables into data frames; generating vectors for image array axes; scaling and writing images as 16-bit integers. Known incompletenesses are reading random group extensions, as well as complex and array descriptor data types in binary tables.
Author: Andrew Harris
Maintainer: Andrew Harris <harris@astro.umd.edu>

Diff between FITSio versions 2.1-5 dated 2021-03-23 and 2.1-6 dated 2021-04-03

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Package SmartEDA updated to version 0.3.7 with previous version 0.3.6 dated 2020-07-10

Title: Summarize and Explore the Data
Description: Exploratory analysis on any input data describing the structure and the relationships present in the data. The package automatically select the variable and does related descriptive statistics. Analyzing information value, weight of evidence, custom tables, summary statistics, graphical techniques will be performed for both numeric and categorical predictors.
Author: Dayanand Ubrangala [aut, cre], Kiran R [aut, ctb], Ravi Prasad Kondapalli [aut, ctb], Sayan Putatunda [aut, ctb]
Maintainer: Dayanand Ubrangala <daya6489@gmail.com>

Diff between SmartEDA versions 0.3.6 dated 2020-07-10 and 0.3.7 dated 2021-04-03

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Package rayrender updated to version 0.21.1 with previous version 0.14.0 dated 2020-08-02

Title: Build and Raytrace 3D Scenes
Description: Render scenes using pathtracing. Build 3D scenes out of spheres, cubes, planes, disks, triangles, cones, curves, line segments, cylinders, ellipsoids, and 3D models in the 'Wavefront' OBJ file format or the PLY Polygon File Format. Supports several material types, textures, multicore rendering, and tone-mapping. Based on the "Ray Tracing in One Weekend" book series. Peter Shirley (2018) <https://raytracing.github.io>.
Author: Tyler Morgan-Wall [aut, cph, cre] (<https://orcid.org/0000-0002-3131-3814>), Syoyo Fujita [ctb, cph], Melissa O'Neill [ctb, cph], Vilya Harvey [ctb, cph]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

Diff between rayrender versions 0.14.0 dated 2020-08-02 and 0.21.1 dated 2021-04-03

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Package incase updated to version 0.3.0 with previous version 0.2.1 dated 2021-01-14

Title: Pipe-Friendly Vector Replacement with Case Statements
Description: Offers a pipe-friendly alternative to the 'dplyr' functions case_when() and if_else(), as well as a number of user-friendly simplifications for common use cases. These functions accept a vector as an optional first argument, allowing conditional statements to be built using the 'magrittr' dot operator. The functions also coerce all outputs to the same type, meaning you no longer have to worry about using specific typed variants of NA or explicitly declaring integer outputs, and evaluate outputs somewhat lazily, so you don't waste time on long operations that won't be used.
Author: Alexander Rossell Hayes [aut, cre, cph] (<https://orcid.org/0000-0001-9412-0457>), Patrice Kiener [ctb] (Contributed example for fn_case(), <https://orcid.org/0000-0002-0505-9920>)
Maintainer: Alexander Rossell Hayes <alexander@rossellhayes.com>

Diff between incase versions 0.2.1 dated 2021-01-14 and 0.3.0 dated 2021-04-03

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Package viewshed3d updated to version 4.0.0 with previous version 3.2.0 dated 2020-07-03

Title: Compute Viewshed in 3D Point Clouds of Ecosystems
Description: A set of tools to compute viewshed in 3D from Terrestrial Laser Scanner data and prepare the data prior to visibility estimation.
Author: Bastien Lecigne [aut, cre] (<https://orcid.org/0000-0002-1496-202X>), Jan Eitel [aut]
Maintainer: Bastien Lecigne <lecignebastien@gmail.com>

Diff between viewshed3d versions 3.2.0 dated 2020-07-03 and 4.0.0 dated 2021-04-03

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Package sparta updated to version 0.7.2 with previous version 0.7.1 dated 2021-03-01

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

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More information about sparta at CRAN
Permanent link

Package mnis updated to version 0.3.1 with previous version 0.2.7 dated 2017-07-03

