Wed, 01 Dec 2021

Package multidplyr updated to version 0.1.1 with previous version 0.1.0 dated 2021-02-08

Title: A Multi-Process 'dplyr' Backend
Description: Partition a data frame across multiple worker processes to provide simple multicore parallelism.
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package mecor updated to version 1.0.0 with previous version 0.9.0 dated 2021-01-14

Title: Measurement Error Correction in Linear Models with a Continuous Outcome
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).
Author: Linda Nab
Maintainer: Linda Nab <lindanab4@gmail.com>

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Package rmcorr updated to version 0.4.5 with previous version 0.4.4 dated 2021-08-10

Title: Repeated Measures Correlation
Description: Compute the repeated measures correlation, a statistical technique for determining the overall within-individual relationship among paired measures assessed on two or more occasions, first introduced by Bland and Altman (1995). Includes functions for diagnostics, p-value, effect size with confidence interval including optional bootstrapping, as well as graphing. Also includes several example datasets. For more details, see Bakdash and Marusich (2017) <doi:10.3389/fpsyg.2017.00456>.
Author: Jonathan Z. Bakdash, Laura R. Marusich
Maintainer: Laura R. Marusich <lmarusich@gmail.com>

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Package causaldata updated to version 0.1.3 with previous version 0.1.1 dated 2021-05-20

Title: Example Data Sets for Causal Inference Textbooks
Description: Example data sets to run the example problems from causal inference textbooks. Currently, contains data sets for Huntington-Klein, Nick (2021) "The Effect" <https://theeffectbook.net>, Cunningham, Scott (2021, ISBN-13: 978-0-300-25168-5) "Causal Inference: The Mixtape", and Hernán, Miguel and James Robins (2020) "Causal Inference: What If" <https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/>.
Author: Nick Huntington-Klein [aut, cre] (<https://orcid.org/0000-0002-7352-3991>), Malcolm Barrett [aut] (<https://orcid.org/0000-0003-0299-5825>)
Maintainer: Nick Huntington-Klein <nhuntington-klein@seattleu.edu>

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Package OECD updated to version 0.2.5 with previous version 0.2.4 dated 2019-10-15

Title: Search and Extract Data from the OECD
Description: Search and extract data from the Organization for Economic Cooperation and Development (OECD).
Author: Eric Persson [aut, cre]
Maintainer: Eric Persson <expersso5@gmail.com>

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Package ConfusionTableR updated to version 1.0.4 with previous version 1.0.3 dated 2021-11-01

Title: Confusion Matrix Toolset
Description: Takes the outputs of a 'caret' confusion matrix and allows for the quick conversion of these list items to lists. The intended usage is to allow the tool to work with the outputs of machine learning classification models. This tool works with classification problems for binary and multi-classification problems and allows for the record level conversion of the confusion matrix outputs. This is useful, as it allows quick conversion of these objects for storage in database systems and to track ML model performance over time. Traditionally, this approach has been used for highlighting model representation and feature slippage.
Author: Gary Hutson [aut, cre] (<https://orcid.org/0000-0003-3534-6143>)
Maintainer: Gary Hutson <hutsons-hacks@outlook.com>

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Package ptmixed updated to version 1.1.1 with previous version 1.1.0 dated 2021-11-05

Title: Poisson-Tweedie Generalized Linear Mixed Model
Description: Fits the Poisson-Tweedie generalized linear mixed model described in Signorelli et al. (2021, <doi:10.1177/1471082X20936017>). Likelihood approximation based on adaptive Gauss Hermite quadrature rule.
Author: Mirko Signorelli [aut, cre, cph] (<https://orcid.org/0000-0002-8102-3356>), Pietro Spitali [ctb], Roula Tsonaka [ctb]
Maintainer: Mirko Signorelli <msignorelli.rpackages@gmail.com>

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Package pencal updated to version 1.0.1 with previous version 1.0.0 dated 2021-09-03

Title: Penalized Regression Calibration (PRC)
Description: Computes penalized regression calibration (PRC), a statistical method that allows to predict survival from high-dimensional longitudinal predictors. PRC is described in Signorelli et al. (2021, <doi:10.1002/sim.9178>)).
Author: Mirko Signorelli [aut, cre, cph] (<https://orcid.org/0000-0002-8102-3356>), Pietro Spitali [ctb], Roula Tsonaka [ctb]
Maintainer: Mirko Signorelli <msignorelli.rpackages@gmail.com>

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Package pak updated to version 0.2.0 with previous version 0.1.2.1 dated 2020-11-19

Title: Another Approach to Package Installation
Description: The goal of 'pak' is to make package installation faster and more reliable. In particular, it performs all HTTP operations in parallel, so metadata resolution and package downloads are fast. Metadata and package files are cached on the local disk as well. 'pak' has a dependency solver, so it finds version conflicts before performing the installation. This version of 'pak' supports CRAN, 'Bioconductor' and 'GitHub' packages as well.
Author: Gábor Csárdi [aut, cre], Jim Hester [aut], RStudio [cph]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

