Thu, 27 Jan 2022

Package nflreadr updated to version 1.1.3 with previous version 1.1.2 dated 2021-12-08

Title: Download 'nflverse' Data
Description: A minimal package for downloading data from 'GitHub' repositories of the 'nflverse' project.
Author: Tan Ho [aut, cre, cph] (<https://orcid.org/0000-0001-8388-5155>), Sebastian Carl [aut], John Edwards [ctb], Ben Baldwin [ctb], Thomas Mock [ctb], Lee Sharpe [ctb]
Maintainer: Tan Ho <tan@tanho.ca>

Diff between nflreadr versions 1.1.2 dated 2021-12-08 and 1.1.3 dated 2022-01-27

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Package filearray updated to version 0.1.3 with previous version 0.1.2 dated 2021-11-25

Title: File-Backed Array for Out-of-Memory Computation
Description: Stores large arrays in files to avoid occupying large memories. Implemented with super fast gigabyte-level multi-threaded reading/writing via 'OpenMP'. Supports multiple non-character data types (double, float, complex, integer, logical, and raw).
Author: Zhengjia Wang [aut, cre, cph]
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>

Diff between filearray versions 0.1.2 dated 2021-11-25 and 0.1.3 dated 2022-01-27

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Package elmNNRcpp updated to version 1.0.4 with previous version 1.0.3 dated 2021-05-04

Title: The Extreme Learning Machine Algorithm
Description: Training and predict functions for Single Hidden-layer Feedforward Neural Networks (SLFN) using the Extreme Learning Machine (ELM) algorithm. The ELM algorithm differs from the traditional gradient-based algorithms for very short training times (it doesn't need any iterative tuning, this makes learning time very fast) and there is no need to set any other parameters like learning rate, momentum, epochs, etc. This is a reimplementation of the 'elmNN' package using 'RcppArmadillo' after the 'elmNN' package was archived. For more information, see "Extreme learning machine: Theory and applications" by Guang-Bin Huang, Qin-Yu Zhu, Chee-Kheong Siew (2006), Elsevier B.V, <doi:10.1016/j.neucom.2005.12.126>.
Author: Lampros Mouselimis [aut, cre] (<https://orcid.org/0000-0002-8024-1546>), Alberto Gosso [aut], Edwin de Jonge [ctb] (<https://orcid.org/0000-0002-6580-4718>, Github Contributor)
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>

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Package tufte updated to version 0.12 with previous version 0.11 dated 2021-12-18

Title: Tufte's Styles for R Markdown Documents
Description: Provides R Markdown output formats to use Tufte styles for PDF and HTML output.
Author: Yihui Xie [aut] (<https://orcid.org/0000-0003-0645-5666>), Christophe Dervieux [ctb, cre] (<https://orcid.org/0000-0003-4474-2498>), JJ Allaire [aut], Andrzej Oles [ctb], Dave Liepmann [ctb] (Tufte CSS in inst/rmarkdown/templates/tufte_html/resources), RStudio, PBC [cph]
Maintainer: Christophe Dervieux <cderv@rstudio.com>

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Package RcppThread updated to version 2.0.1 with previous version 2.0.0 dated 2022-01-25

Title: R-Friendly Threading in C++
Description: Provides a C++11-style thread class and thread pool that can safely be interrupted from R. See Nagler (2021) <doi:10.18637/jss.v097.c01>.
Author: Thomas Nagler [aut, cre] (<https://orcid.org/0000-0003-1855-0046>)
Maintainer: Thomas Nagler <mail@tnagler.com>

Diff between RcppThread versions 2.0.0 dated 2022-01-25 and 2.0.1 dated 2022-01-27

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Package randomizr updated to version 0.22.0 with previous version 0.20.0 dated 2019-09-06

Title: Easy-to-Use Tools for Common Forms of Random Assignment and Sampling
Description: Generates random assignments for common experimental designs and random samples for common sampling designs.
Author: Alexander Coppock [aut, cre] (<https://orcid.org/0000-0002-5733-2386>), Jasper Cooper [ctb] (<https://orcid.org/0000-0002-8639-3188>), Neal Fultz [ctb] (C version of restricted partitions), Graeme Blair [ctb] (<https://orcid.org/0000-0001-9164-2102>)
Maintainer: Alexander Coppock <acoppock@gmail.com>

Diff between randomizr versions 0.20.0 dated 2019-09-06 and 0.22.0 dated 2022-01-27

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Package Platypus updated to version 3.3.2 with previous version 3.2.3 dated 2021-10-19

Title: Single-Cell Immune Repertoire and Gene Expression Analysis
Description: We present 'Platypus', an open-source software platform providing a user-friendly interface to investigate B-cell receptor and T-cell receptor repertoires from scSeq experiments. 'Platypus' provides a framework to automate and ease the analysis of single-cell immune repertoires while also incorporating transcriptional information involving unsupervised clustering, gene expression and gene ontology (Yermanos A, et al (2021) <doi:10.1093/nargab/lqab023>).
Author: Alexander Yermanos [aut, cre], Andreas Agrafiotis [ctb], Raphael Kuhn [ctb], Victor Kreiner [ctb], Damiano Robbiani [ctb], Josephine Yates [ctb], Jiami Han [ctb], Chrysa Papadopoulou [ctb], Cédric Weber [ctb], Danielle Shlesinger [ctb], Raphael Dizerens [ctb]
Maintainer: Alexander Yermanos <ayermanos@gmail.com>

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Package LilRhino updated to version 1.2.1 with previous version 1.2.0 dated 2019-10-31

Title: For Implementation of Feed Reduction, Learning Examples, NLP and Code Management
Description: This is for code management functions, NLP tools, a Monty Hall simulator, and for implementing my own variable reduction technique called Feed Reduction. The Feed Reduction technique is not yet published, but is merely a tool for implementing a series of binary neural networks meant for reducing data into N dimensions, where N is the number of possible values of the response variable.
Author: Travis Barton (2018)
Maintainer: Travis Barton <tbarton@csumb.edu>

Diff between LilRhino versions 1.2.0 dated 2019-10-31 and 1.2.1 dated 2022-01-27

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Package jti updated to version 0.8.2 with previous version 0.8.0 dated 2021-07-05

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

Diff between jti versions 0.8.0 dated 2021-07-05 and 0.8.2 dated 2022-01-27

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New package jetpack with initial version 0.5.1
Package: jetpack
Title: A Friendly Package Manager
Version: 0.5.1
Date: 2022-01-26
Description: Manage project dependencies from your DESCRIPTION file. Create a reproducible virtual environment with minimal additional files in your project. Provides tools to add, remove, and update dependencies as well as install existing dependencies with a single function.
URL: https://github.com/ankane/jetpack
BugReports: https://github.com/ankane/jetpack/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: renv (>= 0.13.1), remotes (>= 2.0.3), desc (>= 1.2.0), docopt (>= 0.4)
Suggests: testthat, withr
NeedsCompilation: no
Packaged: 2022-01-26 11:30:38 UTC; andrew
Author: Andrew Kane [aut, cre]
Maintainer: Andrew Kane <andrew@chartkick.com>
Repository: CRAN
Date/Publication: 2022-01-27 23:20:09 UTC

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Package happign updated to version 0.1.1 with previous version 0.1.0 dated 2022-01-20

Title: R Interface to 'IGN' Web Services
Description: Interface to easily access the National Institute of Geographic and Forestry Information open-source data for any area of interest in France via WFS (shapefile) and WMS (raster) web services <https://geoservices.ign.fr/services-web-experts>.
Author: Paul Carteron [aut, cre] (<https://orcid.org/0000-0002-6942-6662>)
Maintainer: Paul Carteron <carteronpaul@gmail.com>

