Mon, 18 Jan 2021

Package optBiomarker updated to version 1.0-28 with previous version 1.0-27 dated 2013-07-11

Title: Estimation of Optimal Number of Biomarkers for Two-Group Microarray Based Classifications at a Given Error Tolerance Level for Various Classification Rules
Description: Estimates optimal number of biomarkers for two-group classification based on microarray data.
Author: Mizanur Khondoker <mizanur.khondoker@gmail.com>
Maintainer: Mizanur Khondoker <mizanur.khondoker@gmail.com>

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New package AzureCosmosR with initial version 1.0.0
Package: AzureCosmosR
Title: Interface to the 'Azure Cosmos DB' 'NoSQL' Database Service
Version: 1.0.0
Authors@R: c( person("Hong", "Ooi", , "hongooi73@gmail.com", role=c("aut", "cre")), person("Andrew", "Liu", role="ctb", comment="Assistance with Cosmos DB"), person("Microsoft", role="cph") )
Description: An interface to 'Azure CosmosDB': <https://azure.microsoft.com/en-us/services/cosmos-db/>. On the admin side, 'AzureCosmosR' provides functionality to create and manage 'Cosmos DB' instances in Microsoft's 'Azure' cloud. On the client side, it provides an interface to the 'Cosmos DB' SQL API, letting the user store and query documents and attachments in 'Cosmos DB'. Part of the 'AzureR' family of packages.
URL: https://github.com/Azure/AzureCosmosR https://github.com/Azure/AzureR
BugReports: https://github.com/Azure/AzureCosmosR/issues
License: MIT + file LICENSE
VignetteBuilder: knitr
Depends: R (>= 3.3)
Imports: utils, AzureRMR (>= 2.3.3), curl, openssl, jsonlite, httr, uuid, vctrs (>= 0.3.0)
Suggests: AzureTableStor, mongolite, DBI, odbc, dplyr, testthat, knitr, rmarkdown
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-18 21:39:24 UTC; hongo
Author: Hong Ooi [aut, cre], Andrew Liu [ctb] (Assistance with Cosmos DB), Microsoft [cph]
Maintainer: Hong Ooi <hongooi73@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 23:50:05 UTC

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Package netmeta updated to version 1.3-0 with previous version 1.2-1 dated 2020-04-16

Title: Network Meta-Analysis using Frequentist Methods
Description: A comprehensive set of functions providing frequentist methods for network meta-analysis and supporting Schwarzer et al. (2015) <DOI:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <DOI:10.1002/jrsm.1058>; - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) <DOI:10.1186/1471-2288-13-35>; - measures characterizing the flow of evidence between two treatments by König et al. (2013) <DOI:10.1002/sim.6001>; - ranking of treatments (frequentist analogue of SUCRA) according to Rücker & Schwarzer (2015) <DOI:10.1186/s12874-015-0060-8>; - partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) <DOI:10.1002/cem.2569>; (Rücker & Schwarzer, 2017) <DOI:10.1002/jrsm.1270>; - split direct and indirect evidence to check consistency (Dias et al., 2010) <DOI:10.1002/sim.3767>, (Efthimiou et al., 2019) <DOI:10.1002/sim.8158>; - league table with network meta-analysis results; - additive network meta-analysis for combinations of treatments (Rücker et al., 2019) <DOI:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <DOI:10.1002/sim.8158>; - 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012) <DOI:10.1002/jrsm.57>; - automated drawing of network graphs described in Rücker & Schwarzer (2016) <DOI:10.1002/jrsm.1143>.
Author: Gerta Rücker [aut] (<https://orcid.org/0000-0002-2192-2560>), Ulrike Krahn [aut], Jochem König [aut] (<https://orcid.org/0000-0003-4683-0360>), Orestis Efthimiou [aut] (<https://orcid.org/0000-0002-0955-7572>), Guido Schwarzer [aut, cre] (<https://orcid.org/0000-0001-6214-9087>)
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

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Package lineup2 updated to version 0.4 with previous version 0.2-5 dated 2020-11-06

Title: Lining Up Two Sets of Measurements
Description: Tools for detecting and correcting sample mix-ups between two sets of measurements, such as between gene expression data on two tissues. This is a revised version of the 'lineup' package, to be more general and not tied to the 'qtl' package.
Author: Karl W Broman [aut, cre] (<https://orcid.org/0000-0002-4914-6671>)
Maintainer: Karl W Broman <broman@wisc.edu>

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Package spcosa updated to version 0.3-11 with previous version 0.3-10 dated 2021-01-06

Title: Spatial Coverage Sampling and Random Sampling from Compact Geographical Strata
Description: Spatial coverage sampling and random sampling from compact geographical strata created by k-means. See Walvoort et al. (2010) <doi:10.1016/j.cageo.2010.04.005> for details.
Author: Dennis Walvoort [aut, cre, cph], Dick Brus [aut, cph], Jaap de Gruijter [aut, cph]
Maintainer: Dennis Walvoort <dennis.Walvoort@wur.nl>

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Package radous updated to version 0.1.2 with previous version 0.1.1 dated 2021-01-07

Title: Query Random User Data from the Random User Generator API
Description: Generate random user data from the Random User Generator API. For more information, see <https://randomuser.me/>.
Author: Mohamed El Fodil Ihaddaden
Maintainer: Mohamed El Fodil Ihaddaden <ihaddaden.fodeil@gmail.com>

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Package configural updated to version 0.1.4 with previous version 0.1.1 dated 2019-02-19

Title: Multivariate Profile Analysis
Description: R functions for criterion profile analysis, Davison and Davenport (2002) <doi:10.1037/1082-989X.7.4.468> and meta-analytic criterion profile analysis, Wiernik, Wilmot, Davison, and Ones (2020) <doi:10.1037/met0000305>. Sensitivity analyses to aid in interpreting criterion profile analysis results are also included.
Author: Brenton M. Wiernik [aut, cre]
Maintainer: Brenton M. Wiernik <brenton@wiernik.org>

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Package tidygeocoder updated to version 1.0.2 with previous version 1.0.1 dated 2020-08-12

Title: Geocoding Made Easy
Description: An intuitive interface for getting data from geocoder services.
Author: Jesse Cambon [aut, cre], Christopher Belanger [aut]
Maintainer: Jesse Cambon <jesse.cambon@gmail.com>

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Package FuzzyR updated to version 2.3.1 with previous version 2.3 dated 2019-11-20

Title: Fuzzy Logic Toolkit for R
Description: Design and simulate fuzzy logic systems using Type-1 and Interval Type-2 Fuzzy Logic. This toolkit includes with graphical user interface (GUI) and an adaptive neuro- fuzzy inference system (ANFIS). This toolkit is a continuation from the previous package ('FuzzyToolkitUoN'). Produced by the Intelligent Modelling & Analysis Group (IMA) and Lab for UnCertainty In Data and decision making (LUCID), University of Nottingham.
Author: Chao Chen, Jon Garibaldi, Tajul Razak
Maintainer: Chao Chen <fuzzyr@cs.nott.ac.uk>

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Package timetk updated to version 2.6.1 with previous version 2.6.0 dated 2020-11-21

Title: A Tool Kit for Working with Time Series in R
Description: Easy visualization, wrangling, and feature engineering of time series data for forecasting and machine learning prediction. Consolidates and extends time series functionality from packages including 'dplyr', 'stats', 'xts', 'forecast', 'slider', 'padr', 'recipes', and 'rsample'.
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>

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Package rfishbase updated to version 3.1.5 with previous version 3.1.4 dated 2021-01-13

