Thu, 14 Jan 2021

New package icesVocab with initial version 1.1.9
Package: icesVocab
Title: ICES Vocabularies Database Web Services
Date: 2021-01-14
Version: 1.1.9
Authors@R: c(person("Colin", "Millar", email = "colin.millar@ices.dk", role = c("aut","cre")), person("Arni", "Magnusson", role = "aut"))
Imports: utils, xml2
Description: R interface to access the RECO POX web services of the ICES (International Council for the Exploration of the Sea) Vocabularies database <https://vocab.ices.dk/services/POX.aspx>.
License: GPL-3
URL: https://vocab.ices.dk/services/POX.aspx
RoxygenNote: 7.1.1
Encoding: UTF-8
BugReports: https://github.com/ices-tools-prod/icesVocab/issues
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-01-14 22:26:56 UTC; colin
Author: Colin Millar [aut, cre], Arni Magnusson [aut]
Maintainer: Colin Millar <colin.millar@ices.dk>
Repository: CRAN
Date/Publication: 2021-01-15 00:00:02 UTC

More information about icesVocab at CRAN
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Package waiter updated to version 0.2.0 with previous version 0.1.3 dated 2020-09-13

Title: Loading Screen for 'Shiny'
Description: Full screen and partial loading screens for 'Shiny' with spinners, progress bars, and notifications.
Author: John Coene [aut, cre], Jinhwan Kim [ctb], Victor Granda [ctb] (<https://orcid.org/0000-0002-0469-1991>)
Maintainer: John Coene <jcoenep@gmail.com>

Diff between waiter versions 0.1.3 dated 2020-09-13 and 0.2.0 dated 2021-01-14

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Package UKFE updated to version 0.1.3 with previous version 0.1.2 dated 2020-12-05

Title: UK Flood Estimation
Description: Functions to implement the methods of the Flood Estimation Handbook (FEH), associated updates and the revitalised flood hydrograph model (ReFH). Currently the packages uses NRFA peak flow dataset version 9. Aside from FEH functionality, further hydrological functions are available. Most of the methods implemented in this package are described in one or more of the following: "Flood Estimation Handbook", Centre for Ecology & Hydrology (1999, ISBN:0 948540 94 X). "Flood Estimation Handbook Supplementary Report No. 1", Kjeldsen (2007, ISBN:0 903741 15 7). "Regional Frequency Analysis - an approach based on L-moments", Hosking & Wallis (1997, ISBN: 978 0 521 01940 8). "Proposal of the ‘extreme rank plot’ for extreme value analysis: with an emphasis on flood frequency studies", Hammond (2019, <doi:10.2166/nh.2019.157>). "Making better use of local data in flood frequency estimation", Environment Agency (2017, ISBN: 978 1 84911 387 8). "Improving the FEH statistical procedures for flood frequency estimation", Environment Agency (2008, ISBN: 978 1 84432 920 5). "Low flow estimation in the United Kingdom", Institute of Hydrology (1992, ISBN 0 948540 45 1). Wallingford HydroSolutions, (2016, <http://software.hydrosolutions.co.uk/winfap4/Urban-Adjustment-Procedure-Technical-Note.pdf>). Data from the UK National River Flow Archive (<https://nrfa.ceh.ac.uk/>, terms and conditions: <https://nrfa.ceh.ac.uk/costs-terms-and-conditions>.
Author: Anthony Hammond
Maintainer: Anthony Hammond <agqhammond@gmail.com>

Diff between UKFE versions 0.1.2 dated 2020-12-05 and 0.1.3 dated 2021-01-14

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Package repello updated to version 1.0.1 with previous version 1.0.0 dated 2020-11-09

Title: Reports from Trello in R
Description: Creates reports from Trello, a collaborative, project organization and list-making application. <https://trello.com/> Reports are created by comparing individual Trello board cards from two different points in time and documenting any changes made to the cards.
Author: Andrew Guide [aut, cre], Thomas Stewart [aut]
Maintainer: Andrew Guide <andrew.guide@vumc.org>

Diff between repello versions 1.0.0 dated 2020-11-09 and 1.0.1 dated 2021-01-14

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Package nodbi updated to version 0.4.2 with previous version 0.4.0 dated 2019-11-11

Title: 'NoSQL' Database Connector
Description: Simplified document database manipulation and analysis, including support for many 'NoSQL' databases, including document databases ('Elasticsearch', 'CouchDB', 'MongoDB'), 'key-value' databases ('Redis'), and (with limitations) SQLite/json1.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Rich FitzJohn [aut], Jeroen Ooms [aut], Ralf Herold [aut] (<https://orcid.org/0000-0002-8148-6748>)
Maintainer: Scott Chamberlain <sckott@protonmail.com>

Diff between nodbi versions 0.4.0 dated 2019-11-11 and 0.4.2 dated 2021-01-14

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Package nadiv updated to version 2.17.0 with previous version 2.16.2.0 dated 2019-10-20

Title: (Non)Additive Genetic Relatedness Matrices
Description: Constructs (non)additive genetic relationship matrices, and their inverses, from a pedigree to be used in linear mixed effect models (A.K.A. the 'animal model'). Also includes other functions to facilitate the use of animal models. Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<https://www.vsni.co.uk/software/asreml>).
Author: Matthew Wolak [cre, aut]
Maintainer: Matthew Wolak <matthewwolak@gmail.com>

Diff between nadiv versions 2.16.2.0 dated 2019-10-20 and 2.17.0 dated 2021-01-14

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Package ijtiff updated to version 2.2.5 with previous version 2.2.4 dated 2020-11-09

Title: Comprehensive TIFF I/O with Full Support for 'ImageJ' TIFF Files
Description: General purpose TIFF file I/O for R users. Currently the only such package with read and write support for TIFF files with floating point (real-numbered) pixels, and the only package that can correctly import TIFF files that were saved from 'ImageJ' and write TIFF files than can be correctly read by 'ImageJ' <https://imagej.nih.gov/ij/>. Also supports text image I/O.
Author: Rory Nolan [aut, cre] (<https://orcid.org/0000-0002-5239-4043>), Kent Johnson [aut], Simon Urbanek [ctb], Sergi Padilla-Parra [ths] (<https://orcid.org/0000-0002-8010-9481>), Jeroen Ooms [rev, ctb] (<https://orcid.org/0000-0002-4035-0289>), Jon Clayden [rev] (<https://orcid.org/0000-0002-6608-0619>)
Maintainer: Rory Nolan <rorynoolan@gmail.com>