Title: Easy Downloading Capabilities for the Members' Name Information Service
Description: An API package for the Members' Name Information Service operated by the UK parliament. Documentation for the API itself can be found here: <http://data.parliament.uk/membersdataplatform/default.aspx>.
Author: Evan Odell [aut, cre] (<https://orcid.org/0000-0003-1845-808X>)
Maintainer: Evan Odell <evanodell91@gmail.com>

Diff between mnis versions 0.2.7 dated 2017-07-03 and 0.3.1 dated 2021-04-03

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More information about mnis at CRAN
Permanent link

Package jti updated to version 0.7.0 with previous version 0.6.0 dated 2020-12-16

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

Diff between jti versions 0.6.0 dated 2020-12-16 and 0.7.0 dated 2021-04-03

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Permanent link

Package dparser updated to version 1.3.1-2 with previous version 0.1.8 dated 2017-11-13

Title: Port of 'Dparser' Package
Description: A Scannerless GLR parser/parser generator. Note that GLR standing for "generalized LR", where L stands for "left-to-right" and R stands for "rightmost (derivation)". For more information see <https://en.wikipedia.org/wiki/GLR_parser>. This parser is based on the Tomita (1987) algorithm. (Paper can be found at <https://www.aclweb.org/anthology/P84-1073.pdf>). The original 'dparser' package documentation can be found at <http://dparser.sourceforge.net/>. This allows you to add mini-languages to R (like RxODE's ODE mini-language Wang, Hallow, and James 2015 <DOI:10.1002/psp4.12052>) or to parse other languages like 'NONMEM' to automatically translate them to R code. To use this in your code, add a LinkingTo dparser in your DESCRIPTION file and instead of using #include <dparse.h> use #include <dparser.h>. This also provides a R-based port of the make_dparser <http://dparser.sourceforge.net/d/make_dparser.cat> command called mkdparser(). Additionally you can parse an arbitrary grammar within R using the dparse() function, which works on most OSes and is mainly for grammar testing. The fastest parsing, of course, occurs at the C level, and is suggested.
Author: Matthew Fidler [aut, cre], John Plevyak [aut, cph]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

Diff between dparser versions 0.1.8 dated 2017-11-13 and 1.3.1-2 dated 2021-04-03

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Package Dire updated to version 1.0.3 with previous version 1.0.2 dated 2021-03-22

Title: Linear Regressions with a Latent Outcome Variable
Description: Fit linear models, estimating score distributions for groups of people, following Cohen and Jiang (1999) <doi:10.2307/2669917>. In this model, the response is a latent trait (such as student ability) and raw item responses are combined with item difficulties in an item response theory (IRT) framework to form a density for each unit (student). This latent trait is then integrated out. This software is intended to fit the same models as the existing software 'AM' <http://am.air.org/>.
Author: Harold Doran [aut], Paul Bailey [aut, cre], Eric Buehler [aut], Sun-joo Lee [aut], Claire Kelley [ctb], Emmanuel Sikali [pdr]
Maintainer: Paul Bailey <pbailey@air.org>

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Package odbc updated to version 1.3.2 with previous version 1.3.1 dated 2021-03-16

Title: Connect to ODBC Compatible Databases (using the DBI Interface)
Description: A DBI-compatible interface to ODBC databases.
Author: Jim Hester [aut, cre], Hadley Wickham [aut], Oliver Gjoneski [ctb] (detule), lexicalunit [cph] (nanodbc library), Google Inc. [cph] (cctz library), RStudio [cph, fnd]
Maintainer: Jim Hester <jim.hester@rstudio.com>

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Package modeltime updated to version 0.5.1 with previous version 0.5.0 dated 2021-03-29

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.fb.com/blog/2017/02/prophet-forecasting-at-scale/>.).
Author: Matt Dancho [aut, cre], Business Science [cph]
Maintainer: Matt Dancho <mdancho@business-science.io>

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Package diathor updated to version 0.0.5 with previous version 0.0.4 dated 2021-02-24

