Tue, 19 Oct 2021

Package genSurv updated to version 1.0.4 with previous version 1.0.3 dated 2015-11-09

Title: Generating Multi-State Survival Data
Description: Generation of survival data with one (binary) time-dependent covariate. Generation of survival data arising from a progressive illness-death model.
Author: Artur Araujo [aut, cre] (<https://orcid.org/0000-0003-1419-4208>), Luis Meira-Machado [aut] (<https://orcid.org/0000-0002-8577-7665>), Susana Faria [aut] (<https://orcid.org/0000-0001-8014-9902>)
Maintainer: Artur Araujo <artur.stat@gmail.com>

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Package digitalDLSorteR updated to version 0.1.1 with previous version 0.1.0 dated 2021-10-08

Title: Deconvolution of Bulk RNA-Seq Data Based on Deep Learning
Description: Deconvolution of bulk RNA-Seq data using context-specific deconvolution models based on Deep Neural Networks using scRNA-Seq data as input. These models are able to make accurate estimates of the cell composition of bulk RNA-Seq samples from the same context using the advances provided by Deep Learning and the meaningful information provided by scRNA-Seq data. See Torroja and Sanchez-Cabo (2019) <doi:10.3389/fgene.2019.00978> for more details.
Author: Diego Mañanes [aut, cre] (<https://orcid.org/0000-0001-7247-6794>), Carlos Torroja [aut] (<https://orcid.org/0000-0001-8914-3400>), Fatima Sanchez-Cabo [aut] (<https://orcid.org/0000-0003-1881-1664>)
Maintainer: Diego Mañanes <dmananesc@cnic.es>

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Package pricesensitivitymeter updated to version 1.2.2 with previous version 1.2.1 dated 2021-03-21

Title: Van Westendorp Price Sensitivity Meter Analysis
Description: An implementation of the van Westendorp Price Sensitivity Meter in R, which is a survey-based approach to analyze consumer price preferences and sensitivity (van Westendorp 1976, isbn:9789283100386).
Author: Max Alletsee [aut, cre]
Maintainer: Max Alletsee <max.alletsee@gmail.com>

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Package graphicalVAR updated to version 0.3 with previous version 0.2.4 dated 2020-10-23

Title: Graphical VAR for Experience Sampling Data
Description: Estimates within and between time point interactions in experience sampling data, using the Graphical vector autoregression model in combination with regularization. See also Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.
Author: Sacha Epskamp [aut, cre], Eren Asena [ctb]
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package ARPALData updated to version 1.2.1 with previous version 1.2.0 dated 2021-09-12

Title: Retrieving, Managing and Analysing Air Quality and Weather Data for Lombardy (Italy) using ARPA Lombardia Open Database
Description: Contains functions for retrieving, managing and analysing air quality and weather data from Regione Lombardia open database (<https://www.dati.lombardia.it/>). Data are collected by ARPA Lombardia (Lombardia Environmental Protection Agency), Italy, through its ground monitoring network. See the webpage <https://www.arpalombardia.it/Pages/ARPA_Home_Page.aspx> for further information on ARPA Lombardia's activities and history. Data quality (e.g. missing values, exported values, graphical mapping) has been checked involving members of the ARPA Lombardia's office for air quality control. The package makes available observations since 1989 (for weather) and 1996 (for air quality) and are updated with daily frequency by the regional agency.
Author: Paolo Maranzano [aut, cre, cph] (<https://orcid.org/0000-0002-9228-2759>), Andrea Algieri [aut, cph]
Maintainer: Paolo Maranzano <pmaranzano.ricercastatistica@gmail.com>

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Package rcdd updated to version 1.4 with previous version 1.2-2 dated 2019-04-22

Title: Computational Geometry
Description: R interface to (some of) cddlib (<https://github.com/cddlib/cddlib>). Converts back and forth between two representations of a convex polytope: as solution of a set of linear equalities and inequalities and as convex hull of set of points and rays. Also does linear programming and redundant generator elimination (for example, convex hull in n dimensions). All functions can use exact infinite-precision rational arithmetic.
Author: Charles J. Geyer <charlie@stat.umn.edu> and Glen D. Meeden <glen@stat.umn.edu>, incorporates code from cddlib (ver 0.94f) written by Komei Fukuda <fukuda@ifor.math.ethz.ch>
Maintainer: Charles J. Geyer <charlie@stat.umn.edu>

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Package SuperGauss updated to version 2.0.2 with previous version 2.0.1 dated 2020-10-03

Title: Superfast Likelihood Inference for Stationary Gaussian Time Series
Description: Likelihood evaluations for stationary Gaussian time series are typically obtained via the Durbin-Levinson algorithm, which scales as O(n^2) in the number of time series observations. This package provides a "superfast" O(n log^2 n) algorithm written in C++, crossing over with Durbin-Levinson around n = 300. Efficient implementations of the score and Hessian functions are also provided, leading to superfast versions of inference algorithms such as Newton-Raphson and Hamiltonian Monte Carlo. The C++ code provides a Toeplitz matrix class packaged as a header-only library, to simplify low-level usage in other packages and outside of R.
Author: Yun Ling [aut], Martin Lysy [aut, cre]
Maintainer: Martin Lysy <mlysy@uwaterloo.ca>

Diff between SuperGauss versions 2.0.1 dated 2020-10-03 and 2.0.2 dated 2021-10-19

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Package sumFREGAT updated to version 1.2.2 with previous version 1.2.1 dated 2021-02-28

Title: Fast Region-Based Association Tests on Summary Statistics
Description: An adaptation of classical region/gene-based association analysis techniques to the use of summary statistics (P values and effect sizes) and correlations between genetic variants as input. It is a tool to perform the most popular and efficient gene-based tests using the results of genome-wide association (meta-)analyses without having the original genotypes and phenotypes at hand.
Author: Nadezhda M. Belonogova <belon@bionet.nsc.ru> and Gulnara R. Svishcheva <gulsvi@bionet.nsc.ru> with contributions from: Seunggeun Lee (kernel functions), Pierre Lafaye de Micheaux ('davies' method), Minghui Wang, Yiyuan Liu, Shizhong Han (simpleM function), Yaowu Liu (ACAT function), Thomas Lumley ('kuonen' method), and James O. Ramsay (functional data analysis functions)
Maintainer: Nadezhda M. Belonogova <belon@bionet.nsc.ru>

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Package qgraph updated to version 1.9 with previous version 1.6.9 dated 2021-01-28

Title: Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation
Description: Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>.
Author: Sacha Epskamp [aut, cre], Giulio Costantini [aut], Jonas Haslbeck [aut], Adela Isvoranu [aut], Angelique O. J. Cramer [ctb], Lourens J. Waldorp [ctb], Verena D. Schmittmann [ctb], Denny Borsboom [ctb]
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package modeltime.ensemble updated to version 1.0.0 with previous version 0.4.2 dated 2021-07-16

Title: Ensemble Algorithms for Time Series Forecasting with Modeltime
Description: A 'modeltime' extension that implements time series ensemble forecasting methods including model averaging, weighted averaging, and stacking. These techniques are popular methods to improve forecast accuracy and stability. Refer to papers such as "Machine-Learning Models for Sales Time Series Forecasting" Pavlyshenko, B.M. (2019) <doi:10.3390>.
Author: Matt Dancho [aut, cre], Business Science [cph]
Maintainer: Matt Dancho <mdancho@business-science.io>

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Package languageserver updated to version 0.3.12 with previous version 0.3.11 dated 2021-07-22

Title: Language Server Protocol
Description: An implementation of the Language Server Protocol for R. The Language Server protocol is used by an editor client to integrate features like auto completion. See <https://microsoft.github.io/language-server-protocol/> for details.
Author: Randy Lai [aut, cre], Kun Ren [ctb]
Maintainer: Randy Lai <randy.cs.lai@gmail.com>

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Package fairadapt updated to version 0.2.1 with previous version 0.2.0 dated 2021-07-28

Title: Fair Data Adaptation with Quantile Preservation
Description: An implementation of the fair data adaptation with quantile preservation described in Plecko & Meinshausen (2019) <arXiv:1911.06685>. The adaptation procedure uses the specified causal graph to pre-process the given training and testing data in such a way to remove the bias caused by the protected attribute. The procedure uses tree ensembles for quantile regression.
Author: Drago Plecko [aut, cre], Nicolas Bennett [aut]
Maintainer: Drago Plecko <drago.plecko@stat.math.ethz.ch>

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Package NetLogoR updated to version 0.3.9 with previous version 0.3.8 dated 2021-07-10

Title: Build and Run Spatially Explicit Agent-Based Models
Description: Build and run spatially explicit agent-based models using only the R platform. 'NetLogoR' follows the same framework as the 'NetLogo' software (Wilensky, 1999 <http://ccl.northwestern.edu/netlogo/>) and is a translation in R of the structure and functions of 'NetLogo'. 'NetLogoR' provides new R classes to define model agents and functions to implement spatially explicit agent-based models in the R environment. This package allows benefiting of the fast and easy coding phase from the highly developed 'NetLogo' framework, coupled with the versatility, power and massive resources of the R software. Examples of three models (Ants <http://ccl.northwestern.edu/netlogo/models/Ants>, Butterfly (Railsback and Grimm, 2012) and Wolf-Sheep-Predation <http://ccl.northwestern.edu/netlogo/models/WolfSheepPredation>) written using 'NetLogoR' are available. The 'NetLogo' code of the original version of these models is provided alongside. A programming guide inspired from the 'NetLogo' Programming Guide (<https://ccl.northwestern.edu/netlogo/docs/programming.html>) and a dictionary of 'NetLogo' primitives (<https://ccl.northwestern.edu/netlogo/docs/dictionary.html>) equivalences are also available. NOTE: To increment 'time', these functions can use a for loop or can be integrated with a discrete event simulator, such as 'SpaDES' (<https://cran.r-project.org/package=SpaDES>). The suggested package 'fastshp' can be installed with 'install.packages("fastshp", repos = "https://rforge.net", type = "source")'.
Author: Sarah Bauduin [aut] (<https://orcid.org/0000-0002-3252-5894>), Eliot J B McIntire [aut, cre] (<https://orcid.org/0000-0002-6914-8316>), Alex M Chubaty [aut] (<https://orcid.org/0000-0001-7146-8135>), Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada [cph]
Maintainer: Eliot J B McIntire <eliot.mcintire@canada.ca>

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Package Langevin updated to version 1.3.1 with previous version 1.3.0 dated 2021-10-18

Title: Langevin Analysis in One and Two Dimensions
Description: Estimate drift and diffusion functions from time series and generate synthetic time series from given drift and diffusion coefficients.
Author: Philip Rinn [aut, cre], Pedro G. Lind [aut], David Bastine [ctb]
Maintainer: Philip Rinn <philip.rinn@uni-oldenburg.de>

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Package rWind updated to version 1.1.7 with previous version 1.1.5 dated 2020-02-17

Title: Download, Edit and Include Wind and Sea Currents Data in Ecological and Evolutionary Analysis
Description: Tools for download and manage surface wind and sea currents data from the Global Forecasting System <https://www.ncei.noaa.gov/products/weather-climate-models/global-forecast> and to compute connectivity between locations.
Author: Javier Fernández-López [aut, cre], Klaus Schliep [aut], Yurena Arjona [aut]
Maintainer: Javier Fernández-López <jflopez.bio@gmail.com>

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Package cancensus updated to version 0.4.4 with previous version 0.4.3 dated 2021-06-08

Title: Access, Retrieve, and Work with Canadian Census Data and Geography
Description: Integrated, convenient, and uniform access to Canadian Census data and geography retrieved using the 'CensusMapper' API. This package produces analysis-ready tidy data frames and spatial data in multiple formats, as well as convenience functions for working with Census variables, variable hierarchies, and region selection. API keys are freely available with free registration at <https://censusmapper.ca/api>. Census data and boundary geometries are reproduced and distributed on an "as is" basis with the permission of Statistics Canada (Statistics Canada 2001; 2006; 2011; 2016).
Author: Jens von Bergmann [aut] (API creator and maintainer), Dmitry Shkolnik [aut, cre] (Package maintainer, responsible for correspondence), Aaron Jacobs [aut]
Maintainer: Dmitry Shkolnik <shkolnikd@gmail.com>

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Package Ravages updated to version 1.0.0 with previous version 0.1.5 dated 2021-05-12

Title: Rare Variant Analysis and Genetic Simulations
Description: Rare variant association tests: burden tests (Bocher et al. 2019 <doi:10.1002/gepi.22210>) and the Sequence Kernel Association Test (Bocher et al. 2021 <doi:10.1038/s41431-020-00792-8>) in the whole genome; and genetic simulations.
Author: Ozvan Bocher and Hervé Perdry
Maintainer: Ozvan Bocher <bocherozvan@gmail.com>

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Package jstable updated to version 1.0.7 with previous version 1.0.6 dated 2021-07-25

Title: Create Tables from Different Types of Regression
Description: Create regression tables from generalized linear model(GLM), generalized estimating equation(GEE), generalized linear mixed-effects model(GLMM), Cox proportional hazards model, survey-weighted generalized linear model(svyglm) and survey-weighted Cox model results for publication.
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>), Zarathu [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

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Package ggstatsplot updated to version 0.9.0 with previous version 0.8.0 dated 2021-06-09

Title: 'ggplot2' Based Plots with Statistical Details
Description: Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses.
Author: Indrajeet Patil [cre, aut, cph] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package crosstable updated to version 0.2.2 with previous version 0.2.1 dated 2021-03-08

Title: Crosstables for Descriptive Analyses
Description: Create descriptive tables for continuous and categorical variables. Apply summary statistics and counting function, with or without a grouping variable, and create beautiful reports using 'rmarkdown' or 'officer'. You can also compute statistical tests and effect sizes if needed.
Author: Dan Chaltiel [aut, cre] (<https://orcid.org/0000-0003-3488-779X>), David Hajage [ccp]
Maintainer: Dan Chaltiel <dan.chaltiel@gmail.com>

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Package pairwiseComparisons updated to version 3.2.0 with previous version 3.1.6 dated 2021-06-01

Title: Multiple Pairwise Comparison Tests
Description: Multiple pairwise comparison tests on tidy data for one-way analysis of variance for both between-subjects and within-subjects designs. Currently, it supports only the most common types of statistical analyses and tests: parametric (Welch's and Student's t-test), nonparametric (Durbin-Conover and Dunn test), robust (Yuen’s trimmed means test), and Bayes Factor (Student's t-test).
Author: Indrajeet Patil [cre, aut, cph] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package statsExpressions updated to version 1.2.0 with previous version 1.1.0 dated 2021-05-30

Title: Tidy Dataframes and Expressions with Statistical Details
Description: Utilities for producing dataframes with rich details for the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation analyses, contingency table analyses, and meta-analyses. The functions are pipe-friendly and provide a consistent syntax to work with tidy data. These dataframes additionally contain expressions with statistical details, and can be used in graphing packages. This package also forms the statistical processing backend for 'ggstatsplot'.
Author: Indrajeet Patil [cre, aut, cph] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package PMwR updated to version 0.17-0 with previous version 0.16-1 dated 2021-09-18

Title: Portfolio Management with R
Description: Functions and examples for 'Portfolio Management with R': backtesting investment and trading strategies, computing profit/loss and returns, analysing trades, handling lists of transactions, reporting, and more.
Author: Enrico Schumann [aut, cre] (<https://orcid.org/0000-0001-7601-6576>)
Maintainer: Enrico Schumann <es@enricoschumann.net>

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Package solaR updated to version 0.46 with previous version 0.45 dated 2020-01-19

Title: Radiation and Photovoltaic Systems
Description: Calculation methods of solar radiation and performance of photovoltaic systems from daily and intradaily irradiation data sources.
Author: Oscar Perpiñán Lamigueiro [cre, aut] (<https://orcid.org/0000-0002-4134-7196>)
Maintainer: Oscar Perpiñán Lamigueiro <oscar.perpinan@upm.es>

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Package Rd2roxygen updated to version 1.12 with previous version 1.11 dated 2020-06-24

Title: Convert Rd to 'Roxygen' Documentation
Description: Functions to convert Rd to 'roxygen' documentation. It can parse an Rd file to a list, create the 'roxygen' documentation and update the original R script (e.g. the one containing the definition of the function) accordingly. This package also provides utilities that can help developers build packages using 'roxygen' more easily. The 'formatR' package can be used to reformat the R code in the examples sections so that the code will be more readable.
Author: Hadley Wickham [aut], Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>)
Maintainer: Yihui Xie <xie@yihui.name>

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Package RcmdrPlugin.BWS1 updated to version 0.1-5 with previous version 0.1-4 dated 2020-12-17

Title: R Commander Plug-in for Case 1 (Object Case) Best-Worst Scaling
Description: Adds menu items to the R Commander for implementing case 1 (object case) best-worst scaling (BWS1) from designing choice sets to measuring preferences for items. BWS1 is a question-based survey method that constructs various combinations of items (choice sets) using the experimental designs, asks respondents to select the best and worst items in each choice set, and then measures preferences for the items by analyzing the responses. For details on BWS1, refer to Louviere et al. (2015) <doi:10.1017/CBO9781107337855>.
Author: Hideo Aizaki
Maintainer: Hideo Aizaki <azk-r@spa.nifty.com>

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Package logger updated to version 0.2.2 with previous version 0.2.1 dated 2021-07-06

Title: A Lightweight, Modern and Flexible Logging Utility
Description: Inspired by the the 'futile.logger' R package and 'logging' Python module, this utility provides a flexible and extensible way of formatting and delivering log messages with low overhead.
Author: Gergely Daróczi [aut, cre] (<https://orcid.org/0000-0003-3149-8537>), System1 [fnd]
Maintainer: Gergely Daróczi <daroczig@rapporter.net>

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Package tidyseurat updated to version 0.3.0 with previous version 0.2.7 dated 2021-08-25

Title: Brings Seurat to the Tidyverse
Description: It creates an invisible layer that allow to see the 'Seurat' object as tibble and interact seamlessly with the tidyverse.
Author: Stefano Mangiola [aut, cre], Maria Doyle [ctb]
Maintainer: Stefano Mangiola <mangiolastefano@gmail.com>

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Package lm.br updated to version 2.9.4 with previous version 2.9.3 dated 2017-04-27

Title: Linear Model with Breakpoint
Description: Exact significance tests for a changepoint in linear or multiple linear regression. Confidence regions with exact coverage probabilities for the changepoint. Based on Knowles, Siegmund and Zhang (1991) <doi:10.1093/biomet/78.1.15>.
Author: Marc Adams [aut, cre], authors of R function 'lm' [ctb] (general interface), authors of 'lm.gls' [ctb] (interface and R code for covariate weights), U.S. NIST [ctb] (C++ code for TNT::Vector template)
Maintainer: Marc Adams <lm.br.pkg@gmail.com>

Diff between lm.br versions 2.9.3 dated 2017-04-27 and 2.9.4 dated 2021-10-19

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Mon, 18 Oct 2021

Package SPUTNIK updated to version 1.4 with previous version 1.3.3 dated 2021-05-17