Diff between ijtiff versions 2.2.4 dated 2020-11-09 and 2.2.5 dated 2021-01-14

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New package datapackage.r with initial version 1.3.2
Package: datapackage.r
Type: Package
Title: Data Package 'Frictionless Data'
Version: 1.3.2
Date: 2021-01-14
Authors@R: c(person("Kleanthis", "Koupidis", email = "koupidis.okfgr@gmail.com", role = c("aut", "cre")), person("Lazaros", "Ioannidis", email = "larjohn@gmail.com", role = "aut"), person("Charalampos", "Bratsas", email = "cbratsas@math.auth.gr", role = "aut"), person("Open Knowledge International", email = "info@okfn.org", role = "cph"))
Maintainer: Kleanthis Koupidis <koupidis.okfgr@gmail.com>
Description: Work with 'Frictionless Data Packages' (<https://specs.frictionlessdata.io//data-package/>). Allows to load and validate any descriptor for a data package profile, create and modify descriptors and provides expose methods for reading and streaming data in the package. When a descriptor is a 'Tabular Data Package', it uses the 'Table Schema' package (<https://CRAN.R-project.org/package=tableschema.r>) and exposes its functionality, for each resource object in the resources field.
URL: https://github.com/frictionlessdata/datapackage-r
License: MIT + file LICENSE
BugReports: https://github.com/frictionlessdata/datapackage-r/issues
Encoding: UTF-8
LazyData: true
Imports: config, future, httr, iterators, jsonlite, jsonvalidate, purrr, R6, R.utils, readr, rlist, stringr, tableschema.r, tools, urltools, utils, V8
Suggests: covr, curl, data.table, DBI, devtools, foreach, httptest, knitr, rmarkdown, RSQLite, testthat
Collate: 'DataPackageError.R' 'Package.R' 'helpers.R' 'profile.R' 'binary.readable.connection.r' 'binary.readable.r' 'datapackage.r.R' 'infer.R' 'is.valid.R' 'resource.R' 'validate.R'
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-14 15:55:28 UTC; akis_
Author: Kleanthis Koupidis [aut, cre], Lazaros Ioannidis [aut], Charalampos Bratsas [aut], Open Knowledge International [cph]
Repository: CRAN
Date/Publication: 2021-01-14 22:10:11 UTC

More information about datapackage.r at CRAN
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Package coefplot updated to version 1.2.7 with previous version 1.2.6 dated 2018-02-07

Title: Plots Coefficients from Fitted Models
Description: Plots the coefficients from model objects. This very quickly shows the user the point estimates and confidence intervals for fitted models.
Author: Jared P. Lander
Maintainer: Jared P. Lander <packages@jaredlander.com>

Diff between coefplot versions 1.2.6 dated 2018-02-07 and 1.2.7 dated 2021-01-14

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Package pool updated to version 0.1.6 with previous version 0.1.5 dated 2020-11-03

Title: Object Pooling
Description: Enables the creation of object pools, which make it less computationally expensive to fetch a new object. Currently the only supported pooled objects are 'DBI' connections.
Author: Joe Cheng [aut, cre], Barbara Borges [aut], RStudio [cph]
Maintainer: Joe Cheng <joe@rstudio.com>

Diff between pool versions 0.1.5 dated 2020-11-03 and 0.1.6 dated 2021-01-14

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Package NPBayesImputeCat updated to version 0.3 with previous version 0.2 dated 2019-11-08

Title: Non-Parametric Bayesian Multiple Imputation for Categorical Data
Description: These routines create multiple imputations of missing at random categorical data, and create multiply imputed synthesis of categorical data, with or without structural zeros. Imputations and syntheses are based on Dirichlet process mixtures of multinomial distributions, which is a non-parametric Bayesian modeling approach that allows for flexible joint modeling, described in Manrique-Vallier and Reiter (2014) <doi:10.1080/10618600.2013.844700>.
Author: Quanli Wang, Daniel Manrique-Vallier, Jerome P. Reiter and Jingchen Hu
Maintainer: Jingchen Hu <jingchen.monika.hu@gmail.com>

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Permanent link

Package krippendorffsalpha updated to version 1.1 with previous version 1.0 dated 2020-06-04

Title: Measuring Agreement Using Krippendorff's Alpha Coefficient
Description: Provides tools for applying Krippendorff's Alpha methodology <DOI:10.1080/19312450709336664>. The framework supports common and user-defined distance functions, and can accommodate any number of units, any number of coders, and missingness. Bootstrap inference is permitted, and the computation can be done in parallel.
Author: John Hughes
Maintainer: John Hughes <drjphughesjr@gmail.com>

Diff between krippendorffsalpha versions 1.0 dated 2020-06-04 and 1.1 dated 2021-01-14

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 NAMESPACE                           |    6 +
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Permanent link

Package insight updated to version 0.12.0 with previous version 0.11.1 dated 2020-12-08

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>, @strengejacke), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>), Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Mattan S. Ben-Shachar [aut, ctb] (<https://orcid.org/0000-0002-4287-4801>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between insight versions 0.11.1 dated 2020-12-08 and 0.12.0 dated 2021-01-14

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More information about insight at CRAN
Permanent link

Package incase updated to version 0.2.1 with previous version 0.2.0 dated 2020-12-17

Title: Pipe-Friendly Vector Replacement with Case Statements
Description: Offers a pipe-friendly alternative to the 'dplyr' functions case_when() and if_else(). 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 possible outputs to the same type, meaning you no longer have to worry about using specific typed variants of NA or explicitly declaring integer outputs.
Author: Alexander Rossell Hayes [aut, cre, cph] (<https://orcid.org/0000-0001-9412-0457>)
Maintainer: Alexander Rossell Hayes <alexander@rossellhayes.com>

Diff between incase versions 0.2.0 dated 2020-12-17 and 0.2.1 dated 2021-01-14

 DESCRIPTION                   |    8 ++++----
 MD5                           |   20 ++++++++++----------
 NEWS.md                       |    5 +++++
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 R/in_case.R                   |    2 +-
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More information about incase at CRAN
Permanent link

Package apsimx updated to version 1.971 with previous version 1.964 dated 2020-10-16

Title: Inspect, Read, Edit and Run 'APSIM' "Next Generation" and 'APSIM' Classic
Description: The functions in this package inspect, read, edit and run files for 'APSIM' "Next Generation" ('JSON') and 'APSIM' "Classic" ('XML'). The files with an 'apsim' extension correspond to 'APSIM' Classic (7.x) - Windows only - and the ones with an 'apsimx' extension correspond to 'APSIM' "Next Generation". For more information about 'APSIM' see (<https://www.apsim.info/>) and for 'APSIM' next generation (<https://apsimnextgeneration.netlify.app/>).
Author: Fernando Miguez [aut, cre] (<https://orcid.org/0000-0002-4627-8329>)
Maintainer: Fernando Miguez <femiguez@iastate.edu>

Diff between apsimx versions 1.964 dated 2020-10-16 and 1.971 dated 2021-01-14

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More information about apsimx at CRAN
Permanent link

Package RTaxometrics updated to version 3.1 with previous version 3.0 dated 2020-11-01

Title: Taxometric Analysis
Description: We provide functions to perform taxometric analyses. This package contains 44 functions, but only 5 should be called directly by users. CheckData() should be run prior to any taxometric analysis to ensure that the data are appropriate for taxometric analysis. RunTaxometrics() performs taxometric analyses for a sample of data. RunCCFIProfile() performs a series of taxometric analyses to generate a CCFI profile. CreateData() generates a sample of categorical or dimensional data. ClassifyCases() assigns cases to groups using the base-rate classification method.
Author: John Ruscio <ruscio@tcnj.edu> and Shirley Wang <shirleywang@g.harvard.edu>
Maintainer: John Ruscio <ruscio@tcnj.edu>

Diff between RTaxometrics versions 3.0 dated 2020-11-01 and 3.1 dated 2021-01-14

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More information about RTaxometrics at CRAN
Permanent link

Package qualtRics updated to version 3.1.4 with previous version 3.1.3 dated 2020-05-22

Title: Download 'Qualtrics' Survey Data
Description: Provides functions to access survey results directly into R using the 'Qualtrics' API. 'Qualtrics' <https://www.qualtrics.com/about/> is an online survey and data collection software platform. See <https://api.qualtrics.com/> for more information about the 'Qualtrics' API. This package is community-maintained and is not officially supported by 'Qualtrics'.
Author: Jasper Ginn [aut], Jackson Curtis [ctb], Shaun Jackson [ctb], Samuel Kaminsky [ctb], Eric Knudsen [ctb], Joseph O'Brien [ctb], Daniel Seneca [ctb], Julia Silge [aut, cre] (<https://orcid.org/0000-0002-3671-836X>), Phoebe Wong [ctb]
Maintainer: Julia Silge <julia.silge@gmail.com>