Diff between happign versions 0.1.0 dated 2022-01-20 and 0.1.1 dated 2022-01-27

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New package haldensify with initial version 0.2.2
Package: haldensify
Title: Highly Adaptive Lasso Conditional Density Estimation
Version: 0.2.2
Maintainer: Nima Hejazi <nh@nimahejazi.org>
Description: An algorithm for flexible conditional density estimation based on application of pooled hazard regression to an artificial repeated measures dataset constructed by discretizing the support of the outcome variable. To facilitate non/semi-parametric estimation of the conditional density, the highly adaptive lasso, a nonparametric regression function shown to reliably estimate a large class of functions at a fast convergence rate, is utilized. The pooled hazards data augmentation formulation implemented was first described by Díaz and van der Laan (2011) <doi:10.2202/1557-4679.1356>. To complement the conditional density estimation utilities, tools for efficient nonparametric inverse probability weighted (IPW) estimation of the causal effects of stochastic shift interventions (modified treatment policies), directly utilizing the density estimation technique for construction of the generalized propensity score, are provided. These IPW estimators utilize undersmoothing (sieve estimation) of the conditional density estimators in order to achieve the non/semi-parametric efficiency bound.
Depends: R (>= 3.2.0)
Imports: stats, utils, dplyr, tibble, ggplot2, data.table, matrixStats, future.apply, assertthat, hal9001 (>= 0.4.1), origami (>= 1.0.3), rsample, rlang, scales, Rdpack
Suggests: testthat, knitr, rmarkdown, stringr, covr, future
License: MIT + file LICENSE
URL: https://github.com/nhejazi/haldensify
BugReports: https://github.com/nhejazi/haldensify/issues
Encoding: UTF-8
VignetteBuilder: knitr
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2022-01-27 16:25:32 UTC; nsh
Author: Nima Hejazi [aut, cre, cph] (<https://orcid.org/0000-0002-7127-2789>), David Benkeser [aut] (<https://orcid.org/0000-0002-1019-8343>), Mark van der Laan [aut, ths] (<https://orcid.org/0000-0003-1432-5511>), Rachael Phillips [ctb] (<https://orcid.org/0000-0002-8474-591X>)
Repository: CRAN
Date/Publication: 2022-01-27 23:30:04 UTC

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Package ClusterR updated to version 1.2.6 with previous version 1.2.5 dated 2021-05-21

Title: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans, K-Medoids and Affinity Propagation Clustering
Description: Gaussian mixture models, k-means, mini-batch-kmeans, k-medoids and affinity propagation clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of 'RcppArmadillo' to speed up the computationally intensive parts of the functions. For more information, see (i) "Clustering in an Object-Oriented Environment" by Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software, <doi:10.18637/jss.v001.i04>; (ii) "Web-scale k-means clustering" by D. Sculley (2010), ACM Digital Library, <doi:10.1145/1772690.1772862>; (iii) "Armadillo: a template-based C++ library for linear algebra" by Sanderson et al (2016), The Journal of Open Source Software, <doi:10.21105/joss.00026>; (iv) "Clustering by Passing Messages Between Data Points" by Brendan J. Frey and Delbert Dueck, Science 16 Feb 2007: Vol. 315, Issue 5814, pp. 972-976, <doi:10.1126/science.1136800>.
Author: Lampros Mouselimis [aut, cre] (<https://orcid.org/0000-0002-8024-1546>), Conrad Sanderson [cph] (Author of the C++ Armadillo library), Ryan Curtin [cph] (Author of the C++ Armadillo library), Siddharth Agrawal [cph] (Author of the C code of the Mini-Batch-Kmeans algorithm (https://github.com/siddharth-agrawal/Mini-Batch-K-Means)), Brendan Frey [cph] (Author of the matlab code of the Affinity propagation algorithm (for commercial use please contact the author of the matlab code)), Delbert Dueck [cph] (Author of the matlab code of the Affinity propagation algorithm), Vitalie Spinu [ctb] (Github Contributor)
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>

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Package clampSeg updated to version 1.1-1 with previous version 1.1-0 dated 2020-08-25

Title: Idealisation of Patch Clamp Recordings
Description: Implements the model-free multiscale idealisation approaches: Jump-Segmentation by MUltiResolution Filter (JSMURF) <doi:10.1109/TNB.2013.2284063>, JUmp Local dEconvolution Segmentation filter (JULES) <doi:10.1109/TNB.2018.2845126> and Heterogeneous Idealization by Local testing and DEconvolution (HILDE) <arXiv:2008.02658>. Further details on how to use them are given in the accompanying vignette.
Author: Pein Florian [aut, cre], Timo Aspelmeier [ctb]
Maintainer: Pein Florian <f.pein@lancaster.ac.uk>

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Package BinSegBstrap updated to version 1.0-1 with previous version 1.0 dated 2019-11-06

Title: Piecewise Smooth Regression by Bootstrapped Binary Segmentation
Description: Provides methods for piecewise smooth regression. A piecewise smooth signal is estimated by applying a bootstrapped test recursively (binary segmentation approach). Each bootstrapped test decides whether the underlying signal is smooth on the currently considered subsegment or contains at least one further change-point.
Author: McDaid Kate [aut], Pein Florian [aut, cre]
Maintainer: Pein Florian <f.pein@lancaster.ac.uk>

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Package bbl updated to version 1.0.0 with previous version 0.4.1 dated 2021-11-18

Title: Boltzmann Bayes Learner
Description: Supervised learning using Boltzmann Bayes model inference, which extends naive Bayes model to include interactions. Enables classification of data into multiple response groups based on a large number of discrete predictors that can take factor values of heterogeneous levels. Either pseudo-likelihood or mean field inference can be used with L2 regularization, cross-validation, and prediction on new data. <doi:10.18637/jss.v101.i05>.
Author: Jun Woo [aut, cre] (<https://orcid.org/0000-0003-3220-2064>)
Maintainer: Jun Woo <junwoo035@gmail.com>

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Package OpenImageR updated to version 1.2.1 with previous version 1.2.0 dated 2021-09-10

Title: An Image Processing Toolkit
Description: Incorporates functions for image preprocessing, filtering and image recognition. The package takes advantage of 'RcppArmadillo' to speed up computationally intensive functions. The histogram of oriented gradients descriptor is a modification of the 'findHOGFeatures' function of the 'SimpleCV' computer vision platform, the average_hash(), dhash() and phash() functions are based on the 'ImageHash' python library. The Gabor Feature Extraction functions are based on 'Matlab' code of the paper, "CloudID: Trustworthy cloud-based and cross-enterprise biometric identification" by M. Haghighat, S. Zonouz, M. Abdel-Mottaleb, Expert Systems with Applications, vol. 42, no. 21, pp. 7905-7916, 2015, <doi:10.1016/j.eswa.2015.06.025>. The 'SLIC' and 'SLICO' superpixel algorithms were explained in detail in (i) "SLIC Superpixels Compared to State-of-the-art Superpixel Methods", Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Suesstrunk, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, num. 11, p. 2274-2282, May 2012, <doi:10.1109/TPAMI.2012.120> and (ii) "SLIC Superpixels", Radhakrishna Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine Suesstrunk, EPFL Technical Report no. 149300, June 2010.
Author: Lampros Mouselimis [aut, cre] (<https://orcid.org/0000-0002-8024-1546>), Sight Machine [cph] (findHOGFeatures function of the SimpleCV computer vision platform), Johannes Buchner [cph] (average_hash, dhash and phash functions of the ImageHash python library), Mohammad Haghighat [cph] (Gabor Feature Extraction), Radhakrishna Achanta [cph] (Author of the C++ code of the SLIC and SLICO algorithms (for commercial use please contact the author))
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>