Title: SPatially aUTomatic deNoising for Ims toolKit
Description: A set of tools for the peak filtering of mass spectrometry imaging data (MSI or IMS) based on spatial distribution of signal. Given a region-of-interest (ROI), representing the spatial region where the informative signal is expected to be localized, a series of filters determine which peak signals are characterized by an implausible spatial distribution. The filters reduce the dataset dimensionality and increase its information vs noise ratio, improving the quality of the unsupervised analysis results, reducing data dimensionality and simplifying the chemical interpretation.
Author: Paolo Inglese [aut, cre], Goncalo Correia [aut, ctb]
Maintainer: Paolo Inglese <p.inglese@outlook.com>

Diff between SPUTNIK versions 1.3.3 dated 2021-05-17 and 1.4 dated 2021-10-18

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Package rlang updated to version 0.4.12 with previous version 0.4.11 dated 2021-04-30

Title: Functions for Base Types and Core R and 'Tidyverse' Features
Description: A toolbox for working with base types, core R features like the condition system, and core 'Tidyverse' features like tidy evaluation.
Author: Lionel Henry [aut, cre], Hadley Wickham [aut], mikefc [cph] (Hash implementation based on Mike's xxhashlite), Yann Collet [cph] (Author of the embedded xxHash library), RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>

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Package parameters updated to version 0.15.0 with previous version 0.14.0 dated 2021-05-29

Title: Processing of Model Parameters
Description: Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see list of supported models using the function 'insight::supported_models()'), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>, @strengejacke), Dominique Makowski [aut] (<https://orcid.org/0000-0001-5375-9967>, @Dom_Makowski), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Indrajeet Patil [aut] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Søren Højsgaard [aut], Brenton M. Wiernik [aut] (<https://orcid.org/0000-0001-9560-6336>, @bmwiernik), Zen J. Lau [ctb], Vincent Arel-Bundock [ctb] (<https://orcid.org/0000-0003-1995-6531>, @vincentab), Jeffrey Girard [ctb] (<https://orcid.org/0000-0002-7359-3746>, @jeffreymgirard), Christina Maimone [rev], Niels Ohlsen [rev] (@Niels_Bremen)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between parameters versions 0.14.0 dated 2021-05-29 and 0.15.0 dated 2021-10-18

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Package gimme updated to version 0.7-7 with previous version 0.7-6 dated 2021-08-19

Title: Group Iterative Multiple Model Estimation
Description: Data-driven approach for arriving at person-specific time series models. The method first identifies which relations replicate across the majority of individuals to detect signal from noise. These group-level relations are then used as a foundation for starting the search for person-specific (or individual-level) relations. See Gates & Molenaar (2012) <doi:10.1016/j.neuroimage.2012.06.026>.
Author: Stephanie Lane [aut, trl], Kathleen Gates [aut, cre, ccp], Zachary Fisher [aut], Cara Arizmendi [aut], Peter Molenaar [aut, ccp], Michael Hallquist [ctb], Hallie Pike [ctb], Teague Henry [ctb], Kelly Duffy [ctb], Lan Luo [ctb], Adriene Beltz [csp], Aidan Wright [csp], Jonathan Park [ctb], Sebastian Castro Alvarez [ctb]
Maintainer: Kathleen M Gates <gateskm@email.unc.edu>

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Package ecocomDP updated to version 1.2.0 with previous version 1.1.0 dated 2021-07-31

Title: Tools to Create, Use, and Convert ecocomDP Data
Description: Work with the Ecological Community Data Design Pattern. 'ecocomDP' is a flexible data model for harmonizing ecological community surveys, in a research question agnostic format, from source data published across repositories, and with methods that keep the derived data up-to-date as the underlying sources change. Described in O'Brien et al. (2021), <doi:10.1016/j.ecoinf.2021.101374>.
Author: Colin Smith [aut, cre, cph] (<https://orcid.org/0000-0003-2261-9931>), Eric Sokol [aut] (<https://orcid.org/0000-0001-5923-0917>), Margaret O'Brien [aut] (<https://orcid.org/0000-0002-1693-8322>), Matt Bitters [ctb], Melissa Chen [ctb], Savannah Gonzales [ctb], Matt Helmus [ctb], Brendan Hobart [ctb], Ruvi Jaimes [ctb], Lara Janson [ctb], Marta Jarzyna [ctb], Michael Just [ctb], Daijiang Li [ctb], Wynne Moss [ctb], Kari Norman [ctb], Stephanie Parker [ctb], Natalie Robinson [ctb], Thilina Surasinghe [ctb], Kyle Zollo-Venecek [ctb] (<https://orcid.org/0000-0002-1615-590X>)
Maintainer: Colin Smith <colin.smith@wisc.edu>

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Package CLVTools updated to version 0.8.1 with previous version 0.8.0 dated 2021-03-23

Title: Tools for Customer Lifetime Value Estimation
Description: A set of state-of-the-art probabilistic modeling approaches to derive estimates of individual customer lifetime values (CLV). Commonly, probabilistic approaches focus on modelling 3 processes, i.e. individuals' attrition, transaction, and spending process. Latent customer attrition models, which are also known as "buy-'til-you-die models", model the attrition as well as the transaction process. They are used to make inferences and predictions about transactional patterns of individual customers such as their future purchase behavior. Moreover, these models have also been used to predict individuals’ long-term engagement in activities such as playing an online game or posting to a social media platform. The spending process is usually modelled by a separate probabilistic model. Combining these results yields in lifetime values estimates for individual customers. This package includes fast and accurate implementations of various probabilistic models for non-contractual settings (e.g., grocery purchases or hotel visits). All implementations support time-invariant covariates, which can be used to control for e.g., socio-demographics. If such an extension has been proposed in literature, we further provide the possibility to control for time-varying covariates to control for e.g., seasonal patterns. Currently, the package includes the following latent attrition models to model individuals' attrition and transaction process: [1] Pareto/NBD model (Pareto/Negative-Binomial-Distribution), [2] the Extended Pareto/NBD model (Pareto/Negative-Binomial-Distribution with time-varying covariates), [3] the BG/NBD model (Beta-Gamma/Negative-Binomial-Distribution) and the [4] GGom/NBD (Gamma-Gompertz/Negative-Binomial-Distribution). Further, we provide an implementation of the Gamma/Gamma model to model the spending process of individuals.
Author: Patrick Bachmann [cre, aut], Niels Kuebler [aut], Markus Meierer [aut], Jeffrey Naef [aut], Elliot Oblander [aut], Patrik Schilter [aut]
Maintainer: Patrick Bachmann <patrick.bachmann@business.uzh.ch>

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Package abstr updated to version 0.4.0 with previous version 0.3.0 dated 2021-08-19

Title: R Interface to the A/B Street Transport System Simulation Software
Description: Provides functions to convert origin-destination data, represented as straight 'desire lines' in the 'sf' Simple Features class system, into JSON files that can be directly imported into A/B Street <https://www.abstreet.org>, a free and open source tool for simulating urban transport systems and scenarios of change <doi:10.1007/s10109-020-00342-2>.
Author: Nathanael Sheehan [aut, cre] (<https://orcid.org/0000-0002-2779-0976>), Robin Lovelace [aut] (<https://orcid.org/0000-0001-5679-6536>), Trevor Nederlof [aut], Lucas Dias [ctb], Dustin Carlino [aut]
Maintainer: Nathanael Sheehan <nathanaelsheehan@gmail.com>

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Package xfun updated to version 0.27 with previous version 0.26 dated 2021-09-14

Title: Supporting Functions for Packages Maintained by 'Yihui Xie'
Description: Miscellaneous functions commonly used in other packages maintained by 'Yihui Xie'.
Author: Yihui Xie [aut, cre, cph] (<https://orcid.org/0000-0003-0645-5666>), Wush Wu [ctb], Daijiang Li [ctb], Xianying Tan [ctb], Salim Brüggemann [ctb] (<https://orcid.org/0000-0002-5329-5987>), Christophe Dervieux [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package Langevin updated to version 1.3.0 with previous version 1.2.1 dated 2019-01-02

Title: Langevin Analysis in One and Two Dimensions
Description: Estimate drift and diffusion functions from time series and generate synthetic time series from given drift and diffusion coefficients.
Author: Philip Rinn [aut, cre], Pedro G. Lind [aut], David Bastine [ctb]
Maintainer: Philip Rinn <philip.rinn@uni-oldenburg.de>

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Package pillar updated to version 1.6.4 with previous version 1.6.3 dated 2021-09-26

Title: Coloured Formatting for Columns
Description: Provides 'pillar' and 'colonnade' generics designed for formatting columns of data using the full range of colours provided by modern terminals.
Author: Kirill Müller [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

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Package BAMMtools updated to version 2.1.8 with previous version 2.1.7 dated 2019-12-05

Title: Analysis and Visualization of Macroevolutionary Dynamics on Phylogenetic Trees
Description: Provides functions for analyzing and visualizing complex macroevolutionary dynamics on phylogenetic trees. It is a companion package to the command line program BAMM (Bayesian Analysis of Macroevolutionary Mixtures) and is entirely oriented towards the analysis, interpretation, and visualization of evolutionary rates. Functionality includes visualization of rate shifts on phylogenies, estimating evolutionary rates through time, comparing posterior distributions of evolutionary rates across clades, comparing diversification models using Bayes factors, and more.
Author: Dan Rabosky, Mike Grundler, Pascal Title, Carlos Anderson, Jeff Shi, Joseph Brown, Huateng Huang, Jon Mitchell
Maintainer: Pascal Title <ptitle@umich.edu>

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Package wordpiece updated to version 2.0.1 with previous version 1.0.2 dated 2021-02-11

Title: R Implementation of Wordpiece Tokenization
Description: Apply 'Wordpiece' (<arXiv:1609.08144>) tokenization to input text, given an appropriate vocabulary. The 'BERT' (<arXiv:1810.04805>) tokenization conventions are used by default.
Author: Jonathan Bratt [aut, cre] (<https://orcid.org/0000-0003-2859-0076>), Jon Harmon [aut] (<https://orcid.org/0000-0003-4781-4346>), Bedford Freeman & Worth Pub Grp LLC DBA Macmillan Learning [cph]
Maintainer: Jonathan Bratt <jonathan.bratt@macmillan.com>

Diff between wordpiece versions 1.0.2 dated 2021-02-11 and 2.0.1 dated 2021-10-18

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Package txshift updated to version 0.3.6 with previous version 0.3.5 dated 2021-02-07

Title: Efficient Estimation of the Causal Effects of Stochastic Interventions
Description: Efficient estimation of the population-level causal effects of stochastic interventions on a continuous-valued exposure. Both one-step and targeted minimum loss estimators are implemented for the counterfactual mean value of an outcome of interest under an additive modified treatment policy, a stochastic intervention that may depend on the natural value of the exposure. To accommodate settings with outcome-dependent two-phase sampling, procedures incorporating inverse probability of censoring weighting are provided to facilitate the construction of inefficient and efficient one-step and targeted minimum loss estimators. The causal parameter and its estimation were first described by Díaz and van der Laan (2013) <doi:10.1111/j.1541-0420.2011.01685.x>, while the multiply robust estimation procedure and its application to data from two-phase sampling designs is detailed in NS Hejazi, MJ van der Laan, HE Janes, PB Gilbert, and DC Benkeser (2020) <doi:10.1111/biom.13375>. The software package implementation is described in NS Hejazi and DC Benkeser (2020) <doi:10.21105/joss.02447>. Estimation of nuisance parameters may be enhanced through the Super Learner ensemble model in 'sl3', available for download from GitHub using 'remotes::install_github("tlverse/sl3")'.
Author: Nima Hejazi [aut, cre, cph] (<https://orcid.org/0000-0002-7127-2789>), David Benkeser [aut] (<https://orcid.org/0000-0002-1019-8343>), Iván Díaz [ctb] (<https://orcid.org/0000-0001-9056-2047>), Jeremy Coyle [ctb] (<https://orcid.org/0000-0002-9874-6649>), Mark van der Laan [ctb, ths] (<https://orcid.org/0000-0003-1432-5511>)
Maintainer: Nima Hejazi <nh@nimahejazi.org>

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Package TestDataImputation updated to version 2.3 with previous version 2.2 dated 2021-09-02

Title: Missing Item Responses Imputation for Test and Assessment Data
Description: Functions for imputing missing item responses for dichotomous and polytomous test and assessment data. This package enables missing imputation methods that are suitable for test and assessment data, including: listwise (LW) deletion (see De Ayala et al. 2001 <doi:10.1111/j.1745-3984.2001.tb01124.x>), treating as incorrect (IN, see Lord, 1974 <doi: 10.1111/j.1745-3984.1974.tb00996.x>; Mislevy & Wu, 1996 <doi: 10.1002/j.2333-8504.1996.tb01708.x>; Pohl et al., 2014 <doi: 10.1177/0013164413504926>), person mean imputation (PM), item mean imputation (IM), two-way (TW) and response function (RF) imputation, (see Sijtsma & van der Ark, 2003 <doi: 10.1207/s15327906mbr3804_4>), logistic regression (LR) imputation, predictive mean matching (PMM), and expectation–maximization (EM) imputation (see Finch, 2008 <doi: 10.1111/j.1745-3984.2008.00062.x>).
Author: Shenghai Dai [aut, cre], Xiaolin Wang [aut], Dubravka Svetina [aut]
Maintainer: Shenghai Dai <s.dai@wsu.edu>

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Package RVowpalWabbit updated to version 0.0.16 with previous version 0.0.15 dated 2020-08-07

Title: R Interface to the Vowpal Wabbit
Description: The 'Vowpal Wabbit' project is a fast out-of-core learning system sponsored by Microsoft Research (having started at Yahoo! Research) and written by John Langford along with a number of contributors. This R package does not include the distributed computing implementation of the cluster/ directory of the upstream sources. Use of the software as a network service is also not directly supported as the aim is a simpler direct call from R for validation and comparison. Note that this package contains an embedded older version of 'Vowpal Wabbit'. The package 'rvw' at the GitHub repo <https://github.com/rvw-org/rvw-legacy> can provide an alternative using an external 'Vowpal Wabbit' library installation.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package marginaleffects updated to version 0.2.0 with previous version 0.1.0 dated 2021-09-29

Title: Marginal Effects, Marginal Means, Predictions, and Contrasts
Description: Compute, summarize, and plot marginal effects, adjusted predictions, contrasts, and marginal means for a wide variety of models.
Author: Vincent Arel-Bundock [aut, cre] (<https://orcid.org/0000-0003-2042-7063>)
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>

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Package doMIsaul updated to version 1.0.1 with previous version 1.0.0 dated 2021-08-05

Title: Do Multiple Imputation-Based Semi-Supervised and Unsupervised Learning
Description: Algorithms for (i) unsupervised learning for dataset with missing data and/or left-censored data, using multiple imputation and consensus clustering ; (ii) semi-supervised learning with a survival endpoint (right-censored) for complete or incomplete datasets, using multiple imputation and consensus clustering in the latter case. The methods are described in Faucheux et al. (2021) <doi:10.1002/bimj.201900366> and Faucheux et al. (2021) <doi:10.1002/bimj.202000365>, respectively.
Author: Lilith Faucheux [aut, cre], Sylvie Chevret [ths], Matthieu Resche-Rigon [ctb], Marie Perrot-Dockès [ctb], Eric Han [ctb]
Maintainer: Lilith Faucheux <lilith.faucheux@inserm.fr>

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Package dodgr updated to version 0.2.12 with previous version 0.2.11 dated 2021-10-07

Title: Distances on Directed Graphs
Description: Distances on dual-weighted directed graphs using priority-queue shortest paths (Padgham (2019) <doi:10.32866/6945>). Weighted directed graphs have weights from A to B which may differ from those from B to A. Dual-weighted directed graphs have two sets of such weights. A canonical example is a street network to be used for routing in which routes are calculated by weighting distances according to the type of way and mode of transport, yet lengths of routes must be calculated from direct distances.
Author: Mark Padgham [aut, cre], Andreas Petutschnig [aut], Robin Lovelace [ctb], Andrew Smith [ctb], Malcolm Morgan [ctb], Shane Saunders [cph] (Original author of included code for priority heaps)
Maintainer: Mark Padgham <mark.padgham@email.com>

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Package arkdb updated to version 0.0.14 with previous version 0.0.13 dated 2021-10-15

Title: Archive and Unarchive Databases Using Flat Files
Description: Flat text files provide a robust, compressible, and portable way to store tables from databases. This package provides convenient functions for exporting tables from relational database connections into compressed text files and streaming those text files back into a database without requiring the whole table to fit in working memory.
Author: Carl Boettiger [aut, cre, cph] (<https://orcid.org/0000-0002-1642-628X>), Richard FitzJohn [ctb], Brandon Bertelsen [ctb]
Maintainer: Carl Boettiger <cboettig@gmail.com>

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Package argoFloats updated to version 1.0.3 with previous version 1.0.2 dated 2021-09-15

Title: Analysis of Oceanographic Argo Floats
Description: Supports the analysis of oceanographic data recorded by Argo autonomous drifting profiling floats. Functions are provided to (a) download and cache data files, (b) subset data in various ways, (c) handle quality-control flags and (d) plot the results according to oceanographic conventions. A shiny app is provided for easy exploration of datasets. The package is designed to work well with the 'oce' package, providing a wide range of processing capabilities that are particular to oceanographic analysis. See Kelley, Harbin, and Richards (2021) <doi:10.3389/fmars.2021.635922> for more on the scientific context and applications.
Author: Dan Kelley [aut, cre, cph] (<https://orcid.org/0000-0001-7808-5911>), Jaimie Harbin [aut] (<https://orcid.org/0000-0003-3774-3732>), Dewey Dunnington [ctb] (<https://orcid.org/0000-0002-9415-4582>), Clark Richards [ctb] (<https://orcid.org/0000-0002-7833-206X>)
Maintainer: Dan Kelley <dan.kelley@dal.ca>

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Package vcd updated to version 1.4-9 with previous version 1.4-8 dated 2020-09-21

Title: Visualizing Categorical Data
Description: Visualization techniques, data sets, summary and inference procedures aimed particularly at categorical data. Special emphasis is given to highly extensible grid graphics. The package was package was originally inspired by the book "Visualizing Categorical Data" by Michael Friendly and is now the main support package for a new book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer (2015).
Author: David Meyer [aut, cre], Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Kurt Hornik [aut], Florian Gerber [ctb], Michael Friendly [ctb]
Maintainer: David Meyer <David.Meyer@R-project.org>

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Package modeltime updated to version 1.1.0 with previous version 1.0.0 dated 2021-09-14

Title: The Tidymodels Extension for Time Series Modeling
Description: The time series forecasting framework for use with the 'tidymodels' ecosystem. Models include ARIMA, Exponential Smoothing, and additional time series models from the 'forecast' and 'prophet' packages. Refer to "Forecasting Principles & Practice, Second edition" (<https://otexts.com/fpp2/>). Refer to "Prophet: forecasting at scale" (<https://research.fb.com/blog/2017/02/prophet-forecasting-at-scale/>.).
Author: Matt Dancho [aut, cre], Business Science [cph]
Maintainer: Matt Dancho <mdancho@business-science.io>