Diff between qualtRics versions 3.1.3 dated 2020-05-22 and 3.1.4 dated 2021-01-14

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More information about qualtRics at CRAN
Permanent link

Package KarsTS updated to version 2.4.1 with previous version 2.4 dated 2020-12-15

Title: An Interface for Microclimate Time Series Analysis
Description: An R code with a GUI for microclimate time series, with an emphasis on underground environments. 'KarsTS' provides linear and nonlinear methods, including recurrence analysis (Marwan et al. (2007) <doi:10.1016/j.physrep.2006.11.001>) and filling methods (Moffat et al. (2007) <doi:10.1016/j.agrformet.2007.08.011>), as well as tools to manipulate easily time series and gap sets.
Author: Marina Saez [aut, cre], David Benavente [ths], Soledad Cuezva [ths], Concepcion Pla [ctb]
Maintainer: Marina Saez <marinasaez_andreu@hotmail.com>

Diff between KarsTS versions 2.4 dated 2020-12-15 and 2.4.1 dated 2021-01-14

 DESCRIPTION                      |   14 
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More information about KarsTS at CRAN
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Package groundhog updated to version 1.2.0 with previous version 1.1.0 dated 2021-01-04

Title: Reproducible Scripts via Version-Specific Package Loading
Description: Make R scripts that rely on packages reproducible, by ensuring that every time a given script is run, the same version of the used packages are loaded (instead of whichever version the user running the script happens to have installed). This is achieved by using the new command groundhog.library() instead of the base command library(), and including a date in the call. The date is used to call on the same version of the package every time (the most recent version available on CRAN at that date).
Author: Uri Simonsohn [aut, cre] (<https://orcid.org/0000-0002-8601-7211>), Hugo Gruson [ctb, aut] (<https://orcid.org/0000-0002-4094-1476>)
Maintainer: Uri Simonsohn <urisohn@gmail.com>

Diff between groundhog versions 1.1.0 dated 2021-01-04 and 1.2.0 dated 2021-01-14

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Package DDD updated to version 4.4.1 with previous version 4.4 dated 2020-06-02

Title: Diversity-Dependent Diversification
Description: Implements maximum likelihood and bootstrap methods based on the diversity-dependent birth-death process to test whether speciation or extinction are diversity-dependent, under various models including various types of key innovations. See Etienne et al. 2012, Proc. Roy. Soc. B 279: 1300-1309, <DOI:10.1098/rspb.2011.1439>, Etienne & Haegeman 2012, Am. Nat. 180: E75-E89, <DOI:10.1086/667574> and Etienne et al. 2016. Meth. Ecol. Evol. 7: 1092-1099, <DOI:10.1111/2041-210X.12565>. Also contains functions to simulate the diversity-dependent process.
Author: Rampal S. Etienne & Bart Haegeman
Maintainer: Rampal S. Etienne <r.s.etienne@rug.nl>

Diff between DDD versions 4.4 dated 2020-06-02 and 4.4.1 dated 2021-01-14

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Package NACHO updated to version 1.1.0 with previous version 1.0.2 dated 2021-01-05

Title: NanoString Quality Control Dashboard
Description: NanoString nCounter data are gene expression assays where there is no need for the use of enzymes or amplification protocols and work with fluorescent barcodes (Geiss et al. (2018) <doi:10.1038/nbt1385>). Each barcode is assigned a messenger-RNA/micro-RNA (mRNA/miRNA) which after bonding with its target can be counted. As a result each count of a specific barcode represents the presence of its target mRNA/miRNA. 'NACHO' (NAnoString quality Control dasHbOard) is able to analyse the exported NanoString nCounter data and facilitates the user in performing a quality control. 'NACHO' does this by visualising quality control metrics, expression of control genes, principal components and sample specific size factors in an interactive web application.
Author: Mickaël Canouil [aut, cre] (<https://orcid.org/0000-0002-3396-4549>), Roderick Slieker [aut] (<https://orcid.org/0000-0003-0961-9152>), Gerard Bouland [aut]
Maintainer: Mickaël Canouil <mickael.canouil@cnrs.fr>

Diff between NACHO versions 1.0.2 dated 2021-01-05 and 1.1.0 dated 2021-01-14

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Package customLayout updated to version 0.3.2 with previous version 0.3.1 dated 2020-01-17

Title: Arrange Elements on the R's Drawing Area or Inside the PowerPoint's Slide
Description: Create complicated drawing areas for multiple elements by combining much simpler layouts. It is an extended version of layout function from the 'graphics' package, but it also works with 'grid' graphics. It also supports arranging elements inside 'PowerPoint' slides created using the 'officer' package.
Author: Zygmunt Zawadzki [aut, cre]
Maintainer: Zygmunt Zawadzki <zygmunt@zstat.pl>

Diff between customLayout versions 0.3.1 dated 2020-01-17 and 0.3.2 dated 2021-01-14

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Package FSelectorRcpp updated to version 0.3.8 with previous version 0.3.7 dated 2020-10-08

Title: 'Rcpp' Implementation of 'FSelector' Entropy-Based Feature Selection Algorithms with a Sparse Matrix Support
Description: 'Rcpp' (free of 'Java'/'Weka') implementation of 'FSelector' entropy-based feature selection algorithms based on an MDL discretization (Fayyad U. M., Irani K. B.: Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning. In 13'th International Joint Conference on Uncertainly in Artificial Intelligence (IJCAI93), pages 1022-1029, Chambery, France, 1993.) <https://www.ijcai.org/Proceedings/93-2/Papers/022.pdf> with a sparse matrix support.
Author: Zygmunt Zawadzki [aut, cre], Marcin Kosinski [aut], Krzysztof Slomczynski [ctb], Damian Skrzypiec [ctb], Patrick Schratz [ctb] (<https://orcid.org/0000-0003-0748-6624>)
Maintainer: Zygmunt Zawadzki <zygmunt@zstat.pl>

Diff between FSelectorRcpp versions 0.3.7 dated 2020-10-08 and 0.3.8 dated 2021-01-14

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Package hddtools updated to version 0.9.3 with previous version 0.9.1 dated 2020-05-25

Title: Hydrological Data Discovery Tools
Description: Tools to discover hydrological data, accessing catalogues and databases from various data providers.
Author: Claudia Vitolo [aut, cre] (<https://orcid.org/0000-0002-4252-1176>), Wouter Buytaert [ctb] (Supervisor), Erin Le Dell [ctb] (Erin reviewed the package for rOpenSci, see https://github.com/ropensci/software-review/issues/73), Michael Sumner [ctb] (Michael reviewed the package for rOpenSci, see https://github.com/ropensci/software-review/issues/73)
Maintainer: Claudia Vitolo <cvitolodev@gmail.com>

Diff between hddtools versions 0.9.1 dated 2020-05-25 and 0.9.3 dated 2021-01-14

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Package altair updated to version 4.1.1 with previous version 4.0.1 dated 2020-01-23

Title: Interface to 'Altair'
Description: Interface to 'Altair' <https://altair-viz.github.io>, which itself is a 'Python' interface to 'Vega-Lite' <https://vega.github.io/vega-lite/>. This package uses the 'Reticulate' framework <https://rstudio.github.io/reticulate/> to manage the interface between R and 'Python'.
Author: Ian Lyttle [aut, cre] (<https://orcid.org/0000-0001-9962-4849>), Haley Jeppson [aut], Altair Developers [aut], Alicia Schep [ctb] (<https://orcid.org/0000-0002-3915-0618>), Jake Vanderplas [ctb] (Altair library), Brian Granger [ctb] (Altair library)
Maintainer: Ian Lyttle <ian.lyttle@se.com>