Title: Calculate Ecological Information and Diatom Based Indices
Description: Calculates ecological information and biotic indices for diatoms in a sample. It includes number/shape of chloroplasts diversity indices, size classes, ecological guilds, and multiple biotic indices. It outputs both a dataframe with all the results and plots of all the obtained data in a defined output folder. Sample data was taken from Nicolosi Gelis, Cochero & Gómez (2020, <doi:10.1016/j.ecolind.2019.105951>). The package uses the 'Diat.Barcode' database to calculate morphological and ecological information by Rimet & Couchez (2012, <doi:10.1051/kmae/2012018>), and calculates the DES index by Descy (1979, <http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=PASCAL8060205402>), the EPID index by Dell'Uomo (1996, ISBN: 3950009002), the IDAP index by Prygiel & Coste (1993, <doi:10.1007/BF00028033>), the ID-CH index by Hürlimann & Niederhauser (2007, <https://www.bafu.admin.ch/bafu/fr/home/themes/eaux/publications/publications-eaux/methodes-analyse-appreciation-cours-eau-diatomees.html>), the IDP index by Gómez & Licursi (2001, <doi:10.1023/A:1011415209445>), the ILM index by Leclercq & Maquet (1987, <http://www.vliz.be/imisdocs/publications/286641.pdf>), the IPS index by Coste (1982, <https://www.oieau.org/eaudoc/notice/ETUDE-DES-METHODES-BIOLOGIQUES-DAPPRECIATION-QUANTITATIVE-DE-LA-QUALITE-DES-EAUX>), the LOBO index by Lobo, Callegaro, & Bender (2002, ISBN:9788585869908), the SLA by Sládeček (1986, <doi:10.1002/aheh.19860140519>), the TDI index by Kelly, & Whitton (1995, <doi:10.1007/BF00003802>), and the SPEAR(herbicide) index by Wood, Mitrovic, Lim, Warne, Dunlop, & Kefford (2019, <doi:10.1016/j.ecolind.2018.12.035>).
Author: María Mercedes Nicolosi Gelis [aut] (<https://orcid.org/0000-0001-6324-7930>), María Belén Sathicq [aut] (<https://orcid.org/0000-0002-3534-8950>), Joaquín Cochero [cre] (<https://orcid.org/0000-0003-3957-6819>)
Maintainer: Joaquín Cochero <jcochero@ilpla.edu.ar>

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Package WeightIt updated to version 0.12.0 with previous version 0.11.0 dated 2021-02-02

Title: Weighting for Covariate Balance in Observational Studies
Description: Generates weights to form equivalent groups in observational studies with point or longitudinal treatments by easing and extending the functionality of the R packages 'twang' for generalized boosted modeling (McCaffrey, Ridgeway & Morral, 2004) <doi:10.1037/1082-989X.9.4.403>, 'CBPS' for covariate balancing propensity score weighting (Imai & Ratkovic, 2014) <doi:10.1111/rssb.12027>, 'ebal' for entropy balancing (Hainmueller, 2012) <doi:10.1093/pan/mpr025>, 'optweight' for optimization-based weights (Zubizarreta, 2015) <doi:10.1080/01621459.2015.1023805>, 'ATE' for empirical balancing calibration weighting (Chan, Yam, & Zhang, 2016) <doi:10.1111/rssb.12129>, 'SuperLearner' for stacked machine learning-based propensity scores (Pirracchio, Petersen, & van der Laan, 2015) <doi:10.1093/aje/kwu253>, among others. Also allows for assessment of weights and checking of covariate balance by interfacing directly with 'cobalt'.
Author: Noah Greifer [aut, cre] (<https://orcid.org/0000-0003-3067-7154>)
Maintainer: Noah Greifer <noah.greifer@gmail.com>

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Package spdep updated to version 1.1-7 with previous version 1.1-5 dated 2020-06-29