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More information about modeltime at CRAN
Permanent link

Package DesignLibrary updated to version 0.1.10 with previous version 0.1.8 dated 2021-09-02

Title: Library of Research Designs
Description: A simple interface to build designs using the package 'DeclareDesign'. In one line of code, users can specify the parameters of individual designs and diagnose their properties. The designers can also be used to compare performance of a given design across a range of combinations of parameters, such as effect size, sample size, and assignment probabilities.
Author: Graeme Blair [aut], Jasper Cooper [aut, cre], Alexander Coppock [aut], Macartan Humphreys [aut], Clara Bicalho [aut], Neal Fultz [aut], Lily Medina [aut]
Maintainer: Jasper Cooper <jjc2247@columbia.edu>

Diff between DesignLibrary versions 0.1.8 dated 2021-09-02 and 0.1.10 dated 2021-10-18

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More information about DesignLibrary at CRAN
Permanent link

Package cvam updated to version 0.9.2 with previous version 0.9.1 dated 2021-10-01

Title: Coarsened Variable Modeling
Description: Extends R's implementation of categorical variables (factors) to handle coarsened observations; implements log-linear models for coarsened categorical data, including latent-class models. Detailed information and examples are provided in the package vignettes.
Author: Joseph L. Schafer <Joseph.L.Schafer@census.gov>
Maintainer: Joseph L. Schafer <Joseph.L.Schafer@census.gov>

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Package belg updated to version 1.5.0 with previous version 1.4.1 dated 2020-08-31

Title: Boltzmann Entropy of a Landscape Gradient
Description: Calculates the Boltzmann entropy of a landscape gradient. This package uses the analytical method created by Gao, P., Zhang, H. and Li, Z., 2018 (<doi:10.1111/tgis.12315>) and by Gao, P. and Li, Z., 2019 (<doi:10.1007/s10980-019-00854-3>). It also extend the original ideas by allowing calculations on data with missing values.
Author: Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>), Space Informatics Lab [cph]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

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Package HSAUR3 updated to version 1.0-12 with previous version 1.0-11 dated 2021-04-07

Title: A Handbook of Statistical Analyses Using R (3rd Edition)
Description: Functions, data sets, analyses and examples from the third edition of the book ''A Handbook of Statistical Analyses Using R'' (Torsten Hothorn and Brian S. Everitt, Chapman & Hall/CRC, 2014). The first chapter of the book, which is entitled ''An Introduction to R'', is completely included in this package, for all other chapters, a vignette containing all data analyses is available. In addition, Sweave source code for slides of selected chapters is included in this package (see HSAUR3/inst/slides). The publishers web page is '<http://www.crcpress.com/product/isbn/9781482204582>'.
Author: Torsten Hothorn and Brian S. Everitt
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package XBRL updated to version 0.99.19 with previous version 0.99.18 dated 2017-03-28

Title: Extraction of Business Financial Information from 'XBRL' Documents
Description: Functions to extract business financial information from an Extensible Business Reporting Language ('XBRL') instance file and the associated collection of files that defines its 'Discoverable' Taxonomy Set ('DTS').
Author: Roberto Bertolusso
Maintainer: Roberto Bertolusso <rbertolusso@rice.edu>

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Package set6 updated to version 0.2.4 with previous version 0.2.3 dated 2021-07-25

Title: R6 Mathematical Sets Interface
Description: An object-oriented package for mathematical sets, upgrading the current gold-standard {sets}. Many forms of mathematical sets are implemented, including (countably finite) sets, tuples, intervals (countably infinite or uncountable), and fuzzy variants. Wrappers extend functionality by allowing symbolic representations of complex operations on sets, including unions, (cartesian) products, exponentiation, and differences (asymmetric and symmetric).
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>), Franz Kiraly [aut]
Maintainer: Raphael Sonabend <raphaelsonabend@gmail.com>

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Package rotasym updated to version 1.1.3 with previous version 1.1.2 dated 2021-08-19

Title: Tests for Rotational Symmetry on the Hypersphere
Description: Implementation of the tests for rotational symmetry on the hypersphere proposed in García-Portugués, Paindaveine and Verdebout (2020) <doi:10.1080/01621459.2019.1665527>. The package also implements the proposed distributions on the hypersphere, based on the tangent-normal decomposition, and allows for the replication of the data application considered in the paper.
Author: Eduardo García-Portugués [aut, cre] (<https://orcid.org/0000-0002-9224-4111>), Davy Paindaveine [aut], Thomas Verdebout [aut]
Maintainer: Eduardo García-Portugués <edgarcia@est-econ.uc3m.es>

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Package opdisDownsampling updated to version 0.7.0 with previous version 0.6.1 dated 2021-10-11

Title: Optimal Distribution Preserving Down-Sampling of Bio-Medical Data
Description: An optimized method for distribution-preserving class-proportional down-sampling of bio-medical data.
Author: Jorn Lotsch [aut,cre] (<https://orcid.org/0000-0002-5818-6958>), Sebastian Malkusch [aut] (<https://orcid.org/0000-0001-6766-140X>), Alfred Ultsch [aut] (<https://orcid.org/0000-0002-7845-3283>)
Maintainer: Jorn Lotsch <j.lotsch@em.uni-frankfurt.de>

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Package seacarb updated to version 3.3.0 with previous version 3.2.16 dated 2021-02-22

Title: Seawater Carbonate Chemistry
Description: Calculates parameters of the seawater carbonate system and assists the design of ocean acidification perturbation experiments.
Author: Jean-Pierre Gattuso [aut, cre, cph], Jean-Marie Epitalon [aut], Heloise Lavigne [aut], James Orr [aut], Bernard Gentili [ctb], Mathilde Hagens [ctb], Andreas Hofmann [ctb], Jens-Daniel Mueller [ctb], Aurélien Proye [ctb], James Rae [ctb], Karline Soetaert [ctb]
Maintainer: Jean-Pierre Gattuso <jean-pierre.gattuso@imev-mer.fr>

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Package DriveML updated to version 0.1.4 with previous version 0.1.3 dated 2021-06-14

Title: Self-Drive Machine Learning Projects
Description: Implementing some of the pillars of an automated machine learning pipeline such as (i) Automated data preparation, (ii) Feature engineering, (iii) Model building in classification context that includes techniques such as (a) Regularised regression [1], (b) Logistic regression [2], (c) Random Forest [3], (d) Decision tree [4] and (e) Extreme Gradient Boosting (xgboost) [5], and finally, (iv) Model explanation (using lift chart and partial dependency plots). Accomplishes the above tasks by running the function instead of writing lengthy R codes. Also provides some additional features such as generating missing at random (MAR) variables and automated exploratory data analysis. Moreover, function exports the model results with the required plots in an HTML vignette report format that follows the best practices of the industry and the academia. [1] Gonzales G B and De Saeger (2018) <doi:10.1038/s41598-018-21851-7>, [2] Sperandei S (2014) <doi:10.11613/BM.2014.003>, [3] Breiman L (2001) <doi:10.1023/A:1010933404324>, [4] Kingsford C and Salzberg S (2008) <doi:10.1038/nbt0908-1011>, [5] Chen Tianqi and Guestrin Carlos (2016) <doi:10.1145/2939672.2939785>.
Author: Dayanand Ubrangala [aut, cre], Sayan Putatunda [aut, ctb], Kiran R [aut, ctb], Ravi Prasad Kondapalli [aut, ctb]
Maintainer: Dayanand Ubrangala <daya6489@gmail.com>

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Package econetwork updated to version 0.6.0 with previous version 0.5.1 dated 2021-03-02

Title: Analyzing Ecological Networks
Description: A collection of advanced tools, methods and models specifically designed for analyzing different types of ecological networks - especially antagonistic (food webs, host-parasite), mutualistic (plant-pollinator, plant-fungus, etc) and competitive networks, as well as their variability in time and space. Statistical models are developed to describe and understand the mechanisms that determine species interactions, and to decipher the organization of these ecological networks (Ohlmann et al. (2019) <doi:10.1111/ele.13221>, Gonzalez et al. (2020) <doi:10.1101/2020.04.02.021691>, Miele et al. (2021) submitted, Botella et al (2021) <doi:10.1111/2041-210X.13738>).
Author: Vincent Miele [aut, cre], Catherine Matias [ctb], Stephane Dray [ctb], Christophe Botella [ctb], Marc Ohlmann [aut], Giovanni Poggiato [ctb], Wilfried Thuiller [ctb]
Maintainer: Vincent Miele <vincent.miele@univ-lyon1.fr>

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Package rvkstat updated to version 3.2.0 with previous version 3.1.0 dated 2021-09-08

Title: R Interface to API 'vk.com'
Description: Load data from vk.com api about your communiti users and views, ads performance, post on user wall and etc. For more information see API Documentation <https://vk.com/dev/first_guide>.
Author: Alexey Seleznev
Maintainer: Alexey Seleznev <selesnow@gmail.com>

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Package GWPR.light updated to version 0.1.1 with previous version 0.1.0 dated 2021-10-12

Title: Geographically Weighted Panel Regression
Description: Geographically weighted panel regression is grounded in a branch of spatial statistics. Using geographically weights, the geographically weighted panel regression is try to solve the residuals from panel regression clustering spatially. To investigate whether the residuals cluster spatially, the Moran's I test is also improved. Furthermore, three local statistic tests are contained to help the users select model. The major references are Fotheringham et al. (2003, ISBN:978-0-470-85525-6) and Beenstock and Felsenstein (2019, ISBN:978-3-030-03614-0).
Author: Chao Li [aut, cre] (<https://orcid.org/0000-0002-6854-4456>), Shunsuke Managi [aut] (<https://orcid.org/0000-0001-7883-1427>)
Maintainer: Chao Li <chaoli0394@gmail.com>

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Package fastmatrix updated to version 0.3-8196 with previous version 0.3-819 dated 2021-05-08

Title: Fast Computation of some Matrices Useful in Statistics
Description: Small set of functions to fast computation of some matrices and operations useful in statistics and econometrics. Currently, there are functions for efficient computation of duplication, commutation and symmetrizer matrices with minimal storage requirements. Some commonly used matrix decompositions (LU and LDL), basic matrix operations (for instance, Hadamard, Kronecker products and the Sherman-Morrison formula) and iterative solvers for linear systems are also available. In addition, the package includes a number of common statistical procedures such as the sweep operator, weighted mean and covariance matrix using an online algorithm, linear regression (using Cholesky, QR, SVD, sweep operator and conjugate gradients methods), ridge regression (with optimal selection of the ridge parameter considering the GCV procedure), functions to compute the multivariate skewness, kurtosis, Mahalanobis distance (checking the positive defineteness) and the Wilson-Hilferty transformation of chi squared variables. Furthermore, the package provides interfaces to C code callable by another C code from other R packages.
Author: Felipe Osorio [aut, cre] (<https://orcid.org/0000-0002-4675-5201>), Alonso Ogueda [aut]
Maintainer: Felipe Osorio <felipe.osorios@usm.cl>

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Package spsurvey updated to version 5.0.0 with previous version 4.1.4 dated 2020-09-18

Title: Spatial Sampling Design and Analysis
Description: A design-based approach to statistical inference, with a focus on spatial data. Spatially balanced samples are selected using the Generalized Random Tessellation Stratified (GRTS) algorithm. The GRTS algorithm can be applied to finite resources (point geometries) and infinite resources (linear / linestring and areal / polygon geometries) and flexibly accommodates a diverse set of sampling design features, including stratification, unequal inclusion probabilities, proportional (to size) inclusion probabilities, legacy (historical) sites, a minimum distance between sites, and two options for replacement sites (reverse hierarchical order and nearest neighbor). Data are analyzed using a wide range of analysis functions that perform categorical variable analysis, continuous variable analysis, attributable risk analysis, risk difference analysis, relative risk analysis, change analysis, and trend analysis. spsurvey can also be used to summarize objects, visualize objects, select samples that are not spatially balanced, select panel samples, measure the amount of spatial balance in a sample, adjust design weights, and more.
Author: Michael Dumelle [aut, cre] (<https://orcid.org/0000-0002-3393-5529>), Tom Kincaid [aut], Tony Olsen [aut], Marc Weber [aut], Don Stevens [ctb], Denis White [ctb]
Maintainer: Michael Dumelle <Dumelle.Michael@epa.gov>

Diff between spsurvey versions 4.1.4 dated 2020-09-18 and 5.0.0 dated 2021-10-18

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Package ichimoku updated to version 1.2.4 with previous version 1.2.2 dated 2021-10-05

Title: Visualization and Tools for Ichimoku Kinko Hyo Strategies
Description: An implementation of 'Ichimoku Kinko Hyo', also commonly known as 'cloud charts'. Static and interactive visualizations with tools for creating, backtesting and development of quantitative 'ichimoku' strategies. As described in Sasaki (1996, ISBN:4925152009), the technique is a refinement on candlestick charting, originating from Japan and now in widespread use in technical analysis worldwide. Translating as 'one-glance equilibrium chart', it allows the price action and market structure of financial securities to be determined 'at-a-glance'. Incorporates an interface with the OANDA fxTrade API <https://developer.oanda.com/> for retrieving historical and live streaming price data for major currencies, metals, commodities, government bonds and stock indices.
Author: Charlie Gao [aut, cre] (<https://orcid.org/0000-0002-0750-061X>)
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

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Package hhsmm updated to version 0.2.1 with previous version 0.2.0 dated 2021-10-13

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>.
Author: Morteza Amini [aut, cre, cph], Afarin Bayat [aut]
Maintainer: Morteza Amini <morteza.amini@ut.ac.ir>

Diff between hhsmm versions 0.2.0 dated 2021-10-13 and 0.2.1 dated 2021-10-18

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Package gmGeostats updated to version 0.11.0 with previous version 0.10-9 dated 2021-09-17

Title: Geostatistics for Compositional Analysis
Description: Support for geostatistical analysis of multivariate data, in particular data with restrictions, e.g. positive amounts data, compositional data, distributional data, microstructural data, etc. It includes descriptive analysis and modelling for such data, both from a two-point Gaussian perspective and multipoint perspective. The methods mainly follow Tolosana-Delgado, Mueller and van den Boogaart (2018) <doi:10.1007/s11004-018-9769-3>.
Author: Raimon Tolosana-Delgado [aut] (<https://orcid.org/0000-0001-9847-0462>), Ute Mueller [aut], K. Gerald van den Boogaart [ctb, cre], Hassan Talebi [ctb, cph], Helmholtz-Zentrum Dresden-Rossendorf [cph], Edith Cowan University [cph]
Maintainer: K. Gerald van den Boogaart <support@boogaart.de>

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Package franc updated to version 1.1.4 with previous version 1.1.3 dated 2021-01-27

Title: Detect the Language of Text
Description: With no external dependencies and support for 335 languages; all languages spoken by more than one million speakers. 'Franc' is a port of the 'JavaScript' project of the same name, see <https://github.com/wooorm/franc>.
Author: Gabor Csardi, Titus Wormer, Maciej Ceglowski, Jacob R. Rideout, and Kent S. Johnson
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

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Package spidR updated to version 1.0.2 with previous version 1.0.1 dated 2021-04-19

Title: Spider Knowledge Online
Description: Allows the user to connect with the World Spider Catalogue (WSC; <https://wsc.nmbe.ch/>) and the World Spider Trait (WST; <https://spidertraits.sci.muni.cz/>) databases. Also performs several basic functions such as checking names validity, retrieving coordinate data from the Global Biodiversity Information Facility (GBIF; <https://www.gbif.org/>), and mapping.
Author: Pedro Cardoso [aut, cre]
Maintainer: Pedro Cardoso <pedro.cardoso@helsinki.fi>

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Package seqHMM updated to version 1.2.0 with previous version 1.1.1 dated 2021-08-13

Title: Mixture Hidden Markov Models for Social Sequence Data and Other Multivariate, Multichannel Categorical Time Series
Description: Designed for fitting hidden (latent) Markov models and mixture hidden Markov models for social sequence data and other categorical time series. Also some more restricted versions of these type of models are available: Markov models, mixture Markov models, and latent class models. The package supports models for one or multiple subjects with one or multiple parallel sequences (channels). External covariates can be added to explain cluster membership in mixture models. The package provides functions for evaluating and comparing models, as well as functions for visualizing of multichannel sequence data and hidden Markov models. Models are estimated using maximum likelihood via the EM algorithm and/or direct numerical maximization with analytical gradients. All main algorithms are written in C++ with support for parallel computation. Documentation is available via several vignettes in this page, and the paper by Helske and Helske (2019, <doi:10.18637/jss.v088.i03>).
Author: Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>), Satu Helske [aut] (<https://orcid.org/0000-0003-0532-0153>)
Maintainer: Jouni Helske <jouni.helske@iki.fi>

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Package secr updated to version 4.4.7 with previous version 4.4.5 dated 2021-07-12

Title: Spatially Explicit Capture-Recapture
Description: Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.
Author: Murray Efford [aut, cre] (<https://orcid.org/0000-0001-5231-5184>)
Maintainer: Murray Efford <murray.efford@otago.ac.nz>

Diff between secr versions 4.4.5 dated 2021-07-12 and 4.4.7 dated 2021-10-18

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Package generalCorr updated to version 1.1.9 with previous version 1.1.8 dated 2020-12-02

Title: Generalized Correlations and Various Causal Paths
Description: Since causal paths from data are important for all sciences, the package provides many sophisticated functions. causeSummBlk() gives easy-to-interpret causal paths. Let Z denote control variables and compare two flipped kernel regressions: X=f(Y, Z)+e1 and Y=g(X,Z)+e2. Our criterion Cr1 says that if |e1*Y|>|e2*X| then variation in X is more "exogenous or independent" than in Y and causal path is X to Y. Criterion Cr2 requires |e2|<|e1|. These inequalities between many absolute values are quantified by four orders of stochastic dominance. Our third criterion Cr3 for the causal path X to Y requires new generalized partial correlations to satisfy |r*(x|y,z)|< |r*(y|x,z)|. The function parcorVec() reports generalized partials between the first variable and all others. The package provides several R functions including get0outliers() for outlier detection, bigfp() for numerical integration by the trapezoidal rule, stochdom2() for stochastic dominance, pillar3D() for 3D charts, canonRho() for generalized canonical correlations, depMeas() measures nonlinear dependence, and causeSummary(mtx) reports summary of causal paths among matrix columns is easiest to use. Several functions whose names begin with 'boot' provide bootstrap statistical inference including a new bootGcRsq() test for "Granger-causality" allowing nonlinear relations. See five vignettes of the package for theory and usage tips. See Vinod (2019) \doi{10.1080/03610918.2015.1122048}.
Author: Prof. H. D. Vinod, Fordham University, NY.
Maintainer: H. D. Vinod <vinod@fordham.edu>