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Package REddyProc updated to version 1.3.1 with previous version 1.3.0 dated 2021-10-14

Title: Post Processing of (Half-)Hourly Eddy-Covariance Measurements
Description: Standard and extensible Eddy-Covariance data post-processing (Wutzler et al. (2018) <doi:10.5194/bg-15-5015-2018>) includes uStar-filtering, gap-filling, and flux-partitioning. The Eddy-Covariance (EC) micrometeorological technique quantifies continuous exchange fluxes of gases, energy, and momentum between an ecosystem and the atmosphere. It is important for understanding ecosystem dynamics and upscaling exchange fluxes. (Aubinet et al. (2012) <doi:10.1007/978-94-007-2351-1>). This package inputs pre-processed (half-)hourly data and supports further processing. First, a quality-check and filtering is performed based on the relationship between measured flux and friction velocity (uStar) to discard biased data (Papale et al. (2006) <doi:10.5194/bg-3-571-2006>). Second, gaps in the data are filled based on information from environmental conditions (Reichstein et al. (2005) <doi:10.1111/j.1365-2486.2005.001002.x>). Third, the net flux of carbon dioxide is partitioned into its gross fluxes in and out of the ecosystem by night-time based and day-time based approaches (Lasslop et al. (2010) <doi:10.1111/j.1365-2486.2009.02041.x>).
Author: Department for Biogeochemical Integration at MPI-BGC, Jena, Germany [cph], Thomas Wutzler [aut, cre], Markus Reichstein [aut], Antje Maria Moffat [aut, trl], Olaf Menzer [ctb], Mirco Migliavacca [aut], Kerstin Sickel [ctb, trl], Ladislav <U+0160>igut [ctb]
Maintainer: Thomas Wutzler <twutz@bgc-jena.mpg.de>

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Package likelihoodR updated to version 1.0.7 with previous version 1.0.6 dated 2021-10-29

Title: Likelihood Analyses for Common Statistical Tests
Description: A collection of functions that calculate the log likelihood (support) for a range of statistical tests. Where possible the likelihood function and likelihood interval for the observed data are displayed. The evidential approach used here is based on the book "Likelihood" by A.W.F. Edwards (1992, ISBN-13 : 978-0801844430), "Statistical Evidence" by R. Royall (1997, ISBN-13 : 978-0412044113), S.N. Goodman & R. Royall (2011) <doi:10.2105/AJPH.78.12.1568>, "Understanding Psychology as a Science" by Z. Dienes (2008, ISBN-13 : 978-0230542310), S. Glover & P. Dixon <https://link.springer.com/article/10.3758/BF03196706> and others. This package accompanies "Evidence-Based Statistics" by P. Cahusac (2020, ISBN-13 : 978-1119549802).
Author: Peter Cahusac [aut, cre] (<https://orcid.org/0000-0003-4976-2834>)
Maintainer: Peter Cahusac <peteqsac@gmail.com>

Diff between likelihoodR versions 1.0.6 dated 2021-10-29 and 1.0.7 dated 2021-12-01

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Package radix (with last version 0.6) was removed from CRAN

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

2018-12-09 0.6
2018-09-17 0.5

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Package dfphase1 updated to version 1.1.4 with previous version 1.1.3 dated 2021-02-17

Title: Phase I Control Charts (with Emphasis on Distribution-Free Methods)
Description: Statistical methods for retrospectively detecting changes in location and/or dispersion of univariate and multivariate variables. Data values are assumed to be independent, can be individual (one observation at each instant of time) or subgrouped (more than one observation at each instant of time). Control limits are computed, often using a permutation approach, so that a prescribed false alarm probability is guaranteed without making any parametric assumptions on the stable (in-control) distribution. See G. Capizzi and G. Masarotto (2018) <doi:10.1007/978-3-319-75295-2_1> for an introduction to the package.
Author: Giovanna Capizzi and Guido Masarotto
Maintainer: Giovanna Capizzi <giovanna.capizzi@unipd.it>

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Package alookr updated to version 0.3.5 with previous version 0.3.4 dated 2021-02-22

Title: Model Classifier for Binary Classification
Description: A collection of tools that support data splitting, predictive modeling, and model evaluation. A typical function is to split a dataset into a training dataset and a test dataset. Then compare the data distribution of the two datasets. Another feature is to support the development of predictive models and to compare the performance of several predictive models, helping to select the best model.
Author: Choonghyun Ryu [aut, cre]
Maintainer: Choonghyun Ryu <choonghyun.ryu@gmail.com>

Diff between alookr versions 0.3.4 dated 2021-02-22 and 0.3.5 dated 2021-12-01

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Package stringfish updated to version 0.15.5 with previous version 0.15.4 dated 2021-10-15