Title: Spatial Dependence: Weighting Schemes, Statistics
Description: A collection of functions to create spatial weights matrix objects from polygon 'contiguities', from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree; a collection of tests for spatial 'autocorrelation', including global 'Morans I' and 'Gearys C' proposed by 'Cliff' and 'Ord' (1973, ISBN: 0850860369) and (1981, ISBN: 0850860814), 'Hubert/Mantel' general cross product statistic, Empirical Bayes estimates and 'Assunção/Reis' (1999) <doi:10.1002/(SICI)1097-0258(19990830)18:16%3C2147::AID-SIM179%3E3.0.CO;2-I> Index, 'Getis/Ord' G ('Getis' and 'Ord' 1992) <doi:10.1111/j.1538-4632.1992.tb00261.x> and multicoloured join count statistics, 'APLE' ('Li 'et al.' ) <doi:10.1111/j.1538-4632.2007.00708.x>, local 'Moran's I' ('Anselin' 1995) <doi:10.1111/j.1538-4632.1995.tb00338.x> and 'Getis/Ord' G ('Ord' and 'Getis' 1995) <doi:10.1111/j.1538-4632.1995.tb00912.x>, 'saddlepoint' approximations ('Tiefelsdorf' 2002) <doi:10.1111/j.1538-4632.2002.tb01084.x> and exact tests for global and local 'Moran's I' ('Bivand et al.' 2009) <doi:10.1016/j.csda.2008.07.021> and 'LOSH' local indicators of spatial heteroscedasticity ('Ord' and 'Getis') <doi:10.1007/s00168-011-0492-y>. The implementation of most of the measures is described in 'Bivand' and 'Wong' (2018) <doi:10.1007/s11749-018-0599-x>. 'spdep' >= 1.1-1 corresponds to 'spatialreg' >= 1.1-1, in which the model fitting functions are deprecated and pass through to 'spatialreg', but will mask those in 'spatialreg'. From versions 1.2-1, the functions will be made defunct in 'spdep'. For now 'spatialreg' only has functions from 'spdep', where they are shown as deprecated. 'spatialreg' only loads the namespace of 'spdep'; if you attach 'spdep', the same functions in the other package will be masked. Some feed through adequately, others do not.
Author: Roger Bivand [cre, aut] (<https://orcid.org/0000-0003-2392-6140>), Micah Altman [ctb], Luc Anselin [ctb], Renato Assunção [ctb], Olaf Berke [ctb], Andrew Bernat [ctb], Guillaume Blanchet [ctb], Eric Blankmeyer [ctb], Marilia Carvalho [ctb], Bjarke Christensen [ctb], Yongwan Chun [ctb], Carsten Dormann [ctb], Stéphane Dray [ctb], Virgilio Gómez-Rubio [ctb], Martin Gubri [ctb], Rein Halbersma [ctb], Elias Krainski [ctb], Pierre Legendre [ctb], Nicholas Lewin-Koh [ctb], Angela Li [ctb], Hongfei Li [ctb], Jielai Ma [ctb], Abhirup Mallik [ctb, trl], Giovanni Millo [ctb], Werner Mueller [ctb], Hisaji Ono [ctb], Pedro Peres-Neto [ctb], Gianfranco Piras [ctb], Markus Reder [ctb], Michael Tiefelsdorf [ctb], René Westerholt [ctb], Danlin Yu [ctb]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

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Package SDLfilter updated to version 2.1.0 with previous version 2.0.1 dated 2020-07-05

Title: Filtering and Assessing the Sample Size of Tracking Data
Description: Functions to filter GPS/Argos locations, as well as assessing the sample size for the analysis of animal distributions. The filters remove temporal and spatial duplicates, fixes located at a given height from estimated high tide line, and locations with high error as described in Shimada et al. (2012) <doi:10.3354/meps09747> and Shimada et al. (2016) <doi:10.1007/s00227-015-2771-0>. Sample size for the analysis of animal distributions can be assessed by the conventional area-based approach or the alternative probability-based approach as described in Shimada et al. (2021) <doi:10.1111/2041-210X.13506>.
Author: Takahiro Shimada
Maintainer: Takahiro Shimada <taka.shimada@gmail.com>