Diff between altair versions 4.0.1 dated 2020-01-23 and 4.1.1 dated 2021-01-14

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Package Xplortext updated to version 1.4.1 with previous version 1.3.2 dated 2020-05-09

Title: Statistical Analysis of Textual Data
Description: Provides a set of functions devoted to multivariate exploratory statistics on textual data. Classical methods such as correspondence analysis and agglomerative hierarchical clustering are available. Chronologically constrained agglomerative hierarchical clustering enriched with labelled-by-words trees is offered. Given a division of the corpus into parts, their characteristic words and documents are identified. Further, accessing to 'FactoMineR' functions is very easy. Two of them are relevant in textual domain. MFA() addresses multiple lexical table allowing applications such as dealing with multilingual corpora as well as simultaneously analyzing both open-ended and closed questions in surveys. See <http://xplortext.unileon.es> for examples.
Author: Mónica Bécue-Bertaut, Ramón Alvarez-Esteban, Josep-Anton Sánchez-Espigares, Belchin Kostov
Maintainer: Ramón Alvarez-Esteban <ramon.alvarez@unileon.es>

Diff between Xplortext versions 1.3.2 dated 2020-05-09 and 1.4.1 dated 2021-01-14

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New package seasonalclumped with initial version 0.3.2
Package: seasonalclumped
Title: Toolbox for Clumped Isotope Seasonality Reconstructions
Version: 0.3.2
Authors@R: person(given = "Niels", family = "de Winter", role = c("aut", "cre"), email = "niels_de_winter@live.nl", comment = c(ORCID = "0000-0002-1453-5407"))
Description: Compiles a set of functions and dummy data that simplify reconstructions of seasonal temperature variability in the geological past from stable isotope and clumped isotope records in sub–annually resolved carbonate archives (e.g. mollusk shells, corals and speleothems). For more information, see de Winter et al., 2020 (Climate of the Past Discussions, <doi:10.5194/cp-2020-118>).
Imports: ggplot2, gridExtra, TTR, magrittr
License: GPL-3
URL: https://github.com/nielsjdewinter/seasonalclumped
BugReports: https://github.com/nielsjdewinter/seasonalclumped/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2021-01-11 17:17:54 UTC; Convernaum
Author: Niels de Winter [aut, cre] (<https://orcid.org/0000-0002-1453-5407>)
Maintainer: Niels de Winter <niels_de_winter@live.nl>
Repository: CRAN
Date/Publication: 2021-01-14 10:20:02 UTC

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New package remap with initial version 0.2.0
Package: remap
Type: Package
Title: Regional Spatial Modeling with Continuous Borders
Version: 0.2.0
Authors@R: person("Jadon", "Wagstaff", email = "jadonw@gmail.com", role = c("aut", "cre"))
Description: Automatically creates separate regression models for different spatial regions. The prediction surface is smoothed using a novel method developed by the package creator. If regional models are continuous, the resulting prediction surface is continuous across the spatial dimensions, even at region borders.
License: GPL-3
URL: https://github.com/jadonwagstaff/remap
BugReports: https://github.com/jadonwagstaff/remap/issues
Encoding: UTF-8
LazyData: true
Imports: graphics (>= 3.6.0), parallel (>= 3.6.0), sf (>= 0.9.6), stats (>= 3.6.0), units (>= 0.6.7), utils (>= 3.6.0)
RoxygenNote: 7.1.1
Suggests: dplyr (>= 1.0.2), ggplot2 (>= 3.3.2), knitr (>= 1.30), lwgeom (>= 0.2.5), magrittr (>= 2.0.1), maps (>= 3.3.0), mgcv (>= 1.8.33), rmarkdown (>= 2.5), tibble (>= 3.0.4)
VignetteBuilder: knitr
Depends: R (>= 3.6.0)
NeedsCompilation: no
Packaged: 2021-01-11 17:29:49 UTC; Jadon
Author: Jadon Wagstaff [aut, cre]
Maintainer: Jadon Wagstaff <jadonw@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-14 10:30:02 UTC

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New package VAM with initial version 0.4.0
Package: VAM
Type: Package
Title: Variance-Adjusted Mahalanobis
Version: 0.4.0
Author: H. Robert Frost
Maintainer: H. Robert Frost <rob.frost@dartmouth.edu>
Description: Contains logic for cell-specific gene set scoring of single cell RNA sequencing data.
Depends: R (>= 3.6.0), MASS, Matrix
Suggests: Seurat (>= 3.1.4)
License: GPL (>= 2)
Copyright: Dartmouth College
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-01-11 14:14:17 UTC; robfrost
Repository: CRAN
Date/Publication: 2021-01-14 09:30:05 UTC

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New package tabnet with initial version 0.1.0
Package: tabnet
Title: Fit 'TabNet' Models for Classification and Regression
Version: 0.1.0
Authors@R: c( person(given = "Daniel", family = "Falbel", role = c("aut", "cre"), email = "daniel@rstudio.com"), person(family = "RStudio", role = c("cph")) )
Description: Implements the 'TabNet' model by Sercan O. Arik et al (2019) <arXiv:1908.07442> and provides a consistent interface for fitting and creating predictions. It's also fully compatible with the 'tidymodels' ecosystem.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: torch, hardhat, magrittr, glue, progress, rlang, methods, tibble, vctrs
Suggests: testthat, modeldata, recipes, parsnip, dials, withr, knitr, rmarkdown, vip, tidyverse
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-11 13:47:17 UTC; dfalbel
Author: Daniel Falbel [aut, cre], RStudio [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>
Repository: CRAN
Date/Publication: 2021-01-14 09:30:02 UTC

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New package sisireg with initial version 0.7.0
Package: sisireg
Title: Sign-Simplicity-Regression-Solver
Version: 0.7.0
Authors@R: person(given = "Lars", family = "Metzner", role = c("aut", "cre"), email = "lars.metzner@ppi.de")
Description: Implementation of the SSR-Algorithm. The Sign-Simplicity-Regression model is a nonparametric statistical model which is based on residual signs and simplicity assumptions on the regression function. Goal is to calculate the most parsimonious regression function satisfying the statistical adequacy requirements. Theory and functions are specified in Metzner (2020, ISBN: 9798682394203, "Trendbasierte Prognostik") and Metzner (2021, ISBN: 9798593470270, "Adäquates Maschinelles Lernen").
License: GPL (>= 2)
Encoding: UTF-8
Imports: zoo, raster
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-11 13:31:57 UTC; lme
Author: Lars Metzner [aut, cre]
Maintainer: Lars Metzner <lars.metzner@ppi.de>
Repository: CRAN
Date/Publication: 2021-01-14 09:40:02 UTC

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New package shinyRadioMatrix with initial version 0.2.0
Package: shinyRadioMatrix
Type: Package
Title: Create a Matrix with Radio Buttons
Version: 0.2.0
Authors@R: c(person("Zsolt", "Szelepcsényi", email = "szelepcsenyi.zsolt@gmail.com", role = c("aut", "cre")), person("Zoltán", "Szelepcsényi", email = "szelepcsenyi.zoltan@gmail.com", role = "aut"))
Maintainer: Zsolt Szelepcsényi <szelepcsenyi.zsolt@gmail.com>
Description: An input controller for R Shiny: a matrix with radio buttons, where only one option per row can be selected.
Imports: shiny
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-01-11 16:35:29 UTC; evista
Author: Zsolt Szelepcsényi [aut, cre], Zoltán Szelepcsényi [aut]
Repository: CRAN
Date/Publication: 2021-01-14 10:00:02 UTC