Title: Alt String Implementation
Description: Provides an extendable, performant and multithreaded 'alt-string' implementation backed by 'C++' vectors and strings.
Author: Travers Ching [aut, cre, cph], Phillip Hazel [ctb] (Bundled PCRE2 code), Zoltan Herczeg [ctb, cph] (Bundled PCRE2 code), University of Cambridge [cph] (Bundled PCRE2 code), Tilera Corporation [cph] (Stack-less Just-In-Time compiler bundled with PCRE2), Yann Collet [ctb, cph] (Yann Collet is the author of the bundled xxHash code)
Maintainer: Travers Ching <traversc@gmail.com>

Diff between stringfish versions 0.15.4 dated 2021-10-15 and 0.15.5 dated 2021-12-01

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Package relsurv updated to version 2.2-6 with previous version 2.2-5 dated 2021-07-05

Title: Relative Survival
Description: Contains functions for analysing relative survival data, including nonparametric estimators of net (marginal relative) survival, relative survival ratio, crude mortality, methods for fitting and checking additive and multiplicative regression models, transformation approach, methods for dealing with population mortality tables. Work has been described in Pohar Perme, Pavlic (2018) <doi:10.18637/jss.v087.i08>.
Author: Maja Pohar Perme [aut], Damjan Manevski [aut, cre]
Maintainer: Damjan Manevski <damjan.manevski@mf.uni-lj.si>

Diff between relsurv versions 2.2-5 dated 2021-07-05 and 2.2-6 dated 2021-12-01

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New package pedalfast.data with initial version 1.0.0
Package: pedalfast.data
Title: PEDALFAST Data
Version: 1.0.0
Description: Data files and documentation for PEDiatric vALidation oF vAriableS in TBI (PEDALFAST). The data was used in "Functional Status Scale in Children With Traumatic Brain Injury: A Prospective Cohort Study" by Bennett, Dixon, et al (2016) <doi:10.1097/PCC.0000000000000934>.
Language: en-US
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports:
Suggests: car, data.table, digest, dplyr, ggplot2, htmltools, knitr, lubridate, qwraps2 (>= 0.5.0), scales, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-11-30 23:11:23 UTC; peterdewitt
Author: Peter DeWitt [aut, cre] (<https://orcid.org/0000-0002-6391-0795>), Tell Bennet [aut] (<https://orcid.org/0000-0003-1483-4236>)
Maintainer: Peter DeWitt <peter.dewitt@cuanschutz.edu>
Repository: CRAN
Date/Publication: 2021-12-01 11:10:02 UTC

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Package opencpu updated to version 2.2.6 with previous version 2.2.5 dated 2021-08-17

Title: Producing and Reproducing Results
Description: A system for embedded scientific computing and reproducible research with R. The OpenCPU server exposes a simple but powerful HTTP api for RPC and data interchange with R. This provides a reliable and scalable foundation for statistical services or building R web applications. The OpenCPU server runs either as a single-user development server within the interactive R session, or as a multi-user Linux stack based on Apache2. The entire system is fully open source and permissively licensed. The OpenCPU website has detailed documentation and example apps.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between opencpu versions 2.2.5 dated 2021-08-17 and 2.2.6 dated 2021-12-01

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New package nphPower with initial version 1.0.0
Package: nphPower
Title: Sample Size Calculation under Non-Proportional Hazards
Version: 1.0.0
Description: Performs combination tests and sample size calculation for fixed design with survival endpoints using combination tests under either proportional hazards or non-proportional hazards. The combination tests include maximum weighted log-rank test and projection test. The sample size calculation procedure is very flexible, allowing for user-defined hazard ratio function and considering various trial conditions like staggered entry, drop-out etc. Trial simulation function is also provided to facilitate the empirical power calculation. The references for projection test and maximum weighted logrank test include Brendel et al. (2014) <doi:10.1111/sjos.12059> and Cheng and He (2021) <arXiv:2110.03833>. The references for sample size calculation under proportional hazard include Schoenfeld (1981) <doi:10.1093/biomet/68.1.316> and Freedman (1982) <doi:10.1002/sim.4780010204>. The references for calculation under non-proportional hazards include Lakatos (1988) <doi:10.2307/2531910> and Cheng and He (2021) (under review).
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: survival, stats, mvtnorm, MASS, zoo
Suggests: rmarkdown, knitr
URL: https://github.com/hcheng99/nphPower
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-12-01 03:04:02 UTC; hcheng
Author: Huan Cheng [aut, cre] (<https://orcid.org/0000-0002-2552-7656>)
Maintainer: Huan Cheng <hcheng1118@hotmail.com>
Repository: CRAN
Date/Publication: 2021-12-01 11:20:06 UTC

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Package hhsmm updated to version 0.2.3 with previous version 0.2.2 dated 2021-11-23

Title: Hidden Hybrid Markov/Semi-Markov Model Fitting
Description: Develops algorithms for fitting, prediction, simulation and initialization of the hidden hybrid Markov/semi-Markov model, introduced by Guedon (2005) <doi:10.1016/j.csda.2004.05.033>, which also includes several tools for handling missing data, fitting regime sweaching regression and auto-regressive hidden hybrid Markov/semi-Markov model, and many other useful tools.
Author: Morteza Amini [aut, cre, cph], Afarin Bayat [aut]
Maintainer: Morteza Amini <morteza.amini@ut.ac.ir>

