Sat, 17 Oct 2020

Package FoReco updated to version 0.1.1 with previous version 0.1.0 dated 2020-10-01

Title: Point Forecast Reconciliation
Description: Provides classical (bottom-up), optimal and heuristic combination forecast reconciliation procedures for cross-sectional, temporal, and cross-temporal linearly constrained time series.
Author: Daniele Girolimetto [aut, cre, fnd], Tommaso Di Fonzo [aut, fnd]
Maintainer: Daniele Girolimetto <daniele.girolimetto@phd.unipd.it>

Diff between FoReco versions 0.1.0 dated 2020-10-01 and 0.1.1 dated 2020-10-17

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Package AzureVision updated to version 1.0.2 with previous version 1.0.1 dated 2020-04-21

Title: Interface to Azure Computer Vision Services
Description: An interface to 'Azure Computer Vision' <https://docs.microsoft.com/azure/cognitive-services/Computer-vision/Home> and 'Azure Custom Vision' <https://docs.microsoft.com/azure/cognitive-services/custom-vision-service/home>, building on the low-level functionality provided by the 'AzureCognitive' package. These services allow users to leverage the cloud to carry out visual recognition tasks using advanced image processing models, without needing powerful hardware of their own. Part of the 'AzureR' family of packages.
Author: Hong Ooi [aut, cre], Microsoft [cph]
Maintainer: Hong Ooi <hongooi73@gmail.com>

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Package strex updated to version 1.4.1 with previous version 1.4.0 dated 2020-10-10

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

Diff between strex versions 1.4.0 dated 2020-10-10 and 1.4.1 dated 2020-10-17

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Package openSTARS updated to version 1.2.2 with previous version 1.2.0 dated 2020-05-21

Title: An Open Source Implementation of the 'ArcGIS' Toolbox 'STARS'
Description: An open source implementation of the 'STARS' toolbox (Peterson & Ver Hoef, 2014, <doi:10.18637/jss.v056.i02>) using 'R' and 'GRASS GIS'. It prepares the *.ssn object needed for the 'SSN' package. A Digital Elevation Model (DEM) is used to derive stream networks (in contrast to 'STARS' that can clean an existing stream network).
Author: Mira Kattwinkel [aut, cre], Eduard Szöcs [aut]
Maintainer: Mira Kattwinkel <mira.kattwinkel@gmx.net>

Diff between openSTARS versions 1.2.0 dated 2020-05-21 and 1.2.2 dated 2020-10-17

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Package rqdatatable updated to version 1.2.9 with previous version 1.2.8 dated 2020-08-12

Title: 'rquery' for 'data.table'
Description: Implements the 'rquery' piped Codd-style query algebra using 'data.table'. This allows for a high-speed in memory implementation of Codd-style data manipulation tools.
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between rqdatatable versions 1.2.8 dated 2020-08-12 and 1.2.9 dated 2020-10-17

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Package amapGeocode updated to version 0.4.0 with previous version 0.3.1 dated 2020-10-01

Title: An Interface to the 'AutoNavi Maps' API Geocoding Services
Description: Getting and parsing data of location geocode/reverse-geocode and administrative regions from 'AutoNavi Maps'<https://lbs.amap.com/api/webservice/summary> API.
Author: Han Chen [aut, cre], Wanyanhan Jiang [ctb]
Maintainer: Han Chen <chenhan28@gmail.com>

Diff between amapGeocode versions 0.3.1 dated 2020-10-01 and 0.4.0 dated 2020-10-17

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Package rquery updated to version 1.4.6 with previous version 1.4.5 dated 2020-08-12