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Package MetaLandSim updated to version 1.0.9 with previous version 1.0.8 dated 2021-02-16

Title: Landscape and Range Expansion Simulation
Description: Tools to generate random landscape graphs, evaluate species occurrence in dynamic landscapes, simulate future landscape occupation and evaluate range expansion when new empty patches are available (e.g. as a result of climate change). References: Mestre, F., Canovas, F., Pita, R., Mira, A., Beja, P. (2016) <doi:10.1016/j.envsoft.2016.03.007>; Mestre, F., Risk, B., Mira, A., Beja, P., Pita, R. (2017) <doi:10.1016/j.ecolmodel.2017.06.013>; Mestre, F., Pita, R., Mira, A., Beja, P. (2020) <doi:10.1186/s12898-019-0273-5>.
Author: Frederico Mestre, Fernando Canovas, Benjamin Risk, Ricardo Pita, Antonio Mira, Pedro Beja.
Maintainer: Frederico Mestre <mestre.frederico@gmail.com>

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Package did updated to version 2.1.1 with previous version 2.1.0 dated 2021-12-10

Title: Treatment Effects with Multiple Periods and Groups
Description: The standard Difference-in-Differences (DID) setup involves two periods and two groups -- a treated group and untreated group. Many applications of DID methods involve more than two periods and have individuals that are treated at different points in time. This package contains tools for computing average treatment effect parameters in Difference in Differences setups with more than two periods and with variation in treatment timing using the methods developed in Callaway and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>. The main parameters are group-time average treatment effects which are the average treatment effect for a particular group at a a particular time. These can be aggregated into a fewer number of treatment effect parameters, and the package deals with the cases where there is selective treatment timing, dynamic treatment effects, calendar time effects, or combinations of these. There are also functions for testing the Difference in Differences assumption, and plotting group-time average treatment effects.
Author: Brantly Callaway [aut, cre], Pedro H. C. Sant'Anna [aut]
Maintainer: Brantly Callaway <brantly.callaway@uga.edu>

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Package crunch updated to version 1.29.0 with previous version 1.28.2 dated 2021-11-10

Title: Crunch.io Data Tools
Description: The Crunch.io service <https://crunch.io/> provides a cloud-based data store and analytic engine, as well as an intuitive web interface. Using this package, analysts can interact with and manipulate Crunch datasets from within R. Importantly, this allows technical researchers to collaborate naturally with team members, managers, and clients who prefer a point-and-click interface.
Author: Greg Freedman Ellis [aut, cre], Jonathan Keane [aut], Mike Malecki [aut], Neal Richardson [aut], Gordon Shotwell [aut]
Maintainer: Greg Freedman Ellis <greg@crunch.io>

Diff between crunch versions 1.28.2 dated 2021-11-10 and 1.29.0 dated 2022-01-27

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Package blavaan updated to version 0.4-1 with previous version 0.3-18 dated 2021-11-27

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. References: Merkle & Rosseel (2018) <doi:10.18637/jss.v085.i04>; Merkle et al. (2021) <doi:10.18637/jss.v100.i06>.
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 0.3-18 dated 2021-11-27 and 0.4-1 dated 2022-01-27

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New package lboxcox with initial version 1.0
Package: lboxcox
Title: Implementation of Logistic Box-Cox Regression
Version: 1.0
Date: 2022-01-15
Maintainer: Li Xing <sfulxing@gmail.com>
Description: Implements a logistic box-cox model. This model is fully described in Xing, L. et al. (2021) <doi:10.1002/cjs.11587>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Depends: R (>= 2.10)
Imports: survey, maxLik, doParallel, parallel, foreach
NeedsCompilation: no
Packaged: 2022-01-26 22:24:31 UTC; kohlton
Author: Li Xing [cre, aut], Kohlton Booth [aut], Xuekui Zhang [aut], Igor Burstyn [aut], Paul Gustafson [aut]
Repository: CRAN
Date/Publication: 2022-01-27 19:50:02 UTC

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New package gwavr with initial version 0.1.0
Package: gwavr
Title: Get Water Attributes Visually in R
Version: 0.1.0
Description: Provides methods to Get Water Attributes Visually in R ('gwavr'). This allows the user to point and click on areas within the United States and get back hydrological data, e.g. flowlines, catchments, basin boundaries, comids, etc.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, httr, jsonlite, leaflet, leaflet.extras, magrittr, miniUI, nhdplusTools, purrr, scales, sf, shiny, shinyWidgets, tidyr, units, utils, promises
Suggests: spelling
Language: en-US
NeedsCompilation: no
Packaged: 2022-01-25 20:49:39 UTC; joshualerickson
Author: Joshua Erickson [aut, cre]
Maintainer: Joshua Erickson <joshualerickson@gmail.com>
Repository: CRAN
Date/Publication: 2022-01-27 19:40:02 UTC

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New package GREENeR with initial version 0.1.0
Package: GREENeR
Title: Geospatial Regression Equation for European Nutrient Losses (GREEN)
Version: 0.1.0
Author: A. Udias [aut], B. Grizzetti [aut], O. Vigiak [aut], J. Gomez [aut], C. Alfaro [aut, cre], A. Aloe [aut]
Maintainer: C. Alfaro <c.alfarog@gmail.com>
Description: Tools and methods to apply the model Geospatial Regression Equation for European Nutrient losses (GREEN); Grizzetti et al. (2005) <doi:10.1016/j.jhydrol.2004.07.036>; Grizzetti et al. (2008); Grizzetti et al. (2012) <doi:10.1111/j.1365-2486.2011.02576.x>; Grizzetti et al. (2021) <doi:10.1016/j.gloenvcha.2021.102281>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: hydroGOF (>= 0.4-0), FME (>= 1.3.6.1), data.table (>= 1.13.6), reshape2 (>= 1.4.4), ggplot2 (>= 3.3.5), graphics (>= 3.6.1), sf (>= 1.0-2), dplyr (>= 1.0.7), magrittr (>= 2.0.1), tmap (>= 3.3-2), gridExtra (>= 2.3), tidyselect (>= 1.1.0), classInt (>= 0.4-3), grDevices (>= 3.5), networkD3 (>= 0.4), parallelly (>= 1.30.0)
Depends: R (>= 3.5.0)
URL: https://github.com/calfarog/GREENeR
BugReports: https://github.com/calfarog/GREENeR/issues
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-01-26 19:35:19 UTC; urjc
Repository: CRAN
Date/Publication: 2022-01-27 19:40:12 UTC

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New package gps with initial version 1.0
Package: gps
Version: 1.0
Date: 2022-01-27
Title: General P-Splines
Author: Zheyuan Li [aut, cre] (<https://orcid.org/0000-0002-7434-5947>)
Maintainer: Zheyuan Li <zheyuan.li@bath.edu>
Depends: R (>= 4.0.0)
Imports: stats, splines, Matrix, methods, graphics, grDevices
Description: Routines to construct general P-splines for non-uniform B-splines on arbitrary knots, proposed by Li and Cao (2022) <arXiv:2201.06808>. This P-spline variant extends the standard P-splines of Eilers and Marx (1996) <doi:10.1214/ss/1038425655> that are tailored for uniform B-splines on equidistant knots. Includes SparseD() for computing general difference matrices, SparseS() for computing derivative penalty matrix or its sparse root using a sandwich formula, etc. Also includes several demos on B-splines and P-splines. Aims to facilitate other packages to implement general P-splines as a smoothing tool in their model estimation framework.
License: GPL-3
NeedsCompilation: yes
URL: https://github.com/ZheyuanLi/gps
Packaged: 2022-01-26 20:28:19 UTC; lzy
Repository: CRAN
Date/Publication: 2022-01-27 19:40:06 UTC