Diff between hhsmm versions 0.2.2 dated 2021-11-23 and 0.2.3 dated 2021-12-01

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Package blockmodels updated to version 1.1.5 with previous version 1.1.4 dated 2020-11-23

Title: Latent and Stochastic Block Model Estimation by a 'V-EM' Algorithm
Description: Latent and Stochastic Block Model estimation by a Variational EM algorithm. Various probability distribution are provided (Bernoulli, Poisson...), with or without covariates.
Author: Jean-Benoist Leger <jbleger@hds.utc.fr>, Pierre Barbillon <pierre.barbillon@agroparistech.fr>, Julien Chiquet <julien.chiquet@inrae.fr>
Maintainer: Jean-Benoist Leger <jbleger@hds.utc.fr>

Diff between blockmodels versions 1.1.4 dated 2020-11-23 and 1.1.5 dated 2021-12-01

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New package siqr with initial version 0.8.0
Package: siqr
Title: An R Package for Single-Index Quantile Regression
Version: 0.8.0
Language: en-US
Description: Single-Index Quantile Regression is effective in some scenarios. We provides functions that allow users to fit Single-Index Quantile Regression model. It also provides functions to do prediction, estimate standard errors of the single-index coefficients via bootstrap, and visualize the estimated univariate function. Please see W., Y., Y. (2010) <doi:10.1016/j.jmva.2010.02.003> for details.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: MASS, stats, quantreg, KernSmooth
NeedsCompilation: no
Packaged: 2021-11-30 15:56:13 UTC; tianhaizu
Author: Tianhai Zu [cre], Yan Yu [aut]
Maintainer: Tianhai Zu <zuti@mail.uc.edu>
Repository: CRAN
Date/Publication: 2021-12-01 10:30:02 UTC

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New package regweight with initial version 1.0.1
Package: regweight
Title: Convenience Functions for Implicit Regression Weights
Version: 1.0.1
Description: A simple wrapper for calculating regression weights as defined by Aronow and Samii (2015) <doi:10.1111/ajps.12185>. Given a model object and a term of interest, 'regweight' will calculate implicit regression weights and provide a variety of useful visualizations and summary statistics.
URL: https://github.com/ddimmery/regweight https://ddimmery.github.io/regweight/
BugReports: https://github.com/ddimmery/regweight/issues
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: covr, CBPS, devtools, estimatr, knitr, rmarkdown, sf, testthat (>= 3.0.0), USAboundaries
Imports: checkmate, dplyr, ggplot2, glue, gt, lpdensity, rlang, scales, tidyr, tidyselect
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-11-30 15:04:59 UTC; drewd
Author: Drew Dimmery [aut, cre] (<https://orcid.org/0000-0001-9602-6325>)
Maintainer: Drew Dimmery <drew.dimmery@univie.ac.at>
Repository: CRAN
Date/Publication: 2021-12-01 10:30:05 UTC

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Package precommit updated to version 0.2.0 with previous version 0.1.3 dated 2020-10-10

Title: Pre-Commit Hooks
Description: Useful git hooks for R building on top of the multi-language framework 'pre-commit' for hook management. This package provides git hooks for common tasks like formatting files with 'styler' or spell checking as well as wrapper functions to access the 'pre-commit' executable.
Author: Lorenz Walthert
Maintainer: Lorenz Walthert <lorenz.walthert@icloud.com>

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New package optedr with initial version 1.0.0
Package: optedr
Title: Calculating Optimal and D-Augmented Designs
Version: 1.0.0
Description: Calculates D-, Ds-, A- and I-optimal designs for non-linear models, via an implementation of the cocktail algorithm (Yu, 2011, <doi:10.1007/s11222-010-9183-2>). Compares designs via their efficiency, and D-augments any design with a controlled efficiency. An efficient rounding function has been provided to transform approximate designs to exact designs.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/kezrael/optedr
BugReports: https://github.com/kezrael/optedr/issues
Suggests: testthat (>= 3.0.0), mockery, markdown, tidyverse
Imports: ggplot2, purrr, rlang, crayon, cli, magrittr, dplyr, nleqslv, shiny, DT, shinydashboard, shinyalert, plotly, hrbrthemes, shinyjs, nloptr, orthopolynom
NeedsCompilation: no
Packaged: 2021-11-30 09:11:59 UTC; Carlos.CalleArroyo
Author: Carlos de la Calle-Arroyo [aut, cre] (<https://orcid.org/0000-0002-5099-888X>), Jesús López-Fidalgo [aut] (<https://orcid.org/0000-0001-7502-8188>), Licesio J. Rodríguez-Aragón [aut] (<https://orcid.org/0000-0003-4970-3877>)
Maintainer: Carlos de la Calle-Arroyo <carlos.calle.arroyo@gmail.com>
Repository: CRAN
Date/Publication: 2021-12-01 10:10:05 UTC

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Package nodbi updated to version 0.6.0 with previous version 0.5.1 dated 2021-11-26