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New package L0Learn with initial version 2.0.3
Package: L0Learn
Title: Fast Algorithms for Best Subset Selection
Version: 2.0.3
Date: 2021-03-28
Authors@R: c( person("Hussein", "Hazimeh", email = "hazimeh@mit.edu", role = c("aut", "cre")), person("Rahul", "Mazumder", email = "rahulmaz@mit.edu", role = "aut"), person("Tim", "Nonet", email = "tim.nonet@gmail.com", role = "aut"))
Description: Highly optimized toolkit for approximately solving L0-regularized learning problems (a.k.a. best subset selection). The algorithms are based on coordinate descent and local combinatorial search. For more details, check the paper by Hazimeh and Mazumder (2020); the link is provided in the URL field below.
URL: https://pubsonline.informs.org/doi/10.1287/opre.2019.1919 https://github.com/hazimehh
BugReports: https://github.com/hazimehh/L0Learn/issues
License: MIT + file LICENSE
Depends: R (>= 3.3.0)
SystemRequirements: C++11
Imports: Rcpp (>= 0.12.13), Matrix, methods, ggplot2, reshape2, MASS
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat, pracma, raster
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-03-28 21:38:21 UTC; hh
Author: Hussein Hazimeh [aut, cre], Rahul Mazumder [aut], Tim Nonet [aut]
Maintainer: Hussein Hazimeh <hazimeh@mit.edu>
Repository: CRAN
Date/Publication: 2021-04-03 13:50:28 UTC

More information about L0Learn at CRAN
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Package kittyR updated to version 1.1.0 with previous version 1.0.0 dated 2021-01-18

Title: Kitty Pictures and Meows from R Console
Description: Get pictures of cats and their meows from your R console.
Author: Indrajeet Patil [aut, cre, cph] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package irrNA updated to version 0.2.0 with previous version 0.1.4 dated 2018-04-11

Title: Coefficients of Interrater Reliability - Generalized for Randomly Incomplete Datasets
Description: Provides coefficients of interrater reliability that are generalized to cope with randomly incomplete (i.e. unbalanced) datasets without any imputation of missing values or any (row-wise or column-wise) omissions of actually available data. Applied to complete (balanced) datasets, these generalizations yield the same results as the common procedures, namely the Intraclass Correlation according to McGraw & Wong (1996) <doi:10.1037/1082-989X.1.1.30> and the Coefficient of Concordance according to Kendall & Babington Smith (1939) <doi:10.1214/aoms/1177732186>.
Author: Markus Brueckl [aut, cre], Florian Heuer [aut, trl]
Maintainer: Markus Brueckl <markus.brueckl@tu-berlin.de>

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New package ICAMS with initial version 2.3.10
Package: ICAMS
Title: In-Depth Characterization and Analysis of Mutational Signatures ('ICAMS')
Version: 2.3.10
Author: Steve Rozen, Nanhai Jiang, Arnoud Boot, Mo Liu, Yang Wu
Maintainer: Steve Rozen <steverozen@gmail.com>
Description: Analysis and visualization of experimentally elucidated mutational signatures -- the kind of analysis and visualization in Boot et al., "In-depth characterization of the cisplatin mutational signature in human cell lines and in esophageal and liver tumors", Genome Research 2018, <doi:10.1101/gr.230219.117> and "Characterization of colibactin-associated mutational signature in an Asian oral squamous cell carcinoma and in other mucosal tumor types", Genome Research 2020 <doi:10.1101/gr.255620.119>. 'ICAMS' stands for In-depth Characterization and Analysis of Mutational Signatures. 'ICAMS' has functions to read in variant call files (VCFs) and to collate the corresponding catalogs of mutational spectra and to analyze and plot catalogs of mutational spectra and signatures. Handles both "counts-based" and "density-based" catalogs of mutational spectra or signatures.
License: GPL-3 | file LICENSE
URL: https://github.com/steverozen/ICAMS
BugReports: https://github.com/steverozen/ICAMS/issues
Encoding: UTF-8
LazyData: true
Language: en-US
biocViews:
Imports: Biostrings, BSgenome, data.table, dplyr, GenomeInfoDb, GenomicRanges, graphics, grDevices, IRanges, RColorBrewer, stats, stringi, utils, zip
Depends: R (>= 3.5),
Suggests: BSgenome.Hsapiens.1000genomes.hs37d5, BSgenome.Hsapiens.UCSC.hg38, BSgenome.Mmusculus.UCSC.mm10, testthat
NeedsCompilation: no
Packaged: 2021-03-31 01:16:32 UTC; e0012078
Repository: CRAN
Date/Publication: 2021-04-03 13:50:31 UTC