Title: Relational Query Generator for Data Manipulation at Scale
Description: A piped query generator based on Edgar F. Codd's relational algebra, and on production experience using 'SQL' and 'dplyr' at big data scale. The design represents an attempt to make 'SQL' more teachable by denoting composition by a sequential pipeline notation instead of nested queries or functions. The implementation delivers reliable high performance data processing on large data systems such as 'Spark', databases, and 'data.table'. Package features include: data processing trees or pipelines as observable objects (able to report both columns produced and columns used), optimized 'SQL' generation as an explicit user visible table modeling step, plus explicit query reasoning and checking.
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between rquery versions 1.4.5 dated 2020-08-12 and 1.4.6 dated 2020-10-17

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Package recipes updated to version 0.1.14 with previous version 0.1.13 dated 2020-06-23

Title: Preprocessing Tools to Create Design Matrices
Description: An extensible framework to create and preprocess design matrices. Recipes consist of one or more data manipulation and analysis "steps". Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting design matrices can then be used as inputs into statistical or machine learning models.
Author: Max Kuhn [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

Diff between recipes versions 0.1.13 dated 2020-06-23 and 0.1.14 dated 2020-10-17

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Package missDeaths updated to version 2.7 with previous version 2.6 dated 2020-05-17

Title: Simulating and Analyzing Time to Event Data in the Presence of Population Mortality
Description: Implements two methods: a nonparametric risk adjustment and a data imputation method that use general population mortality tables to allow a correct analysis of time to disease recurrence. Also includes a powerful set of object oriented survival data simulation functions.
Author: Tomaz Stupnik [aut, cre], Maja Pohar Perme [ctb]
Maintainer: Tomaz Stupnik <tomaz.stupnik@guest.arnes.si>

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Package embed updated to version 0.1.2 with previous version 0.1.1 dated 2020-07-03

Title: Extra Recipes for Encoding Categorical Predictors
Description: Predictors can be converted to one or more numeric representations using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737>. Most encoding methods are supervised.
Author: Max Kuhn [aut, cre], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

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Package cdata updated to version 1.1.9 with previous version 1.1.8 dated 2020-08-25

Title: Fluid Data Transformations
Description: Supplies higher-order coordinatized data specification and fluid transform operators that include pivot and anti-pivot as special cases. The methodology is describe in 'Zumel', 2018, "Fluid data reshaping with 'cdata'", <https://winvector.github.io/FluidData/FluidDataReshapingWithCdata.html> , <DOI:10.5281/zenodo.1173299> . This package introduces the idea of explicit control table specification of data transforms. Works on in-memory data or on remote data using 'rquery' and 'SQL' database interfaces.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between cdata versions 1.1.8 dated 2020-08-25 and 1.1.9 dated 2020-10-17

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Package WVPlots updated to version 1.3.1 with previous version 1.3.0 dated 2020-10-03

Title: Common Plots for Analysis
Description: Select data analysis plots, under a standardized calling interface implemented on top of 'ggplot2' and 'plotly'. Plots of interest include: 'ROC', gain curve, scatter plot with marginal distributions, conditioned scatter plot with marginal densities, box and stem with matching theoretical distribution, and density with matching theoretical distribution.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between WVPlots versions 1.3.0 dated 2020-10-03 and 1.3.1 dated 2020-10-17

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Package WriteXLS updated to version 6.0.0 with previous version 5.0.0 dated 2019-05-25

Title: Cross-Platform Perl Based R Function to Create Excel 2003 (XLS) and Excel 2007 (XLSX) Files
Description: Cross-platform Perl based R function to create Excel 2003 (XLS) and Excel 2007 (XLSX) files from one or more data frames. Each data frame will be written to a separate named worksheet in the Excel spreadsheet. The worksheet name will be the name of the data frame it contains or can be specified by the user.
Author: Marc Schwartz <marc_schwartz@me.com> and various authors for Perl modules listed in each .pm file.
Maintainer: Marc Schwartz <marc_schwartz@me.com>

Diff between WriteXLS versions 5.0.0 dated 2019-05-25 and 6.0.0 dated 2020-10-17

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Package digest updated to version 0.6.26 with previous version 0.6.25 dated 2020-02-22