Title: R Interface to 'FishBase'
Description: A programmatic interface to 'FishBase', re-written based on an accompanying 'RESTful' API. Access tables describing over 30,000 species of fish, their biology, ecology, morphology, and more. This package also supports experimental access to 'SeaLifeBase' data, which contains nearly 200,000 species records for all types of aquatic life not covered by 'FishBase.'
Author: Carl Boettiger [cre, aut] (<https://orcid.org/0000-0002-1642-628X>), Scott Chamberlain [aut] (<https://orcid.org/0000-0003-1444-9135>), Duncan Temple Lang [aut], Peter Wainwright [aut], Kevin Cazelles [ctb] (<https://orcid.org/0000-0001-6619-9874>)
Maintainer: Carl Boettiger <cboettig@gmail.com>

Diff between rfishbase versions 3.1.4 dated 2021-01-13 and 3.1.5 dated 2021-01-18

 DESCRIPTION  |   11 +++++------
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More information about rfishbase at CRAN
Permanent link

Package OBASpatial updated to version 1.8 with previous version 1.7 dated 2020-09-29

Title: Objective Bayesian Analysis for Spatial Regression Models
Description: It makes an objective Bayesian analysis of the spatial regression model using both the normal (NSR) and student-T (TSR) distributions. The functions provided give prior and posterior objective densities and allow default Bayesian estimation of the model regression parameters. Details can be found in Ordonez et al. (2020) <arXiv:2004.04341>.
Author: Alejandro Ordonez, Marcos O. Prates , Larissa A. Matos, Victor H. Lachos.
Maintainer: Alejandro Ordonez <ordonezjosealejandro@gmail.com>

Diff between OBASpatial versions 1.7 dated 2020-09-29 and 1.8 dated 2021-01-18

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More information about OBASpatial at CRAN
Permanent link

Package lidR updated to version 3.1.0 with previous version 3.0.4 dated 2020-10-10

Title: Airborne LiDAR Data Manipulation and Visualization for Forestry Applications
Description: Airborne LiDAR (Light Detection and Ranging) interface for data manipulation and visualization. Read/write 'las' and 'laz' files, computation of metrics in area based approach, point filtering, artificial point reduction, classification from geographic data, normalization, individual tree segmentation and other manipulations.
Author: Jean-Romain Roussel [aut, cre, cph], David Auty [aut, ctb] (Reviews the documentation), Florian De Boissieu [ctb] (Fixed bugs and improved catalog features), Andrew Sánchez Meador [ctb] (Implemented wing2015() for segment_snags()), Bourdon Jean-François [ctb] (Contributed to Roussel2020() for track_sensor()), Gatziolis Demetrios [ctb] (Implemented Gatziolis2019() for track_sensor())
Maintainer: Jean-Romain Roussel <jean-romain.roussel.1@ulaval.ca>

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Package effectsize updated to version 0.4.3 with previous version 0.4.1 dated 2020-12-07

Title: Indices of Effect Size and Standardized Parameters
Description: Provide utilities to work with indices of effect size and standardized parameters for a wide variety of models (see support list of insight; Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), allowing computation and conversion of indices such as Cohen's d, r, odds, etc.
Author: Mattan S. Ben-Shachar [aut, cre] (<https://orcid.org/0000-0002-4287-4801>), Dominique Makowski [aut] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Indrajeet Patil [ctb] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Ken Kelley [ctb], David Stanley [ctb]
Maintainer: Mattan S. Ben-Shachar <matanshm@post.bgu.ac.il>

Diff between effectsize versions 0.4.1 dated 2020-12-07 and 0.4.3 dated 2021-01-18

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More information about effectsize at CRAN
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Package blavaan updated to version 0.3-13 with previous version 0.3-12 dated 2020-11-12

Title: Bayesian Latent Variable Analysis
Description: Fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models.
Author: Edgar Merkle [aut, cre] (<https://orcid.org/0000-0001-7158-0653>), Yves Rosseel [aut], Ben Goodrich [aut], Mauricio Garnier-Villarreal [ctb] (<https://orcid.org/0000-0002-2951-6647>, R/blav_compare.R, R/ctr_bayes_fit.R), Terrence D. Jorgensen [ctb] (<https://orcid.org/0000-0001-5111-6773>, R/ctr_bayes_fit.R, R/ctr_ppmc.R), Huub Hoofs [ctb] (R/ctr_bayes_fit.R), Rens van de Schoot [ctb] (R/ctr_bayes_fit.R)
Maintainer: Edgar Merkle <merklee@missouri.edu>

Diff between blavaan versions 0.3-12 dated 2020-11-12 and 0.3-13 dated 2021-01-18

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Package tidygate updated to version 0.4.0 with previous version 0.3.2 dated 2020-12-03

Title: Add Gate Information to Your Tibble
Description: It interactively or programmatically label points within custom gates on two dimensions. The information is added to your tibble. It is based on the package 'gatepoints' from Wajid Jawaid (who is also author of this package). The code of gatepoints was nto integrated in tidygate. The benefits are (i) in interactive mode you can draw your gates on extensive 'ggplot'-like scatter plots; (ii) you can draw multiple gates; and (iii) you can save your gates and apply the programmatically.
Author: Stefano Mangiola [aut, cre], Wajid Jawaid [ctb]
Maintainer: Stefano Mangiola <mangiolastefano@gmail.com>

Diff between tidygate versions 0.3.2 dated 2020-12-03 and 0.4.0 dated 2021-01-18

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Package taxotools updated to version 0.0.79 with previous version 0.0.43 dated 2020-03-08

Title: Tools to Handle Taxonomic Lists
Description: Tools include matching and merging taxonomic lists, casting and melting scientific names, managing taxonomic lists from GBIF and ITIS, harvesting names from wikipedia and fuzzy matching.
Author: Vijay Barve [aut, cre] (<https://orcid.org/0000-0002-4852-2567>)
Maintainer: Vijay Barve <vijay.barve@gmail.com>

Diff between taxotools versions 0.0.43 dated 2020-03-08 and 0.0.79 dated 2021-01-18

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Package SSBtools updated to version 0.9.0 with previous version 0.8.0 dated 2020-09-17

Title: Statistics Norway's Miscellaneous Tools
Description: Functions used by other packages from Statistics Norway are gathered. General data manipulation functions, and functions for hierarchical computations are included (Langsrud, 2020) <doi:10.13140/RG.2.2.27313.61283>. The hierarchy specification functions are useful within statistical disclosure control.
Author: Øyvind Langsrud [aut, cre], Bjørn-Helge Mevik [cph]
Maintainer: Øyvind Langsrud <oyl@ssb.no>

Diff between SSBtools versions 0.8.0 dated 2020-09-17 and 0.9.0 dated 2021-01-18

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New package RAEN with initial version 0.1
Package: RAEN
Title: Random Approximate Elastic Net (RAEN) Variable Selection Method
Version: 0.1
Encoding: UTF-8
Description: The Proportional Subdistribution Hazard (PSH) model has been popular for estimating the effects of the covariates on the cause of interest in Competing Risks analysis. The fast accumulation of large scale datasets has posed a challenge to classical statistical methods. Current penalized variable selection methods show unsatisfactory performance in ultra-high dimensional data. We propose a novel method, the Random Approximate Elastic Net (RAEN), with a robust and generalized solution to the variable selection problem for the PSH model. Our method shows improved sensitivity for variable selection compared with current methods.
Author: Han Sun and Xiaofeng Wang
Maintainer: Han Sun <han.sunny@gmail.com>
URL: https://github.com/saintland/RAEN
Imports: boot, foreach, doParallel,glmnet, fastcmprsk
Depends: R(>= 3.5.0), lars
Suggests: testthat, knitr, rmarkdown
License: GPL (>= 2)
RoxygenNote: 7.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-15 06:23:38 UTC; sunh
Repository: CRAN
Date/Publication: 2021-01-18 16:50:15 UTC