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New package gofcat with initial version 0.1.1
Package: gofcat
Title: Goodness-of-Fit Measures for Categorical Response Models
Version: 0.1.1
Description: A post-estimation method for categorical response models (CRM). Inputs from objects of class serp(), clm(), polr(), multinom(), mlogit(), vglm() and glm() are currently supported. Available tests include the Hosmer-Lemeshow tests for the binary, multinomial and ordinal logistic regression; the Lipsitz and the Pulkstenis-Robinson tests for the ordinal models. The proportional odds, adjacent-category, and constrained continuation-ratio models are particularly supported at ordinal level. Tests for the proportional odds assumptions in ordinal models are also possible with the Brant and the Likelihood-Ratio tests. Moreover, several summary measures of predictive strength (Pseudo R-squared), and some useful error metrics, including, the brier score, misclassification rate and logloss are also available for the binary, multinomial and ordinal models. Ugba, E. R. and Gertheiss, J. (2018) <http://www.statmod.org/workshops_archive_proceedings_2018.html>.
License: GPL-2
Depends: R (>= 3.2.0)
Imports: methods, utils, crayon, stats, Matrix, epiR, reshape, stringr, VGAM (>= 1.1-4)
Encoding: UTF-8
LazyData: True
Suggests: serp, dfidx, mlogit, nnet, ordinal, MASS, testthat, covr
NeedsCompilation: no
Packaged: 2022-01-27 01:31:33 UTC; EJIKE
Author: Ejike R. Ugba [aut, cre, cph] (<https://orcid.org/0000-0003-2572-0023>)
Maintainer: Ejike R. Ugba <ejike.ugba@outlook.com>
Repository: CRAN
Date/Publication: 2022-01-27 20:00:02 UTC

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New package dwp with initial version 1.0
Package: dwp
Title: Density-Weighted Proportion
Version: 1.0
Date: 2022-01-20
Description: Fit a Poisson regression to carcass distance data and integrate over the searched area at a wind farm to estimate the fraction of carcasses falling in the searched area and format the output for use as the dwp parameter in the 'GenEst' or 'eoa' package for estimating bird and bat mortality, following Dalthorp, et al. (2022) <arXiv:2201.10064>.
Depends: R (>= 3.6.0)
License: CC0
LazyData: true
Encoding: UTF-8
Imports: boot, expint, GenEst, gtools, invgamma, magrittr, MASS, matrixStats, methods, mvtnorm, numDeriv, plotrix, pracma, sf, statmod, VGAM
Suggests: gpclib
NeedsCompilation: no
Packaged: 2022-01-26 19:30:56 UTC; ddalt
Author: Daniel Dalthorp [aut, cre], Manuela Huso [aut]
Maintainer: Daniel Dalthorp <ddalthorp@protonmail.com>
Repository: CRAN
Date/Publication: 2022-01-27 19:40:08 UTC

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Package Nmix updated to version 1.2.0 with previous version 1.1.2 dated 2022-01-12

Title: Bayesian Inference on Univariate Normal Mixtures
Description: A program for Bayesian analysis of univariate normal mixtures with an unknown number of components, following the approach of Richardson and Green (1997) <doi:10.1111/1467-9868.00095>. This makes use of reversible jump Markov chain Monte Carlo methods that are capable of jumping between the parameter sub-spaces corresponding to different numbers of components in the mixture. A sample from the full joint distribution of all unknown variables is thereby generated, and this can be used as a basis for a thorough presentation of many aspects of the posterior distribution.
Author: Peter Green [aut, cre] (<https://orcid.org/0000-0002-4367-4756>)
Maintainer: Peter Green <P.J.Green@bristol.ac.uk>

Diff between Nmix versions 1.1.2 dated 2022-01-12 and 1.2.0 dated 2022-01-27

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Package supernova updated to version 2.5.1 with previous version 2.5.0 dated 2022-01-04

Title: Judd, McClelland, & Ryan Formatting for ANOVA Output
Description: Produces ANOVA tables in the format used by Judd, McClelland, and Ryan (2017, ISBN: 978-1138819832) in their introductory textbook, Data Analysis. This includes proportional reduction in error and formatting to improve ease the transition between the book and R.
Author: Adam Blake [cre, aut] (<https://orcid.org/0000-0001-7881-8652>), Jeff Chrabaszcz [aut], Ji Son [aut] (<https://orcid.org/0000-0002-4258-4791>), Jim Stigler [aut] (<https://orcid.org/0000-0001-6107-7827>)
Maintainer: Adam Blake <adamblake@g.ucla.edu>

Diff between supernova versions 2.5.0 dated 2022-01-04 and 2.5.1 dated 2022-01-27

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Package dipsaus updated to version 0.2.0 with previous version 0.1.9 dated 2021-10-13

Title: A Dipping Sauce for Data Analysis and Visualizations
Description: Works as an "add-on" to packages like 'shiny', 'future', as well as 'rlang', and provides utility functions. Just like dipping sauce adding flavors to potato chips or pita bread, 'dipsaus' for data analysis and visualizations adds handy functions and enhancements to popular packages. The goal is to provide simple solutions that are frequently asked for online, such as how to synchronize 'shiny' inputs without freezing the app, or how to get memory size on 'Linux' or 'MacOS' system. The enhancements roughly fall into these four categories: 1. 'shiny' input widgets; 2. high-performance computing using 'RcppParallel' and 'future' package; 3. modify R calls and convert among numbers, strings, and other objects. 4. utility functions to get system information such like CPU chip-set, memory limit, etc.
Author: Zhengjia Wang [aut, cre], John Magnotti [ctb] (Contributed to `rutabaga.R`), Xiang Zhang [ctb] (Contributed to `rutabaga.R`)
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>

Diff between dipsaus versions 0.1.9 dated 2021-10-13 and 0.2.0 dated 2022-01-27

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Package upsetjs updated to version 1.10.11 with previous version 1.10.10 dated 2022-01-04

Title: 'HTMLWidget' Wrapper of 'UpSet.js' for Exploring Large Set Intersections
Description: 'UpSet.js' is a re-implementation of 'UpSetR' to create interactive set visualizations for more than three sets. This is a 'htmlwidget' wrapper around the 'JavaScript' library 'UpSet.js'.
Author: Samuel Gratzl [aut, cre]
Maintainer: Samuel Gratzl <sam@sgratzl.com>

Diff between upsetjs versions 1.10.10 dated 2022-01-04 and 1.10.11 dated 2022-01-27

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Package Tplyr updated to version 0.4.4 with previous version 0.4.3 dated 2021-12-06

Title: A Grammar of Clinical Data Summary
Description: A tool created to simplify the data manipulation necessary to create clinical reports.
Author: Eli Miller [aut] (<https://orcid.org/0000-0002-2127-9456>), Mike Stackhouse [aut, cre] (<https://orcid.org/0000-0001-6030-723X>), Ashley Tarasiewicz [aut], Nathan Kosiba [aut] (<https://orcid.org/0000-0001-5359-4234>), Atorus Research LLC [cph]
Maintainer: Mike Stackhouse <mike.stackhouse@atorusresearch.com>