Title: Create Compact Hash Digests of R Objects
Description: Implementation of a function 'digest()' for the creation of hash digests of arbitrary R objects (using the 'md5', 'sha-1', 'sha-256', 'crc32', 'xxhash', 'murmurhash', 'spookyhash' and 'blake3' algorithms) permitting easy comparison of R language objects, as well as functions such as'hmac()' to create hash-based message authentication code. Please note that this package is not meant to be deployed for cryptographic purposes for which more comprehensive (and widely tested) libraries such as 'OpenSSL' should be used.
Author: Dirk Eddelbuettel <edd@debian.org> with contributions by Antoine Lucas, Jarek Tuszynski, Henrik Bengtsson, Simon Urbanek, Mario Frasca, Bryan Lewis, Murray Stokely, Hannes Muehleisen, Duncan Murdoch, Jim Hester, Wush Wu, Qiang Kou, Thierry Onkelinx, Michel Lang, Viliam Simko, Kurt Hornik, Radford Neal, Kendon Bell, Matthew de Queljoe, Ion Suruceanu, Bill Denney, Dirk Schumacher, and Winston Chang.
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between digest versions 0.6.25 dated 2020-02-22 and 0.6.26 dated 2020-10-17

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Package vtreat updated to version 1.6.2 with previous version 1.6.1 dated 2020-08-12

Title: A Statistically Sound 'data.frame' Processor/Conditioner
Description: A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. 'vtreat' prepares variables so that data has fewer exceptional cases, making it easier to safely use models in production. Common problems 'vtreat' defends against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new categorical levels (levels seen during application, but not during training). Reference: "'vtreat': a data.frame Processor for Predictive Modeling", Zumel, Mount, 2016, <DOI:10.5281/zenodo.1173313>.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between vtreat versions 1.6.1 dated 2020-08-12 and 1.6.2 dated 2020-10-17

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Package soundgen updated to version 1.8.2 with previous version 1.8.1 dated 2020-09-18

Title: Sound Synthesis and Acoustic Analysis
Description: Performs parametric synthesis of sounds with harmonic and noise components such as animal vocalizations or human voice. Also offers tools for spectral analysis, audio segmentation, self-similarity matrices, modulation spectra, morphing, etc., as well as interactive web apps for manually corrected pitch tracking and formant measurement. Reference: Anikin (2019) <doi:10.3758/s13428-018-1095-7>.
Author: Andrey Anikin [aut, cre]
Maintainer: Andrey Anikin <rty.anik@rambler.ru>

Diff between soundgen versions 1.8.1 dated 2020-09-18 and 1.8.2 dated 2020-10-17

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Package RcppDynProg updated to version 0.1.5 with previous version 0.1.4 dated 2020-08-12

Title: 'Rcpp' Dynamic Programming
Description: Dynamic Programming implemented in 'Rcpp'. Includes example partition and out of sample fitting applications. Also supplies additional custom coders for the 'vtreat' package.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between RcppDynProg versions 0.1.4 dated 2020-08-12 and 0.1.5 dated 2020-10-17

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Package wrapr updated to version 2.0.4 with previous version 2.0.2 dated 2020-08-10

Title: Wrap R Tools for Debugging and Parametric Programming
Description: Tools for writing and debugging R code. Provides: '%.>%' dot-pipe (an 'S3' configurable pipe), unpack/to (R style multiple assignment/return), 'build_frame()'/'draw_frame()' ('data.frame' example tools), 'qc()' (quoting concatenate), ':=' (named map builder), 'let()' (converts non-standard evaluation interfaces to parametric standard evaluation interfaces, inspired by 'gtools::strmacro()' and 'base::bquote()'), and more.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between wrapr versions 2.0.2 dated 2020-08-10 and 2.0.4 dated 2020-10-17