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Package dycdtools updated to version 0.3.1 with previous version 0.3.0 dated 2021-09-19

Title: Tools for DYRESM-CAEDYM Model Development: Calibration Assistant and Post-Processing
Description: Tools for DYRESM-CAEDYM model development, including assisting with calibrating selected model parameters and visualising model output through time series plot, profile plot, contour plot, and scatter plot.
Author: Songyan Yu [aut, cre] (<https://orcid.org/0000-0001-5765-7060>), Christopher McBride [ctb], Marieke Frassl [ctb]
Maintainer: Songyan Yu <sunny.yu@griffith.edu.au>

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Sun, 17 Oct 2021

Package JBrowseR updated to version 0.9.0 with previous version 0.8.1 dated 2021-07-07

Title: An R Interface to the JBrowse 2 Genome Browser
Description: Provides an R interface to the JBrowse 2 genome browser. Enables embedding a JB2 genome browser in a Shiny app or R Markdown document. The browser can also be launched from an interactive R console. The browser can be loaded with a variety of common genomics data types, and can be used with a custom theme.
Author: Elliot Hershberg [aut, cre] (<https://orcid.org/0000-0003-2068-3366>), the JBrowse 2 Team [aut]
Maintainer: Elliot Hershberg <eahershberg@gmail.com>

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Package tidygeocoder updated to version 1.0.4 with previous version 1.0.3 dated 2021-04-19

Title: Geocoding Made Easy
Description: An intuitive interface for getting data from geocoding services.
Author: Jesse Cambon [aut, cre] (<https://orcid.org/0000-0001-6854-1514>), Diego Hernangómez [aut] (<https://orcid.org/0000-0001-8457-4658>), Christopher Belanger [aut] (<https://orcid.org/0000-0003-2070-5721>), Daniel Possenriede [aut] (<https://orcid.org/0000-0002-6738-9845>)
Maintainer: Jesse Cambon <jesse.cambon@gmail.com>

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Package Seurat updated to version 4.0.5 with previous version 4.0.4 dated 2021-08-20

Title: Tools for Single Cell Genomics
Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031>, and Hao, Hao, et al (2020) <doi:10.1101/2020.10.12.335331> for more details.
Author: Andrew Butler [ctb] (<https://orcid.org/0000-0003-3608-0463>), Saket Choudhary [ctb] (<https://orcid.org/0000-0001-5202-7633>), Charlotte Darby [ctb] (<https://orcid.org/0000-0003-2195-5300>), Jeff Farrell [ctb], Christoph Hafemeister [ctb] (<https://orcid.org/0000-0001-6365-8254>), Yuhan Hao [ctb] (<https://orcid.org/0000-0002-1810-0822>), Paul Hoffman [aut, cre] (<https://orcid.org/0000-0002-7693-8957>), Jaison Jain [ctb] (<https://orcid.org/0000-0002-9478-5018>), Efthymia Papalexi [ctb] (<https://orcid.org/0000-0001-5898-694X>), Patrick Roelli [ctb], Rahul Satija [ctb] (<https://orcid.org/0000-0001-9448-8833>), Karthik Shekhar [ctb], Avi Srivastava [ctb] (<https://orcid.org/0000-0001-9798-2079>), Tim Stuart [ctb] (<https://orcid.org/0000-0002-3044-0897>), Kristof Torkenczy [ctb] (<https://orcid.org/0000-0002-4869-7957>), Shiwei Zheng [ctb] (<https://orcid.org/0000-0001-6682-6743>), Satija Lab and Collaborators [fnd]
Maintainer: Paul Hoffman <seurat@nygenome.org>

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Package rcdk updated to version 3.6.0 with previous version 3.5.0 dated 2020-03-11

Title: Interface to the 'CDK' Libraries
Description: Allows the user to access functionality in the 'CDK', a Java framework for chemoinformatics. This allows the user to load molecules, evaluate fingerprints, calculate molecular descriptors and so on. In addition, the 'CDK' API allows the user to view structures in 2D.
Author: Rajarshi Guha [aut, cph], Zachary Charlop-Powers [cre], Emma Schymanski [ctb]
Maintainer: Zachary Charlop-Powers <zach.charlop.powers@gmail.com>

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Package qtl2 updated to version 0.28 with previous version 0.24 dated 2020-12-18

Title: Quantitative Trait Locus Mapping in Experimental Crosses
Description: Provides a set of tools to perform quantitative trait locus (QTL) analysis in experimental crosses. It is a reimplementation of the 'R/qtl' package to better handle high-dimensional data and complex cross designs. Broman et al. (2018) <doi:10.1534/genetics.118.301595>.
Author: Karl W Broman [aut, cre] (<https://orcid.org/0000-0002-4914-6671>), R Core Team [ctb]
Maintainer: Karl W Broman <broman@wisc.edu>

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Package FKF updated to version 0.2.2 with previous version 0.2.1 dated 2021-09-28

Title: Fast Kalman Filter
Description: This is a fast and flexible implementation of the Kalman filter and smoother, which can deal with NAs. It is entirely written in C and relies fully on linear algebra subroutines contained in BLAS and LAPACK. Due to the speed of the filter, the fitting of high-dimensional linear state space models to large datasets becomes possible. This package also contains a plot function for the visualization of the state vector and graphical diagnostics of the residuals.
Author: David Luethi [aut], Philipp Erb [aut], Simon Otziger [aut], Daniel McDonald [aut], Paul Smith [aut, cre] (<https://orcid.org/0000-0002-0034-3412>)
Maintainer: Paul Smith <paul@waternumbers.co.uk>

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Package portfolioBacktest updated to version 0.3.1 with previous version 0.3.0 dated 2021-09-21

Title: Automated Backtesting of Portfolios over Multiple Datasets
Description: Automated backtesting of multiple portfolios over multiple datasets of stock prices in a rolling-window fashion. Intended for researchers and practitioners to backtest a set of different portfolios, as well as by a course instructor to assess the students in their portfolio design in a fully automated and convenient manner, with results conveniently formatted in tables and plots. Each portfolio design is easily defined as a function that takes as input a window of the stock prices and outputs the portfolio weights. Multiple portfolios can be easily specified as a list of functions or as files in a folder. Multiple datasets can be conveniently extracted randomly from different markets, different time periods, and different subsets of the stock universe. The results can be later assessed and ranked with tables based on a number of performance criteria (e.g., expected return, volatility, Sharpe ratio, drawdown, turnover rate, return on investment, computational time, etc.), as well as plotted in a number of ways with nice barplots and boxplots.
Author: Daniel P. Palomar [cre, aut], Rui Zhou [aut]
Maintainer: Daniel P. Palomar <daniel.p.palomar@gmail.com>

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Package LMMstar updated to version 0.3.3 with previous version 0.3.2 dated 2021-10-05

Title: Repeated Measurement Models for Discrete Times
Description: Companion R package for the course "Statistical analysis of correlated and repeated measurements for health science researchers" taught by the section of Biostatistics of the University of Copenhagen. It provides functions for computing summary statistics and obtaining graphical displays of longitudinal data, as well as for statistical modeling and statistical inference using linear mixed model.
Author: Brice Ozenne [aut, cre] (<https://orcid.org/0000-0001-9694-2956>), Julie Forman [aut] (<https://orcid.org/0000-0001-7368-0869>)
Maintainer: Brice Ozenne <brice.mh.ozenne@gmail.com>

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Package NMproject updated to version 0.6.7 with previous version 0.6.5 dated 2021-09-02

Title: Script Based 'NONMEM' Model Development
Description: Industrialisation of 'NONMEM' <https://www.iconplc.com/innovation/nonmem/> via fully and rapidly reusable model development 'workflows' entirely within 'RStudio'. Quickly get started with new models by importing 'NONMEM' templates from the built-in code library. Manipulate 'NONMEM' code from within R either via the tracked 'manual edit' interface or 'programmatically' via convenience functions. Script 'workflows' by piping sequences of model building steps from control file creation, to execution, to post-processing and evaluation. Run caching makes 'workflows' R markdown friendly for easy documentation of thoughts and modelling decisions alongside executable code. Share, reuse and recycle 'workflows' for new problems.
Author: Tarj Sahota [aut, cre, cph], AstraZeneca [cph], Nuria Buil Bruna [ctb], Stein Schalkwijk [ctb]
Maintainer: Tarj Sahota <t.sahota0@gmail.com>

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Package covid19br updated to version 0.1.3 with previous version 0.1.2 dated 2021-10-08

Title: Brazilian COVID-19 Pandemic Data
Description: Set of functions to import COVID-19 pandemic data into R. The Brazilian COVID-19 data, obtained from the official Brazilian repository at <https://covid.saude.gov.br/>, is available at country, region, state, and city-levels. The package also downloads the world-level COVID-19 data from the John Hopkins University's repository.
Author: Fabio Demarqui [aut, cre], Cristiano Santos [aut], Matheus Costa [ctb]
Maintainer: Fabio Demarqui <fndemarqui@est.ufmg.br>

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Package MFPCA updated to version 1.3-9 with previous version 1.3-8 dated 2021-08-09

Title: Multivariate Functional Principal Component Analysis for Data Observed on Different Dimensional Domains
Description: Calculate a multivariate functional principal component analysis for data observed on different dimensional domains. The estimation algorithm relies on univariate basis expansions for each element of the multivariate functional data (Happ & Greven, 2018) <doi:10.1080/01621459.2016.1273115>. Multivariate and univariate functional data objects are represented by S4 classes for this type of data implemented in the package 'funData'. For more details on the general concepts of both packages and a case study, see Happ-Kurz (2020) <doi:10.18637/jss.v093.i05>.
Author: Clara Happ-Kurz [aut, cre] (<https://orcid.org/0000-0003-4737-3835>)
Maintainer: Clara Happ-Kurz <chk_R@gmx.de>

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Package funData updated to version 1.3-8 with previous version 1.3-7 dated 2021-08-03

Title: An S4 Class for Functional Data
Description: S4 classes for univariate and multivariate functional data with utility functions. See <doi:10.18637/jss.v093.i05> for a detailed description of the package functionalities and its interplay with the MFPCA package for multivariate functional principal component analysis <https://CRAN.R-project.org/package=MFPCA>.
Author: Clara Happ-Kurz [aut, cre]
Maintainer: Clara Happ-Kurz <chk_R@gmx.de>

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Package treebalance updated to version 1.1.0 with previous version 1.0.0 dated 2021-09-22

Title: Computation of Tree (Im)Balance Indices
Description: The aim of the 'R' package 'treebalance' is to provide functions for the computation of a large variety of (im)balance indices for rooted trees. The package accompanies the manuscript ''Tree balance indices: a comprehensive survey'' by M. Fischer, L. Herbst, S. Kersting, L. Kuehn and K. Wicke (2021) <arXiv:2109.12281>, which gives a precise definition for the terms 'balance index' and 'imbalance index' (Section 3) and provides an overview of the terminology in this manual (Section 2). For further information on (im)balance indices, see also Fischer et al. (2021) <https://treebalance.wordpress.com>. Considering both established and new (im)balance indices, 'treebalance' provides (among others) functions for calculating the following 18 established indices: the average leaf depth, the B1 and B2 index, the Colijn-Plazzotta rank, the normal, corrected, quadratic and equal weights Colless index, the family of Colless-like indices, the family of I-based indices, the Rogers J index, the Furnas rank, the rooted quartet index, the s-shape statistic, the Sackin index, the symmetry nodes index, the total cophenetic index and the variance of leaf depths. Additionally, we include 5 tree shape statistics that satisfy the definition of an (im)balance index but have not been thoroughly analyzed in terms of tree balance in the literature yet. These are: the maximum width, the maximum difference in widths, the maximal depth, the stairs1 and the stairs2 index. As input, most functions of 'treebalance' require a rooted (phylogenetic) tree in 'phylo' format (as introduced in 'ape' 1.9 in November 2006). 'phylo' is used to store (phylogenetic) trees with no vertices of out-degree one. For further information on the format we kindly refer the reader to E. Paradis (2012) <http://ape-package.ird.fr/misc/FormatTreeR_24Oct2012.pdf>.
Author: Mareike Fischer [aut], Lina Herbst [aut], Sophie Kersting [aut], Luise Kuehn [aut, cre], Kristina Wicke [aut]
Maintainer: Luise Kuehn <treebalanceindices@gmail.com>

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Package dang updated to version 0.0.14 with previous version 0.0.13 dated 2021-02-17

Title: 'Dang' Associated New Goodies
Description: A collection of utility functions.
Author: Dirk Eddelbuettel with contributions by Brodie Gaslam, Kevin Denny, Kabira Namit, Colin Gillespie, R Core, Josh Ulrich, Jordan Mark Barbone, and others.
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package osmdata updated to version 0.1.8 with previous version 0.1.7 dated 2021-10-07

Title: Import 'OpenStreetMap' Data as Simple Features or Spatial Objects
Description: Download and import of 'OpenStreetMap' ('OSM') data as 'sf' or 'sp' objects. 'OSM' data are extracted from the 'Overpass' web server (<https://overpass-api.de/>) and processed with very fast 'C++' routines for return to 'R'.
Author: Mark Padgham [aut, cre], Bob Rudis [aut], Robin Lovelace [aut], Maëlle Salmon [aut], Andrew Smith [ctb], James Smith [ctb], Andrea Gilardi [ctb], Enrico Spinielli [ctb], Anthony North [ctb], Marcin Kalicinski [ctb, cph] (Author of included RapidXML code), Finkelstein Noam [ctb, cph] (Author of included stub.R code), Bartnik Lukasz [ctb, cph] (Author of included stub.R code)
Maintainer: Mark Padgham <mark.padgham@email.com>

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Package conjurer updated to version 1.3.0 with previous version 1.2.0 dated 2020-09-08

Title: A Parametric Method for Generating Synthetic Data
Description: Builds synthetic data applicable across multiple domains. This package also provides flexibility to control data distribution to make it relevant to many industry examples.
Author: Sidharth Macherla [aut, cre] (<https://orcid.org/0000-0002-4825-2026>)
Maintainer: Sidharth Macherla <msidharthrasik@gmail.com>

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Package bayesnec updated to version 2.0.2 with previous version 2.0.1 dated 2021-09-20

Title: A Bayesian No-Effect- Concentration (NEC) Algorithm
Description: Implementation of No-Effect-Concentration estimation that uses 'brms' (see Burkner (2017)<doi:10.18637/jss.v080.i01>; Burkner (2018)<doi:10.32614/RJ-2018-017>; Carpenter 'et al.' (2017)<doi:10.18637/jss.v076.i01> to fit concentration(dose)-response data using Bayesian methods for the purpose of estimating 'ECX' values, but more particularly 'NEC' (see Fox (2010)<doi:10.1016/j.ecoenv.2009.09.012>. This package expands and supersedes an original version implemented in R2jags, see Fisher, Ricardo and Fox (2020)<doi:10.5281/ZENODO.3966864>.
Author: Rebecca Fisher [aut, cre], Diego Barneche [aut], Gerard Ricardo [aut], David Fox [aut]
Maintainer: Rebecca Fisher <r.fisher@aims.gov.au>

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Package prismatic updated to version 1.1.0 with previous version 1.0.0 dated 2021-01-05

Title: Color Manipulation Tools
Description: Manipulate and visualize colors in a intuitive, low-dependency and functional way.
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>

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Package pedSimulate updated to version 1.2.1 with previous version 1.2.0 dated 2021-09-06

Title: Pedigree, Genetic Merit, Phenotype, and Genotype Simulation
Description: Simulate pedigree, genetic merits and phenotypes with random/non-random matings followed by random/non-random selection with different intensities and patterns in males and females. Genotypes can be simulated for a given pedigree. Bijma, P. & Rutten, M. (2002) <https://www.wur.nl/en/Research-Results/Chair-groups/Animal-Sciences/Animal-Breeding-and-Genomics-Group/Research/Software.htm>.
Author: Mohammad Ali Nilforooshan [aut, cre] (<https://orcid.org/0000-0003-0339-5442>)
Maintainer: Mohammad Ali Nilforooshan <m.a.nilforooshan@gmail.com>

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Sat, 16 Oct 2021

Package usethis updated to version 2.1.0 with previous version 2.0.1 dated 2021-02-10

Title: Automate Package and Project Setup
Description: Automate package and project setup tasks that are otherwise performed manually. This includes setting up unit testing, test coverage, continuous integration, Git, 'GitHub', licenses, 'Rcpp', 'RStudio' projects, and more.
Author: Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>), Jennifer Bryan [aut, cre] (<https://orcid.org/0000-0002-6983-2759>), Malcolm Barrett [aut] (<https://orcid.org/0000-0003-0299-5825>), RStudio [cph, fnd]
Maintainer: Jennifer Bryan <jenny@rstudio.com>

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Package rvest updated to version 1.0.2 with previous version 1.0.1 dated 2021-07-26

Title: Easily Harvest (Scrape) Web Pages
Description: Wrappers around the 'xml2' and 'httr' packages to make it easy to download, then manipulate, HTML and XML.
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package naturaList updated to version 0.4.2 with previous version 0.4.1 dated 2021-08-21

Title: Classify Occurrences by Confidence Levels in the Species ID
Description: Classify occurrence records based on confidence levels of species identification. In addition, implement tools to filter occurrence inside grid cells and to manually check for possibles errors with an interactive shiny application.
Author: Arthur Vinicius Rodrigues [cre], Gabriel Nakamura [aut], Leandro Duarte [aut]
Maintainer: Arthur Vinicius Rodrigues <rodrigues.arthur.v@gmail.com>

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Package mvGPS updated to version 1.2.1 with previous version 1.1.1 dated 2021-04-28

Title: Causal Inference using Multivariate Generalized Propensity Score
Description: Methods for estimating and utilizing the multivariate generalized propensity score (mvGPS) for multiple continuous exposures described in Williams, J.R, and Crespi, C.M. (2020) <arxiv:2008.13767>. The methods allow estimation of a dose-response surface relating the joint distribution of multiple continuous exposure variables to an outcome. Weights are constructed assuming a multivariate normal density for the marginal and conditional distribution of exposures given a set of confounders. Confounders can be different for different exposure variables. The weights are designed to achieve balance across all exposure dimensions and can be used to estimate dose-response surfaces.
Author: Justin Williams [aut, cre] (<https://orcid.org/0000-0002-5045-2764>)
Maintainer: Justin Williams <williazo@ucla.edu>

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Package decisionSupport updated to version 1.108 with previous version 1.107 dated 2021-10-16

Title: Quantitative Support of Decision Making under Uncertainty
Description: Supporting the quantitative analysis of binary welfare based decision making processes using Monte Carlo simulations. Decision support is given on two levels: (i) The actual decision level is to choose between two alternatives under probabilistic uncertainty. This package calculates the optimal decision based on maximizing expected welfare. (ii) The meta decision level is to allocate resources to reduce the uncertainty in the underlying decision problem, i.e to increase the current information to improve the actual decision making process. This problem is dealt with using the Value of Information Analysis. The Expected Value of Information for arbitrary prospective estimates can be calculated as well as Individual Expected Value of Perfect Information. The probabilistic calculations are done via Monte Carlo simulations. This Monte Carlo functionality can be used on its own.
Author: Eike Luedeling [cre, aut] (University of Bonn), Lutz Goehring [aut] (ICRAF and Lutz Goehring Consulting), Katja Schiffers [aut] (University of Bonn), Cory Whitney [aut] (University of Bonn), Eduardo Fernandez [aut] (University of Bonn)
Maintainer: Eike Luedeling <eike@eikeluedeling.com>