Diff between Tplyr versions 0.4.3 dated 2021-12-06 and 0.4.4 dated 2022-01-27

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Package ompr.roi updated to version 1.0.0 with previous version 0.8.0 dated 2018-06-11

Title: A Solver for 'ompr' that Uses the R Optimization Infrastructure ('ROI')
Description: A solver for 'ompr' based on the R Optimization Infrastructure ('ROI'). The package makes all solvers in 'ROI' available to solve 'ompr' models. Please see the 'ompr' website <https://dirkschumacher.github.io/ompr/> and package docs for more information and examples on how to use it.
Author: Dirk Schumacher [aut, cre]
Maintainer: Dirk Schumacher <mail@dirk-schumacher.net>

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Package neptune updated to version 0.2.1 with previous version 0.2.0 dated 2022-01-13

Title: MLOps Metadata Store - Experiment Tracking and Model Registry for Production Teams
Description: An interface to Neptune. A metadata store for MLOps, built for teams that run a lot of experiments. It gives you a single place to log, store, display, organize, compare, and query all your model-building metadata. Neptune is used for: • Experiment tracking: Log, display, organize, and compare ML experiments in a single place. • Model registry: Version, store, manage, and query trained models, and model building metadata. • Monitoring ML runs live: Record and monitor model training, evaluation, or production runs live For more information see <https://neptune.ai/>.
Author: Mateusz Dominiak [aut], Rafal Jankowski [aut, cre]
Maintainer: Rafal Jankowski <rafal.jankowski@neptune.ai>

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Package MAGEE updated to version 1.0.2 with previous version 1.0.1 dated 2021-11-18

Title: Mixed Model Association Test for GEne-Environment Interaction
Description: Use a 'glmmkin' class object (GMMAT package) from the null model to perform generalized linear mixed model-based single-variant and variant set main effect tests, gene-environment interaction tests, and joint tests for association, as proposed in Wang et al. (2020) <DOI:10.1002/gepi.22351>.
Author: Xinyu Wang [aut], Han Chen [aut, cre], Duy Pham [aut], Kenneth Westerman [aut]
Maintainer: Han Chen <han.chen.2@uth.tmc.edu>

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Package lemna updated to version 0.9.1 with previous version 0.9.0 dated 2021-12-21

Title: Lemna Ecotox Effect Model
Description: An implementation of model equations and default parameters for the toxicokinetic-toxicodynamic (TKTD) model of the Lemna (duckweed) aquatic plant. Lemna is a standard test macrophyte used in ecotox effect studies. The model was described and published by the SETAC Europe Interest Group Effect Modeling. It is a refined description of the Lemna TKTD model published by Schmitt et al. (2013) <doi:10.1016/j.ecolmodel.2013.01.017>.
Author: Nils Kehrein [aut, cre], SETAC Europe IG Effect Modeling [ccp]
Maintainer: Nils Kehrein <nils.kehrein@gmail.com>

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Package FKSUM updated to version 1.0.0 with previous version 0.1.4 dated 2020-04-29

Title: Fast Kernel Sums
Description: Implements the method of Hofmeyr, D.P. (2021) <DOI:10.1109/TPAMI.2019.2930501> for fast evaluation of univariate kernel smoothers based on recursive computations. Applications to the basic problems of density and regression function estimation are provided, as well as some projection pursuit methods for which the objective is based on non-parametric functionals of the projected density, or conditional density of a response given projected covariates. The package is accompanied by an instructive paper in the Journal of Statistical Software <doi:10.18637/jss.v101.i03>.
Author: David P. Hofmeyr
Maintainer: David P. Hofmeyr <dhofmeyr@sun.ac.za>

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Package disclap updated to version 1.5.1 with previous version 1.5 dated 2014-04-07

Title: Discrete Laplace Exponential Family
Description: The discrete Laplace exponential family for use in fitting generalized linear models.
Author: Mikkel Meyer Andersen and Poul Svante Eriksen
Maintainer: Mikkel Meyer Andersen <mikl@math.aau.dk>

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Package BSL updated to version 3.2.3 with previous version 3.2.2 dated 2021-10-26

Title: Bayesian Synthetic Likelihood
Description: Bayesian synthetic likelihood (BSL, Price et al. (2018) <doi:10.1080/10618600.2017.1302882>) is an alternative to standard, non-parametric approximate Bayesian computation (ABC). BSL assumes a multivariate normal distribution for the summary statistic likelihood and it is suitable when the distribution of the model summary statistics is sufficiently regular. This package provides a Metropolis Hastings Markov chain Monte Carlo implementation of four methods (BSL, uBSL, semiBSL and BSLmisspec) and two shrinkage estimators (graphical lasso and Warton's estimator). uBSL (Price et al. (2018) <doi:10.1080/10618600.2017.1302882>) uses an unbiased estimator to the normal density. A semi-parametric version of BSL (semiBSL, An et al. (2018) <arXiv:1809.05800>) is more robust to non-normal summary statistics. BSLmisspec (Frazier et al. 2019 <arXiv:1904.04551>) estimates the Gaussian synthetic likelihood whilst acknowledging that there may be incompatibility between the model and the observed summary statistic. Shrinkage estimation can help to decrease the number of model simulations when the dimension of the summary statistic is high (e.g., BSLasso, An et al. (2019) <doi:10.1080/10618600.2018.1537928>). Extensions to this package are planned. For a journal article describing how to use this package, see An et al. (2022) <doi:10.18637/jss.v101.i11>.
Author: Ziwen An [aut] (<https://orcid.org/0000-0002-9947-5182>), Leah F. South [aut, cre] (<https://orcid.org/0000-0002-5646-2963>), Christopher C. Drovandi [aut] (<https://orcid.org/0000-0001-9222-8763>)
Maintainer: Leah F. South <l1.south@qut.edu.au>

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Package AgroR updated to version 1.2.6 with previous version 1.2.5 dated 2021-12-03

Title: Experimental Statistics and Graphics for Agricultural Sciences
Description: Performs the analysis of completely randomized experimental designs (CRD), randomized blocks (RBD) and Latin square (LSD), experiments in double and triple factorial scheme (in CRD and RBD), experiments in subdivided plot scheme (in CRD and RBD), subdivided and joint analysis of experiments in CRD and RBD, linear regression analysis, test for two samples. The package performs analysis of variance, ANOVA assumptions and multiple comparison test of means or regression, according to Pimentel-Gomes (2009, ISBN: 978-85-7133-055-9), nonparametric test (Conover, 1999, ISBN: 0471160687), test for two samples, joint analysis of experiments according to Ferreira (2018, ISBN: 978-85-7269-566-4), ANOVA of aligned ranks (Wobbrock, J.O., Findlater, L., Gergle, D., Higgins, JJ (2011), <doi:10.1145/1978942.1978963>) and generalized linear model (glm) for binomial and Poisson family in CRD and RBD (Carvalho, FJ (2019), <doi:10.14393/ufu.te.2019.1244>). It can also be used to obtain descriptive measures and graphics, in addition to correlations and creative graphics used in agricultural sciences (Agronomy, Zootechnics, Food Science and related areas).
Author: Gabriel Danilo Shimizu [aut, cre] (<https://orcid.org/0000-0001-8524-508X>), Rodrigo Yudi Palhaci Marubayashi [aut, ctb] (<https://orcid.org/0000-0003-2778-8654>), Leandro Simoes Azeredo Goncalves [aut, ctb] (<https://orcid.org/0000-0001-9700-9375>)
Maintainer: Gabriel Danilo Shimizu <shimizu@uel.br>

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Package UKFE updated to version 0.2.2 with previous version 0.2.0 dated 2021-10-14