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New package representr with initial version 0.1.0
Package: representr
Type: Package
Title: Create Representative Records After Entity Resolution
Version: 0.1.0
Authors@R: c(person("Andee", "Kaplan", email = "andee.kaplan@colostate.edu", role = c("aut", "cre")), person("Brenda", "Betancourt", role = "aut"), person("Rebecca C.", "Steorts", email = "beka@stat.duke.edu", role = c("aut")))
Description: An implementation of Kaplan, Betancourt, Steorts (2020) <arXiv:1810.01538> that creates representative records for use in downstream tasks after entity resolution is performed. Multiple methods for creating the representative records (data sets) are provided.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: doParallel, foreach, dplyr
Suggests: knitr, rmarkdown, blink, ggplot2, stringdist
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-10-09 23:40:05 UTC; andeek
Author: Andee Kaplan [aut, cre], Brenda Betancourt [aut], Rebecca C. Steorts [aut]
Maintainer: Andee Kaplan <andee.kaplan@colostate.edu>
Repository: CRAN
Date/Publication: 2020-10-17 12:40:02 UTC

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New package provExplainR with initial version 1.0
Package: provExplainR
Title: Compare Provenance Collections to Explain Changed Script Outputs
Version: 1.0
Date: 2020-10-09
Authors@R: c( person("Barbara", "Lerner", role = "cre", email = "blerner@mtholyoke.edu"), person("Emery", "Boose", role = "aut", email = "boose@fas.harvard.edu"), person("Khanh", "Ngo", role = "aut", email = "ngo22k@mtholyoke.edu") )
Copyright: President and Fellows of Harvard College, Trustees of Mount Holyoke College
Description: Inspects provenance collected by the 'rdt' or 'rdtLite' packages, or other tools providing compatible PROV JSON output created by the execution of a script, and find differences between two provenance collections. Factors under examination included the hardware and software used to execute the script, versions of attached libraries, use of global variables, modified inputs and outputs, and changes in main and sourced scripts. Based on detected changes, 'provExplainR' can be used to study how these factors affect the behavior of the script and generate a promising diagnosis of the causes of different script results. More information about 'rdtLite' and associated tools is available at <https://github.com/End-to-end-provenance/> and Barbara Lerner, Emery Boose, and Luis Perez (2018), Using Introspection to Collect Provenance in R, Informatics, <doi:10.3390/informatics5010012>.
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, provParseR (>= 0.1.2), diffobj, digest, stringr
Suggests: testthat
URL: https://github.com/End-to-end-provenance
BugReports: https://github.com/End-to-end-provenance/provExplainR/issues
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-10-09 20:08:23 UTC; blerner
Author: Barbara Lerner [cre], Emery Boose [aut], Khanh Ngo [aut]
Maintainer: Barbara Lerner <blerner@mtholyoke.edu>
Repository: CRAN
Date/Publication: 2020-10-17 12:30:02 UTC

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New package mcmcensemble with initial version 2.0
Package: mcmcensemble
Title: Ensemble Sampler for Affine-Invariant MCMC
Version: 2.0
Authors@R: c(person(given = "Hugo", family = "Gruson", role = c("cre", "aut", "cph"), email = "hugo.gruson+R@normalesup.org", comment = c(ORCID = "0000-0002-4094-1476")), person(given = "Sanda", family = "Dejanic", role = c("aut", "cph")), person(given = "Andreas", family = "Scheidegger", role = c("aut", "cph"), comment = c(ORCID = "0000-0003-2575-2172")))
Description: Provides ensemble samplers for affine-invariant Monte Carlo Markov Chain, which allow a faster convergence for badly scaled estimation problems. Two samplers are proposed: the 'differential.evolution' sampler from ter Braak and Vrugt (2008) <doi:10.1007/s11222-008-9104-9> and the 'stretch' sampler from Goodman and Weare (2010) <doi:10.2140/camcos.2010.5.65>.
License: GPL-2
URL: https://github.com/Bisaloo/mcmcensemble, https://bisaloo.github.io/mcmcensemble/
BugReports: https://github.com/Bisaloo/mcmcensemble/issues
Suggests: coda, mockery, testthat
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-10-09 14:08:44 UTC; hugo
Author: Hugo Gruson [cre, aut, cph] (<https://orcid.org/0000-0002-4094-1476>), Sanda Dejanic [aut, cph], Andreas Scheidegger [aut, cph] (<https://orcid.org/0000-0003-2575-2172>)
Maintainer: Hugo Gruson <hugo.gruson+R@normalesup.org>
Repository: CRAN
Date/Publication: 2020-10-17 12:20:02 UTC