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Package gRc updated to version 0.4.4 with previous version 0.4-3.2 dated 2019-04-17

Title: Inference in Graphical Gaussian Models with Edge and Vertex Symmetries
Description: Estimation, model selection and other aspects of statistical inference in Graphical Gaussian models with edge and vertex symmetries (Graphical Gaussian models with colours). Documentation about 'gRc' is provided in the paper by Hojsgaard and Lauritzen (2007, <doi:10.18637/jss.v023.i06>) and the paper by Hojsgaard and Lauritzen (2008, <doi:10.1111/j.1467-9868.2008.00666.x>).
Author: Søren Højsgaard <sorenh@math.aau.dk>, Steffen L. Lauritzen <lauritzen@math.ku.dk>
Maintainer: Søren Højsgaard <sorenh@math.aau.dk>

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Package diversityForest updated to version 0.3.1 with previous version 0.3.0 dated 2021-04-01

Title: Complex Split Procedures in Random Forests Through Candidate Split Sampling
Description: Implements interaction forests [1], which are specific diversity forests, and the basic form of diversity forests that uses univariable, binary splitting [2]. Interaction forests (IFs) are ensembles of decision trees that model quantitative and qualitative interaction effects using bivariable splitting. IFs come with the Effect Importance Measure (EIM), which can be used to identify variable pairs that feature quantitative and qualitative interaction effects with high predictive relevance. IFs and EIM focus on well interpretable forms of interactions. The package also offers plot functions for visualising the estimated forms of interaction effects. Categorical, metric, and survival outcomes are supported. This is a fork of the R package 'ranger' (main author: Marvin N. Wright) that implements random forests using an efficient C++ implementation. References: [1] Hornung, R. & Boulesteix, A.-L. (2021) Interaction Forests: Identifying and exploiting interpretable quantitative and qualitative interaction effects. Technical Report No. 237, Department of Statistics, University of Munich [2] Hornung, R. (2020) Diversity Forests: Using split sampling to allow for complex split procedures in random forest. Technical Report No. 234, Department of Statistics, University of Munich.
Author: Roman Hornung [aut, cre], Marvin N. Wright [ctb, cph]
Maintainer: Roman Hornung <hornung@ibe.med.uni-muenchen.de>

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Package dartR updated to version 1.9.1 with previous version 1.8.3 dated 2020-09-01

Title: Importing and Analysing SNP and Silicodart Data Generated by Genome-Wide Restriction Fragment Analysis
Description: Functions are provided that facilitate the import and analysis of SNP (single nucleotide polymorphism) and silicodart (presence/absence) data. The main focus is on data generated by DarT (Diversity Arrays Technology). However, once SNP or related fragment presence/absence data from any source is imported into a genlight object many of the functions can be used. Functions are available for input and output of SNP and silicodart data, for reporting on and filtering on various criteria (e.g. CallRate, Heterozygosity, Reproducibility, maximum allele frequency). Advanced filtering is based on Linkage Disequilibrium and HWE (Hardy-Weinberg equilibrium). Other functions are available for visualization after PCoA (Principle Coordinate Analysis), or to facilitate transfer of data between genlight/genind objects and newhybrids, related, phylip, structure, faststructure packages.
Author: Bernd Gruber [aut, cre], Arthur Georges [aut], Jose L. Mijangos [aut], Peter J. Unmack [ctb], Oliver Berry [ctb], Lindsay V. Clark [ctb], Floriaan Devloo-Delva [ctb]
Maintainer: Bernd Gruber <bernd.gruber@canberra.edu.au>

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Package bayesTFR updated to version 7.0-4 with previous version 6.4-0 dated 2019-10-18

Title: Bayesian Fertility Projection
Description: Making probabilistic projections of total fertility rate for all countries of the world, using a Bayesian hierarchical model.
Author: Hana Sevcikova (hanas@uw.edu), Leontine Alkema (alkema@nus.edu.sg), Peiran Liu (prliu@uw.edu), Adrian Raftery (raftery@uw.edu), Bailey Fosdick (bfosdick@uw.edu), Patrick Gerland (gerland@un.org)
Maintainer: Hana Sevcikova <hanas@uw.edu>