Title: UK Flood Estimation
Description: Functions to implement the methods of the Flood Estimation Handbook (FEH), associated updates and the revitalised flood hydrograph model (ReFH). Currently the package uses NRFA peak flow dataset version 10. Aside from FEH functionality, further hydrological functions are available. Most of the methods implemented in this package are described in one or more of the following: "Flood Estimation Handbook", Centre for Ecology & Hydrology (1999, ISBN:0 948540 94 X). "Flood Estimation Handbook Supplementary Report No. 1", Kjeldsen (2007, ISBN:0 903741 15 7). "Regional Frequency Analysis - an approach based on L-moments", Hosking & Wallis (1997, ISBN: 978 0 521 01940 8). "Proposal of the extreme rank plot for extreme value analysis: with an emphasis on flood frequency studies", Hammond (2019, <doi:10.2166/nh.2019.157>). "Making better use of local data in flood frequency estimation", Environment Agency (2017, ISBN: 978 1 84911 387 8). "Sampling uncertainty of UK design flood estimation" , Hammond (2021, <doi:10.2166/nh.2021.059>). "Improving the FEH statistical procedures for flood frequency estimation", Environment Agency (2008, ISBN: 978 1 84432 920 5). "Low flow estimation in the United Kingdom", Institute of Hydrology (1992, ISBN 0 948540 45 1). Wallingford HydroSolutions, (2016, <http://software.hydrosolutions.co.uk/winfap4/Urban-Adjustment-Procedure-Technical-Note.pdf>). Data from the UK National River Flow Archive (<https://nrfa.ceh.ac.uk/>, terms and conditions: <https://nrfa.ceh.ac.uk/costs-terms-and-conditions>).
Author: Anthony Hammond
Maintainer: Anthony Hammond <agqhammond@gmail.com>

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Package permute updated to version 0.9-7 with previous version 0.9-5 dated 2019-03-12

Title: Functions for Generating Restricted Permutations of Data
Description: A set of restricted permutation designs for freely exchangeable, line transects (time series), and spatial grid designs plus permutation of blocks (groups of samples) is provided. 'permute' also allows split-plot designs, in which the whole-plots or split-plots or both can be freely-exchangeable or one of the restricted designs. The 'permute' package is modelled after the permutation schemes of 'Canoco 3.1' (and later) by Cajo ter Braak.
Author: Gavin L. Simpson [aut, cph, cre] (<https://orcid.org/0000-0002-9084-8413>), R Core Team [cph], Douglas M. Bates [ctb], Jari Oksanen [ctb]
Maintainer: Gavin L. Simpson <ucfagls@gmail.com>

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Package eatGADS updated to version 0.19.1 with previous version 0.18.1 dated 2021-10-06

Title: Data Management of Large Hierarchical Data
Description: Import 'SPSS' data, handle and change 'SPSS' meta data, store and access large hierarchical data in 'SQLite' data bases.
Author: Benjamin Becker [aut, cre], Karoline Sachse [ctb], Johanna Busse [ctb]
Maintainer: Benjamin Becker <b.becker@iqb.hu-berlin.de>

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Package yuima updated to version 1.15.2 with previous version 1.15.0 dated 2022-01-12

Title: The YUIMA Project Package for SDEs
Description: Simulation and Inference for SDEs and Other Stochastic Processes.
Author: YUIMA Project Team
Maintainer: Stefano M. Iacus <stefano.iacus@unimi.it>

Diff between yuima versions 1.15.0 dated 2022-01-12 and 1.15.2 dated 2022-01-27

 DESCRIPTION       |    6 +--
 MD5               |   20 ++++++------
 NEWS              |   90 ++++++++++++++++++++++++++++++------------------------
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 man/cce.Rd        |    3 +
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New package nic with initial version 0.0.1
Package: nic
Title: Nature Inspired Colours
Version: 0.0.1
Description: Color palettes based on nature inspired colours in "Sri Lanka".
URL: https://github.com/thiyangt/nic
BugReports: https://github.com/thiyangt/nic/issues
License: CC0
Encoding: UTF-8
Suggests: knitr, palmerpenguins, rmarkdown, tidyverse
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-01-26 01:54:04 UTC; thiyangashaminitalagala
Author: Thiyanga S. Talagala [aut, cre] (<https://orcid.org/0000-0002-5058-7503>), Janith C. Wanniarachchi [aut], Udeshi Salgado [ctb]
Maintainer: Thiyanga S. Talagala <ttalagala@sjp.ac.lk>
Repository: CRAN
Date/Publication: 2022-01-27 10:30:02 UTC

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Package HH updated to version 3.1-47 with previous version 3.1-43 dated 2020-11-28

Title: Statistical Analysis and Data Display: Heiberger and Holland
Description: Support software for Statistical Analysis and Data Display (Second Edition, Springer, ISBN 978-1-4939-2121-8, 2015) and (First Edition, Springer, ISBN 0-387-40270-5, 2004) by Richard M. Heiberger and Burt Holland. This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The second edition includes redesigned graphics and additional chapters. The authors emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises. All functions introduced in the book are in the package. R code for all examples, both graphs and tables, in the book is included in the scripts directory of the package.
Author: Richard M. Heiberger
Maintainer: Richard M. Heiberger <rmh@temple.edu>

Diff between HH versions 3.1-43 dated 2020-11-28 and 3.1-47 dated 2022-01-27

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 55 files changed, 197 insertions(+), 113 deletions(-)

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New package freqpcr with initial version 0.4.0
Package: freqpcr
Title: Estimates Allele Frequency on qPCR DeltaDeltaCq from Bulk Samples
Version: 0.4.0
Maintainer: Masaaki Sudo <masaaki@sudori.info>
Description: Interval estimation of the population allele frequency from qPCR analysis based on the restriction enzyme digestion (RED)-DeltaDeltaCq method (Osakabe et al. 2017, <doi:10.1016/j.pestbp.2017.04.003>), as well as general DeltaDeltaCq analysis. Compatible with the Cq measurement of DNA extracted from multiple individuals at once, so called "group-testing", this model assumes that the quantity of DNA extracted from an individual organism follows a gamma distribution. Therefore, the point estimate is robust regarding the uncertainty of the DNA yield.
URL: https://github.com/sudoms/freqpcr
Depends: R (>= 3.6), cubature
Imports: methods
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown, remotes
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-01-26 10:57:50 UTC; masaa
Author: Masaaki Sudo [aut, cre] (<https://orcid.org/0000-0001-9834-9857>)
Repository: CRAN
Date/Publication: 2022-01-27 10:30:04 UTC

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New package citationchaser with initial version 0.0.4
Package: citationchaser
Title: Perform Forward and Backwards Chasing in Evidence Syntheses
Version: 0.0.4
Description: In searching for research articles, we often want to obtain lists of references from across studies, and also obtain lists of articles that cite a particular study. In systematic reviews, this supplementary search technique is known as 'citation chasing': forward citation chasing looks for all records citing one or more articles of known relevance; backward citation chasing looks for all records referenced in one or more articles. Traditionally, this process would be done manually, and the resulting records would need to be checked one-by-one against included studies in a review to identify potentially relevant records that should be included in a review. This package contains functions to automate this process by making use of the Lens.org API. An input article list can be used to return a list of all referenced records, and/or all citing records in the Lens.org database (consisting of PubMed, PubMed Central, CrossRef, Microsoft Academic Graph and CORE; <https://www.lens.org>).
Imports: dplyr, httr, jsonlite, maditr, MESS, networkD3, scales, tibble, utils, data.table
Suggests: knitr, rmarkdown
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2022-01-26 16:19:11 UTC; neal.haddaway
Author: Neal Haddaway [aut, cre] (<https://orcid.org/0000-0003-3902-2234>), Matthew Grainger [ctb], Charles Gray [ctb]
Maintainer: Neal Haddaway <nealhaddaway@gmail.com>
Repository: CRAN
Date/Publication: 2022-01-27 10:40:02 UTC