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New package lucas with initial version 1.0
Package: lucas
Type: Package
Title: Package to Download and Create the DB of LUCAS Data Harmonized
Version: 1.0
Date: 2020-09-28
Authors@R: c(person("Momchil", "Yordanov", email = "momchilyordanov@abv.bg", role = "cre"), person("Laura", "Martinez", email = "lmartisa@gmail.com", role = "aut"), person("Raphael", "dAndrimont", email = "raphael.dandrimont@ec.europa.eu", role = "aut"))
Description: Reproduces the harmonized DB of the ESTAT survey of the same name. The survey data is served as separate spreadsheets with noticeable differences in the collected attributes. The tool here presented carries out a series of instructions that harmonize the attributes in terms of name, meaning, and occurrence, while also introducing a series of new variables, instrumental to adding value to the product. Outputs include one harmonized table with all the years, and three separate geometries, corresponding to the theoretical point, the gps location where the measurement was made and the 250m east-facing transect.
Depends: R (>= 3.4)
Imports: RPostgreSQL, rpostgis, plyr, utils, DBI
License: GPL (>= 3)
LazyData: TRUE
RoxygenNote: 7.0.2
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-10-09 17:38:38 UTC; momut1
Author: Momchil Yordanov [cre], Laura Martinez [aut], Raphael dAndrimont [aut]
Maintainer: Momchil Yordanov <momchilyordanov@abv.bg>
Repository: CRAN
Date/Publication: 2020-10-17 12:20:05 UTC

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New package hkdatasets with initial version 0.0.3
Package: hkdatasets
Title: Datasets Related to Hong Kong
Version: 0.0.3
Authors@R: c(person(given = "Martin", family = "Chan", role = c("aut", "cre"), email = "martinchan53@gmail.com"), person(given = "Avision", family = "Ho", role = c("ctb"), email = "hkdistricts.info@gmail.com"), person(given = "Ocean", family = "Cheung", role = c("ctb")), person(given = "Justin", family = "Yim", role = c("ctb")), person(given = "Gabriel", family = "Tam", role = c("ctb")))
Description: Datasets related to Hong Kong, including information on the 2019 elected District Councillors (<https://www.districtcouncils.gov.hk> and <https://dce2019.hk01.com/>) and traffic collision data from the Hong Kong Department of Transport (<https://www.td.gov.hk/>). All of the data in this package is available in the public domain.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://hong-kong-districts-info.github.io/hkdatasets/
BugReports: https://github.com/Hong-Kong-Districts-Info/hkdatasets/issues
Maintainer: Martin Chan <martinchan53@gmail.com>
Depends: R (>= 3.5.0)
Suggests: dplyr, tidyr, here, showtext
NeedsCompilation: no
Packaged: 2020-10-03 11:52:53 UTC; Martin Chan
Author: Martin Chan [aut, cre], Avision Ho [ctb], Ocean Cheung [ctb], Justin Yim [ctb], Gabriel Tam [ctb]
Repository: CRAN
Date/Publication: 2020-10-17 12:10:02 UTC

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Package LexisNexisTools updated to version 0.3.2 with previous version 0.3.1 dated 2020-06-03