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Package albatross updated to version 0.3-1 with previous version 0.3-0 dated 2021-03-26

Title: PARAFAC Analysis of Fluorescence Excitation-Emission Matrices
Description: Perform parallel factor analysis (PARAFAC: Hitchcock, 1927) <doi:10.1002/sapm192761164> on fluorescence excitation-emission matrices (FEEMs): handle scattering signal and inner filter effect, scale the dataset, fit the model; perform split-half validation or jack-knifing. A modified approach called "randomised split-half" is also available. The package has a low dependency footprint (only two direct dependencies not in core or recommended; four total non-core/recommended dependencies) and has been tested on a wide range of R versions (including R as old as 3.3.3 from Debian Stretch).
Author: Ivan Krylov [aut, cre], Timur Labutin [ths]
Maintainer: Ivan Krylov <ikrylov@laser.chem.msu.ru>

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Package CatPredi (with last version 1.1) was removed from CRAN

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

2017-10-09 1.1

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Package IntClust (with last version 0.1.0) was removed from CRAN

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

2018-07-30 0.1.0
2016-03-31 0.0.2

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Package EMA (with last version 1.4.7) was removed from CRAN

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

2020-02-14 1.4.7
2019-12-16 1.4.6
2016-09-07 1.4.5
2014-03-28 1.4.4
2013-08-05 1.4.3
2013-07-08 1.4.2
2013-07-01 1.4.1
2013-04-29 1.4.0

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Package heatmap.plus (with last version 1.3) was removed from CRAN

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

2007-09-05 1.3
2007-03-30 1.2

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Package SNFtool (with last version 2.3.0) was removed from CRAN

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

2018-04-24 2.3.0
2017-11-24 2.2.1
2014-09-08 2.2
2014-03-29 2.1
2014-03-03 2.0.3

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Package spatstat updated to version 2.1-0 with previous version 2.0-1 dated 2021-03-13

Title: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Description: Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images. Contains over 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.
Author: Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package provenance updated to version 3.2 with previous version 3.0 dated 2021-02-24

Title: Statistical Toolbox for Sedimentary Provenance Analysis
Description: Bundles a number of established statistical methods to facilitate the visual interpretation of large datasets in sedimentary geology. Includes functionality for adaptive kernel density estimation, principal component analysis, correspondence analysis, multidimensional scaling, generalised procrustes analysis and individual differences scaling using a variety of dissimilarity measures. Univariate provenance proxies, such as single-grain ages or (isotopic) compositions are compared with the Kolmogorov-Smirnov, Kuiper or Sircombe-Hazelton L2 distances. Categorical provenance proxies such as chemical compositions are compared with the Aitchison and Bray-Curtis distances, and point-counting data with the chi-square distance. Also included are tools to plot compositional and point-counting data on ternary diagrams and point-counting data on radial plots, to calculate the sample size required for specified levels of statistical precision, and to assess the effects of hydraulic sorting on detrital compositions. Includes an intuitive query-based user interface for users who are not proficient in R.
Author: Pieter Vermeesch [aut, cre]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

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Package tfdatasets updated to version 2.4.0 with previous version 2.2.0 dated 2020-05-25

Title: Interface to 'TensorFlow' Datasets
Description: Interface to 'TensorFlow' Datasets, a high-level library for building complex input pipelines from simple, re-usable pieces. See <https://www.tensorflow.org/guide> for additional details.
Author: Daniel Falbel [ctb, cph, cre], JJ Allaire [aut, cph], Yuan Tang [aut] (<https://orcid.org/0000-0001-5243-233X>), Kevin Ushey [aut], RStudio [cph, fnd], Google Inc. [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>

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Package gbfs updated to version 1.3.7 with previous version 1.3.6 dated 2021-01-06

Title: Interface with Live Bikeshare Data
Description: Supplies a set of functions to interface with bikeshare data following the General Bikeshare Feed Specification, allowing users to query and accumulate tidy datasets for specified cities/bikeshare programs.
Author: Simon P. Couch [aut, cre], Kaelyn Rosenberg [aut], Mark Padgham [ctb]
Maintainer: Simon P. Couch <simonpatrickcouch@gmail.com>

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