Title: 'NoSQL' Database Connector
Description: Simplified document database access and manipulation, providing a common API across supported 'NoSQL' databases 'Elasticsearch', 'CouchDB', 'MongoDB' as well as 'SQLite/JSON1' and 'PostgreSQL'.
Author: Ralf Herold [aut, cre] (<https://orcid.org/0000-0002-8148-6748>), Scott Chamberlain [aut] (<https://orcid.org/0000-0003-1444-9135>), Rich FitzJohn [aut], Jeroen Ooms [aut]
Maintainer: Ralf Herold <ralf.herold@mailbox.org>

Diff between nodbi versions 0.5.1 dated 2021-11-26 and 0.6.0 dated 2021-12-01

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New package huito with initial version 0.1.0
Package: huito
Version: 0.1.0
Title: Flexible and Reproducible Label Designs
Description: An open-source R package to deploys flexible and reproducible labels using layers. The 'huito' package is part of the 'inkaverse' project for developing different procedures and tools used in plant science and experimental designs. Learn more about the 'inkaverse' project at <https://inkaverse.com/>.
Date: 2021-11-30
URL: https://huito.inkaverse.com/, https://github.com/flavjack/huito
BugReports: https://github.com/flavjack/huito/issues/
Depends: magick, cowplot, ggplot2, dplyr
Imports: tidyr, tibble, purrr, sysfonts, showtext, qrcode, pdftools
Suggests: knitr, rmarkdown, gsheet, inti
VignetteBuilder: knitr
License: GPL-3 | file LICENSE
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-11-30 09:34:53 UTC; flavjack
Author: Flavio Lozano-Isla [aut, cre] (<https://orcid.org/0000-0002-0714-669X>)
Maintainer: Flavio Lozano-Isla <flavjack@gmail.com>
Repository: CRAN
Date/Publication: 2021-12-01 10:10:09 UTC

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New package CAMML with initial version 0.1.0
Package: CAMML
Title: Cell-Typing using Variance Adjusted Mahalanobis Distances with Multi-Labeling
Version: 0.1.0
Maintainer: Courtney Schiebout <courtney.t.schiebout.gr@dartmouth.edu>
Description: Creates multi-label cell-types for single-cell RNA-sequencing data based on weighted VAM scoring of cell-type specific gene sets. Schiebout, Frost (2022) <https://psb.stanford.edu/psb-online/proceedings/psb22/schiebout.pdf>.
License: GPL (>= 2)
Copyright: Dartmouth College
Depends: R (>= 3.6.0)
Imports: VAM, Seurat (>= 4.0.0), MASS, Matrix, dplyr, utils, edgeR, org.Hs.eg.db, org.Mm.eg.db, AnnotationDbi, SeuratObject (>= 4.0.0)
Suggests: sctransform (>= 0.3.2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-11-30 14:07:14 UTC; ctschiebout
Author: H. Robert Frost [aut], Courtney Schiebout [aut, cre] (<https://orcid.org/0000-0002-4830-8237>)
Repository: CRAN
Date/Publication: 2021-12-01 10:20:05 UTC

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Package anticlust updated to version 0.6.0 with previous version 0.5.6 dated 2020-11-24

Title: Subset Partitioning via Anticlustering
Description: The method of anticlustering partitions a pool of elements into groups (i.e., anticlusters) with the goal of maximizing between-group similarity or within-group heterogeneity. The anticlustering approach thereby reverses the logic of cluster analysis that strives for high within-group homogeneity and low similarity of the different groups. Computationally, anticlustering is accomplished by maximizing instead of minimizing a clustering objective function, such as the intra-cluster variance (used in k-means clustering) or the sum of pairwise distances within clusters. The function anticlustering() implements exact and heuristic anticlustering algorithms as described in Papenberg and Klau (2021; <doi:10.1037/met0000301>). The exact algorithms require that the GNU linear programming kit (<https://www.gnu.org/software/glpk/glpk.html>) is available and the R package 'Rglpk' (<https://cran.R-project.org/package=Rglpk>) is installed. A bicriterion anticlustering method proposed by Brusco et al. (2020; <doi:10.1111/bmsp.12186>) is available through the function bicriterion_anticlustering(). Some other functions are available to solve classical clustering problems. The function balanced_clustering() applies a cluster analysis under size constraints, i.e., creates equal-sized clusters. The function matching() can be used for (unrestricted, bipartite, or K-partite) matching. The function wce() can be used optimally solve the (weighted) cluster editing problem, also known as correlation clustering, clique partitioning problem or transitivity clustering.
Author: Martin Papenberg [aut, cre] (<https://orcid.org/0000-0002-9900-4268>), Meik Michalke [ctb] (centroid based clustering algorithm), Gunnar W. Klau [ths], Juliane V. Tkotz [ctb] (package logo), Martin Breuer [ctb] (Bicriterion algorithm by Brusco et al.)
Maintainer: Martin Papenberg <martin.papenberg@hhu.de>