Title: Working with Files from 'LexisNexis'
Description: My PhD supervisor once told me that everyone doing newspaper analysis starts by writing code to read in files from the 'LexisNexis' newspaper archive (retrieved e.g., from <http://www.nexis.com/> or any of the partner sites). However, while this is a nice exercise I do recommend, not everyone has the time. This package takes files downloaded from the newspaper archive of 'LexisNexis', reads them into R and offers functions for further processing.
Author: Johannes Gruber [aut, cre]
Maintainer: Johannes Gruber <j.gruber.1@research.gla.ac.uk>

Diff between LexisNexisTools versions 0.3.1 dated 2020-06-03 and 0.3.2 dated 2020-10-17

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New package IBMPopSim with initial version 0.3.0
Package: IBMPopSim
Type: Package
Title: Individual Based Model Population Simulation
Version: 0.3.0
Date: 2020-10-09
Authors@R: c( person('Daphné', 'Giorgi', role = c('aut', 'cre'), email = 'daphne.giorgi@sorbonne-universite.fr'), person('Sarah', 'Kaakai', role = 'aut', email = 'sarah.kaakai@univ-lemans.fr'), person('Vincent', 'Lemaire', role = 'aut', email = 'vincent.lemaire@sorbonne-universite.fr') )
Maintainer: Daphné Giorgi <daphne.giorgi@sorbonne-universite.fr>
Description: Simulation of the random evolution of structured population dynamics, called stochastic Individual Based Models (IBMs) (see e.g. Ferrière and Tran (2009) <doi:10.1051/proc/2009033>, Bansaye and Méléard (2015) <doi:10.1007/978-3-319-21711-6>, Boumezoued (2016)). The package allows users to simulate the random evolution of a population in which individuals are characterised by their date of birth, a set of attributes, and their potential date of death.
URL: https://github.com/DaphneGiorgi/IBMPopSim, https://DaphneGiorgi.github.io/IBMPopSim/
BugReports: https://github.com/DaphneGiorgi/IBMPopSim/issues
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 0.12), checkmate, stats, utils, readr, rlang, tidyr, dplyr (>= 0.8.0), reshape, purrr, ggplot2
Suggests: RcppArmadillo, knitr, rmarkdown, bookdown, ggfortify, magick, colorspace, gridExtra
LazyData: true
SystemRequirements: C++11
NeedsCompilation: no
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Encoding: UTF-8
Packaged: 2020-10-09 10:56:02 UTC; giorgi
Author: Daphné Giorgi [aut, cre], Sarah Kaakai [aut], Vincent Lemaire [aut]
Repository: CRAN
Date/Publication: 2020-10-17 12:00:02 UTC

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Package fruclimadapt updated to version 0.4.4 with previous version 0.4.3 dated 2020-08-24

Title: Evaluation Tools for Assessing Climate Adaptation of Fruit Tree Species
Description: Climate is a critical component limiting growing range of plant species, which also determines cultivar adaptation to a region. The evaluation of climate influence on fruit production is critical for decision-making in the design stage of orchards and vineyards and in the evaluation of the potential consequences of future climate. Bio- climatic indices and plant phenology are commonly used to describe the suitability of climate for growing quality fruit and to provide temporal and spatial information about regarding ongoing and future changes. 'fruclimadapt' streamlines the assessment of climate adaptation and the identification of potential risks for grapevines and fruit trees. Procedures in the package allow to i) downscale daily meteorological variables to hourly values (Forster et al (2016) <doi:10.5194/gmd-9-2315-2016>), ii) estimate chilling and forcing heat accumulation (Miranda et al (2019) <https://ec.europa.eu/eip/agriculture/sites/agri-eip/files/fg30_mp5_phenology_critical_temperatures.pdf>), iii) estimate plant phenology (Schwartz (2012) <doi:10.1007/978-94-007-6925-0>), iv) calculate bioclimatic indices to evaluate fruit tree and grapevine adaptation (e.g. Badr et al (2017) <doi:10.3354/cr01532>), v) estimate the incidence of weather-related disorders in fruits (e.g. Snyder and de Melo-Abreu (2005, ISBN:92-5-105328-6) and vi) estimate plant water requirements (Allen et al (1998, ISBN:92-5-104219-5)).
Author: Carlos Miranda
Maintainer: Carlos Miranda <carlos.miranda@unavarra.es>