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Package csppData updated to version 0.1.4 with previous version 0.1.3 dated 2021-06-07

Title: Data Only: The Correlates of State Policy Project Dataset
Description: Contains the Correlates of State Policy Project dataset (+ codebook) assembled by Marty P. Jordan and Matt Grossmann (2020) <http://ippsr.msu.edu/public-policy/correlates-state-policy> used by the 'cspp' package. The Correlates data contains over 2000 variables across more than 100 years that pertain to state politics and policy in the United States.
Author: Caleb Lucas (https://caleblucas.com/) and Joshua McCrain (http://joshuamccrain.com/)
Maintainer: Caleb Lucas <calebjlucas@gmail.com>

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Package cspp updated to version 0.3.2 with previous version 0.3.1 dated 2021-01-04

Title: A Tool for the Correlates of State Policy Project Data
Description: A tool that imports, subsets, visualizes, and exports the Correlates of State Policy Project dataset assembled by Marty P. Jordan and Matt Grossmann (2020) <http://ippsr.msu.edu/public-policy/correlates-state-policy>. The Correlates data contains over 2000 variables across more than 100 years that pertain to state politics and policy in the United States. Users with only a basic understanding of R can subset this data across multiple dimensions, export their search results, create map visualizations, export the citations associated with their searches, and more.
Author: Caleb Lucas (https://caleblucas.com/) and Joshua McCrain (http://joshuamccrain.com/)
Maintainer: Caleb Lucas <calebjlucas@gmail.com>

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Package disordR updated to version 0.0-8 with previous version 0.0-7 dated 2021-08-05

Title: Non-Ordered Vectors
Description: Functionality for manipulating values of associative maps. Ordinary R vectors are unsuitable for working with values of associative maps because elements of an R vector may be accessed by reference to their location in the vector, but associative maps are stored in arbitrary order. However, when associating keys with values one needs both parts to be in 1-1 correspondence, so one cannot dispense with the order entirely. The 'disordR' package includes a single S4 class, disord. This class allows one to perform only those operations appropriate for manipulating values of associative maps and prevents any other operation (such as accessing an element at a particular location). A useful heuristic is that one is only allowed to access or modify a disord object using a python list comprehension. The idea is to prevent ill-defined operations on values (or keys) of associative maps, whose order is undefined or at best implementation-specific, while allowing and facilitating sensible operations. The package is needed for development versions of 'mvp', 'hyper2', 'spray', 'clifford', and 'freealg'.
Author: Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>)
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

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Package rts updated to version 1.1-3 with previous version 1.0-49 dated 2019-02-03

Title: Raster Time Series Analysis
Description: This framework aims to provide classes and methods for manipulating and processing of raster time series data (e.g. a time series of satellite images).
Author: Babak Naimi
Maintainer: Babak Naimi <naimi.b@gmail.com>

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Package starvz updated to version 0.6.0 with previous version 0.5.0 dated 2021-03-25

Title: R-Based Visualization Techniques for Task-Based Applications
Description: Performance analysis workflow that combines the power of the R language (and the tidyverse realm) and many auxiliary tools to provide a consistent, flexible, extensible, fast, and versatile framework for the performance analysis of task-based applications that run on top of the StarPU runtime (with its MPI (Message Passing Interface) layer for multi-node support). Its goal is to provide a fruitful prototypical environment to conduct performance analysis hypothesis-checking for task-based applications that run on heterogeneous (multi-GPU, multi-core) multi-node HPC (High-performance computing) platforms.
Author: Lucas Mello Schnorr [aut, ths] (<https://orcid.org/0000-0003-4828-9942>), Vinicius Garcia Pinto [aut] (<https://orcid.org/0000-0002-6845-9358>), Lucas Leandro Nesi [aut, cre] (<https://orcid.org/0000-0001-8874-1839>), Marcelo Cogo Miletto [aut] (<https://orcid.org/0000-0002-1191-3863>), Guilherme Alles [ctb], Arnaud Legrand [ctb], Luka Stanisic [ctb], Rémy Drouilhet [ctb]
Maintainer: Lucas Leandro Nesi <lucas.nesi@inf.ufrgs.br>

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Package scMappR updated to version 1.0.7 with previous version 1.0.2 dated 2021-05-14

Title: Single Cell Mapper
Description: The single cell mapper (scMappR) R package contains a suite of bioinformatic tools that provide experimentally relevant cell-type specific information to a list of differentially expressed genes (DEG). The function "scMappR_and_pathway_analysis" reranks DEGs to generate cell-type specificity scores called cell-weighted fold-changes. Users input a list of DEGs, normalized counts, and a signature matrix into this function. scMappR then re-weights bulk DEGs by cell-type specific expression from the signature matrix, cell-type proportions from RNA-seq deconvolution and the ratio of cell-type proportions between the two conditions to account for changes in cell-type proportion. With cwFold-changes calculated, scMappR uses two approaches to utilize cwFold-changes to complete cell-type specific pathway analysis. The "process_dgTMatrix_lists" function in the scMappR package contains an automated scRNA-seq processing pipeline where users input scRNA-seq count data, which is made compatible for scMappR and other R packages that analyze scRNA-seq data. We further used this to store hundreds up regularly updating signature matrices. The functions "tissue_by_celltype_enrichment", "tissue_scMappR_internal", and "tissue_scMappR_custom" combine these consistently processed scRNAseq count data with gene-set enrichment tools to allow for cell-type marker enrichment of a generic gene list (e.g. GWAS hits). Reference: Sokolowski,D.J., Faykoo-Martinez,M., Erdman,L., Hou,H., Chan,C., Zhu,H., Holmes,M.M., Goldenberg,A. and Wilson,M.D. (2021) Single-cell mapper (scMappR): using scRNA-seq to infer cell-type specificities of differentially expressed genes. NAR Genomics and Bioinformatics. 3(1). Iqab011. <doi:10.1093/nargab/lqab011>.
Author: Dustin Sokolowski [aut, cre], Mariela Faykoo-Martinez [aut], Lauren Erdman [aut], Houyun Hou [aut], Cadia Chan [aut], Helen Zhu [aut], Melissa Holmes [aut], Anna Goldenberg [aut], Michael Wilson [aut]
Maintainer: Dustin Sokolowski <dustin.sokolowski@sickkids.ca>

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Package mixmeta updated to version 1.2.0 with previous version 1.1.3 dated 2021-06-12

Title: An Extended Mixed-Effects Framework for Meta-Analysis
Description: A collection of functions to perform various meta-analytical models through a unified mixed-effects framework, including standard univariate fixed and random-effects meta-analysis and meta-regression, and non-standard extensions such as multivariate, multilevel, longitudinal, and dose-response models.
Author: Antonio Gasparrini [aut, cre], Francesco Sera [aut]
Maintainer: Antonio Gasparrini <antonio.gasparrini@lshtm.ac.uk>

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Package MBESS updated to version 4.8.1 with previous version 4.8.0 dated 2020-08-05

Title: The MBESS R Package
Description: Implements methods that are useful in designing research studies and analyzing data, with particular emphasis on methods that are developed for or used within the behavioral, educational, and social sciences (broadly defined). That being said, many of the methods implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a suite of functions for a variety of related topics, such as effect sizes, confidence intervals for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and minimum-risk point estimation perspectives), mediation analysis, various properties of distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but MBESS became more general and now contains methods applicable and used in a wide variety of fields and is an orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has greatly benefited from others, see <https://www3.nd.edu/~kkelley/site/MBESS.html> for a detailed list of those that have contributed and other details.
Author: Ken Kelley [aut, cre]
Maintainer: Ken Kelley <kkelley@nd.edu>

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Package legco updated to version 0.1.4 with previous version 0.1.3 dated 2020-03-31

Title: R Bindings for the Hong Kong Legislative Council API
Description: Fetching data from Hong Kong Legislative Council's open data API in R. Functions correspond to the data endpoints of the API. Documentations of supported API databases: <https://www.legco.gov.hk/odata/english/billsdb.html>, <https://www.legco.gov.hk/odata/english/hansard-db.html>, <https://www.legco.gov.hk/odata/english/attendance-db.html>, <https://www.legco.gov.hk/odata/english/schedule-db.html> and <https://www.legco.gov.hk/odata/english/vrdb.html>.
Author: Elgar Teo
Maintainer: Elgar Teo <elgarteo@connect.hku.hk>

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Package insight updated to version 0.14.5 with previous version 0.14.4 dated 2021-09-02

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>, @strengejacke), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>, @Dom_Makowski), Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Mattan S. Ben-Shachar [aut, ctb] (<https://orcid.org/0000-0002-4287-4801>), Brenton M. Wiernik [aut] (<https://orcid.org/0000-0001-9560-6336>, @bmwiernik), Vincent Arel-Bundock [ctb] (<https://orcid.org/0000-0003-2042-7063>), Alex Hayes [rev] (<https://orcid.org/0000-0002-4985-5160>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package ForestFit updated to version 1.2.3 with previous version 0.7.1 dated 2021-02-06

Title: Statistical Modelling for Plant Size Distributions
Description: Developed for the following tasks. 1 ) Computing the probability density function, cumulative distribution function, random generation, and estimating the parameters of the eleven mixture models. 2 ) Point estimation of the parameters of two - parameter Weibull distribution using twelve methods and three - parameter Weibull distribution using nine methods. 3 ) The Bayesian inference for the three - parameter Weibull distribution. 4 ) Estimating parameters of the three - parameter Birnbaum - Saunders, generalized exponential, and Weibull distributions fitted to grouped data using three methods including approximated maximum likelihood, expectation maximization, and maximum likelihood. 5 ) Estimating the parameters of the gamma, log-normal, and Weibull mixture models fitted to the grouped data through the EM algorithm, 6 ) Estimating parameters of the nonlinear height curve fitted to the height - diameter observation, 7 ) Estimating parameters, computing probability density function, cumulative distribution function, and generating realizations from gamma shape mixture model introduced by Venturini et al. (2008) <doi:10.1214/07-AOAS156> , 8 ) The Bayesian inference, computing probability density function, cumulative distribution function, and generating realizations from four-parameter Johnson SB distribution, 9 ) Robust multiple linear regression analysis when error term follows skewed t distribution, 10 ) Estimating parameters of a given distribution fitted to grouped data using method of maximum likelihood, and 11 ) Estimating parameters of the Johnson SB distribution through the Bayesian, method of moment, conditional maximum likelihood, and two - percentile method.
Author: Mahdi Teimouri
Maintainer: Mahdi Teimouri <teimouri@aut.ac.ir>

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Package decisionSupport updated to version 1.107 with previous version 1.106 dated 2021-03-01

Title: Quantitative Support of Decision Making under Uncertainty
Description: Supporting the quantitative analysis of binary welfare based decision making processes using Monte Carlo simulations. Decision support is given on two levels: (i) The actual decision level is to choose between two alternatives under probabilistic uncertainty. This package calculates the optimal decision based on maximizing expected welfare. (ii) The meta decision level is to allocate resources to reduce the uncertainty in the underlying decision problem, i.e to increase the current information to improve the actual decision making process. This problem is dealt with using the Value of Information Analysis. The Expected Value of Information for arbitrary prospective estimates can be calculated as well as Individual Expected Value of Perfect Information. The probabilistic calculations are done via Monte Carlo simulations. This Monte Carlo functionality can be used on its own.
Author: Eike Luedeling [cre, aut] (University of Bonn), Lutz Goehring [aut] (ICRAF and Lutz Goehring Consulting), Katja Schiffers [aut] (University of Bonn), Cory Whitney [aut] (University of Bonn), Eduardo Fernandez [aut] (University of Bonn)
Maintainer: Eike Luedeling <eike@eikeluedeling.com>

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Package CensSpatial updated to version 2.59 with previous version 2.58 dated 2020-05-04

Title: Censored Spatial Models
Description: It fits linear regression models for censored spatial data. It provides different estimation methods as the SAEM (Stochastic Approximation of Expectation Maximization) algorithm and seminaive that uses Kriging prediction to estimate the response at censored locations and predict new values at unknown locations. It also offers graphical tools for assessing the fitted model. More details can be found in Ordonez et al. (2018) <doi:10.1016/j.spasta.2017.12.001>.
Author: Alejandro Ordonez, Christian E. Galarza, Victor H. Lachos
Maintainer: Alejandro Ordonez <ordonezjosealejandro@gmail.com>

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Package nfl4th updated to version 1.0.1 with previous version 1.0.0 dated 2021-03-17

Title: Functions to Calculate Optimal Fourth Down Decisions in the National Football League
Description: A set of functions to estimate outcomes of fourth down plays in the National Football League and obtain fourth down plays from <https://www.nfl.com/> and <https://www.espn.com/>.
Author: Ben Baldwin [aut, cre, cph], Sebastian Carl [ctb]
Maintainer: Ben Baldwin <bbaldwin206@gmail.com>

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Package gtsummary updated to version 1.5.0 with previous version 1.4.2 dated 2021-07-13

Title: Presentation-Ready Data Summary and Analytic Result Tables
Description: Creates presentation-ready tables summarizing data sets, regression models, and more. The code to create the tables is concise and highly customizable. Data frames can be summarized with any function, e.g. mean(), median(), even user-written functions. Regression models are summarized and include the reference rows for categorical variables. Common regression models, such as logistic regression and Cox proportional hazards regression, are automatically identified and the tables are pre-filled with appropriate column headers.
Author: Daniel D. Sjoberg [aut, cre] (<https://orcid.org/0000-0003-0862-2018>), Michael Curry [aut] (<https://orcid.org/0000-0002-0261-4044>), Joseph Larmarange [aut] (<https://orcid.org/0000-0001-7097-700X>), Jessica Lavery [aut] (<https://orcid.org/0000-0002-2746-5647>), Karissa Whiting [aut] (<https://orcid.org/0000-0002-4683-1868>), Emily C. Zabor [aut] (<https://orcid.org/0000-0002-1402-4498>), Xing Bai [ctb], Esther Drill [ctb] (<https://orcid.org/0000-0002-3315-4538>), Jessica Flynn [ctb] (<https://orcid.org/0000-0001-8310-6684>), Margie Hannum [ctb] (<https://orcid.org/0000-0002-2953-0449>), Stephanie Lobaugh [ctb], Gustavo Zapata Wainberg [ctb] (<https://orcid.org/0000-0002-2524-3637>)
Maintainer: Daniel D. Sjoberg <danield.sjoberg@gmail.com>

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Package soundgen updated to version 2.4.0 with previous version 2.3.0 dated 2021-09-06

Title: Sound Synthesis and Acoustic Analysis
Description: Performs parametric synthesis of sounds with harmonic and noise components such as animal vocalizations or human voice. Also offers tools for audio manipulation and acoustic analysis, including pitch tracking, spectral analysis, audio segmentation, pitch and formant shifting, etc. Includes four interactive web apps for synthesizing and annotating audio, manually correcting pitch contours, and measuring formant frequencies. Reference: Anikin (2019) <doi:10.3758/s13428-018-1095-7>.
Author: Andrey Anikin [aut, cre]
Maintainer: Andrey Anikin <rty.anik@rambler.ru>

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Package carat updated to version 2.0.2 with previous version 2.0.1 dated 2021-10-02

Title: Covariate-Adaptive Randomization for Clinical Trials
Description: Provides functions and command-line user interface to generate allocation sequence by covariate-adaptive randomization for clinical trials. The package currently supports six covariate-adaptive randomization procedures. Three hypothesis testing methods that are valid and robust under covariate-adaptive randomization are also available in the package to facilitate the inference for treatment effect under the included randomization procedures. Additionally, the package provides comprehensive and efficient tools to allow one to evaluate and compare the performance of randomization procedures and tests based on various criteria.
Author: Fuyi Tu [aut], Xiaoqing Ye [aut, cre], Wei Ma [aut, ths], Feifang Hu [aut, ths]
Maintainer: Xiaoqing Ye <ye_xiaoq@163.com>

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Package rEDM updated to version 1.9.3 with previous version 1.9.2 dated 2021-09-16

Title: Empirical Dynamic Modeling ('EDM')
Description: An implementation of 'EDM' algorithms based on research software developed for internal use at the Sugihara Lab ('UCSD/SIO'). The package is implemented with 'Rcpp' wrappers around the 'cppEDM' library. It implements the 'simplex' projection method from Sugihara & May (1990) <doi:10.1038/344734a0>, the 'S-map' algorithm from Sugihara (1994) <doi:10.1098/rsta.1994.0106>, convergent cross mapping described in Sugihara et al. (2012) <doi:10.1126/science.1227079>, and, 'multiview embedding' described in Ye & Sugihara (2016) <doi:10.1126/science.aag0863>.
Author: Joseph Park [aut, cre] (<https://orcid.org/0000-0001-5411-1409>), Cameron Smith [aut] (<https://orcid.org/0000-0003-0020-5607>), George Sugihara [aut, ccp] (<https://orcid.org/0000-0002-2863-6946>), Ethan Deyle [aut] (<https://orcid.org/0000-0001-8704-8434>), Erik Saberski [ctb] (<https://orcid.org/0000-0002-6475-6187>), Hao Ye [ctb] (<https://orcid.org/0000-0002-8630-1458>), The Regents of the University of California [cph]
Maintainer: Joseph Park <JosephPark@IEEE.org>

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Package seriation updated to version 1.3.1 with previous version 1.3.0 dated 2021-06-30

Title: Infrastructure for Ordering Objects Using Seriation
Description: Infrastructure for ordering objects with an implementation of several seriation/sequencing/ordination techniques to reorder matrices, dissimilarity matrices, and dendrograms. Also provides (optimally) reordered heatmaps, color images and clustering visualizations like dissimilarity plots, and visual assessment of cluster tendency plots (VAT and iVAT). Hahsler et al (2008) <doi:10.18637/jss.v025.i03>.
Author: Michael Hahsler [aut, cre, cph], Christian Buchta [aut, cph], Kurt Hornik [aut, cph], Fionn Murtagh [ctb, cph], Michael Brusco [ctb, cph], Stephanie Stahl [ctb, cph], Hans-Friedrich Koehn [ctb, cph]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

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Package RaSEn updated to version 3.0.0 with previous version 2.2.0 dated 2021-08-19