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New package bibs with initial version 1.1.1
Package: bibs
Title: Bayesian Inference for the Birnbaum-Saunders Distribution
Author: Mahdi Teimouri
Maintainer: Mahdi Teimouri <teimouri@aut.ac.ir>
Description: Developed for the following tasks. 1- Simulating and computing the maximum likelihood estimator for the Birnbaum-Saunders (BS) distribution, 2- Computing the Bayesian estimator for the parameters of the BS distribution based on reference prior proposed by Xu and Tang (2010) <doi:10.1016/j.csda.2009.08.004> and conjugate prior. 3- Computing the Bayesian estimator for the BS distribution based on conjugate prior. 4- Computing the Bayesian estimator for the BS distribution based on Jeffrey prior given by Achcar (1993) <doi:10.1016/0167-9473(93)90170-X> 5- Computing the Bayesian estimator for the BS distribution under progressive type-II censoring scheme.
Encoding: UTF-8
License: GPL (>= 2)
Depends: R(>= 3.1.0)
Imports: GIGrvg
Repository: CRAN
Version: 1.1.1
Date: 2022-01-25
NeedsCompilation: no
Packaged: 2022-01-26 15:57:37 UTC; NikPardaz
Date/Publication: 2022-01-27 10:40:05 UTC

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Package popkin updated to version 1.3.17 with previous version 1.3.13 dated 2021-07-27

Title: Estimate Kinship and FST under Arbitrary Population Structure
Description: Provides functions to estimate the kinship matrix of individuals from a large set of biallelic SNPs, and extract inbreeding coefficients and the generalized FST (Wright's fixation index). Method described in Ochoa and Storey (2021) <doi:10.1371/journal.pgen.1009241>.
Author: Alejandro Ochoa [aut, cre] (<https://orcid.org/0000-0003-4928-3403>), John D. Storey [aut] (<https://orcid.org/0000-0001-5992-402X>)
Maintainer: Alejandro Ochoa <alejandro.ochoa@duke.edu>

Diff between popkin versions 1.3.13 dated 2021-07-27 and 1.3.17 dated 2022-01-27

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 23 files changed, 1026 insertions(+), 566 deletions(-)

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New package rasterpic with initial version 0.1.0
Package: rasterpic
Title: Create a Spatial Raster from Plain Images
Version: 0.1.0
Description: Creates a spatial raster, as the ones provided by 'terra', from regular pictures.
License: MIT + file LICENSE
URL: https://dieghernan.github.io/rasterpic/, https://github.com/dieghernan/rasterpic
BugReports: https://github.com/dieghernan/rasterpic/issues
Depends: R (>= 3.6.0)
Imports: png (>= 0.1-5), sf (>= 1.0.0), terra (>= 1.4-22)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), vdiffr (>= 1.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-01-25 15:25:36 UTC; diego
Author: Diego Hernangómez [aut, cre, cph] (<https://orcid.org/0000-0001-8457-4658>)
Maintainer: Diego Hernangómez <diego.hernangomezherrero@gmail.com>
Repository: CRAN
Date/Publication: 2022-01-27 08:30:02 UTC

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New package maybe with initial version 0.1.0
Package: maybe
Title: The Maybe Monad
Version: 0.1.0
Description: The maybe type represents the possibility of some value or nothing. It is often used instead of throwing an error or returning `NULL`. The advantage of using a maybe type over `NULL` is that it is both composable and requires the developer to explicitly acknowledge the potential absence of a value, helping to avoid the existence of unexpected behaviour.
License: MIT + file LICENSE
URL: https://github.com/armcn/maybe, https://armcn.github.io/maybe/
BugReports: https://github.com/armcn/maybe/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0), covr, quickcheck
NeedsCompilation: no
Packaged: 2022-01-25 22:50:53 UTC; mcneil
Author: Andrew McNeil [aut, cre]
Maintainer: Andrew McNeil <andrew.richard.mcneil@gmail.com>
Repository: CRAN
Date/Publication: 2022-01-27 08:50:01 UTC

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New package imaginator with initial version 1.0.0
Package: imaginator
Title: Simulate General Insurance Policies and Losses
Version: 1.0.0
Maintainer: Brian Fannin <bfannin@casact.org>
Description: Simulate general insurance policies, losses and loss emergence. The functions contemplate deterministic and stochastic policy retention and growth scenarios. Retention and growth rates are percentages relative to the expiring portfolio. Claims are simulated for each policy. This is accomplished either be assuming a frequency distribution per development lag or by generating random wait times until claim emergence and settlement. Loss simulation uses standard loss distributions for claim amounts.
License: MPL-2.0 | file LICENSE
Depends: R (>= 3.2.3)
Imports: assertthat, checkmate, distributions3, dplyr, lubridate, magrittr, rlang, stringi, tibble
Suggests: testthat, knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
Encoding: UTF-8
URL: https://github.com/casact/imaginator
NeedsCompilation: no
Packaged: 2022-01-25 19:23:21 UTC; bfannin
Author: Brian Fannin [aut, cre]
Repository: CRAN
Date/Publication: 2022-01-27 08:40:02 UTC

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New package HCV with initial version 1.1.0
Package: HCV
Title: Hierarchical Clustering from Vertex-Links
Description: Hierarchical clustering for spatial data, which requires clustering results not only homogeneous in non-geographical features among samples but also geographically close to each other within a cluster. It modified typically used hierarchical agglomerative clustering algorithms for introducing the spatial homogeneity, by considering geographical locations as vertices and converting spatial adjacency into whether a shared edge exists between a pair of vertices (Tzeng & Hsu, 2022) <arXiv:2201.08302>. The constraints of the vertex links automatically enforce the spatial contiguity property at each step of iterations. In addition, methods to find an appropriate number of clusters and to report cluster members are also provided.
Version: 1.1.0
Date: 2022-01-24
Depends: R (>= 4.0.0)
Imports: BLSM (>= 0.1.0), cluster, geometry (>= 0.4.5), graphics, grDevices, M3C (>= 1.12.0), MASS, Matrix, rgeos (>= 0.5.1), sp (>= 1.4.2)
Suggests: alphahull, knitr, fields (>= 11.4)
Maintainer: ShengLi Tzeng <slt.cmu@gmail.com>
NeedsCompilation: no
License: LGPL-3
Date/Publication: 2022-01-27 08:50:05 UTC
Encoding: UTF-8
Packaged: 2022-01-25 22:30:55 UTC; h0h1
Author: ShengLi Tzeng [cre, aut], Hao-Yun Hsu [aut]
Repository: CRAN

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New package ElliptCopulas with initial version 0.1.1
Package: ElliptCopulas
Title: Inference of Elliptical Distributions and Copulas
Version: 0.1.1
Description: Provides functions for the simulation and the nonparametric estimation of elliptical distributions, meta-elliptical copulas and trans-elliptical distributions, following the article Derumigny and Fermanian (2021) <arXiv:2106.12367>.
License: GPL-3
Encoding: UTF-8
LazyLoad: yes
Depends: R (>= 3.6.0)
Imports: Runuran, pcaPP, Matrix
BugReports: https://github.com/AlexisDerumigny/ElliptCopulas/issues
URL: https://github.com/AlexisDerumigny/ElliptCopulas
NeedsCompilation: no
Packaged: 2022-01-25 17:03:23 UTC; Alexis
Author: Alexis Derumigny [aut, cre] (<https://orcid.org/0000-0002-6163-8097>), Jean-David Fermanian [aut] (<https://orcid.org/0000-0001-5960-5555>)
Maintainer: Alexis Derumigny <a.f.f.derumigny@tudelft.nl>
Repository: CRAN
Date/Publication: 2022-01-27 08:40:05 UTC