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Package princurve updated to version 2.1.6 with previous version 2.1.5 dated 2020-08-25

Title: Fit a Principal Curve in Arbitrary Dimension
Description: Fitting a principal curve to a data matrix in arbitrary dimensions. Hastie and Stuetzle (1989) <doi:10.2307/2289936>.
Author: Trevor Hastie [aut], Andreas Weingessel [aut], Kurt Hornik [aut] (<https://orcid.org/0000-0003-4198-9911>), Henrik Bengtsson [ctb] (HenrikBengtsson), Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>, rcannood)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>

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Package PowerTOST updated to version 1.5-3 with previous version 1.5-2 dated 2020-10-27

Title: Power and Sample Size for (Bio)Equivalence Studies
Description: Contains functions to calculate power and sample size for various study designs used in bioequivalence studies. Use known.designs() to see the designs supported. Power and sample size can be obtained based on different methods, amongst them prominently the TOST procedure (two one-sided t-tests). See README and NEWS for further information.
Author: Detlew Labes [aut, cre] (<https://orcid.org/0000-0003-2169-426X>), Helmut Schütz [aut] (<https://orcid.org/0000-0002-1167-7880>), Benjamin Lang [aut]
Maintainer: Detlew Labes <DetlewLabes@gmx.de>

Diff between PowerTOST versions 1.5-2 dated 2020-10-27 and 1.5-3 dated 2021-01-18

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Permanent link

New package partR2 with initial version 0.9.1
Package: partR2
Title: Partitioning R2 in GLMMs
Version: 0.9.1
Depends: R (>= 3.5.0)
Authors@R: c(person(given = "Martin A.", family = "Stoffel", role = c("aut", "cre"), email = "martin.adam.stoffel@gmail.com"), person(given = "Shinichi", family = "Nakagawa", role = c("aut"), email = "s.nakagawa@unsw.edu.au"), person(given = "Holger", family = "Schielzeth", role = c("aut"), email = "holger.schielzeth@uni-jena.de"))
Description: Partitioning the R2 of GLMMs into variation explained by each predictor and combination of predictors using semi-partial (part) R2 and inclusive R2. Methods are based on the R2 for GLMMs described in Nakagawa & Schielzeth (2013) <doi:10.1111/j.2041-210x.2012.00261.x> and Nakagawa, Johnson & Schielzeth (2017) <doi:10.1098/rsif.2017.0213>.
License: GPL (>= 2)
URL: https://github.com/mastoffel/partR2
BugReports: https://github.com/mastoffel/partR2/issues
Imports: methods, stats, lme4 (>= 1.1-21), pbapply (>= 1.4-2), dplyr (>= 0.8.3), purrr (>= 0.3.3), rlang (>= 0.4.2), tibble (>= 2.1.3), magrittr (>= 1.5), ggplot2 (>= 3.3.0), tidyr (>= 1.1)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, future, furrr, knitr, rmarkdown, patchwork, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-14 18:45:39 UTC; mstoffel
Author: Martin A. Stoffel [aut, cre], Shinichi Nakagawa [aut], Holger Schielzeth [aut]
Maintainer: Martin A. Stoffel <martin.adam.stoffel@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 16:30:04 UTC

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New package panelr with initial version 0.7.5
Package: panelr
Title: Regression Models and Utilities for Repeated Measures and Panel Data
Version: 0.7.5
Authors@R: person("Jacob A.", "Long", email = "jacob.long@sc.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1582-6214"))
Description: Provides an object type and associated tools for storing and wrangling panel data. Implements several methods for creating regression models that take advantage of the unique aspects of panel data. Among other capabilities, automates the "within-between" (also known as "between-within" and "hybrid") panel regression specification that combines the desirable aspects of both fixed effects and random effects econometric models and fits them as multilevel models (Allison, 2009 <doi:10.4135/9781412993869.d33>; Bell & Jones, 2015 <doi:10.1017/psrm.2014.7>). These models can also be estimated via generalized estimating equations (GEE; McNeish, 2019 <doi:10.1080/00273171.2019.1602504>) and Bayesian estimation is (optionally) supported via 'Stan'. Supports estimation of asymmetric effects models via first differences (Allison, 2019 <doi:10.1177/2378023119826441>) as well as a generalized linear model extension thereof using GEE.
URL: https://panelr.jacob-long.com
BugReports: https://github.com/jacob-long/panelr
Depends: R (>= 3.4.0), lme4
Imports: crayon, dplyr, Formula, ggplot2, jtools (>= 2.0.1), lmerTest, magrittr, methods, purrr, rlang (>= 0.3.0), stringr, tibble (>= 2.0.0)
Suggests: brms, broom.mixed, car, clubSandwich, geepack, generics, nlme, plm, sandwich, skimr, tidyr (>= 0.8.3), testthat, covr, knitr, rmarkdown
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-18 04:00:06 UTC; jacoblong
Author: Jacob A. Long [aut, cre] (<https://orcid.org/0000-0002-1582-6214>)
Maintainer: Jacob A. Long <jacob.long@sc.edu>
Repository: CRAN
Date/Publication: 2021-01-18 17:00:02 UTC

More information about panelr at CRAN
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Package msaeDB updated to version 0.1.2 with previous version 0.1.1 dated 2021-01-13

Title: Difference Benchmarking for Multivariate Small Area Estimation
Description: Implements Benchmarking Method for Multivariate Small Area Estimation under Fay Herriot Model. Multivariate Small Area Estimation (MSAE) is a development of Univariate Small Area Estimation that considering the correlation among response variables and borrowing the strength from related areas and auxiliary variables to increase the effectiveness of sample size, the multivariate model in this package is based on multivariate model 1 proposed by Roberto Benavent and Domingo Morales (2015) <doi:10.1016/j.csda.2015.07.013>. Benchmarking in Small Area Estimation is a modification of Small Area Estimation model to guarantee that the aggregate weighted mean of the county predictors equals the corresponding weighted mean of survey estimates. Difference Benchmarking is the simplest benchmarking method but widely used by multiplying empirical best linear unbiased prediction (EBLUP) estimator by the common adjustment factors (J.N.K Rao and Isabel Molina, 2015).
Author: Zaza Yuda Perwira, Azka Ubaidillah
Maintainer: Zaza Yuda Perwira <221710086@stis.ac.id>

Diff between msaeDB versions 0.1.1 dated 2021-01-13 and 0.1.2 dated 2021-01-18

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Package mosaic updated to version 1.8.3 with previous version 1.8.2 dated 2020-09-16

Title: Project MOSAIC Statistics and Mathematics Teaching Utilities
Description: Data sets and utilities from Project MOSAIC (<http://www.mosaic-web.org>) used to teach mathematics, statistics, computation and modeling. Funded by the NSF, Project MOSAIC is a community of educators working to tie together aspects of quantitative work that students in science, technology, engineering and mathematics will need in their professional lives, but which are usually taught in isolation, if at all.
Author: Randall Pruim [aut, cre], Daniel T. Kaplan [aut], Nicholas J. Horton [aut]
Maintainer: Randall Pruim <rpruim@calvin.edu>

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Package mixture updated to version 2.0.2 with previous version 2.0.1 dated 2021-01-15

Title: Mixture Models for Clustering and Classification
Description: An implementation of 14 parsimonious mixture models for model-based clustering or model-based classification. Gaussian, generalized hyperbolic, variance-gamma or skew-t mixtures are available. All approaches work with missing data. Celeux and Govaert (1995) <doi:10.1016/0031-3203(94)00125-6>, Browne and McNicholas (2014) <doi:10.1007/s11634-013-0139-1>, Browne and McNicholas (2015) <doi:10.1002/cjs.11246>.
Author: Nik Pocuca [aut], Ryan P. Browne [aut], Paul D. McNicholas [aut, cre]
Maintainer: Paul D. McNicholas <mcnicholas@math.mcmaster.ca>