Diff between anticlust versions 0.5.6 dated 2020-11-24 and 0.6.0 dated 2021-12-01

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Package smooth updated to version 3.1.4 with previous version 3.1.3 dated 2021-09-22

Title: Forecasting Using State Space Models
Description: Functions implementing Single Source of Error state space models for purposes of time series analysis and forecasting. The package includes ADAM (Svetunkov, 2021, <https://openforecast.org/adam/>), Exponential Smoothing (Hyndman et al., 2008, <doi: 10.1007/978-3-540-71918-2>), SARIMA (Svetunkov & Boylan, 2019 <doi: 10.1080/00207543.2019.1600764>), Complex Exponential Smoothing (Svetunkov & Kourentzes, 2018, <doi: 10.13140/RG.2.2.24986.29123>), Simple Moving Average (Svetunkov & Petropoulos, 2018 <doi: 10.1080/00207543.2017.1380326>) and several simulation functions. It also allows dealing with intermittent demand based on the iETS framework (Svetunkov & Boylan, 2019, <doi: 10.13140/RG.2.2.35897.06242>).
Author: Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK)
Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>

Diff between smooth versions 3.1.3 dated 2021-09-22 and 3.1.4 dated 2021-12-01

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Package rcosmo updated to version 1.1.3 with previous version 1.1.2 dated 2020-02-14

Title: Cosmic Microwave Background Data Analysis
Description: Handling and Analysing Spherical, HEALPix and Cosmic Microwave Background data on a HEALPix grid.
Author: Daniel Fryer [aut, cre] (<https://orcid.org/0000-0001-6032-0522>), Andriy Olenko [aut] (<https://orcid.org/0000-0002-0917-7000>), Ming Li [aut] (<https://orcid.org/0000-0002-1218-2804>), Yuguang Wang [aut]
Maintainer: Daniel Fryer <d.fryer@latrobe.edu.au>

Diff between rcosmo versions 1.1.2 dated 2020-02-14 and 1.1.3 dated 2021-12-01

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New package onemap with initial version 2.8.0
Package: onemap
Title: Construction of Genetic Maps in Experimental Crosses
Version: 2.8.0
Description: Analysis of molecular marker data from model (backcrosses, F2 and recombinant inbred lines) and non-model systems (i. e. outcrossing species). For the later, it allows statistical analysis by simultaneously estimating linkage and linkage phases (genetic map construction) according to Wu et al. (2002) <doi:10.1006/tpbi.2002.1577>. All analysis are based on multipoint approaches using hidden Markov models.
Date: 2021-11-30
Author: Gabriel Margarido [aut], Marcelo Mollinari [aut], Cristiane Taniguti [ctb, cre], Getulio Ferreira [ctb], Rodrigo Amadeu [ctb], Karl Broman [ctb], Katharine Preedy [ctb, cph] (MDS ordering algorithm), Bastian Schiffthaler [ctb, cph] (HMM parallelization), Augusto Garcia [aut, ctb]
LinkingTo: Rcpp (>= 0.10.5)
Depends: R (>= 3.6.0)
Imports: ggplot2 (>= 2.2.1), plotly (>= 4.7.1), reshape2 (>= 1.4.1), Rcpp (>= 0.10.5), graphics, methods, stats, utils, grDevices, smacof, princurve, parallel, dplyr, tidyr, htmlwidgets, ggpubr, RColorBrewer, dendextend, rebus, vcfR (>= 1.6.0)
Suggests: knitr (>= 1.10), rmarkdown, testthat, stringr
VignetteBuilder: knitr
Encoding: UTF-8
License: GPL-3
URL: https://github.com/augusto-garcia/onemap
BugReports: https://github.com/augusto-garcia/onemap/wiki
Maintainer: Cristiane Taniguti <chtaniguti@tamu.edu>
Repository: CRAN
Packaged: 2021-11-30 21:25:58 UTC; chtan
NeedsCompilation: yes
Date/Publication: 2021-12-01 10:00:02 UTC
biocViews:

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New package nowcastDFM with initial version 1.0.0
Package: nowcastDFM
Title: DFMs for Nowcasting
Version: 1.0.0
Description: Run dynamic factor models (DFM) in R. Adapted from Bok et al. (2017) <https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr830.pdf>. The package provides the ability to estimate a DFM model, obtain predictions from estimated models, and obtain the impact of new data releases on model predictions.
Depends: R (>= 3.3.0), dplyr (>= 0.8.0.1), matlab (>= 1.0.2), pracma (>= 2.3.3), signal (>= 0.7-7)
License: GPL-3
Encoding: UTF-8
URL: https://github.com/dhopp1/nowcastDFM/, https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr830.pdf, https://github.com/FRBNY-TimeSeriesAnalysis/Nowcasting
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2021-11-30 09:00:54 UTC; Daniel.Hopp
Author: Daniel Hopp [aut, cre], Fernando Cantu [aut]
Maintainer: Daniel Hopp <daniel.hopp@un.org>
Repository: CRAN
Date/Publication: 2021-12-01 10:00:07 UTC