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Package NPP updated to version 0.3.0 with previous version 0.2.0 dated 2019-08-21

Title: Normalized Power Prior Bayesian Analysis
Description: Posterior sampling in several commonly used distributions using normalized power prior as described in Duan, Ye and Smith (2006) <doi:10.1002/env.752> and Ibrahim et.al. (2015) <doi:10.1002/sim.6728>. Sampling of the power parameter is achieved via either independence Metropolis-Hastings or random walk Metropolis-Hastings based on transformation.
Author: Zifei Han, Tianyu Bai and Keying Ye
Maintainer: Zifei Han <hanzifei1@gmail.com>

Diff between NPP versions 0.2.0 dated 2019-08-21 and 0.3.0 dated 2021-01-14

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New package mecor with initial version 0.9.0
Package: mecor
Type: Package
Title: Measurement Error Correction in Linear Models with a Continuous Outcome
Version: 0.9.0
Author: Linda Nab
Maintainer: Linda Nab <lindanab4@gmail.com>
Description: Covariate measurement error correction is implemented by means of regression calibration by Carroll RJ, Ruppert D, Stefanski LA & Crainiceanu CM (2006, ISBN:1584886331), efficient regression calibration by Spiegelman D, Carroll RJ & Kipnis V (2001) <doi:10.1002/1097-0258(20010115)20:1%3C139::AID-SIM644%3E3.0.CO;2-K> and maximum likelihood estimation by Bartlett JW, Stavola DBL & Frost C (2009) <doi:10.1002/sim.3713>. Outcome measurement error correction is implemented by means of the method of moments by Buonaccorsi JP (2010, ISBN:1420066560) and efficient method of moments by Keogh RH, Carroll RJ, Tooze JA, Kirkpatrick SI & Freedman LS (2014) <doi:10.1002/sim.7011>. Standard error estimation of the corrected estimators is implemented by means of the Delta method by Rosner B, Spiegelman D & Willett WC (1990) <doi:10.1093/oxfordjournals.aje.a115715> and Rosner B, Spiegelman D & Willett WC (1992) <doi:10.1093/oxfordjournals.aje.a116453>, the Fieller method described by Buonaccorsi JP (2010, ISBN:1420066560), and the Bootstrap by Carroll RJ, Ruppert D, Stefanski LA & Crainiceanu CM (2006, ISBN:1584886331).
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/LindaNab/mecor
Imports: lme4, lmerTest, numDeriv
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-11 09:35:55 UTC; lindanab
Repository: CRAN
Date/Publication: 2021-01-14 09:20:02 UTC

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New package MARSANNhybrid with initial version 0.1.0
Package: MARSANNhybrid
Type: Package
Title: MARS Based ANN Hybrid Model
Version: 0.1.0
Authors@R: c(person("Pankaj", "Das", role = c("aut","cre"),email="pankaj.das2@icar.gov.in"),person("Achal", "Lama", role = "aut",email="achal.lama@icar.gov.in"), person("Girish Kumar", "Jha", role = "aut",email="grish.stat@gmail.com"))
Author: Pankaj Das [aut, cre], Achal Lama [aut], Girish Kumar Jha [aut]
Maintainer: Pankaj Das <pankaj.das2@icar.gov.in>
Depends: R (>= 3.3.0),neuralnet,earth,stats
Description: Multivariate Adaptive Regression Spline (MARS) based Artificial Neural Network (ANN) hybrid model is combined Machine learning hybrid approach which selects important variables using MARS and then fits ANN on the extracted important variables.
Encoding: UTF-8
LazyData: true
License: GPL-3
NeedsCompilation: no
Packaged: 2021-01-11 10:45:22 UTC; USER
Repository: CRAN
Date/Publication: 2021-01-14 09:40:11 UTC

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Package KFAS updated to version 1.4.2 with previous version 1.4.1 dated 2020-12-08

Title: Kalman Filter and Smoother for Exponential Family State Space Models
Description: State space modelling is an efficient and flexible framework for statistical inference of a broad class of time series and other data. KFAS includes computationally efficient functions for Kalman filtering, smoothing, forecasting, and simulation of multivariate exponential family state space models, with observations from Gaussian, Poisson, binomial, negative binomial, and gamma distributions. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details.
Author: Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>)
Maintainer: Jouni Helske <jouni.helske@iki.fi>

Diff between KFAS versions 1.4.1 dated 2020-12-08 and 1.4.2 dated 2021-01-14

 ChangeLog             |    8 ++
 DESCRIPTION           |    9 +-
 MD5                   |   52 ++++++++--------
 NAMESPACE             |  156 +++++++++++++++++++++++++-------------------------
 R/KFAS-package.R      |  129 +++++++++++++++++++++++++++++++----------
 R/KFS.R               |   26 +++++---
 R/approxSSM.R         |    8 +-
 R/fitSSM.R            |    5 +
 R/importanceSSM.R     |   13 ++--
 R/logLik.SSModel.R    |   37 ++++++++---
 inst/doc/KFAS.pdf     |binary
 man/GlobalTemp.Rd     |   23 +++++++
 man/KFAS.Rd           |  100 +++++++++++++++++++++++---------
 man/KFS.Rd            |   15 ++++
 man/alcohol.Rd        |    1 
 man/approxSSM.Rd      |   12 +++
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 man/fitSSM.Rd         |    5 +
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 src/approx.f95        |   11 +++
 src/init.c            |   12 +--
 src/isample.f95       |    8 +-
 src/isamplefilter.f95 |    6 +
 src/ngfilter.f95      |    7 +-
 src/ngloglik.f95      |   12 +--
 src/ngsmooth.f95      |   13 +---
 27 files changed, 450 insertions(+), 235 deletions(-)

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New package log with initial version 1.1.0
Package: log
Title: Record Events and Issues
Version: 1.1.0
Authors@R: c( person(given = "John", family = "Coene", role = c("aut", "cre"), email = "john@opifex.org"), person(family = "Opifex", role = c("cph"), email = "john@opifex.org") )
Description: Logger to keep track of informational events and errors useful for debugging.
License: AGPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1.9000
Imports: R6, cli, crayon
Suggests: shiny, plumber, testthat (>= 3.0.0), covr
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2021-01-10 22:11:22 UTC; jp
Author: John Coene [aut, cre], Opifex [cph]
Maintainer: John Coene <john@opifex.org>
Repository: CRAN
Date/Publication: 2021-01-14 09:10:02 UTC

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New package ICSsmoothing with initial version 1.2.5
Package: ICSsmoothing
Type: Package
Title: Data Smoothing by Interpolating Cubic Splines
Version: 1.2.5
Authors@R: c( person("Juraj", "Hudak", role = c("aut")), person("Viliam", "Kacala", email = "viliam.kacala.ml@gmail.com", role = c("cre")), person("Csaba", "Torok", email = "csaba.torok@upjs.sk", role = c("ctb")))
Description: We construct the explicit form of clamped cubic interpolating spline (both uniform - knots are equidistant and non-uniform - knots are arbitrary). Using this form, we propose a linear regression model suitable for real data smoothing. This package is based on a diploma thesis Hudak (2017) <https://opac.crzp.sk/?fn=detailBiblioForm&sid=7FE4E0810F66E41DF9A9CA23557F&seo=CRZP-detail-kniha>.
Depends: R (>= 3.5.0), polynom, ggplot2
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-11 07:59:46 UTC; vildibald
Author: Juraj Hudak [aut], Viliam Kacala [cre], Csaba Torok [ctb]
Maintainer: Viliam Kacala <viliam.kacala.ml@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-14 09:10:09 UTC