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Package meta updated to version 4.16-0 with previous version 4.15-1 dated 2020-10-02

Title: General Package for Meta-Analysis
Description: User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015): - fixed effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - statistical tests and trim-and-fill method to evaluate bias in meta-analysis; - import data from 'RevMan 5'; - prediction interval, Hartung-Knapp method for random effects model; - cumulative meta-analysis and leave-one-out meta-analysis; - meta-regression; - generalised linear mixed models; - produce forest plot summarising several (subgroup) meta-analyses.
Author: Guido Schwarzer [cre, aut] (<https://orcid.org/0000-0001-6214-9087>)
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

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New package memify with initial version 0.1.1
Package: memify
Type: Package
Title: Constructing Functions That Keep State
Version: 0.1.1
Author: Bert Gunter
Maintainer: Bert Gunter <bgunter.4567@gmail.com>
Description: A simple way to construct and maintain functions that keep state i.e. remember their argument lists. This can be useful when one needs to repeatedly invoke the same function with only a small number of argument changes at each invocation.
Depends: R (>= 4.0)
Imports: utils
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-01-14 20:39:19 UTC; bgunter
Repository: CRAN
Date/Publication: 2021-01-18 16:40:09 UTC

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Package JMbayes2 updated to version 0.1-3 with previous version 0.1-2 dated 2021-01-13

Title: Extended Joint Models for Longitudinal and Time-to-Event Data
Description: Fit joint models for longitudinal and time-to-event data under the Bayesian approach. Multiple longitudinal outcomes of mixed type (continuous/categorical) and multiple event times (competing risks and multi-state processes) are accommodated. Rizopoulos (2012, ISBN:9781439872864).
Author: Dimitris Rizopoulos [aut, cre] (<https://orcid.org/0000-0001-9397-0900>), Grigorios Papageorgiou [aut], Pedro Miranda Afonso [aut]
Maintainer: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>

Diff between JMbayes2 versions 0.1-2 dated 2021-01-13 and 0.1-3 dated 2021-01-18

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New package Inflect with initial version 1.0.3
Package: Inflect
Type: Package
Title: Melt Curve Fitting and Melt Shift Analysis
Version: 1.0.3
Authors@R: c(person("Neil", "McCracken", email = "namccrac@iu.edu",role = c("aut")), person("Aruna", "Wijeratne", role = c("ctb")), person("Amber", "Mosley", email = "almosley@iu.edu",role = c("cre")))
Description: This program analyzes raw abundance data from a cellular thermal shift experiment and calculates melt temperatures and melt shifts for each protein in the experiment. Reference to software development can be found at <doi:10.1101/2020.10.31.363523>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: readxl, writexl, optimr, data.table, plotrix, tidyr, ggplot2
Suggests: knitr, rmarkdown,
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-15 00:45:13 UTC; namccrac
Config/testthat/edition: 3
Author: Neil McCracken [aut], Aruna Wijeratne [ctb], Amber Mosley [cre]
Maintainer: Amber Mosley <almosley@iu.edu>
Repository: CRAN
Date/Publication: 2021-01-18 16:40:12 UTC

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New package GSDA with initial version 1.0
Package: GSDA
Type: Package
Title: Gene Set Distance Analysis (GSDA)
Version: 1.0
Date: 2021-01-014
Authors@R: c(person("Xueyuan", "Cao", email = "xcao12@uthsc.edu", role = c("aut", "cre")), person("Stanley", "Pounds", email = "stanley.pounds@stjude.org", role = c("aut")))
Description: The gene-set distance analysis of omic data is implemented by generalizing distance correlations to evaluate the association of a gene set with categorical and censored event-time variables.
Depends: R (>= 3.5.0),msigdbr
License: GPL (>= 2)
biocViews: Microarray, Bioinformatics, Gene expression
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LazyLoad: yes
NeedsCompilation: no
Packaged: 2021-01-14 17:30:56 UTC; xcao12
Author: Xueyuan Cao [aut, cre], Stanley Pounds [aut]
Maintainer: Xueyuan Cao <xcao12@uthsc.edu>
Repository: CRAN
Date/Publication: 2021-01-18 16:20:27 UTC

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Package extRatum updated to version 1.0.4 with previous version 1.0.3 dated 2021-01-15

Title: Summary Statistics for Geospatial Features
Description: Provides summary statistics of local geospatial features within a given geographic area. It does so by calculating the area covered by a target geospatial feature (i.e. buildings, parks, lakes, etc.). The geospatial features can be of any type of geospatial data, including point, polygon or line data.
Author: Nikos Patias [aut, cre] (<https://orcid.org/0000-0002-6542-2330>), Francisco Rowe [aut]
Maintainer: Nikos Patias <n.patias@liverpool.ac.uk>

Diff between extRatum versions 1.0.3 dated 2021-01-15 and 1.0.4 dated 2021-01-18

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Package ExhaustiveSearch updated to version 1.0.1 with previous version 1.0.0 dated 2021-01-15

Title: A Fast and Scalable Exhaustive Feature Selection Framework
Description: The goal of this package is to provide an easy to use, fast and scalable exhaustive search framework. Exhaustive feature selections typically require a very large number of models to be fitted and evaluated. Execution speed and memory management are crucial factors here. This package provides solutions for both. Execution speed is optimized by using a multi-threaded C++ backend, and memory issues are solved by by only storing the best results during execution and thus keeping memory usage constant.
Author: Rudolf Jagdhuber [aut, cre], Jorge Nocedal [cph] (lbfgs c library), Naoaki Okazaki [cph] (lbfgs c library)
Maintainer: Rudolf Jagdhuber <r.jagdhuber@gmail.com>

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Package discourseGT updated to version 1.1.3 with previous version 1.1.2 dated 2020-12-08

Title: Analyze Group Patterns using Graph Theory in Educational Settings
Description: Analyzes group patterns using discourse analysis data with graph theory mathematics. Takes the order of which individuals talk and converts it to a network edge and weight list. Returns the density, centrality, centralization, and subgroup information for each group. Based on the analytical framework laid out in Chai et al. (2019) <doi:10.1187/cbe.18-11-0222>.
Author: Albert Chai [aut], Andrew Lee [aut], Joshua Le [aut, cre], Katherine Ly [ctb], Kevin Banh [ctb], Priya Pahal [ctb], Stanley Lo [aut]
Maintainer: Joshua Le <jpl038@ucsd.edu>

Diff between discourseGT versions 1.1.2 dated 2020-12-08 and 1.1.3 dated 2021-01-18

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New package bigmds with initial version 0.0.1
Package: bigmds
Title: Multidimensional Scaling for Big Data
Version: 0.0.1
Authors@R: c( person(given = "Cristian", family = "Pachón García", role = c("aut", "cre"), email = "cc.pachon@gmail.com", comment = c(ORCID = "0000-0001-9518-4874")), person(given = "Pedro", family = "Delicado", role = c("aut"), email = "pedro.delicado@upc.edu", comment = c(ORCID = "0000-0003-3933-4852")) )
Description: We present a set of algorithms for Multidimensional Scaling (MDS) to be used with large datasets. MDS is a statistic tool for reduction of dimensionality, using as input a distance matrix of dimensions n × n. When n is large, classical algorithms suffer from computational problems and MDS configuration can not be obtained. With this package, we address these problems by means of three algorithms: Divide and Conquer MDS, Fast MDS and MDS based on Gower interpolation. The main idea of these methods is based on partitioning the dataset into small pieces, where classical methods can work.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: MCMCpack, stats, pdist
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
URL: https://github.com/pachoning/bigmds
BugReports: https://github.com/pachoning/bigmds/issues
NeedsCompilation: no
Packaged: 2021-01-14 17:39:05 UTC; cristianpachongarcia
Author: Cristian Pachón García [aut, cre] (<https://orcid.org/0000-0001-9518-4874>), Pedro Delicado [aut] (<https://orcid.org/0000-0003-3933-4852>)
Maintainer: Cristian Pachón García <cc.pachon@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 16:20:10 UTC