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Package bigstatsr updated to version 1.5.5 with previous version 1.5.1 dated 2021-04-05

Title: Statistical Tools for Filebacked Big Matrices
Description: Easy-to-use, efficient, flexible and scalable statistical tools. Package bigstatsr provides and uses Filebacked Big Matrices via memory-mapping. It provides for instance matrix operations, Principal Component Analysis, sparse linear supervised models, utility functions and more <doi:10.1093/bioinformatics/bty185>.
Author: Florian Privé [aut, cre], Michael Blum [ths], Hugues Aschard [ths]
Maintainer: Florian Privé <florian.prive.21@gmail.com>

Diff between bigstatsr versions 1.5.1 dated 2021-04-05 and 1.5.5 dated 2021-12-01

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Package RJSplot updated to version 2.7 with previous version 2.5 dated 2017-11-02

Title: Interactive Graphs with R
Description: Creates interactive graphs with 'R'. It joins the data analysis power of R and the visualization libraries of JavaScript in one package.
Author: Carlos Prieto <cprietos@usal.es>, David Barrios <metal@usal.es>
Maintainer: Carlos Prieto <cprietos@usal.es>

Diff between RJSplot versions 2.5 dated 2017-11-02 and 2.7 dated 2021-12-01

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New package weathercan with initial version 0.6.2
Package: weathercan
Title: Download Weather Data from Environment and Climate Change Canada
Version: 0.6.2
Description: Provides means for downloading historical weather data from the Environment and Climate Change Canada website (<https://climate.weather.gc.ca/historical_data/search_historic_data_e.html>). Data can be downloaded from multiple stations and over large date ranges and automatically processed into a single dataset. Tools are also provided to identify stations either by name or proximity to a location.
License: GPL-3
Language: en-CA
BugReports: https://github.com/ropensci/weathercan/issues/
LazyData: TRUE
URL: https://docs.ropensci.org/weathercan/, https://github.com/ropensci/weathercan/
Depends: R (>= 3.3.0)
Imports: dplyr (>= 1.0.0), httr (>= 1.4.2), lubridate (>= 1.7.1), memoise (>= 2.0.0), methods (>= 3.2.2), purrr (>= 0.3.4), rlang (>= 0.1.4), readr (>= 2.0.0), rvest (>= 0.3.4), stringi (>= 1.1.2), stringr (>= 1.4.0), tidyr (>= 1.1.3), tidyselect (>= 1.0.0), xml2 (>= 0.1.2), rappdirs (>= 0.3.3)
Suggests: devtools, ggplot2, htmltools, knitr, leaflet, lutz, mockery, naniar, rmarkdown, sf, sp, testthat, vcr (>= 1.0.2)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-11-30 18:33:58 UTC; steffi
Author: Steffi LaZerte [aut, cre] (<https://orcid.org/0000-0002-7690-8360>), Sam Albers [ctb] (<https://orcid.org/0000-0002-9270-7884>), Nick Brown [ctb] (<https://orcid.org/0000-0002-2719-0671>), Kevin Cazelles [ctb] (<https://orcid.org/0000-0001-6619-9874>)
Maintainer: Steffi LaZerte <steffi@steffi.ca>
Repository: CRAN
Date/Publication: 2021-12-01 08:00:02 UTC

More information about weathercan at CRAN
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Package lsr updated to version 0.5.2 with previous version 0.5.1 dated 2021-09-20

Title: Companion to "Learning Statistics with R"
Description: A collection of tools intended to make introductory statistics easier to teach, including wrappers for common hypothesis tests and basic data manipulation. It accompanies Navarro, D. J. (2015). Learning Statistics with R: A Tutorial for Psychology Students and Other Beginners, Version 0.6.
Author: Danielle Navarro [aut, cre] (<https://orcid.org/0000-0001-7648-6578>)
Maintainer: Danielle Navarro <djnavarro@protonmail.com>

Diff between lsr versions 0.5.1 dated 2021-09-20 and 0.5.2 dated 2021-12-01

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Package greybox updated to version 1.0.2 with previous version 1.0.1 dated 2021-09-22

Title: Toolbox for Model Building and Forecasting
Description: Implements functions and instruments for regression model building and its application to forecasting. The main scope of the package is in variables selection and models specification for cases of time series data. This includes promotional modelling, selection between different dynamic regressions with non-standard distributions of errors, selection based on cross validation, solutions to the fat regression model problem and more. Models developed in the package are tailored specifically for forecasting purposes. So as a results there are several methods that allow producing forecasts from these models and visualising them.
Author: Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK), Yves R. Sagaert [ctb] (Visiting Research at Centre for Marketing Analytics and Forecasting, Lancaster University, UK)
Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>

Diff between greybox versions 1.0.1 dated 2021-09-22 and 1.0.2 dated 2021-12-01

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Package digest updated to version 0.6.29 with previous version 0.6.28 dated 2021-09-23

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

Diff between digest versions 0.6.28 dated 2021-09-23 and 0.6.29 dated 2021-12-01

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Package bcTSNE updated to version 0.11.1 with previous version 0.10.0 dated 2020-04-28