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Package HelpersMG updated to version 4.4 with previous version 4.3 dated 2020-08-12

Title: Tools for Environmental Analyses, Ecotoxicology and Various R Functions
Description: Contains miscellaneous functions useful for managing 'NetCDF' files (see <https://en.wikipedia.org/wiki/NetCDF>), get moon phase and time for sun rise and fall, analyse and reconstruct periodic time series of temperature with irregular sinusoidal pattern, show scales and wind rose in plot with change of color of text, Metropolis-Hastings algorithm for Bayesian MCMC analysis, plot graphs or boxplot with error bars, search files in disk by there names or their content, read the contents of all files from a folder at one time.
Author: Marc Girondot
Maintainer: Marc Girondot <marc.girondot@u-psud.fr>

Diff between HelpersMG versions 4.3 dated 2020-08-12 and 4.4 dated 2021-01-14

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 HelpersMG-4.4/HelpersMG/R/MHalgoGen.R                  |   50 ++++--
 HelpersMG-4.4/HelpersMG/R/RandomFromHessianOrMCMC.R    |  139 +++++++++++++----
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 HelpersMG-4.4/HelpersMG/R/nlConfint.R                  |    6 
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New package ggOceanMaps with initial version 1.0.9
Package: ggOceanMaps
Type: Package
Title: Plot Data on Oceanographic Maps using 'ggplot2'
Version: 1.0.9
Date: 2021-01-08
Authors@R: c(person("Mikko", "Vihtakari", email = "mikko.vihtakari@hi.no", role = c("aut", "cre"), comment = c(affiliation = "Institute of Marine Research", ORCID = "0000-0003-0371-4319")), person("Hadley", "Wickham", role = "ctb"), person("Simon", "O'Hanlon", role = "ctb"), person("Roger", "Bivand", role = "ctb") )
URL: https://mikkovihtakari.github.io/ggOceanMaps/
BugReports: https://github.com/MikkoVihtakari/ggOceanMaps/issues
Description: Allows plotting data on bathymetric maps using 'ggplot2'. Plotting oceanographic spatial data is made as simple as feasible, but also flexible for custom modifications. Data that contain geographic information from anywhere around the globe can be plotted on maps generated by the basemap() function using 'ggplot2' layers separated by the '+' operator. The package uses spatial shapefiles stored in the 'ggOceanMapsData' package, geospatial packages for R to manipulate, and the 'ggspatial' package to help to plot these shapefiles.
Depends: R (>= 3.5.0), ggplot2, ggspatial
Imports: sp, raster, rgdal, rgeos, methods, utils, sf, stars, smoothr, units, dplyr, parallel
Suggests: ggOceanMapsData, cowplot, knitr, rmarkdown, scales
Additional_repositories: https://mikkovihtakari.github.io/drat
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-11 10:25:24 UTC; a22357
Author: Mikko Vihtakari [aut, cre] (Institute of Marine Research, <https://orcid.org/0000-0003-0371-4319>), Hadley Wickham [ctb], Simon O'Hanlon [ctb], Roger Bivand [ctb]
Maintainer: Mikko Vihtakari <mikko.vihtakari@hi.no>
Repository: CRAN
Date/Publication: 2021-01-14 09:40:05 UTC

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Package GET updated to version 0.2-2 with previous version 0.2-1 dated 2020-12-12

Title: Global Envelopes
Description: Implementation of global envelopes for a set of general d-dimensional vectors T in various applications. A 100(1-alpha)% global envelope is a band bounded by two vectors such that the probability that T falls outside this envelope in any of the d points is equal to alpha. Global means that the probability is controlled simultaneously for all the d elements of the vectors. The global envelopes can be used for graphical Monte Carlo and permutation tests where the test statistic is a multivariate vector or function (e.g. goodness-of-fit testing for point patterns and random sets, functional analysis of variance, functional general linear model, n-sample test of correspondence of distribution functions), for central regions of functional or multivariate data (e.g. outlier detection, functional boxplot) and for global confidence and prediction bands (e.g. confidence band in polynomial regression, Bayesian posterior prediction). See Myllymäki and Mrkvička (2020) <arXiv:1911.06583>, Myllymäki et al. (2017) <doi: 10.1111/rssb.12172>, Mrkvička et al. (2017) <doi: 10.1007/s11222-016-9683-9>, Mrkvička et al. (2020) <doi: 10.14736/kyb-2020-3-0432>, Mrkvička et al. (2019) <doi: 10.1007/s11009-019-09756-y>, Mrkvička et al. (2019) <arXiv:1902.04926>, Mrkvička et al. (2016) <doi: 10.1016/j.spasta.2016.04.005>, and Myllymäki et al. (2020) <doi: 10.1016/j.spasta.2020.100436>.
Author: Mari Myllymäki [aut, cre], Tomáš Mrkvička [aut], Pavel Grabarnik [ctb], Ute Hahn [ctb], Mikko Kuronen [ctb], Michael Rost [ctb], Henri Seijo [ctb]
Maintainer: Mari Myllymäki <mari.myllymaki@luke.fi>

Diff between GET versions 0.2-1 dated 2020-12-12 and 0.2-2 dated 2021-01-14

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 GET-0.2-2/GET/R/deviation_test.r                                      |    4 
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 GET-0.2-2/GET/R/envelopes2d.r                                         |   26 +
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 GET-0.2-2/GET/R/forder.r                                              |   18 -
 GET-0.2-2/GET/R/glm.R                                                 |   71 ++---
 GET-0.2-2/GET/R/graphfanova.r                                         |   46 +--
 GET-0.2-2/GET/R/imageset3.r                                           |    4 
 GET-0.2-2/GET/R/plot_envelope_helper.R                                |    2 
 GET-0.2-2/GET/R/saplings.r                                            |   34 +-
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New package faviconPlease with initial version 0.1.1
Package: faviconPlease
Title: Find the URL to the 'Favicon' for a Website
Version: 0.1.1
Authors@R: person(given = "John", family = "Blischak", role = c("aut", "cre"), email = "jdblischak@gmail.com")
Description: Finds the URL to the 'favicon' for a website. This is useful if you want to display the 'favicon' in an HTML document or web application, especially if the website is behind a firewall.
URL: https://github.com/jdblischak/faviconPlease
BugReports: https://github.com/jdblischak/faviconPlease/issues
Imports: utils, xml2
Suggests: httr, tinytest, ttdo
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-11 15:12:22 UTC; jdblischak
Author: John Blischak [aut, cre]
Maintainer: John Blischak <jdblischak@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-14 09:40:08 UTC

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New package eCAR with initial version 0.1.0
Package: eCAR
Type: Package
Title: Eigenvalue CAR Models
Version: 0.1.0
Authors@R: c( person(given = "Garritt", family = "L. Page", email = "page@stat.byu.edu", role = c("aut", "cre")), person(given = "Massimo", family = "Ventrucci", email = "massimo.ventrucci@unibo.it", role = c("aut")), person(given = "S. McKay", family = "Curtis", email = "s.mckay.curtis@gmail.com", role = c("cph")), person(given = "Radford", family = "M. Neal", role = c("cph")))
Maintainer: Garritt L. Page <page@stat.byu.edu>
Description: Fits Leroux model in spectral domain to estimate causal spatial effect as detailed in Guan, Y; Page, G.L.; Reich, B.J.; Ventrucci, M.; Yang, S; (2020) <arXiv:2012.11767>. Both the parametric and semi-parametric models are available. The semi-parametric model relies on 'INLA'. The 'INLA' package can be obtained from <https://www.r-inla.org/>.
License: GPL
Encoding: UTF-8
Depends: R (>= 3.5.0)
Suggests: INLA
Imports: Matrix
LazyData: true
RoxygenNote: 7.1.1
Additional_repositories: https://inla.r-inla-download.org/R/stable/
URL: https://github.com/gpage2990/eCAR
NeedsCompilation: yes
Packaged: 2021-01-11 15:30:29 UTC; gpage
Author: Garritt L. Page [aut, cre], Massimo Ventrucci [aut], S. McKay Curtis [cph], Radford M. Neal [cph]
Repository: CRAN
Date/Publication: 2021-01-14 09:50:02 UTC