Title: Random Subspace Ensemble Classification and Variable Screening
Description: We propose a general ensemble classification framework, RaSE algorithm, for the sparse classification problem. In RaSE algorithm, for each weak learner, some random subspaces are generated and the optimal one is chosen to train the model on the basis of some criterion. To be adapted to the problem, a novel criterion, ratio information criterion (RIC) is put up with based on Kullback-Leibler divergence. Besides minimizing RIC, multiple criteria can be applied, for instance, minimizing extended Bayesian information criterion (eBIC), minimizing training error, minimizing the validation error, minimizing the cross-validation error, minimizing leave-one-out error. There are various choices of base classifier, for instance, linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbour, logistic regression, decision trees, random forest, support vector machines. RaSE algorithm can also be applied to do feature ranking, providing us the importance of each feature based on the selected percentage in multiple subspaces. RaSE framework can be extended to the general prediction framework, including both classification and regression. We can use the selected percentages of variables for variable screening. The latest version added the variable screening function for both regression and classification problems.
Author: Ye Tian [aut, cre] and Yang Feng [aut]
Maintainer: Ye Tian <ye.t@columbia.edu>

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Package r2dii.plot updated to version 0.2.0 with previous version 0.1.0 dated 2021-06-29

Title: Visualize the Climate Scenario Alignment of a Financial Portfolio
Description: Create plots to visualize the alignment of a corporate lending financial portfolio to climate change scenarios based on climate indicators (production and emission intensities) across key climate relevant sectors of the 'PACTA' methodology (Paris Agreement Capital Transition Assessment; <https://2degrees-investing.org/>). Financial institutions use 'PACTA' to study how their capital allocation decisions align with climate change mitigation goals.
Author: Monika Furdyna [aut, ctr, cre] (<https://orcid.org/0000-0002-3728-0646>), Mauro Lepore [aut, ctr] (<https://orcid.org/0000-0002-1986-7988>), Alex Axthelm [aut, ctr] (<https://orcid.org/0000-0001-8579-8565>), 2 Degrees Investing Initiative [cph, fnd]
Maintainer: Monika Furdyna <monika.furdyna@gmail.com>

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Package fdth updated to version 1.2-6 with previous version 1.2-5 dated 2020-04-17

Title: Frequency Distribution Tables, Histograms and Polygons
Description: Perform frequency distribution tables, associated histograms and polygons from vector, data.frame and matrix objects for numerical and categorical variables.
Author: Jos<e9> Cl<e1>udio Faria, Enio G. Jelihovschi and Ivan B. Allaman
Maintainer: Jos<e9> Cl<e1>udio Faria <joseclaudio.faria@gmail.com>

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Package evalITR updated to version 0.2.2 with previous version 0.2.1 dated 2021-07-07

Title: Evaluating Individualized Treatment Rules
Description: Provides various statistical methods for evaluating Individualized Treatment Rules under randomized data. The provided metrics include Population Average Value (PAV), Population Average Prescription Effect (PAPE), Area Under Prescription Effect Curve (AUPEC). It also provides the tools to analyze Individualized Treatment Rules under budget constraints. Detailed reference in Imai and Li (2019) <arXiv:1905.05389>.
Author: Michael Lingzhi Li [aut, cre], Kosuke Imai [aut]
Maintainer: Michael Lingzhi Li <mlli@mit.edu>

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Fri, 15 Oct 2021

Package retriever updated to version 0.2.0 with previous version 0.1.0 dated 2021-10-08

Title: Generate Disease-Specific Response Signatures from the LINCS-L1000 Data
Description: Generates disease-specific drug-response profiles that are independent of time, concentration, and cell-line. Based on the cell lines used as surrogates, the returned profiles represent the unique transcriptional changes induced by a compound in a given disease.
Author: Daniel Osorio [aut, cre] (<https://orcid.org/0000-0003-4424-8422>), Marieke Kuijjer [aut] (<https://orcid.org/0000-0001-6280-3130>)
Maintainer: Daniel Osorio <daniecos@uio.no>

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Package Rage updated to version 1.2.0 with previous version 1.1.0 dated 2021-07-09

Title: Life History Metrics from Matrix Population Models
Description: Functions for calculating life history metrics using matrix population models ('MPMs'). Described in Jones et al. (2021) <doi:10.1101/2021.04.26.441330>.
Author: Patrick Barks [aut] (<https://orcid.org/0000-0002-5947-8151>), Danny Buss [ctb], Pol Capdevila [aut] (<https://orcid.org/0000-0002-2842-4302>), Hal Caswell [aut] (<https://orcid.org/0000-0003-4394-6894>), Judy P. Che-Castaldo [aut] (<https://orcid.org/0000-0002-9118-9202>), John Jackson [aut] (<https://orcid.org/0000-0002-4563-2840>), Tamora James [aut] (<https://orcid.org/0000-0003-1363-4742>), Owen Jones [aut, cre] (<https://orcid.org/0000-0001-5720-4686>), Sam Levin [aut] (<https://orcid.org/0000-0002-3289-9925>), William K. Petry [aut] (<https://orcid.org/0000-0002-5230-5987>), Roberto Salguero-Gomez [aut] (<https://orcid.org/0000-0002-6085-4433>), Caroline Schuette [ctb] (<https://orcid.org/0000-0002-2063-8736>), Iain Stott [aut] (<https://orcid.org/0000-0003-2724-7436>), Chelsea C. Thomas [aut] (<https://orcid.org/0000-0002-8155-9353>)
Maintainer: Owen Jones <jones@biology.sdu.dk>

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Package pchc updated to version 0.6 with previous version 0.5 dated 2021-03-21

Title: Bayesian Network Learning with the PCHC and Related Algorithms
Description: Bayesian network learning using the PCHC algorithm. PCHC stands for PC Hill-Climbing, a new hybrid algorithm that uses PC to construct the skeleton of the BN and then applies the Hill-Climbing greedy search. More algorithms and variants have been added, such as MMHC, FEDHC, and the Tabu search variants, PCTABU, MMTABU and FEDTABU. The relevant papers are a) Tsagris M. (2021). A new scalable Bayesian network learning algorithm with applications to economics. Computational Economics, 57(1): 341-367. <doi:10.1007/s10614-020-10065-7>. b) Tsagris M. (2021). The FEDHC Bayesian network learning algorithm. <arXiv:2012.00113>.
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package POFIBGE updated to version 0.1.4 with previous version 0.1.3 dated 2021-06-24

Title: Downloading, Reading and Analysing POF Microdata
Description: Provides tools for downloading, reading and analysing the POF, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package 'survey'.
Author: Gabriel Assuncao [aut, cre], Luna Hidalgo [aut], Douglas Braga [ctb]
Maintainer: Gabriel Assuncao <pacotesipd@ibge.gov.br>

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Package PNSIBGE updated to version 0.1.5 with previous version 0.1.4 dated 2021-06-24

Title: Downloading, Reading and Analysing PNS Microdata
Description: Provides tools for downloading, reading and analysing the PNS, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package 'survey'.
Author: Gabriel Assuncao [aut, cre], Luna Hidalgo [aut], Douglas Braga [ctb]
Maintainer: Gabriel Assuncao <pacotesipd@ibge.gov.br>

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Package isoreader updated to version 1.3.1 with previous version 1.3.0 dated 2021-02-16

Title: Read Stable Isotope Data Files
Description: Interface to the raw data file formats commonly encountered in scientific disciplines that make use of stable isotopes.
Author: Sebastian Kopf [aut, cre] (<https://orcid.org/0000-0002-2044-0201>), Brett Davidheiser-Kroll [aut] (<https://orcid.org/0000-0002-6153-7851>), Ilja Kocken [aut] (<https://orcid.org/0000-0003-2196-8718>)
Maintainer: Sebastian Kopf <sebastian.kopf@colorado.edu>

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Package dm updated to version 0.2.5 with previous version 0.2.4 dated 2021-09-30

Title: Relational Data Models
Description: Provides tools for working with multiple related tables, stored as data frames or in a relational database. Multiple tables (data and metadata) are stored in a compound object, which can then be manipulated with a pipe-friendly syntax.
Author: Tobias Schieferdecker [aut], Kirill Müller [aut, cre] (<https://orcid.org/0000-0002-1416-3412>), Darko Bergant [aut], Katharina Brunner [ctb], James Wondrasek [ctb], energie360° AG [fnd], cynkra GmbH [fnd, cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

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Package arkdb updated to version 0.0.13 with previous version 0.0.12 dated 2021-04-05

Title: Archive and Unarchive Databases Using Flat Files
Description: Flat text files provide a robust, compressible, and portable way to store tables from databases. This package provides convenient functions for exporting tables from relational database connections into compressed text files and streaming those text files back into a database without requiring the whole table to fit in working memory.
Author: Carl Boettiger [aut, cre, cph] (<https://orcid.org/0000-0002-1642-628X>), Richard FitzJohn [ctb], Brandon Bertelsen [ctb]
Maintainer: Carl Boettiger <cboettig@gmail.com>

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Package Rcompadre updated to version 1.1.0 with previous version 1.0.0 dated 2021-04-30

Title: Utilities for using the 'COM(P)ADRE' Matrix Model Database
Description: Utility functions for interacting with the 'COMPADRE' and 'COMADRE' databases of matrix population models. Described in Jones et al. (2021) <doi:10.1101/2021.04.26.441330>.
Author: Patrick Barks [aut] (<https://orcid.org/0000-0002-5947-8151>), Danny Buss [aut], Roberto Salguero-Gomez [aut] (<https://orcid.org/0000-0002-6085-4433>), Iain Stott [aut] (<https://orcid.org/0000-0003-2724-7436>), William K. Petry [aut] (<https://orcid.org/0000-0002-5230-5987>), Tamora James [aut] (<https://orcid.org/0000-0003-1363-4742>), Owen Jones [aut, cre] (<https://orcid.org/0000-0001-5720-4686>), Julia Jones [aut] (<https://orcid.org/0000-0001-9223-1778>), Gesa Römer [aut] (<https://orcid.org/0000-0002-4859-5870>), Sam Levin [aut] (<https://orcid.org/0000-0002-3289-9925>)
Maintainer: Owen Jones <jones@biology.sdu.dk>

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Package DTAplots updated to version 1.0.2.5 with previous version 1.0.2.4 dated 2021-03-17

Title: Creates Plots Accompanying Bayesian Diagnostic Test Accuracy Meta-Analyses
Description: Function to create forest plots. Functions to use posterior samples from Bayesian bivariate meta-analysis model, Bayesian hierarchical summary receiver operating characteristic (HSROC) meta-analysis model or Bayesian latent class (LC) meta-analysis model to create Summary Receiver Operating Characteristic (SROC) plots using methods described by Harbord et al (2007)<doi:10.1093/biostatistics/kxl004>.
Author: Ian Schiller [aut, cre], Nandini Dendukuri [ctb]
Maintainer: Ian Schiller <ian.schiller@rimuhc.ca>

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Package COVIDIBGE updated to version 0.1.6 with previous version 0.1.5 dated 2021-06-24

Title: Downloading, Reading and Analysing PNAD COVID19 Microdata
Description: Provides tools for downloading, reading and analysing the PNAD COVID19, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package 'survey'.
Author: Gabriel Assuncao [aut, cre], Luna Hidalgo [aut], Douglas Braga [ctb]
Maintainer: Gabriel Assuncao <pacotesipd@ibge.gov.br>

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Package migrate updated to version 0.4.0 with previous version 0.3.0 dated 2020-12-07

Title: Create Credit State Migration (Transition) Matrices
Description: Tools to help convert credit risk data at two time points into traditional credit state migration (aka, "transition") matrices. At a higher level, 'migrate' is intended to help an analyst understand how risk moved in their credit portfolio over a time interval. References to this methodology include: 1. Schuermann, T. (2008) <doi:10.1002/9780470061596.risk0409>. 2. Perederiy, V. (2017) <arXiv:1708.00062>.
Author: Michael Thomas [aut, cre], Brad Lindblad [ctb]
Maintainer: Michael Thomas <mthomas@ketchbrookanalytics.com>

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Package islasso updated to version 1.4.0 with previous version 1.3.1 dated 2021-06-16

Title: The Induced Smoothed Lasso
Description: An implementation of the induced smoothing (IS) idea to lasso regularization models to allow estimation and inference on the model coefficients (currently hypothesis testing only). Linear, logistic, Poisson and gamma regressions with several link functions are implemented. The algorithm is described in the original paper: Cilluffo, G., Sottile, G., La Grutta, S. and Muggeo, V. (2019) The Induced Smoothed lasso: A practical framework for hypothesis testing in high dimensional regression. <doi:10.1177/0962280219842890>, and discussed in a tutorial: Sottile, G., Cilluffo, G., and Muggeo, V. (2019) The R package islasso: estimation and hypothesis testing in lasso regression. <doi:10.13140/RG.2.2.16360.11521>.
Author: Gianluca Sottile [aut, cre], Giovanna Cilluffo [aut, ctb], Vito MR Muggeo [aut, cre]
Maintainer: Gianluca Sottile <gianluca.sottile@unipa.it>

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Package shinybrms updated to version 1.5.2 with previous version 1.5.1 dated 2021-03-06

Title: Graphical User Interface ('shiny' App) for 'brms'
Description: A graphical user interface (GUI) for fitting Bayesian regression models using the package 'brms' which in turn relies on 'Stan' (<https://mc-stan.org/>). The 'shinybrms' GUI is a 'shiny' app.
Author: Frank Weber [aut, cre] (<https://orcid.org/0000-0002-4842-7922>), Thomas Park [ctb, cph] ('Bootswatch' theme "United"), Twitter, Inc. [ctb, cph] ('Bootstrap' (basis for the 'Bootswatch' theme "United")), Google, LLC [ctb, cph] ("Open Sans" font)
Maintainer: Frank Weber <fweber144@protonmail.com>

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Package MortCast updated to version 2.6-1 with previous version 2.6-0 dated 2021-10-08

Title: Estimation and Projection of Age-Specific Mortality Rates
Description: Age-specific mortality rates are estimated and projected using the Kannisto, Lee-Carter and related methods as described in Sevcikova et al. (2016) <doi:10.1007/978-3-319-26603-9_15>.
Author: Hana Sevcikova, Nan Li and Patrick Gerland
Maintainer: Hana Sevcikova <hanas@uw.edu>

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Package arm updated to version 1.12-2 with previous version 1.11-2 dated 2020-07-27

Title: Data Analysis Using Regression and Multilevel/Hierarchical Models
Description: Functions to accompany A. Gelman and J. Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2007.
Author: Andrew Gelman [aut], Yu-Sung Su [aut, cre], Masanao Yajima [ctb], Jennifer Hill [ctb], Maria Grazia Pittau [ctb], Jouni Kerman [ctb], Tian Zheng [ctb], Vincent Dorie [ctb]
Maintainer: Yu-Sung Su <suyusung@tsinghua.edu.cn>

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Package wpa updated to version 1.6.2 with previous version 1.6.1 dated 2021-09-01

Title: Tools for Analysing and Visualising Workplace Analytics Data
Description: Opinionated functions that enable easier and faster analysis of Workplace Analytics data. There are three main types of functions in 'wpa': (i) Standard functions create a 'ggplot' visual or a summary table based on a specific Workplace Analytics metric; (2) Report Generation functions generate HTML reports on a specific analysis area, e.g. Collaboration; (3) Other miscellaneous functions cover more specific applications (e.g. Subject Line text mining) of Workplace Analytics data. This package adheres to 'tidyverse' principles and works well with the pipe syntax. 'wpa' is built with the beginner-to-intermediate R users in mind, and is optimised for simplicity.
Author: Martin Chan [aut, cre], Carlos Morales [aut], Mark Powers [ctb], Ainize Cidoncha [ctb], Rosamary Ochoa Vargas [ctb], Tannaz Sattari [ctb], Lucas Hogner [ctb], Jasminder Thind [ctb], Simone Liebal [ctb], Aleksey Ashikhmin [ctb], Ellen Trinklein [ctb], Microsoft Corporation [cph]
Maintainer: Martin Chan <martin.chan@microsoft.com>

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Package randomForestSRC updated to version 2.13.0 with previous version 2.12.1 dated 2021-09-05

Title: Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)
Description: Fast OpenMP parallel computing of Breiman's random forests for univariate, multivariate, unsupervised, survival, competing risks, class imbalanced classification and quantile regression. New Mahalanobis splitting for correlated outcomes. Extreme random forests and randomized splitting. Suite of imputation methods for missing data. Fast random forests using subsampling. Confidence regions and standard errors for variable importance. New improved holdout importance. Case-specific importance. Minimal depth variable importance. Visualize trees on your Safari or Google Chrome browser. Anonymous random forests for data privacy.
Author: Hemant Ishwaran <hemant.ishwaran@gmail.com>, Udaya B. Kogalur <ubk@kogalur.com>
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>

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Package Tplyr updated to version 0.4.2 with previous version 0.4.1 dated 2021-07-13

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>

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Package postGGIR updated to version 2.4.0.1 with previous version 2.4.0 dated 2021-07-14

Title: Data Processing after Running 'GGIR' for Accelerometer Data
Description: Generate all necessary R/Rmd/shell files for data processing after running 'GGIR' (v2.4.0) for accelerometer data. In part 1, all csv files in the GGIR output directory were read, transformed and then merged. In part 2, the GGIR output files were checked and summarized in one excel sheet. In part 3, the merged data was cleaned according to the number of valid hours on each night and the number of valid days for each subject. In part 4, the cleaned activity data was imputed by the average Euclidean norm minus one (ENMO) over all the valid days for each subject. Finally, a comprehensive report of data processing was created using Rmarkdown, and the report includes few exploratory plots and multiple commonly used features extracted from minute level actigraphy data.
Author: Wei Guo [aut, cre], Vadim Zipunnikov [aut], Kathleen Merikangas [aut]
Maintainer: Wei Guo <wei.guo3@nih.gov>

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Package micemd updated to version 1.8.0 with previous version 1.7.0 dated 2021-07-30

Title: Multiple Imputation by Chained Equations with Multilevel Data
Description: Addons for the 'mice' package to perform multiple imputation using chained equations with two-level data. Includes imputation methods dedicated to sporadically and systematically missing values. Imputation of continuous, binary or count variables are available. Following the recommendations of Audigier, V. et al (2018) <doi:10.1214/18-STS646>, the choice of the imputation method for each variable can be facilitated by a default choice tuned according to the structure of the incomplete dataset. Allows parallel calculation and overimputation for 'mice'.
Author: Vincent Audigier [aut, cre] (CNAM MSDMA team), Matthieu Resche-Rigon [aut] (INSERM ECSTRA team)
Maintainer: Vincent Audigier <vincent.audigier@cnam.fr>

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Package ghypernet updated to version 1.1.0 with previous version 1.0.1 dated 2020-10-21