Title: Projected t-SNE for Batch Correction
Description: Implements the projected t-SNE method for batch correction of high-dimensional data. Please see Aliverti et al. (2020) <doi:10.1093/bioinformatics/btaa189> for more information.
Author: Dayne L Filer [aut, cre], Emanuele Aliverti [aut], Jeff Tilson [aut], Kirk C Wilhelmsen [aut], David B Dunson [aut]
Maintainer: Dayne L Filer <dayne.filer@gmail.com>

Diff between bcTSNE versions 0.10.0 dated 2020-04-28 and 0.11.1 dated 2021-12-01

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Package occCite (with last version 0.5.1) was removed from CRAN

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

2021-11-01 0.5.1

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Package litRiddle (with last version 0.4.0) was removed from CRAN

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

2021-11-10 0.4.0

Permanent link
Package bRacatus (with last version 1.0.6) was removed from CRAN

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

2021-11-09 1.0.6

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Package himach updated to version 0.2.3 with previous version 0.2.2 dated 2021-11-21

Title: High Mach Finds Routes for Supersonic Aircraft
Description: For supersonic aircraft, flying subsonic over land, High Mach finds the best route between airports. Allows for coastal buffer and potentially closed regions. Uses a minimal model of aircraft performance: the focus is on time saved versus subsonic flight, rather than on vertical flight profile. For modelling and forecasting, not for planning your flight!
Author: David Marsh [aut, cre], EUROCONTROL [fnd, cph]
Maintainer: David Marsh <david.marsh@eurocontrol.int>

Diff between himach versions 0.2.2 dated 2021-11-21 and 0.2.3 dated 2021-12-01

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Package rnoaa updated to version 1.3.8 with previous version 1.3.7 dated 2021-11-18

Title: 'NOAA' Weather Data from R
Description: Client for many 'NOAA' data sources including the 'NCDC' climate 'API' at <https://www.ncdc.noaa.gov/cdo-web/webservices/v2>, with functions for each of the 'API' 'endpoints': data, data categories, data sets, data types, locations, location categories, and stations. In addition, we have an interface for 'NOAA' sea ice data, the 'NOAA' severe weather inventory, 'NOAA' Historical Observing 'Metadata' Repository ('HOMR') data, 'NOAA' storm data via 'IBTrACS', tornado data via the 'NOAA' storm prediction center, and more.
Author: Scott Chamberlain [aut] (<https://orcid.org/0000-0003-1444-9135>), Daniel Hocking [ctb, cre] (<https://orcid.org/0000-0003-1889-9184>), Brooke Anderson [ctb], Maëlle Salmon [ctb], Adam Erickson [ctb], Nicholas Potter [ctb], Joseph Stachelek [ctb], Alex Simmons [ctb], Karthik Ram [ctb], Hart Edmund [ctb], rOpenSci [fnd] (https://ropensci.org)
Maintainer: Daniel Hocking <djhocking@gmail.com>

Diff between rnoaa versions 1.3.7 dated 2021-11-18 and 1.3.8 dated 2021-12-01

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Package polycor updated to version 0.8-0 with previous version 0.7-10 dated 2019-08-05

Title: Polychoric and Polyserial Correlations
Description: Computes polychoric and polyserial correlations by quick "two-step" methods or ML, optionally with standard errors; tetrachoric and biserial correlations are special cases.
Author: John Fox [aut, cre]
Maintainer: John Fox <jfox@mcmaster.ca>

Diff between polycor versions 0.7-10 dated 2019-08-05 and 0.8-0 dated 2021-12-01

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Package OmicNavigator updated to version 1.8.0 with previous version 1.4.3 dated 2021-08-05

Title: Open-Source Software for 'Omic' Data Analysis and Visualization
Description: A tool for interactive exploration of the results from 'omics' experiments to facilitate novel discoveries from high-throughput biology. The software includes R functions for the 'bioinformatician' to deposit study metadata and the outputs from statistical analyses (e.g. differential expression, enrichment). These results are then exported to an interactive JavaScript dashboard that can be interrogated on the user’s local machine or deployed online to be explored by collaborators. The dashboard includes 'sortable' tables, interactive plots including network visualization, and fine-grained filtering based on statistical significance.
Author: Terrence Ernst [aut] (Web application), John Blischak [aut, cre] (<https://orcid.org/0000-0003-2634-9879>), Paul Nordlund [aut] (Web application), Justin Moore [aut] (UpSet-related functions and web application), Joe Dalen [aut] (Barcode functionality and web application), Akshay Bhamidipati [aut] (Web application), Brett Engelmann [aut], Marco Curado [aut] (Improved plotting capabilities), AbbVie Inc. [cph, fnd]
Maintainer: John Blischak <jdblischak@gmail.com>

Diff between OmicNavigator versions 1.4.3 dated 2021-08-05 and 1.8.0 dated 2021-12-01

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Built and running on Debian GNU/Linux using R, littler and blosxom. Styled with Bootstrap.