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New package DIFshiny with initial version 0.1.0
Package: DIFshiny
Type: Package
Title: Differential Item Functioning via Shiny Application
Version: 0.1.0
Author: Huseyin Yildiz [aut, cre]
Maintainer: Huseyin Yildiz <huseyinyildiz35@gmail.com>
Description: Differential Item Functioning (DIF) Analysis with shiny application interfaces. You can run the functions in this package without any arguments and perform your DIF analysis using user-friendly interfaces.
Depends: R (>= 3.4.0)
License: GPL-2
RoxygenNote: 7.1.1
Imports: shiny, shinydashboard, difR, stats, readxl
Encoding: UTF-8
LazyData: true
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-01-11 13:14:47 UTC; husey
Repository: CRAN
Date/Publication: 2021-01-14 09:20:06 UTC

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New package utilities with initial version 0.1.0
Package: utilities
Type: Package
Title: Data Utility Functions
Version: 0.1.0
Date: 2021-01-07
Authors@R: person("Ben", "O'Neill", email = "ben.oneill@hotmail.com", role = c("aut", "cre"))
Author: Ben O'Neill [aut, cre]
Maintainer: Ben O'Neill <ben.oneill@hotmail.com>
Description: Data utility functions for use in probability and statistics. Includes functions for computing higher-moments for samples and their decompositions. Also includes utilities to examine functional mappings between factor variables and other variables in a data set.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: stats
Suggests: ggplot2, ggdag
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-11 02:39:00 UTC; nfultz
Repository: CRAN
Date/Publication: 2021-01-14 08:30:02 UTC

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New package node2vec with initial version 0.1.0
Package: node2vec
Title: Algorithmic Framework for Representational Learning on Graphs
Version: 0.1.0
Authors@R: c( person(given = "Yang", family = "Tian", role = c("aut", "cre"), email = "tianyang1211@126.com"), person(given="Xu", family="Li", role="aut"), person(given="Jing", family="Ren", role="aut") )
Description: Given any graph, the 'node2vec' algorithm can learn continuous feature representations for the nodes, which can then be used for various downstream machine learning tasks.The techniques are detailed in the paper "node2vec: Scalable Feature Learning for Networks" by Aditya Grover, Jure Leskovec(2016),available at <arXiv:1607.00653>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Imports: data.table, igraph, word2vec, rlist, dplyr, vctrs, vegan
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-12-27 15:31:28 UTC; Administrator
Author: Yang Tian [aut, cre], Xu Li [aut], Jing Ren [aut]
Maintainer: Yang Tian <tianyang1211@126.com>
Repository: CRAN
Date/Publication: 2021-01-14 09:00:02 UTC

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New package EMDANNhybrid with initial version 0.1.0
Package: EMDANNhybrid
Type: Package
Title: Ensemble Machine Learning Hybrid Model
Version: 0.1.0
Authors@R: c(person("Pankaj", "Das", role = c("aut","cre"),email="pankaj.das2@icar.gov.in"),person("Achal", "Lama", role = "aut",email="achal.lama@icar.gov.in"), person("Girish", "Jha", role = "aut",email="grish.stat@gmail.com"))
Author: Pankaj Das [aut, cre], Achal Lama [aut], Girish Jha [aut]
Maintainer: Pankaj Das <pankaj.das2@icar.gov.in>
Depends: R (>= 3.3.0),EMD,nnfor,forecast
Description: The researchers can use this package to fit Empirical Mode Decomposition and Artificial Neural Network based hybrid model for nonlinear and non stationary time series data.
Encoding: UTF-8
LazyData: true
License: GPL-3
NeedsCompilation: no
Packaged: 2021-01-11 04:42:31 UTC; USER
Repository: CRAN
Date/Publication: 2021-01-14 08:30:05 UTC

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New package EEMDelm with initial version 0.1.0
Package: EEMDelm
Type: Package
Title: Ensemble Empirical Mode Decomposition and Its Variant Based ELM Model
Version: 0.1.0
Authors@R: c(person(given = "Girish Kumar", family = "Jha", role = c("aut", "cre"), email = "girish.stat@gmail.com"), person(given = "Kapil", family = "Choudhary", role = c("aut", "ctb")), person(given = "Rajeev Ranjan", family = "Kumar", role = "ctb"), person(given = "Ronit", family = "Jaiswal", role = "ctb"))
Maintainer: Girish Kumar Jha <girish.stat@gmail.com>
Description: Forecasting univariate time series with different decomposition based Extreme Learning Machine models. For method details see Yu L, Wang S, Lai KK (2008). <doi:10.1016/j.eneco.2008.05.003>, Parida M, Behera MK, Nayak N (2018). <doi:10.1109/ICSESP.2018.8376723>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: forecast, nnfor, Rlibeemd
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-01-09 06:58:46 UTC; Rajeev-PC
Author: Girish Kumar Jha [aut, cre], Kapil Choudhary [aut, ctb], Rajeev Ranjan Kumar [ctb], Ronit Jaiswal [ctb]
Repository: CRAN
Date/Publication: 2021-01-14 08:50:03 UTC

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New package bayesian with initial version 0.0.2
Package: bayesian
Type: Package
Version: 0.0.2
Title: Bindings for Bayesian TidyModels
Authors@R: c(person(given = "Hamada S.", family = "Badr", role = c("aut", "cre"), email = "badr@jhu.edu", comment = c(ORCID = "0000-0002-9808-2344")))
Description: Fit Bayesian models using 'brms'/'Stan' with 'parsnip'/'tidymodels'. 'tidymodels' is a collection of packages for machine learning, developed by Wickham (2020) <https://www.tidymodels.org>). The technical details of 'brms' and 'Stan' are described in Bürkner (2017) <doi:10.18637/jss.v080.i01>, Bürkner (2018) <doi:10.32614/RJ-2018-017>, and Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
License: MIT + file LICENSE
URL: https://hsbadr.github.io/bayesian/, https://github.com/hsbadr/bayesian
BugReports: https://github.com/hsbadr/bayesian/issues
Depends: brms (>= 2.14.4), parsnip (>= 0.1.4), R (>= 2.10)
Imports: dplyr, purrr, rlang, stats, tibble, utils
Suggests: covr, devtools, knitr, rmarkdown, roxygen2, spelling, testthat
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.1.1
Collate: 'bayesian_init.R' 'bayesian_load.R' 'bayesian_make.R' 'bayesian.R'
LazyData: yes
LazyLoad: yes
Language: en-US
NeedsCompilation: no
Packaged: 2021-01-11 00:10:40 UTC; runner
Author: Hamada S. Badr [aut, cre] (<https://orcid.org/0000-0002-9808-2344>)
Maintainer: Hamada S. Badr <badr@jhu.edu>
Repository: CRAN
Date/Publication: 2021-01-14 08:20:02 UTC

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Package VGAM updated to version 1.1-5 with previous version 1.1-4 dated 2020-10-23