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Package amt updated to version 0.1.4 with previous version 0.1.3 dated 2020-10-01

Title: Animal Movement Tools
Description: Manage and analyze animal movement data. The functionality of 'amt' includes methods to calculate home ranges <doi:10.1101/2020.08.19.256859v2>, track statistics (e.g. step lengths, speed, or turning angles), prepare data for fitting habitat selection analyses <doi:10.1101/2020.11.12.379834v4>, and simulation of space-use from fitted step-selection functions <doi:10.1002/ecs2.1771>.
Author: Johannes Signer [aut, cre], Brian Smith [ctb], Bjoern Reineking [ctb], Ulrike Schlaegel [ctb], John Fieberg [ctb], Scott LaPoint [dtc]
Maintainer: Johannes Signer <jsigner@gwdg.de>

Diff between amt versions 0.1.3 dated 2020-10-01 and 0.1.4 dated 2021-01-18

 amt-0.1.3/amt/R/hr_intersection.R               |only
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 amt-0.1.4/amt/R/coercion.R                      |   22 +-
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 amt-0.1.4/amt/R/fit_ctmm.R                      |   23 +-
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 amt-0.1.4/amt/R/hr_isopleths.R                  |   24 ++
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 amt-0.1.4/amt/R/simulate_movement2.R            |    2 
 amt-0.1.4/amt/R/site_fidelity.R                 |    4 
 amt-0.1.4/amt/R/time_of_day.R                   |    3 
 amt-0.1.4/amt/R/track.R                         |   40 +++
 amt-0.1.4/amt/build/partial.rdb                 |binary
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 amt-0.1.4/amt/inst/doc/p5_other_packages.html   |  152 +++++++++-----
 amt-0.1.4/amt/inst/tinytest/test_as_sf_star.R   |   24 +-
 amt-0.1.4/amt/inst/tinytest/test_as_telemetry.R |only
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 amt-0.1.4/amt/man/summarize_sampling_rate.Rd    |    8 
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 60 files changed, 1201 insertions(+), 614 deletions(-)

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New package sims with initial version 0.0.2
Package: sims
Title: Simulate Data from R or 'JAGS' Code
Version: 0.0.2
Authors@R: c(person(given = "Audrey", family = "Beliveau", role = "aut", email = "audrey.beliveau@uwaterloo.ca"), person(given = "Joe", family = "Thorley", role = c("aut", "cre"), email = "joe@poissonconsulting.ca", comment = c(ORCID = "0000-0002-7683-4592")))
Description: Generates data from R or 'JAGS' code for use in simulation studies. The data are returned as an 'nlist::nlists' object and/or saved to file as individual '.rds' files. Parallelization is implemented using the 'future' package. Progress is reported using the 'progressr' package.
License: MIT + file LICENSE
Depends: R (>= 3.6)
Imports: chk, future.apply, nlist, parallel, stats, yesno
Suggests: covr, future, knitr, progressr, rjags, rmarkdown, testthat
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-01-14 15:52:52 UTC; joe
Author: Audrey Beliveau [aut], Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>)
Maintainer: Joe Thorley <joe@poissonconsulting.ca>
Repository: CRAN
Date/Publication: 2021-01-18 15:50:02 UTC

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Package EvidenceSynthesis (with last version 0.2.2) was removed from CRAN

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

2020-12-18 0.2.2

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Package ProcMod (with last version 1.0.7) was removed from CRAN

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

2020-10-02 1.0.7
2020-09-21 1.0.6
2019-11-25 1.0.3

Permanent link
Package heemod updated to version 0.14.1 with previous version 0.14.0 dated 2020-12-08

Title: Markov Models for Health Economic Evaluations
Description: An implementation of the modelling and reporting features described in reference textbook and guidelines (Briggs, Andrew, et al. Decision Modelling for Health Economic Evaluation. Oxford Univ. Press, 2011; Siebert, U. et al. State-Transition Modeling. Medical Decision Making 32, 690-700 (2012).): deterministic and probabilistic sensitivity analysis, heterogeneity analysis, time dependency on state-time and model-time (semi-Markov and non-homogeneous Markov models), etc.
Author: Kevin Zarca [aut, cre], Antoine Filipovic-Pierucci [aut], Matthew Wiener [ctb], Zdenek Kabat [ctb], Vojtech Filipec [ctb], Jordan Amdahl [ctb], Yonatan Carranza Alarcon [ctb], Vince Daniels [ctb]
Maintainer: Kevin Zarca <kevin.zarca@gmail.com>

Diff between heemod versions 0.14.0 dated 2020-12-08 and 0.14.1 dated 2021-01-18

 DESCRIPTION                     |    6 -
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 NEWS.md                         |    3 
 R/tabular_input.R               |   10 ++
 README.md                       |    4 -
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 inst/doc/b_time_dependency.html |    4 -
 inst/doc/c_homogeneous.Rmd      |    2 
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 vignettes/c_homogeneous.Rmd     |    2 
 vignettes/d_non_homogeneous.Rmd |    2 
 vignettes/i_reproduction.Rmd    |    2 
 22 files changed, 168 insertions(+), 165 deletions(-)

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Package xgboost updated to version 1.3.2.1 with previous version 1.3.1.1 dated 2021-01-05

Title: Extreme Gradient Boosting
Description: Extreme Gradient Boosting, which is an efficient implementation of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>. This package is its R interface. The package includes efficient linear model solver and tree learning algorithms. The package can automatically do parallel computation on a single machine which could be more than 10 times faster than existing gradient boosting packages. It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that users are also allowed to define their own objectives easily.
Author: Tianqi Chen [aut], Tong He [aut, cre], Michael Benesty [aut], Vadim Khotilovich [aut], Yuan Tang [aut] (<https://orcid.org/0000-0001-5243-233X>), Hyunsu Cho [aut], Kailong Chen [aut], Rory Mitchell [aut], Ignacio Cano [aut], Tianyi Zhou [aut], Mu Li [aut], Junyuan Xie [aut], Min Lin [aut], Yifeng Geng [aut], Yutian Li [aut], XGBoost contributors [cph] (base XGBoost implementation)
Maintainer: Tong He <hetong007@gmail.com>

Diff between xgboost versions 1.3.1.1 dated 2021-01-05 and 1.3.2.1 dated 2021-01-18

 DESCRIPTION                               |    8 ++++----
 MD5                                       |   18 +++++++++---------
 inst/doc/discoverYourData.html            |    8 ++++----
 inst/doc/xgboost.pdf                      |binary
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 inst/doc/xgboostfromJSON.html             |    2 +-
 src/include/xgboost/base.h                |    2 +-
 src/include/xgboost/version_config.h      |    2 +-
 src/rabit/include/rabit/internal/socket.h |    4 ++++
 src/src/gbm/gblinear_model.cc             |    4 ----
 10 files changed, 36 insertions(+), 36 deletions(-)