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Package h2o updated to version 3.32.0.1 with previous version 3.30.1.3 dated 2020-09-30

Title: R Interface for the 'H2O' Scalable Machine Learning Platform
Description: R interface for 'H2O', the scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models (GLM), Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Generalized Additive Models (GAM), Cox Proportional Hazards, K-Means, PCA, Word2Vec, as well as a fully automatic machine learning algorithm (H2O AutoML).
Author: Erin LeDell [aut, cre], Navdeep Gill [aut], Spencer Aiello [aut], Anqi Fu [aut], Arno Candel [aut], Cliff Click [aut], Tom Kraljevic [aut], Tomas Nykodym [aut], Patrick Aboyoun [aut], Michal Kurka [aut], Michal Malohlava [aut], Ludi Rehak [ctb], Eric Eckstrand [ctb], Brandon Hill [ctb], Sebastian Vidrio [ctb], Surekha Jadhawani [ctb], Amy Wang [ctb], Raymond Peck [ctb], Wendy Wong [ctb], Jan Gorecki [ctb], Matt Dowle [ctb], Yuan Tang [ctb], Lauren DiPerna [ctb], H2O.ai [cph, fnd]
Maintainer: Erin LeDell <erin@h2o.ai>

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Package codetools updated to version 0.2-17 with previous version 0.2-16 dated 2018-12-24

Title: Code Analysis Tools for R
Description: Code analysis tools for R.
Author: Luke Tierney <luke-tierney@uiowa.edu>
Maintainer: Luke Tierney <luke-tierney@uiowa.edu>

Diff between codetools versions 0.2-16 dated 2018-12-24 and 0.2-17 dated 2020-10-17

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Package GpGp updated to version 0.3.1 with previous version 0.3.0 dated 2020-10-03

Title: Fast Gaussian Process Computation Using Vecchia's Approximation
Description: Functions for fitting and doing predictions with Gaussian process models using Vecchia's (1988) approximation. Package also includes functions for reordering input locations, finding ordered nearest neighbors (with help from 'FNN' package), grouping operations, and conditional simulations. Covariance functions for spatial and spatial-temporal data on Euclidean domains and spheres are provided. The original approximation is due to Vecchia (1988) <http://www.jstor.org/stable/2345768>, and the reordering and grouping methods are from Guinness (2018) <doi:10.1080/00401706.2018.1437476>. Model fitting employs a Fisher scoring algorithm described in Guinness (2019) <arXiv:1905.08374>.
Author: Joseph Guinness [aut, cre], Matthias Katzfuss [aut], Youssef Fahmy [aut]
Maintainer: Joseph Guinness <joeguinness@gmail.com>

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Package ADAPTS updated to version 1.0.6 with previous version 1.0.5 dated 2020-08-31

Title: Automated Deconvolution Augmentation of Profiles for Tissue Specific Cells
Description: Tools to construct (or add to) cell-type signature matrices using flow sorted or single cell samples and deconvolve bulk gene expression data. Useful for assessing the quality of single cell RNAseq experiments, estimating the accuracy of signature matrices, and determining cell-type spillover. Please cite: Danziger SA et al. (2019) ADAPTS: Automated Deconvolution Augmentation of Profiles for Tissue Specific cells <doi:10.1371/journal.pone.0224693>.
Author: Samuel A Danziger
Maintainer: Samuel A Danziger <sam.danziger@gmail.com>

Diff between ADAPTS versions 1.0.5 dated 2020-08-31 and 1.0.6 dated 2020-10-17

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