Title: Fit and Simulate Generalised Hypergeometric Ensembles of Graphs
Description: Provides functions for model fitting and selection of generalised hypergeometric ensembles of random graphs (gHypEG). To learn how to use it, check the vignettes for a quick tutorial. Please reference its use as Casiraghi, G., Nanumyan, V. (2019) <doi:10.5281/zenodo.2555300> together with those relevant references from the one listed below. The package is based on the research developed at the Chair of Systems Design, ETH Zurich. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2016) <arXiv:1607.02441>. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2017) <doi:10.1007/978-3-319-67256-4_11>. Casiraghi, G., (2017) <arXiv:1702.02048> Brandenberger, L., Casiraghi, G., Nanumyan, V., Schweitzer, F. (2019) <doi:10.1145/3341161.3342926> Casiraghi, G. (2019) <doi:10.1007/s41109-019-0241-1>. Casiraghi, G., Nanumyan, V. (2021) <doi:10.1038/s41598-021-92519-y>. Casiraghi, G. (2021) <doi:10.1088/2632-072X/ac0493>.
Author: Giona Casiraghi [aut, cre] (<https://orcid.org/0000-0003-0233-5747>), Vahan Nanumyan [aut] (<https://orcid.org/0000-0001-9054-3217>), Laurence Brandenberger [ctb], Giacomo Vaccario [ctb]
Maintainer: Giona Casiraghi <giona@ethz.ch>

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Package ebdbNet updated to version 1.2.6 with previous version 1.2.5 dated 2016-11-21

Title: Empirical Bayes Estimation of Dynamic Bayesian Networks
Description: Infer the adjacency matrix of a network from time course data using an empirical Bayes estimation procedure based on Dynamic Bayesian Networks.
Author: Andrea Rau <andrea.rau@inra.fr>
Maintainer: Andrea Rau <andrea.rau@inra.fr>

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Package TPmsm updated to version 1.2.5 with previous version 1.2.4 dated 2021-10-09

Title: Estimation of Transition Probabilities in Multistate Models
Description: Estimation of transition probabilities for the illness-death model and or the three-state progressive model.
Author: Artur Araujo [aut, cre] (<https://orcid.org/0000-0003-1419-4208>), Javier Roca-Pardinas [aut] (<https://orcid.org/0000-0003-3107-4515>), Luis Meira-Machado [aut] (<https://orcid.org/0000-0002-8577-7665>)
Maintainer: Artur Araujo <artur.stat@gmail.com>

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Package stringfish updated to version 0.15.4 with previous version 0.15.3 dated 2021-10-10

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>

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Package phenofit updated to version 0.3.2 with previous version 0.2.7 dated 2020-04-02

Title: Extract Remote Sensing Vegetation Phenology
Description: The merits of 'TIMESAT' and 'phenopix' are adopted. Besides, a simple and growing season dividing method and a practical snow elimination method based on Whittaker were proposed. 7 curve fitting methods and 4 phenology extraction methods were provided. Parameters boundary are considered for every curve fitting methods according to their ecological meaning. And 'optimx' is used to select best optimization method for different curve fitting methods. Reference: Kong, D., (2020). R package: A state-of-the-art Vegetation Phenology extraction package, phenofit version 0.3.1, <doi:10.5281/zenodo.5150204>; Kong, D., Zhang, Y., Wang, D., Chen, J., & Gu, X. (2020). Photoperiod Explains the Asynchronization Between Vegetation Carbon Phenology and Vegetation Greenness Phenology. Journal of Geophysical Research: Biogeosciences, 125(8), e2020JG005636. <doi:10.1029/2020JG005636>; Kong, D., Zhang, Y., Gu, X., & Wang, D. (2019). A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 155, 13–24; Zhang, Q., Kong, D., Shi, P., Singh, V.P., Sun, P., 2018. Vegetation phenology on the Qinghai-Tibetan Plateau and its response to climate change (1982–2013). Agric. For. Meteorol. 248, 408–417. <doi:10.1016/j.agrformet.2017.10.026>.
Author: Dongdong Kong [aut, cre], Mingzhong Xiao [aut], Yongqiang Zhang [aut], Xihui Gu [aut], Jianjian Cui [aut]
Maintainer: Dongdong Kong <kongdd.sysu@gmail.com>

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Package ncdf4.helpers updated to version 0.3-6 with previous version 0.3-5 dated 2020-06-08

Title: Helper Functions for Use with the 'ncdf4' Package
Description: Contains a collection of helper functions for dealing with 'NetCDF' files <https://www.unidata.ucar.edu/software/netcdf/> opened using 'ncdf4', particularly 'NetCDF' files that conform to the Climate and Forecast (CF) Metadata Conventions <http://cfconventions.org/Data/cf-conventions/cf-conventions-1.7/cf-conventions.html>.
Author: David Bronaugh <bronaugh@uvic.ca> for the Pacific Climate Impacts Consortium (PCIC)
Maintainer: Lee Zeman <lzeman@uvic.ca>

Diff between ncdf4.helpers versions 0.3-5 dated 2020-06-08 and 0.3-6 dated 2021-10-15

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Package igraph updated to version 1.2.7 with previous version 1.2.6 dated 2020-10-06

Title: Network Analysis and Visualization
Description: Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.
Author: See AUTHORS file.
Maintainer: Tamás Nepusz <ntamas@gmail.com>

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 igraph-1.2.7/igraph/man/which_mutual.Rd                           |    2 
 igraph-1.2.7/igraph/src/DensityGrid.cpp                           |  387 
 igraph-1.2.7/igraph/src/DensityGrid.h                             |   89 
 igraph-1.2.7/igraph/src/DensityGrid_3d.cpp                        |  431 
 igraph-1.2.7/igraph/src/DensityGrid_3d.h                          |   89 
 igraph-1.2.7/igraph/src/Makevars.in                               |    3 
 igraph-1.2.7/igraph/src/Makevars.win                              |    7 
 igraph-1.2.7/igraph/src/NetDataTypes.cpp                          |  264 
 igraph-1.2.7/igraph/src/NetDataTypes.h                            | 1129 -
 igraph-1.2.7/igraph/src/NetRoutines.cpp                           |  424 
 igraph-1.2.7/igraph/src/NetRoutines.h                             |   18 
 igraph-1.2.7/igraph/src/adjlist.c                                 |  992 
 igraph-1.2.7/igraph/src/arpack.c                                  | 2095 +-
 igraph-1.2.7/igraph/src/array.c                                   |   10 
 igraph-1.2.7/igraph/src/array.pmt                                 |  102 
 igraph-1.2.7/igraph/src/atlas-edges.h                             | 2528 +-
 igraph-1.2.7/igraph/src/atlas.c                                   |   78 
 igraph-1.2.7/igraph/src/attributes.c                              |  650 
 igraph-1.2.7/igraph/src/basic_query.c                             |   36 
 igraph-1.2.7/igraph/src/bfgs.c                                    |  341 
 igraph-1.2.7/igraph/src/bigint.c                                  |  438 
 igraph-1.2.7/igraph/src/bigint.h                                  |   52 
 igraph-1.2.7/igraph/src/bignum.c                                  | 2486 +-
 igraph-1.2.7/igraph/src/bignum.h                                  |   46 
 igraph-1.2.7/igraph/src/bipartite.c                               | 1613 -
 igraph-1.2.7/igraph/src/blas.c                                    |   85 
 igraph-1.2.7/igraph/src/bliss.cc                                  |  209 
 igraph-1.2.7/igraph/src/bliss/bignum.hh                           |    4 
 igraph-1.2.7/igraph/src/bliss/bliss_heap.cc                       |    6 
 igraph-1.2.7/igraph/src/bliss/defs.cc                             |   12 
 igraph-1.2.7/igraph/src/bliss/defs.hh                             |    7 
 igraph-1.2.7/igraph/src/bliss/graph.cc                            |   65 
 igraph-1.2.7/igraph/src/bliss/graph.hh                            |   16 
 igraph-1.2.7/igraph/src/bliss/orbit.cc                            |    4 
 igraph-1.2.7/igraph/src/bliss/partition.cc                        |    6 
 igraph-1.2.7/igraph/src/bliss/partition.hh                        |    6 
 igraph-1.2.7/igraph/src/bliss/uintseqhash.hh                      |    2 
 igraph-1.2.7/igraph/src/bliss/utils.cc                            |    2 
 igraph-1.2.7/igraph/src/bliss/utils.hh                            |    6 
 igraph-1.2.7/igraph/src/cattributes.c                             | 6522 +++---
 igraph-1.2.7/igraph/src/centrality.c                              | 4892 ++--
 igraph-1.2.7/igraph/src/cliquer/cliquer.c                         |    9 
 igraph-1.2.7/igraph/src/cliquer/cliquer_graph.c                   |    8 
 igraph-1.2.7/igraph/src/cliquer/reorder.c                         |    2 
 igraph-1.2.7/igraph/src/cliquer/set.h                             |    4 
 igraph-1.2.7/igraph/src/cliques.c                                 | 1810 -
 igraph-1.2.7/igraph/src/clustertool.cpp                           |  981 
 igraph-1.2.7/igraph/src/cocitation.c                              |  587 
 igraph-1.2.7/igraph/src/cohesive_blocks.c                         | 1019 
 igraph-1.2.7/igraph/src/coloring.c                                |   49 
 igraph-1.2.7/igraph/src/community.c                               | 5617 ++---
 igraph-1.2.7/igraph/src/community_leiden.c                        |only
 igraph-1.2.7/igraph/src/complex.c                                 |  572 
 igraph-1.2.7/igraph/src/components.c                              | 1686 -
 igraph-1.2.7/igraph/src/config.h.in                               |   17 
 igraph-1.2.7/igraph/src/conversion.c                              | 1389 -
 igraph-1.2.7/igraph/src/cores.c                                   |  220 
 igraph-1.2.7/igraph/src/decomposition.c                           |  756 
 igraph-1.2.7/igraph/src/degree_sequence.cpp                       |only
 igraph-1.2.7/igraph/src/distances.c                               |  265 
 igraph-1.2.7/igraph/src/dotproduct.c                              |  326 
 igraph-1.2.7/igraph/src/dqueue.c                                  |   10 
 igraph-1.2.7/igraph/src/dqueue.pmt                                |  385 
 igraph-1.2.7/igraph/src/drl_Node.h                                |   64 
 igraph-1.2.7/igraph/src/drl_Node_3d.h                             |   64 
 igraph-1.2.7/igraph/src/drl_graph.cpp                             | 2024 -
 igraph-1.2.7/igraph/src/drl_graph.h                               |  178 
 igraph-1.2.7/igraph/src/drl_graph_3d.cpp                          | 1461 -
 igraph-1.2.7/igraph/src/drl_graph_3d.h                            |  162 
 igraph-1.2.7/igraph/src/drl_layout.cpp                            |  562 
 igraph-1.2.7/igraph/src/drl_layout.h                              |   62 
 igraph-1.2.7/igraph/src/drl_layout_3d.cpp                         |   86 
 igraph-1.2.7/igraph/src/drl_layout_3d.h                           |   62 
 igraph-1.2.7/igraph/src/drl_parse.cpp                             |  240 
 igraph-1.2.7/igraph/src/drl_parse.h                               |   74 
 igraph-1.2.7/igraph/src/eigen.c                                   | 2669 +-
 igraph-1.2.7/igraph/src/embedding.c                               | 1703 -
 igraph-1.2.7/igraph/src/fast_community.c                          | 1666 -
 igraph-1.2.7/igraph/src/feedback_arc_set.c                        | 1046 -
 igraph-1.2.7/igraph/src/flow.c                                    | 3469 +--
 igraph-1.2.7/igraph/src/foreign-dl-header.h                       |   37 
 igraph-1.2.7/igraph/src/foreign-dl-lexer.c                        |   95 
 igraph-1.2.7/igraph/src/foreign-dl-lexer.l                        |    7 
 igraph-1.2.7/igraph/src/foreign-gml-header.h                      |   18 
 igraph-1.2.7/igraph/src/foreign-gml-lexer.c                       |   48 
 igraph-1.2.7/igraph/src/foreign-gml-lexer.l                       |    8 
 igraph-1.2.7/igraph/src/foreign-graphml.c                         | 3179 +--
 igraph-1.2.7/igraph/src/foreign-lgl-header.h                      |   26 
 igraph-1.2.7/igraph/src/foreign-lgl-lexer.c                       |   48 
 igraph-1.2.7/igraph/src/foreign-lgl-lexer.l                       |    8 
 igraph-1.2.7/igraph/src/foreign-ncol-header.h                     |   24 
 igraph-1.2.7/igraph/src/foreign-ncol-lexer.c                      |   48 
 igraph-1.2.7/igraph/src/foreign-ncol-lexer.l                      |    8 
 igraph-1.2.7/igraph/src/foreign-pajek-header.h                    |   42 
 igraph-1.2.7/igraph/src/foreign-pajek-lexer.c                     |   48 
 igraph-1.2.7/igraph/src/foreign-pajek-lexer.l                     |    8 
 igraph-1.2.7/igraph/src/foreign-pajek-parser.c                    |    4 
 igraph-1.2.7/igraph/src/foreign-pajek-parser.y                    |    4 
 igraph-1.2.7/igraph/src/foreign.c                                 | 5304 ++---
 igraph-1.2.7/igraph/src/forestfire.c                              |  343 
 igraph-1.2.7/igraph/src/fortran_intrinsics.c                      |   38 
 igraph-1.2.7/igraph/src/games.c                                   | 6785 +++---
 igraph-1.2.7/igraph/src/gengraph_box_list.cpp                     |  119 
 igraph-1.2.7/igraph/src/gengraph_box_list.h                       |   82 
 igraph-1.2.7/igraph/src/gengraph_definitions.h                    |  119 
 igraph-1.2.7/igraph/src/gengraph_degree_sequence.cpp              |  451 
 igraph-1.2.7/igraph/src/gengraph_degree_sequence.h                |  111 
 igraph-1.2.7/igraph/src/gengraph_graph_molloy_hash.cpp            | 1080 -
 igraph-1.2.7/igraph/src/gengraph_graph_molloy_hash.h              |  311 
 igraph-1.2.7/igraph/src/gengraph_graph_molloy_optimized.cpp       | 2775 +-
 igraph-1.2.7/igraph/src/gengraph_graph_molloy_optimized.h         |  447 
 igraph-1.2.7/igraph/src/gengraph_hash.h                           |  342 
 igraph-1.2.7/igraph/src/gengraph_header.h                         |   85 
 igraph-1.2.7/igraph/src/gengraph_mr-connected.cpp                 |  196 
 igraph-1.2.7/igraph/src/gengraph_powerlaw.cpp                     |  356 
 igraph-1.2.7/igraph/src/gengraph_powerlaw.h                       |   86 
 igraph-1.2.7/igraph/src/gengraph_qsort.h                          |  718 
 igraph-1.2.7/igraph/src/gengraph_random.cpp                       |   60 
 igraph-1.2.7/igraph/src/gengraph_random.h                         |   54 
 igraph-1.2.7/igraph/src/gengraph_vertex_cover.h                   |   68 
 igraph-1.2.7/igraph/src/glet.c                                    | 1404 -
 igraph-1.2.7/igraph/src/glpk_support.c                            |   87 
 igraph-1.2.7/igraph/src/gml_tree.c                                |  370 
 igraph-1.2.7/igraph/src/hacks.c                                   |   13 
 igraph-1.2.7/igraph/src/heap.c                                    | 1273 -
 igraph-1.2.7/igraph/src/heap.pmt                                  |  326 
 igraph-1.2.7/igraph/src/hrg_dendro.h                              |  351 
 igraph-1.2.7/igraph/src/hrg_graph.h                               |  158 
 igraph-1.2.7/igraph/src/hrg_graph_simp.h                          |  134 
 igraph-1.2.7/igraph/src/hrg_rbtree.h                              |  148 
 igraph-1.2.7/igraph/src/hrg_splittree_eq.h                        |  180 
 igraph-1.2.7/igraph/src/igraph_arpack_internal.h                  |  310 
 igraph-1.2.7/igraph/src/igraph_blas_internal.h                    |   69 
 igraph-1.2.7/igraph/src/igraph_buckets.c                          |  210 
 igraph-1.2.7/igraph/src/igraph_cliquer.c                          |  124 
 igraph-1.2.7/igraph/src/igraph_cliquer.h                          |   16 
 igraph-1.2.7/igraph/src/igraph_error.c                            |  219 
 igraph-1.2.7/igraph/src/igraph_estack.c                           |   54 
 igraph-1.2.7/igraph/src/igraph_estack.h                           |   22 
 igraph-1.2.7/igraph/src/igraph_f2c.h                              |  286 
 igraph-1.2.7/igraph/src/igraph_fixed_vectorlist.c                 |   98 
 igraph-1.2.7/igraph/src/igraph_flow_internal.h                    |   25 
 igraph-1.2.7/igraph/src/igraph_glpk_support.h                     |   20 
 igraph-1.2.7/igraph/src/igraph_gml_tree.h                         |   74 
 igraph-1.2.7/igraph/src/igraph_grid.c                             |  832 
 igraph-1.2.7/igraph/src/igraph_hacks_internal.h                   |   32 
 igraph-1.2.7/igraph/src/igraph_handle_exceptions.h                |only
 igraph-1.2.7/igraph/src/igraph_hashtable.c                        |  148 
 igraph-1.2.7/igraph/src/igraph_heap.c                             |   10 
 igraph-1.2.7/igraph/src/igraph_hrg.cc                             | 1549 -
 igraph-1.2.7/igraph/src/igraph_hrg_types.cc                       | 5912 ++---
 igraph-1.2.7/igraph/src/igraph_interrupt_internal.h               |   38 
 igraph-1.2.7/igraph/src/igraph_isoclasses.h                       |only
 igraph-1.2.7/igraph/src/igraph_lapack_internal.h                  |  280 
 igraph-1.2.7/igraph/src/igraph_marked_queue.c                     |  112 
 igraph-1.2.7/igraph/src/igraph_marked_queue.h                     |   28 
 igraph-1.2.7/igraph/src/igraph_math.h                             |   40 
 igraph-1.2.7/igraph/src/igraph_psumtree.c                         |  102 
 igraph-1.2.7/igraph/src/igraph_set.c                              |  250 
 igraph-1.2.7/igraph/src/igraph_stack.c                            |   32 
 igraph-1.2.7/igraph/src/igraph_strvector.c                        |  651 
 igraph-1.2.7/igraph/src/igraph_threading.h                        |   16 
 igraph-1.2.7/igraph/src/igraph_trie.c                             |  504 
 igraph-1.2.7/igraph/src/igraph_types_internal.h                   |  246 
 igraph-1.2.7/igraph/src/igraph_version.h                          |   20 
 igraph-1.2.7/igraph/src/include/igraph.h                          |   12 
 igraph-1.2.7/igraph/src/include/igraph_adjlist.h                  |  145 
 igraph-1.2.7/igraph/src/include/igraph_arpack.h                   |  114 
 igraph-1.2.7/igraph/src/include/igraph_array.h                    |   10 
 igraph-1.2.7/igraph/src/include/igraph_array_pmt.h                |   46 
 igraph-1.2.7/igraph/src/include/igraph_attributes.h               |  545 
 igraph-1.2.7/igraph/src/include/igraph_bipartite.h                |   88 
 igraph-1.2.7/igraph/src/include/igraph_blas.h                     |   27 
 igraph-1.2.7/igraph/src/include/igraph_centrality.h               |  242 
 igraph-1.2.7/igraph/src/include/igraph_cliques.h                  |   78 
 igraph-1.2.7/igraph/src/include/igraph_cocitation.h               |   38 
 igraph-1.2.7/igraph/src/include/igraph_cohesive_blocks.h          |   24 
 igraph-1.2.7/igraph/src/include/igraph_coloring.h                 |   24 
 igraph-1.2.7/igraph/src/include/igraph_community.h                |  271 
 igraph-1.2.7/igraph/src/include/igraph_complex.h                  |   78 
 igraph-1.2.7/igraph/src/include/igraph_components.h               |   39 
 igraph-1.2.7/igraph/src/include/igraph_constants.h                |  211 
 igraph-1.2.7/igraph/src/include/igraph_constructors.h             |   58 
 igraph-1.2.7/igraph/src/include/igraph_conversion.h               |   37 
 igraph-1.2.7/igraph/src/include/igraph_datatype.h                 |   49 
 igraph-1.2.7/igraph/src/include/igraph_decls.h                    |   29 
 igraph-1.2.7/igraph/src/include/igraph_dqueue.h                   |   14 
 igraph-1.2.7/igraph/src/include/igraph_dqueue_pmt.h               |   46 
 igraph-1.2.7/igraph/src/include/igraph_eigen.h                    |  132 
 igraph-1.2.7/igraph/src/include/igraph_embedding.h                |   57 
 igraph-1.2.7/igraph/src/include/igraph_epidemics.h                |   24 
 igraph-1.2.7/igraph/src/include/igraph_error.h                    |  373 
 igraph-1.2.7/igraph/src/include/igraph_flow.h                     |  156 
 igraph-1.2.7/igraph/src/include/igraph_foreign.h                  |   64 
 igraph-1.2.7/igraph/src/include/igraph_games.h                    |  287 
 igraph-1.2.7/igraph/src/include/igraph_graphlets.h                |   30 
 igraph-1.2.7/igraph/src/include/igraph_heap.h                     |   10 
 igraph-1.2.7/igraph/src/include/igraph_heap_pmt.h                 |   42 
 igraph-1.2.7/igraph/src/include/igraph_hrg.h                      |   67 
 igraph-1.2.7/igraph/src/include/igraph_interface.h                |  109 
 igraph-1.2.7/igraph/src/include/igraph_interrupt.h                |   16 
 igraph-1.2.7/igraph/src/include/igraph_iterators.h                |  208 
 igraph-1.2.7/igraph/src/include/igraph_lapack.h                   |  100 
 igraph-1.2.7/igraph/src/include/igraph_layout.h                   |  263 
 igraph-1.2.7/igraph/src/include/igraph_lsap.h                     |   10 
 igraph-1.2.7/igraph/src/include/igraph_matching.h                 |   28 
 igraph-1.2.7/igraph/src/include/igraph_matrix.h                   |   12 
 igraph-1.2.7/igraph/src/include/igraph_matrix_pmt.h               |  286 
 igraph-1.2.7/igraph/src/include/igraph_memory.h                   |   14 
 igraph-1.2.7/igraph/src/include/igraph_microscopic_update.h       |   38 
 igraph-1.2.7/igraph/src/include/igraph_mixing.h                   |   30 
 igraph-1.2.7/igraph/src/include/igraph_motifs.h                   |   48 
 igraph-1.2.7/igraph/src/include/igraph_neighborhood.h             |   27 
 igraph-1.2.7/igraph/src/include/igraph_nongraph.h                 |   49 
 igraph-1.2.7/igraph/src/include/igraph_operators.h                |   44 
 igraph-1.2.7/igraph/src/include/igraph_paths.h                    |  181 
 igraph-1.2.7/igraph/src/include/igraph_pmt.h                      |  186 
 igraph-1.2.7/igraph/src/include/igraph_pmt_off.h                  |   78 
 igraph-1.2.7/igraph/src/include/igraph_progress.h                 |  114 
 igraph-1.2.7/igraph/src/include/igraph_psumtree.h                 |   30 
 igraph-1.2.7/igraph/src/include/igraph_qsort.h                    |   16 
 igraph-1.2.7/igraph/src/include/igraph_random.h                   |   77 
 igraph-1.2.7/igraph/src/include/igraph_scan.h                     |   50 
 igraph-1.2.7/igraph/src/include/igraph_scg.h                      |  219 
 igraph-1.2.7/igraph/src/include/igraph_separators.h               |   26 
 igraph-1.2.7/igraph/src/include/igraph_sparsemat.h                |  464 
 igraph-1.2.7/igraph/src/include/igraph_spmatrix.h                 |   42 
 igraph-1.2.7/igraph/src/include/igraph_stack.h                    |   10 
 igraph-1.2.7/igraph/src/include/igraph_stack_pmt.h                |   38 
 igraph-1.2.7/igraph/src/include/igraph_statusbar.h                |   86 
 igraph-1.2.7/igraph/src/include/igraph_structural.h               |  128 
 igraph-1.2.7/igraph/src/include/igraph_strvector.h                |   68 
 igraph-1.2.7/igraph/src/include/igraph_threading.h.in             |   16 
 igraph-1.2.7/igraph/src/include/igraph_topology.h                 |  293 
 igraph-1.2.7/igraph/src/include/igraph_transitivity.h             |   60 
 igraph-1.2.7/igraph/src/include/igraph_types.h                    |   34 
 igraph-1.2.7/igraph/src/include/igraph_vector.h                   |   55 
 igraph-1.2.7/igraph/src/include/igraph_vector_pmt.h               |  302 
 igraph-1.2.7/igraph/src/include/igraph_vector_ptr.h               |   38 
 igraph-1.2.7/igraph/src/include/igraph_vector_type.h              |   18 
 igraph-1.2.7/igraph/src/include/igraph_version.h.in               |   18 
 igraph-1.2.7/igraph/src/include/igraph_visitor.h                  |   80 
 igraph-1.2.7/igraph/src/infomap.cc                                |  462 
 igraph-1.2.7/igraph/src/infomap_FlowGraph.cc                      |  637 
 igraph-1.2.7/igraph/src/infomap_FlowGraph.h                       |   68 
 igraph-1.2.7/igraph/src/infomap_Greedy.cc                         | 1077 -
 igraph-1.2.7/igraph/src/infomap_Greedy.h                          |   98 
 igraph-1.2.7/igraph/src/infomap_Node.cc                           |   87 
 igraph-1.2.7/igraph/src/infomap_Node.h                            |   43 
 igraph-1.2.7/igraph/src/init.c                                    |   22 
 igraph-1.2.7/igraph/src/interrupt.c                               |   35 
 igraph-1.2.7/igraph/src/iterators.c                               | 2119 +-
 igraph-1.2.7/igraph/src/lad.c                                     | 2940 +-
 igraph-1.2.7/igraph/src/lapack.c                                  | 1311 -
 igraph-1.2.7/igraph/src/layout.c                                  | 3804 +--
 igraph-1.2.7/igraph/src/layout_dh.c                               |  673 
 igraph-1.2.7/igraph/src/layout_fr.c                               | 1143 -
 igraph-1.2.7/igraph/src/layout_gem.c                              |  375 
 igraph-1.2.7/igraph/src/layout_kk.c                               | 1098 -
 igraph-1.2.7/igraph/src/lsap.c                                    |  753 
 igraph-1.2.7/igraph/src/matching.c                                | 1534 -
 igraph-1.2.7/igraph/src/math.c                                    |  320 
 igraph-1.2.7/igraph/src/matrix.c                                  |  120 
 igraph-1.2.7/igraph/src/matrix.pmt                                | 1366 -
 igraph-1.2.7/igraph/src/maximal_cliques.c                         |  607 
 igraph-1.2.7/igraph/src/maximal_cliques_template.h                |  551 
 igraph-1.2.7/igraph/src/memory.c                                  |   30 
 igraph-1.2.7/igraph/src/microscopic_update.c                      | 1100 -
 igraph-1.2.7/igraph/src/mixing.c                                  |  372 
 igraph-1.2.7/igraph/src/motifs.c                                  | 1651 -
 igraph-1.2.7/igraph/src/operators.c                               | 1891 -
 igraph-1.2.7/igraph/src/optimal_modularity.c                      |  345 
 igraph-1.2.7/igraph/src/other.c                                   |  480 
 igraph-1.2.7/igraph/src/paths.c                                   |  210 
 igraph-1.2.7/igraph/src/plfit/error.c                             |   11 
 igraph-1.2.7/igraph/src/plfit/error.h                             |    6 
 igraph-1.2.7/igraph/src/plfit/gss.c                               |    7 
 igraph-1.2.7/igraph/src/plfit/gss.h                               |    8 
 igraph-1.2.7/igraph/src/plfit/hzeta.c                             |only
 igraph-1.2.7/igraph/src/plfit/hzeta.h                             |only
 igraph-1.2.7/igraph/src/plfit/kolmogorov.c                        |    6 
 igraph-1.2.7/igraph/src/plfit/kolmogorov.h                        |   10 
 igraph-1.2.7/igraph/src/plfit/mt.c                                |only
 igraph-1.2.7/igraph/src/plfit/mt.h                                |only
 igraph-1.2.7/igraph/src/plfit/options.c                           |   31 
 igraph-1.2.7/igraph/src/plfit/platform.c                          |only
 igraph-1.2.7/igraph/src/plfit/platform.h                          |   25 
 igraph-1.2.7/igraph/src/plfit/plfit.c                             | 1037 
 igraph-1.2.7/igraph/src/plfit/plfit.h                             |  104 
 igraph-1.2.7/igraph/src/plfit/plfit.inc                           |    5 
 igraph-1.2.7/igraph/src/plfit/rbinom.c                            |only
 igraph-1.2.7/igraph/src/plfit/sampling.c                          |only
 igraph-1.2.7/igraph/src/plfit/sampling.h                          |only
 igraph-1.2.7/igraph/src/pottsmodel_2.cpp                          | 3914 +--
 igraph-1.2.7/igraph/src/pottsmodel_2.h                            |  130 
 igraph-1.2.7/igraph/src/progress.c                                |  131 
 igraph-1.2.7/igraph/src/prpack.cpp                                |   24 
 igraph-1.2.7/igraph/src/prpack.h                                  |   26 
 igraph-1.2.7/igraph/src/prpack/prpack_base_graph.h                |    2 
 igraph-1.2.7/igraph/src/prpack/prpack_csc.h                       |    2 
 igraph-1.2.7/igraph/src/prpack/prpack_csr.h                       |    2 
 igraph-1.2.7/igraph/src/prpack/prpack_edge_list.h                 |    2 
 igraph-1.2.7/igraph/src/prpack/prpack_igraph_graph.h              |    2 
 igraph-1.2.7/igraph/src/prpack/prpack_preprocessed_ge_graph.h     |    2 
 igraph-1.2.7/igraph/src/prpack/prpack_preprocessed_graph.h        |    2 
 igraph-1.2.7/igraph/src/prpack/prpack_preprocessed_gs_graph.h     |    2 
 igraph-1.2.7/igraph/src/prpack/prpack_preprocessed_scc_graph.h    |    2 
 igraph-1.2.7/igraph/src/prpack/prpack_preprocessed_schur_graph.h  |    2 
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Package GA updated to version 3.2.2 with previous version 3.2.1 dated 2021-04-21