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New package spNetwork with initial version 0.1.0
Package: spNetwork
Type: Package
Title: Spatial Analysis on Network
Version: 0.1.0
Authors@R: c( person("Jeremy", "Gelb", email = "jeremy.gelb@ucs.inrs.ca",role = c("aut", "cre")), person("Philippe", "Apparicio", email="philippe.apparicio@ucs.inrs.ca", role=c("ctb")))
Description: Perform spatial analysis on network. Allow to calculate Network Kernel Density Estimate, and to build spatial matrices ('listw' objects like in 'spdep' package) to conduct any kind of traditional spatial analysis with spatial weights based on reticular distances. K functions on network are also available but still experimental. References: Okabe et al (2019) <doi:10.1080/13658810802475491>; Okabe et al (2012, ISBN:978-0470770818);Baddeley el al (2015, ISBN:9781482210200).
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: spdep (>= 1.1.2), maptools (>= 0.9-5), rgeos (>= 0.5-2), sp (>= 1.3-1), sf (>= 0.9-0), raster (>= 3.0-12), igraph (>= 1.2.4.2), cubature (>= 2.0.4.1), future.apply (>= 1.4.0), methods (>= 1.7.1), ggplot2 (>= 3.3.0), progressr (>= 0.4.0), data.table (>= 1.12.8), SearchTrees (>= 0.5.2), Rcpp (>= 1.0.4.6)
Depends: R (>= 3.6)
Suggests: future (>= 1.16.0), testthat (>= 3.0.0), knitr (>= 1.28), kableExtra (>= 1.1.0), rmarkdown (>= 2.1), RColorBrewer (>= 1.1-2), classInt (>= 0.4-3), reshape2 (>= 1.4.3), dplyr (>= 0.8.3), rlang (>= 0.4.6), rgdal (>= 1.5-18), plot3D (>= 1.3)
RoxygenNote: 7.1.1
VignetteBuilder: knitr
URL: https://github.com/JeremyGelb/spNetwork
BugReports: https://github.com/JeremyGelb/spNetwork/issues
LinkingTo: Rcpp, RcppProgress, RcppArmadillo
SystemRequirements: C++11
NeedsCompilation: yes
Packaged: 2021-01-14 14:32:32 UTC; gelbj
Author: Jeremy Gelb [aut, cre], Philippe Apparicio [ctb]
Maintainer: Jeremy Gelb <jeremy.gelb@ucs.inrs.ca>
Repository: CRAN
Date/Publication: 2021-01-18 10:10:07 UTC

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New package aghq with initial version 0.1.0
Package: aghq
Type: Package
Title: Adaptive Gauss Hermite Quadrature for Bayesian Inference
Version: 0.1.0
Author: Alex Stringer
Maintainer: Alex Stringer <alex.stringer@mail.utoronto.ca>
Description: Adaptive Gauss Hermite Quadrature for Bayesian inference. The AGHQ method for normalizing posterior distributions and making Bayesian inferences based on them. Functions are provided for doing quadrature and marginal Laplace approximations, and summary methods are provided for making inferences based on the results. See Stringer (2021). "Implementing Adaptive Quadrature for Bayesian Inference: the aghq Package" <arXiv:2101.04468>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
Imports: methods, mvQuad, matrixStats, Matrix, stringr, magrittr, dplyr, tidyr, tidyselect, rlang, polynom, tibble, purrr
Suggests: trustOptim, trust, numDeriv, testthat (>= 2.1.0), knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2021-01-14 14:59:42 UTC; alexstringer
Repository: CRAN
Date/Publication: 2021-01-18 10:30:02 UTC

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New package torchaudio with initial version 0.1.1.0
Package: torchaudio
Title: R Interface to 'pytorch''s 'torchaudio'
Version: 0.1.1.0
Authors@R: c( person(given = "Athos", family = "Damiani", role = c("aut", "cre"), email = "athos.damiani@gmail.com" ) )
Description: Provides access to datasets, models and preprocessing facilities for deep learning in audio.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, monitoR, tuneR, knitr, rmarkdown, stringr, numbers, purrr, scales, httr, viridis
Imports: torch (>= 0.2.0), fs, rlang, rappdirs, utils, tools, glue
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-14 14:08:35 UTC; athos
Author: Athos Damiani [aut, cre]
Maintainer: Athos Damiani <athos.damiani@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 10:00:02 UTC

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New package parallelPlot with initial version 0.1.0
Package: parallelPlot
Title: 'Htmlwidget' for a Parallel Coordinates Plot
Version: 0.1.0
Authors@R: c( person("Mike", "Bostock", role = c("aut", "cph"), comment = "d3.js library in htmlwidgets/lib, http://d3js.org"), person("David", "Chazalviel", email = "david.chazalviel@club-internet.fr", role = c("aut", "cre")), person("Benoit", "Lehman", email = "benoit.lehman@tech-advantage.com", role = c("aut")) )
Description: Create a parallel coordinates plot, using 'htmlwidgets' package and 'd3.js'.
URL: https://gitlab.com/drti/parallelplot
BugReports: https://gitlab.com/drti/parallelplot/-/issues
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: htmlwidgets
Suggests: testthat, shiny, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-01-14 11:02:53 UTC; cuckooland
Author: Mike Bostock [aut, cph] (d3.js library in htmlwidgets/lib, http://d3js.org), David Chazalviel [aut, cre], Benoit Lehman [aut]
Maintainer: David Chazalviel <david.chazalviel@club-internet.fr>
Repository: CRAN
Date/Publication: 2021-01-18 09:10:03 UTC

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New package noah with initial version 0.1.0
Package: noah
Title: Create Unique Pseudonymous Animal Names
Version: 0.1.0
Authors@R: person(given = "Tobias", family = "Busch", role = c("aut", "cre"), email = "teebusch@gmail.com", comment = c(ORCID = "https://orcid.org/0000-0002-8390-7892"))
Description: Generate pseudonymous animal names that are delightful and easy to remember like the Likable Leech and the Proud Chickadee. A unique pseudonym can be created for every unique element in a vector or row in a data frame. Pseudonyms can be customized and tracked over time, so that the same input is always assigned the same pseudonym.
License: MIT + file LICENSE
Suggests: testthat, covr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/Teebusch/noah
BugReports: https://github.com/Teebusch/noah/issues
Imports: R6, hash, digest, assertthat, purrr, dplyr, magrittr, crayon, rlang, stringr
Depends: R (>= 3.1.0)
NeedsCompilation: no
Packaged: 2021-01-14 10:47:54 UTC; teebu
Author: Tobias Busch [aut, cre] (<https://orcid.org/0000-0002-8390-7892>)
Maintainer: Tobias Busch <teebusch@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 09:10:06 UTC

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New package kittyR with initial version 1.0.0
Type: Package
Package: kittyR
Title: Kitty Pictures and Meows from R Console
Version: 1.0.0
Authors@R: person(given = "Indrajeet", family = "Patil", role = c("aut", "cre", "cph"), email = "patilindrajeet.science@gmail.com", comment = c(ORCID = "0000-0003-1995-6531", Twitter = "@patilindrajeets"))
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>
Description: Get pictures of cats and their meows from your R console.
License: MIT + file LICENSE
URL: https://github.com/IndrajeetPatil/kittyR
BugReports: https://github.com/IndrajeetPatil/kittyR/issues
Depends: R (>= 3.6.0)
Imports: beepr, dplyr, graphics, imager, magrittr, purrr, rvest, stringr, tibble
Suggests: spelling, testthat
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.1
Config/testthat/edition: 3
Config/testthat/parallel: true
NeedsCompilation: no
Packaged: 2021-01-14 12:11:24 UTC; inp099
Author: Indrajeet Patil [aut, cre, cph] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets)
Repository: CRAN
Date/Publication: 2021-01-18 09:30:02 UTC