Title: Vector Generalized Linear and Additive Models
Description: An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of the statistical framework and the package. Currently only fixed-effects models are implemented. Many (150+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction models)---these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). Hauck-Donner effect detection is implemented. Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.
Author: Thomas Yee [aut, cre], Cleve Moler [ctb] (author of several LINPACK routines)
Maintainer: Thomas Yee <t.yee@auckland.ac.nz>

Diff between VGAM versions 1.1-4 dated 2020-10-23 and 1.1-5 dated 2021-01-14

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 VGAM-1.1-5/VGAM/R/attrassign.R          |    2 
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Package remss updated to version 1.0.1 with previous version 1.0.0 dated 2019-11-20

Title: Refining Evaluation Methodology on Stage System
Description: T (extent of the primary tumor), N (absence or presence and extent of regional lymph node metastasis) and M (absence or presence of distant metastasis) are three components to describe the anatomical tumor extent. TNM stage is important in treatment decision-making and outcome predicting. The existing oropharyngeal Cancer (OPC) TNM stages have not made distinction of the two sub sites of Human papillomavirus positive (HPV+) and Human papillomavirus negative (HPV-) diseases. We developed novel criteria to assess performance of the TNM stage grouping schemes based on parametric modeling adjusting on important clinical factors. These criteria evaluate the TNM stage grouping scheme in five different measures: hazard consistency, hazard discrimination, explained variation, likelihood difference, and balance. The methods are described in Xu, W., et al. (2015) <https://www.austinpublishinggroup.com/biometrics/fulltext/biometrics-v2-id1014.php>.
Author: Wei Xu [aut], Susie Su [aut], Yi Zhu [cre]
Maintainer: Yi Zhu <yizhu87@gmail.com>

Diff between remss versions 1.0.0 dated 2019-11-20 and 1.0.1 dated 2021-01-14

 DESCRIPTION             |    6 +++---
 MD5                     |   18 +++++++++---------
 R/balance_measure.R     |    2 +-
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Package ECOSolveR updated to version 0.5.4 with previous version 0.5.3 dated 2019-11-06

Title: Embedded Conic Solver in R
Description: R interface to the Embedded COnic Solver (ECOS), an efficient and robust C library for convex problems. Conic and equality constraints can be specified in addition to integer and boolean variable constraints for mixed-integer problems. This R interface is inspired by the python interface and has similar calling conventions.
Author: Anqi Fu [aut], Balasubramanian Narasimhan [aut, cre], Florian Schwendinger [ctb], Martin Maechler [ctb]
Maintainer: Balasubramanian Narasimhan <naras@stat.Stanford.EDU>

Diff between ECOSolveR versions 0.5.3 dated 2019-11-06 and 0.5.4 dated 2021-01-14

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Package dialrjars updated to version 8.12.16 with previous version 8.12.6 dated 2020-07-17

Title: Required 'libphonenumber' jars for the 'dialr' Package
Description: Collects 'libphonenumber' jars required for the 'dialr' package.
Author: Danny Smith [aut, cre], Google Inc. [ctb, cph] (libphonenumber), Vonage Holdings Corp. [ctb, cph] (libphonenumber), Ian Galpin [ctb, cph] (libphonenumber), Ben Gertzfield [ctb, cph] (libphonenumber)
Maintainer: Danny Smith <danny@gorcha.org>

Diff between dialrjars versions 8.12.6 dated 2020-07-17 and 8.12.16 dated 2021-01-14

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Package whSample updated to version 0.9.4 with previous version 0.9.2 dated 2020-09-02

Title: Utilities for Sampling
Description: Interactive tools for generating random samples. Users select an .xlsx, .csv, or delimited .txt file with population data and are walked through selecting the sample type (Simple Random Sample or Stratified), the number of backups desired, and a "stratify_on" value (if desired). The sample size is determined using a normal approximation to the hypergeometric distribution based on Nicholson (1956) <doi:10.1214/aoms/1177728270>. An .xlsx file is created with the sample and key metadata for reference. It is menu-driven and lets users pick an output directory. See vignettes for a detailed walk-through.
Author: Paul West [aut, cre]
Maintainer: Paul West <fp8049@gmail.com>

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Package pwrFDR updated to version 2.8.7 with previous version 2.8.6 dated 2020-11-03

Title: FDR Power
Description: This is a package for calculating two differing notions of power, or deriving sample sizes for specified requisite power in multiple testing experiments under a variety of methods for control of the distribution of the False Discovery Proportion (FDP). More specifically, one can choose to control the FDP distribution according to control of its (i) mean, e.g. the usual BH-FDR procedure, or via the probability that it exceeds a given value, delta, via (ii) the Romano procedure, or via (iii) my procedure based upon asymptotic approximation. Likewise, we can think of the power in multiple testing experiments in terms of a summary of the distribution of the True Positive Proportion (TPP). The package will compute power, sample size or any other missing parameter required for power based upon (i) the mean of the TPP which is the average power (ii) the probability that the TPP exceeds a given value, lambda, via my asymptotic approximation procedure. The theoretical results are described in Izmirlian, G. (2020) Stat. and Prob. letters, <doi:10.1016/j.spl.2020.108713>, and an applied paper describing the methodology with a simulation study is in preparation.
Author: Grant Izmirlian Jr <izmirlig@mail.nih.gov>
Maintainer: Grant Izmirlian Jr <izmirlig@mail.nih.gov>

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Package ivmodel updated to version 1.9.0 with previous version 1.8.1 dated 2020-02-20

Title: Statistical Inference and Sensitivity Analysis for Instrumental Variables Model
Description: Carries out instrumental variable estimation of causal effects, including power analysis, sensitivity analysis, and diagnostics. See Kang, Jiang, Zhao, and Small (2020) <http://pages.cs.wisc.edu/~hyunseung/> for details.
Author: Hyunseung Kang, Yang Jiang, Qingyuan Zhao, and Dylan Small
Maintainer: Hyunseung Kang <hyunseung@stat.wisc.edu>

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Package hR updated to version 0.2.50 with previous version 0.2.41 dated 2020-11-09

Title: Toolkit for Data Analytics in Human Resources
Description: Transform and analyze workforce data in meaningful ways for human resources (HR) analytics. Get started with workforce planning using a simple Shiny app.
Author: Dale Kube [aut, cre]
Maintainer: Dale Kube <dkube@uwalumni.com>

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Package edmdata updated to version 1.1.0 with previous version 1.0.0 dated 2020-08-17

Title: Data Sets for Psychometric Modeling
Description: Collection of data sets from various assessments that can be used to evaluate psychometric models. These data sets have been analyzed in the following papers that introduced new methodology as part of the application section: Chen, Y., Culpepper, S. A., & Liang, F. (2020) <doi:10.1007/s11336-019-09693-2> Culpepper, S. A. (2019a) <doi:10.1007/s11336-019-09683-4>, Culpepper, S. A. (2019b) <doi:10.1007/s11336-018-9643-8>, Culpepper, S. A., & Chen, Y. (2019) <doi:10.3102/1076998618791306>, Culpepper, S. A., & Balamuta, J. J. (2017) <doi:10.1007/s11336-015-9484-7>, and Culpepper, S. A. (2015) <doi:10.3102/1076998615595403>.
Author: James Joseph Balamuta [aut, cre, cph] (<https://orcid.org/0000-0003-2826-8458>), Steven Andrew Culpepper [aut, cph] (<https://orcid.org/0000-0003-4226-6176>), Jeffrey Alan Douglas [aut, cph]
Maintainer: James Joseph Balamuta <balamut2@illinois.edu>

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