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New package caretForecast with initial version 0.0.2
Package: caretForecast
Title: Time Series Forecasting Using Caret Infrastructure
Version: 0.0.2
Description: Recursive time series forecast using Caret infrastructure. The models are selected based on time series cross-validation and forecasting is done recursively.
License: GPL-3
URL: https://github.com/Akai01/caretForecast
BugReports: https://github.com/Akai01/caretForecast/issues
Depends: R (>= 3.2.0)
Imports: forecast (>= 8.15), caret (>= 6.0.88), magrittr (>= 2.0.1), methods (>= 4.1.1)
Suggests: Cubist (>= 0.3.0), knitr (>= 1.29), testthat (>= 2.3.2)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2022-01-25 14:24:04 UTC; resul
Author: Resul Akay [aut, cre]
Maintainer: Resul Akay <resulakay1@gmail.com>
Repository: CRAN
Date/Publication: 2022-01-27 08:20:02 UTC

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New package biodosetools with initial version 3.6.0
Package: biodosetools
Title: An R Shiny Application for Biological Dosimetry
Version: 3.6.0
Description: A tool to perform all different statistical tests and calculations needed by Biological Dosimetry Laboratories.
License: GPL-3
URL: https://biodosetools-team.github.io/biodosetools/, https://github.com/biodosetools-team/biodosetools/
BugReports: https://github.com/biodosetools-team/biodosetools/issues/
Depends: R (>= 3.5.0)
Imports: bsplus, dplyr (>= 1.0.0), ggplot2, magrittr, MASS, maxLik, mixtools, msm, rhandsontable, rlang (>= 0.4.0), rmarkdown, shiny, shinydashboard, shinyWidgets (>= 0.5.0), tidyr (>= 1.0.0), config, golem, htmltools, pkgload, cli
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 3.0.0), covr, knitr, kableExtra, markdown, pander, tinytex, xtable
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-01-25 14:13:46 UTC; aldomann
Author: Alfredo Hernández [aut, cre] (<https://orcid.org/0000-0002-2660-4545>), David Endesfelder [aut], Pere Puig [aut] (<https://orcid.org/0000-0002-6607-9642>)
Maintainer: Alfredo Hernández <aldomann.designs@gmail.com>
Repository: CRAN
Date/Publication: 2022-01-27 08:20:05 UTC

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New package tobit1 with initial version 0.1-2
Package: tobit1
Version: 0.1-2
Date: 2022-01-25
Title: One Equation Tobit Model
Depends: R (>= 4.0.0)
Imports: numDeriv, tibble, Rdpack, Formula, prediction, margins, generics
Suggests: knitr, rmarkdown, testthat, AER, censReg, dplyr, ggplot2, modelsummary, bookdown
Description: A set of estimators and tests for models for which the response is truncated. The package includes a lot of developments following the seminal paper of Tobin (1958) <doi:10.2307/1907382>.
Encoding: UTF-8
License: GPL (>= 2)
URL: https://www.r-project.org
VignetteBuilder: knitr
LazyData: true
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2022-01-25 12:20:55 UTC; yves
Author: Yves Croissant [aut, cre] (<https://orcid.org/0000-0002-4857-7736>)
Maintainer: Yves Croissant <yves.croissant@univ-reunion.fr>
Repository: CRAN
Date/Publication: 2022-01-27 07:40:02 UTC

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Package SpatialVx updated to version 0.9 with previous version 0.8 dated 2021-03-27

Title: Spatial Forecast Verification
Description: Spatial forecast verification refers to verifying weather forecasts when the verification set (forecast and observations) is on a spatial field, usually a high-resolution gridded spatial field. Most of the functions here require the forecast and observed fields to be gridded and on the same grid. For a thorough review of most of the methods in this package, please see Gilleland et al. (2009) <doi: 10.1175/2009WAF2222269.1>.
Author: Eric Gilleland [aut, cre], Kim Elmore [ctb], Caren Marzban [ctb], Matt Pocernich [ctb], Gregor Skok [ctb]
Maintainer: Eric Gilleland <EricG@ucar.edu>

Diff between SpatialVx versions 0.8 dated 2021-03-27 and 0.9 dated 2022-01-27

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 SpatialVx-0.9/SpatialVx/DESCRIPTION                                              |   27 
 SpatialVx-0.9/SpatialVx/MD5                                                      |   49 
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 SpatialVx-0.9/SpatialVx/R/calculate_summed_field.R                               |only
 SpatialVx-0.9/SpatialVx/R/enlarge_matrix.R                                       |only
 SpatialVx-0.9/SpatialVx/R/iwarper.R                                              |  312 +-
 SpatialVx-0.9/SpatialVx/R/plot.warped.R                                          |  154 -
 SpatialVx-0.9/SpatialVx/R/warper.R                                               |  448 +-
 SpatialVx-0.9/SpatialVx/data/datalist                                            |    6 
 SpatialVx-0.9/SpatialVx/man/Aindex.Rd                                            |   11 
 SpatialVx-0.9/SpatialVx/man/Cindex.Rd                                            |   11 
 SpatialVx-0.9/SpatialVx/man/CircleHistogram.Rd                                   |    4 
 SpatialVx-0.9/SpatialVx/man/SpatialVx-internal.Rd                                |    5 
 SpatialVx-0.9/SpatialVx/man/SpatialVx-package.Rd                                 |    2 
 SpatialVx-0.9/SpatialVx/man/datasets.Rd                                          |    6 
 SpatialVx-0.9/SpatialVx/man/imomenter.Rd                                         |    2 
 SpatialVx-0.9/SpatialVx/man/iwarper.Rd                                           |only
 SpatialVx-0.9/SpatialVx/man/surrogater2d.Rd                                      |    2 
 SpatialVx-0.9/SpatialVx/man/vxstats.Rd                                           |    2 
 SpatialVx-0.9/SpatialVx/man/warper.Rd                                            |only
 34 files changed, 1495 insertions(+), 1479 deletions(-)

More information about SpatialVx at CRAN
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Package plotHMM updated to version 2022.1.25 with previous version 2022.1.18 dated 2022-01-19

Title: Plot Hidden Markov Models
Description: Hidden Markov Models are useful for modeling sequential data. This package provides several functions implemented in C++ for explaining the algorithms used for Hidden Markov Models (forward, backward, decoding, learning).
Author: Toby Hocking [aut, cre]
Maintainer: Toby Hocking <toby.hocking@r-project.org>

Diff between plotHMM versions 2022.1.18 dated 2022-01-19 and 2022.1.25 dated 2022-01-27

 DESCRIPTION                    |    6 +++---
 MD5                            |   18 +++++++++---------
 NEWS                           |    8 ++++++++
 inst/doc/compare_depmixS4.html |    8 ++++----
 src/backward.cpp               |    2 +-
 src/forward.cpp                |    4 ++--
 src/multiply.cpp               |    4 ++--
 src/pairwise.cpp               |    4 ++--
 src/transition.cpp             |    4 ++--
 src/viterbi.cpp                |    4 ++--
 10 files changed, 35 insertions(+), 27 deletions(-)

More information about plotHMM at CRAN
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