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New package geysertimes with initial version 0.1.2
Package: geysertimes
Title: Geyser Data from GeyserTimes.org
Version: 0.1.2
Imports: jsonlite, lubridate, rappdirs, readr, tools, utils
Suggests: curl, dplyr, knitr, rmarkdown
Authors@R: person(given = "Stephen", family = "Kaluzny", role = c("aut", "cre"), email = "spkaluzny@gmail.com")
Description: Download geyser eruption and observation data from the GeyserTimes site (<https://geysertimes.org>) and optionally store it locally. The vignette shows the a simple analysis of downloading, accessing, and summarizing the data.
License: MIT + file LICENSE
URL: https://github.com/geysertimes/geysertimes-r-package
BugReports: https://github.com/geysertimes/geysertimes-r-package/issues
VignetteBuilder: knitr, rmarkdown
LazyData: yes
NeedsCompilation: no
Packaged: 2021-01-13 17:14:28 UTC; spk
Author: Stephen Kaluzny [aut, cre]
Maintainer: Stephen Kaluzny <spkaluzny@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 09:00:02 UTC

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New package coder with initial version 0.13.5
Package: coder
Type: Package
Title: Deterministic Categorization of Items Based on External Code Data
Version: 0.13.5
Authors@R: c( person("Erik", "Bulow", email = "eriklgb@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9973-456X")), person("Emely C", "Zabore", role = "rev", comment = "Emily reviewed the package (v. 0.12.1) for rOpenSci, see <https://github.com/ropensci/software-review/issues/381>"), person("David", "Robinson", role = "rev", comment = "David reviewed the package (v. 0.12.1) for rOpenSci, see <https://github.com/ropensci/software-review/issues/381>") )
Description: Fast categorization of items based on external code data identified by regular expressions. A typical use case considers patient with medically coded data, such as codes from the International Classification of Diseases ('ICD') or the Anatomic Therapeutic Chemical ('ATC') classification system. Functions of the package relies on a triad of objects: (1) case data with unit id:s and possible dates of interest; (2) external code data for corresponding units in (1) and with optional dates of interest and; (3) a classification scheme ('classcodes' object) with regular expressions to identify and categorize relevant codes from (2). It is easy to introduce new classification schemes ('classcodes' objects) or to use default schemes included in the package. Use cases includes patient categorization based on 'comorbidity indices' such as 'Charlson', 'Elixhauser', 'RxRisk V', or the 'comorbidity-polypharmacy' score (CPS), as well as adverse events after hip and knee replacement surgery.
License: GPL-2
Depends: R (>= 3.3)
Suggests: covr, testthat, knitr, rmarkdown, writexl
Imports: data.table, decoder, generics, methods, tibble
LazyData: TRUE
RoxygenNote: 7.1.1
VignetteBuilder: knitr
URL: https://docs.ropensci.org/coder/
BugReports: https://github.com/ropensci/coder/issues
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2021-01-14 10:07:41 UTC; erikbulow
Author: Erik Bulow [aut, cre] (<https://orcid.org/0000-0002-9973-456X>), Emely C Zabore [rev] (Emily reviewed the package (v. 0.12.1) for rOpenSci, see <https://github.com/ropensci/software-review/issues/381>), David Robinson [rev] (David reviewed the package (v. 0.12.1) for rOpenSci, see <https://github.com/ropensci/software-review/issues/381>)
Maintainer: Erik Bulow <eriklgb@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 09:00:05 UTC

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New package cecs with initial version 0.1.0
Package: cecs
Title: R Interface for the C Implementation of CEC Benchmark Functions
Version: 0.1.0
Authors@R: c( person("Eryk", "Warchulski", role = c("aut", "cre"), email = "ewarchul@gmail.com"), person("Dariusz", "Jagodziński", role = c("cph"), email = "d.jagodzinski@elka.pw.edu.pl"), person("Yasser", "Gonzalez-Fernandez", role = c("cph"), email = "yasser@yassergonzalez.com"), person("Mauricio", "Zambrano-Bigiarini", role = c("cph"), email = "mzb.devel@gmail.com") )
Description: Goal of this package is to provide access to benchmark functions defined for the Special Session and Competition on Real-Parameter Single Objective Optimization in one place. The package contains functions from following years: 2013, 2014, 2017, 2021 (<https://github.com/P-N-Suganthan>). Implementations of CEC-2013 (Y. Gonzalez-Fernandez & M. Zambrano-Bigiarini) and CEC2017 (D. Jagodziński) are taken from existed R packages. Also, the original C source code has been cleaned and reorganized for better readability.
License: GPL (>= 3)
BugReports: https://github.com/ewarchul/cecs/issues
URL: https://github.com/ewarchul/cecs
Depends: R (>= 3.6.0)
Imports: stringr (>= 1.4.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat (>= 3.0.0), purrr (>= 0.3.4)
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2021-01-13 19:40:41 UTC; ewarchul
Author: Eryk Warchulski [aut, cre], Dariusz Jagodziński [cph], Yasser Gonzalez-Fernandez [cph], Mauricio Zambrano-Bigiarini [cph]
Maintainer: Eryk Warchulski <ewarchul@gmail.com>
Repository: CRAN
Date/Publication: 2021-01-18 08:40:02 UTC

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New package cachem with initial version 1.0.0
Package: cachem
Version: 1.0.0
Title: Cache R Objects with Automatic Pruning
Description: Key-value stores with automatic pruning. Caches can limit either their total size or the age of the oldest object (or both), automatically pruning objects to maintain the constraints.
Authors@R: c( person("Winston", "Chang", , "winston@rstudio.com", c("aut", "cre")), person(family = "RStudio", role = c("cph", "fnd")))
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
URL: https://cachem.r-lib.org/, https://github.com/r-lib/cachem
Imports: rlang, fastmap
Suggests: testthat
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-01-13 20:52:01 UTC; winston
Author: Winston Chang [aut, cre], RStudio [cph, fnd]
Maintainer: Winston Chang <winston@rstudio.com>
Repository: CRAN
Date/Publication: 2021-01-18 08:50:02 UTC

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Package paws.common updated to version 0.3.7 with previous version 0.3.6 dated 2020-12-05

Title: Paws Low-Level Amazon Web Services API
Description: Functions for making low-level API requests to Amazon Web Services <https://aws.amazon.com>. The functions handle building, signing, and sending requests, and receiving responses. They are designed to help build higher-level interfaces to individual services, such as Simple Storage Service (S3).
Author: David Kretch [aut, cre], Adam Banker [aut], Amazon.com, Inc. [cph]
Maintainer: David Kretch <david.kretch@gmail.com>

Diff between paws.common versions 0.3.6 dated 2020-12-05 and 0.3.7 dated 2021-01-18

 DESCRIPTION   |    6 +++---
 MD5           |   12 ++++++------
 NEWS.md       |    5 +++++
 R/config.R    |    8 ++++++--
 R/custom_s3.R |   26 +++++++++++++++++++++++++-
 R/net.R       |   10 +++++++---
 R/url.R       |    6 +++---
 7 files changed, 55 insertions(+), 18 deletions(-)

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Package hdrcde updated to version 3.4 with previous version 3.3 dated 2018-12-21

Title: Highest Density Regions and Conditional Density Estimation
Description: Computation of highest density regions in one and two dimensions, kernel estimation of univariate density functions conditional on one covariate,and multimodal regression.
Author: Rob Hyndman [aut, cre, cph] (<https://orcid.org/0000-0002-2140-5352>), Jochen Einbeck [aut] (<https://orcid.org/0000-0002-9457-2020>), Matthew Wand [aut] (<https://orcid.org/0000-0003-2555-896X>), Simon Carrignon [ctb] (<https://orcid.org/0000-0002-4416-1389>), Fan Cheng [ctb] (<https://orcid.org/0000-0003-0009-3262>)
Maintainer: Rob Hyndman <Rob.Hyndman@monash.edu>

Diff between hdrcde versions 3.3 dated 2018-12-21 and 3.4 dated 2021-01-18

 DESCRIPTION           |   26 +++---
 MD5                   |   62 ++++++++-------
 NAMESPACE             |    4 
 NEWS.md               |    4 
 R/HDRbw.r             |   40 ++++-----
 R/cde.bandwidths.R    |    6 -
 R/cde.est.R           |   12 +-
 R/hdr.R               |  206 ++++++++++++++++++++++++++++++++++----------------
 R/hdr.boxplot.2d.R    |   27 +++++-
 R/hdr.conf.R          |   18 +---
 R/hdrcde-package.R    |    8 -
 R/hdrscatterplot.R    |   13 ++-
 R/modalreg.r          |   67 +++++++---------
 R/plot.hdr.conf.R     |    9 --
 R/plotcde.R           |    6 -
 README.md             |    9 --
 inst/CITATION         |    4 
 man/alpha.Rd          |only
 man/cde.Rd            |   36 ++++++--
 man/cde.bandwidths.Rd |   25 ++++--
 man/hdr.Rd            |   87 +++------------------
 man/hdr.boxplot.2d.Rd |   55 +++++++++----
 man/hdr.boxplot.Rd    |only
 man/hdr.cde.Rd        |   22 ++++-
 man/hdr.den.Rd        |only
 man/hdrbw.Rd          |    5 -
 man/hdrconf.Rd        |   10 --
 man/hdrscatterplot.Rd |   14 ++-
 man/lane2.Rd          |    7 -
 man/maxtemp.Rd        |    5 -
 man/modalreg.Rd       |   28 ++++--
 man/plot.cde.Rd       |   16 ++-
 man/plot.hdrconf.Rd   |    9 --
 man/shades.Rd         |only
 34 files changed, 472 insertions(+), 368 deletions(-)

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Package rdacca.hp updated to version 0.2.0 with previous version 0.1.0 dated 2020-12-04

Title: Hierarchical Partitioning for Canonical Analysis
Description: This function calculates the independent contribution of each explanatory variable to explained variation (R-squared) on RDA,CCA and db-RDA, applying the hierarchy algorithm of Chevan, A. and Sutherland, M. 1991 Hierarchical Partitioning.The American Statistician, 90-96 <DOI:10.1080/00031305.1991.10475776>.
Author: Jiangshan Lai,Pedro Peres-neto
Maintainer: Jiangshan Lai <lai@ibcas.ac.cn>

Diff between rdacca.hp versions 0.1.0 dated 2020-12-04 and 0.2.0 dated 2021-01-18

 rdacca.hp-0.1.0/rdacca.hp/R/CanonicalFunctions_withResiduals.r |only
 rdacca.hp-0.2.0/rdacca.hp/DESCRIPTION                          |   10 ++--
 rdacca.hp-0.2.0/rdacca.hp/MD5                                  |   21 ++++++----
 rdacca.hp-0.2.0/rdacca.hp/NAMESPACE                            |   13 +++++-
 rdacca.hp-0.2.0/rdacca.hp/R/CanonicalFunctions.r               |only
 rdacca.hp-0.2.0/rdacca.hp/R/GMI.r                              |only
 rdacca.hp-0.2.0/rdacca.hp/R/creatbin.r                         |    5 ++
 rdacca.hp-0.2.0/rdacca.hp/R/genList.r                          |    6 +-
 rdacca.hp-0.2.0/rdacca.hp/R/globals.r                          |only
 rdacca.hp-0.2.0/rdacca.hp/R/rdacca.hp.r                        |   20 +++++++--
 rdacca.hp-0.2.0/rdacca.hp/man/Canonical.Rsq.Rd                 |only
 rdacca.hp-0.2.0/rdacca.hp/man/GMI.Rd                           |only
 rdacca.hp-0.2.0/rdacca.hp/man/creatbin.Rd                      |only
 rdacca.hp-0.2.0/rdacca.hp/man/genList.Rd                       |only
 rdacca.hp-0.2.0/rdacca.hp/man/odd.Rd                           |only
 rdacca.hp-0.2.0/rdacca.hp/man/rdacca.hp.Rd                     |   12 +++--
 16 files changed, 62 insertions(+), 25 deletions(-)

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Package outliertree updated to version 1.3.4 with previous version 1.3.1 dated 2020-12-11

Title: Explainable Outlier Detection Through Decision Tree Conditioning
Description: Will try to fit decision trees that try to "predict" values for each column based on the values of each other column. Along the way, each time a split is evaluated, it will take the observations that fall into each branch as a homogeneous cluster in which it will search for outliers in the 1-d distribution of the column being predicted. Outliers are determined according to confidence intervals in this 1-d distribution, and need to have a large gap with respect to the next observation in sorted order to be flagged as outliers. Since outliers are searched for in a decision tree branch, it will know the conditions that make it a rare observation compared to others that meet the same conditions, and the conditions will always be correlated with the target variable (as it's being predicted from them). Full procedure is described in Cortes (2020) <arXiv:2001.00636>. Loosely based on the 'GritBot' <https://www.rulequest.com/gritbot-info.html> software.
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

Diff between outliertree versions 1.3.1 dated 2020-12-11 and 1.3.4 dated 2021-01-18

 DESCRIPTION                   |    8 ++--
 MD5                           |   34 ++++++++++---------
 NAMESPACE                     |   28 +++++++++------
 R/helpers.R                   |    4 +-
 R/obj_methods.R               |    3 +
 R/outliertree.R               |   49 ++++++++++++++++++++++++++-
 man/as.list.outlieroutputs.Rd |only
 man/outlier.tree.Rd           |    5 ++
 man/predict.outliertree.Rd    |    3 +
 man/print.outlieroutputs.Rd   |    2 -
 man/print.outliertree.Rd      |    3 +
 man/sub-.outlieroutputs.Rd    |only
 man/summary.outliertree.Rd    |    3 +
 src/Makevars                  |    1 
 src/RcppExports.cpp           |    5 --
 src/Rwrapper.cpp              |   29 ++++++++++++----
 src/fit_model.cpp             |   26 ++++++++++++++
 src/misc.cpp                  |   74 ++++++++++++++++++++++++++++++++++++++++++
 src/outlier_tree.h            |   23 +++++++++++++
 19 files changed, 249 insertions(+), 51 deletions(-)

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Package comprehenr updated to version 0.6.9 with previous version 0.6.8 dated 2020-07-22

Title: List Comprehensions
Description: Provides 'Python'-style list comprehensions. List comprehension expressions use usual loops (for(), while() and repeat()) and usual if() as list producers. In many cases it gives more concise notation than standard "*apply + filter" strategy.
Author: Gregory Demin [aut, cre]
Maintainer: Gregory Demin <gdemin@gmail.com>

Diff between comprehenr versions 0.6.8 dated 2020-07-22 and 0.6.9 dated 2021-01-18

 DESCRIPTION                  |    6 ++---
 MD5                          |   12 +++++-----
 NEWS                         |    6 ++++-
 R/to_list.R                  |   36 ++++++++++++++++++++++----------
 build/vignette.rds           |binary
 inst/doc/Introduction.html   |   48 +++++++++++++++++++++++++++++++++++++++++++
 inst/tinytest/test_to_list.R |   37 +++++++++++++++++++++++++++++++++
 7 files changed, 124 insertions(+), 21 deletions(-)

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