Title: Genetic Algorithms
Description: Flexible general-purpose toolbox implementing genetic algorithms (GAs) for stochastic optimisation. Binary, real-valued, and permutation representations are available to optimize a fitness function, i.e. a function provided by users depending on their objective function. Several genetic operators are available and can be combined to explore the best settings for the current task. Furthermore, users can define new genetic operators and easily evaluate their performances. Local search using general-purpose optimisation algorithms can be applied stochastically to exploit interesting regions. GAs can be run sequentially or in parallel, using an explicit master-slave parallelisation or a coarse-grain islands approach.
Author: Luca Scrucca [aut, cre] (<https://orcid.org/0000-0003-3826-0484>)
Maintainer: Luca Scrucca <luca.scrucca@unipg.it>

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Package cmsafvis updated to version 1.1.7 with previous version 1.1.5 dated 2021-09-06

Title: Tools to Visualize CM SAF NetCDF Data
Description: The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (<http://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The 'cmsafvis' R-package provides a collection of R-operators for the analysis and visualization of CM SAF NetCDF data. CM SAF climate data records are provided for free via (<https://wui.cmsaf.eu/safira>). Detailed information and test data are provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox>).
Author: Steffen Kothe [aut, cre], Danny Parsons [ctb]
Maintainer: Steffen Kothe <Steffen.Kothe@dwd.de>

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Package tidyndr updated to version 0.1.1 with previous version 0.1.0 dated 2021-03-23

Title: Analysis of the Nigeria National Data Repository (NDR)
Description: The goal is to simplify routine analysis of the Nigeria National Data Repository (NDR) <https://ndr.shieldnigeriaproject.com> using the PEPFAR Monitoring, Evaluation, and Reporting (MER) indicators (see <https://datim.zendesk.com/hc/en-us/articles/360000084446-MER-Indicator-Reference-Guides>). It is designed to import in to R patient-level line-list downloaded as 'csv' file from the front-end of the NDR.
Author: Stephen Balogun [aut, cre] (<https://orcid.org/0000-0002-9928-3703>), Scholastica Olanrewaju [ctb], Oluwaseun Okunuga [ctb], Temitope Kolade [ctb], Geraldine Abone [ctb]
Maintainer: Stephen Balogun <stephentaiyebalogun@gmail.com>

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Package natstrat updated to version 2.0.0 with previous version 1.0.0 dated 2021-05-26

Title: Obtain Unweighted Natural Strata that Balance Many Covariates
Description: Natural strata can be used in observational studies to balance the distributions of many covariates across any number of treatment groups and any number of comparisons. These strata have proportional amounts of units within each stratum across the treatments, allowing for simple interpretation and aggregation across strata. Within each stratum, the units are chosen using randomized rounding of a linear program that balances many covariates. To solve the linear program, the 'Gurobi' commercial optimization software is recommended, but not required. The 'gurobi' R package can be installed following the instructions at <https://www.gurobi.com/documentation/9.1/refman/ins_the_r_package.html>.
Author: Katherine Brumberg [aut, cre]
Maintainer: Katherine Brumberg <kbrum@wharton.upenn.edu>

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Package ivreg updated to version 0.6-1 with previous version 0.6-0 dated 2021-05-28

Title: Instrumental-Variables Regression by '2SLS', '2SM', or '2SMM', with Diagnostics
Description: Instrumental variable estimation for linear models by two-stage least-squares (2SLS) regression or by robust-regression via M-estimation (2SM) or MM-estimation (2SMM). The main ivreg() model-fitting function is designed to provide a workflow as similar as possible to standard lm() regression. A wide range of methods is provided for fitted ivreg model objects, including extensive functionality for computing and graphing regression diagnostics in addition to other standard model tools.
Author: John Fox [aut, cre] (<https://orcid.org/0000-0002-1196-8012>), Christian Kleiber [aut] (<https://orcid.org/0000-0002-6781-4733>), Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Nikolas Kuschnig [ctb] (<https://orcid.org/0000-0002-6642-2543>)
Maintainer: John Fox <jfox@mcmaster.ca>

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Package hockeyR updated to version 0.1.1 with previous version 0.1.0 dated 2021-09-20

Title: Collect and Clean Hockey Stats
Description: Various functions to scrape hockey play-by-play data from the <https://www.nhl.com/>. It also contains functions to scrape data from <https://www.hockey-reference.com/>, including standings, player stats, and jersey number history.
Author: Daniel Morse [aut, cre]
Maintainer: Daniel Morse <danmorse8642@gmail.com>

Diff between hockeyR versions 0.1.0 dated 2021-09-20 and 0.1.1 dated 2021-10-15

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Package glmtlp updated to version 2.0.0 with previous version 1.1 dated 2018-02-07

Title: Generalized Linear Models with Truncated Lasso Penalty
Description: Extremely efficient procedures for fitting regularization path with l0, l1, and truncated lasso penalty for linear regression and logistic regression models. This version is a completely new version compared with our previous version, which was mainly based on R. New core algorithms are developed and are now written in C++ and highly optimized.
Author: Chunlin Li [aut], Yu Yang [aut, cre], Chong Wu [aut]
Maintainer: Yu Yang <yang6367@umn.edu>

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Package dfvad updated to version 0.3.6 with previous version 0.3.0 dated 2020-03-05

Title: Diewert and Fox's Method of Value Added Growth Decomposition
Description: Decomposing value added growth into explanatory factors. A cost constrained value added function is defined to specify the production frontier. Industry estimates can also be aggregated using a weighted average approach. Details about the methodology and data can be found in Diewert and Fox (2018) <doi:10.1093/oxfordhb/9780190226718.013.19> and Zeng, Parsons, Diewert and Fox (2018) <https://www.business.unsw.edu.au/research-site/centreforappliedeconomicresearch-site/Documents/emg2018-6_SZeng_EMG-Slides.pdf>.
Author: Shipei Zeng
Maintainer: Shipei Zeng <shipei.zeng@unswalumni.com>

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Package PerFit updated to version 1.4.6 with previous version 1.4.5 dated 2021-02-21

Title: Person Fit
Description: Several person-fit statistics (PFSs; Meijer and Sijtsma, 2001, <doi:10.1177/01466210122031957>) are offered. These statistics allow assessing whether individual response patterns to tests or questionnaires are (im)plausible given the other respondents in the sample or given a specified item response theory model. Some PFSs apply to dichotomous data, such as the likelihood-based PFSs (lz, lz*) and the group-based PFSs (personal biserial correlation, caution index, (normed) number of Guttman errors, agreement/disagreement/dependability statistics, U3, ZU3, NCI, Ht). PFSs suitable to polytomous data include extensions of lz, U3, and (normed) number of Guttman errors.
Author: Jorge N. Tendeiro
Maintainer: Jorge N. Tendeiro <tendeiro@hiroshima-u.ac.jp>

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Package LDLcalc updated to version 1.1 with previous version 1.0 dated 2021-09-30

Title: Calculate and Predict the Low Density Lipoprotein Values
Description: A wide variety of ways to calculate (through equations) or predict (using 9 Machine learning methods as well as a stack algorithm combination of them all) the Low Density Lipoprotein values of patients based on the values of three other metrics as Total Cholesterol , Triglyceride and High Density Lipoprotein.
Author: Petros Paplomatas [aut, cre], Kostas Anagnostopoulos [aut]
Maintainer: Petros Paplomatas <P.paplomatas@hotmail.com>

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Package parcats updated to version 0.0.3 with previous version 0.0.2 dated 2020-09-09

Title: Interactive Parallel Categories Diagrams for 'easyalluvial'
Description: Complex graphical representations of data are best explored using interactive elements. 'parcats' adds interactive graphing capabilities to the 'easyalluvial' package. The 'plotly.js' parallel categories diagrams offer a good framework for creating interactive flow graphs that allow manual drag and drop sorting of dimensions and categories, highlighting single flows and displaying mouse over information. The 'plotly.js' dependency is quite heavy and therefore is outsourced into a separate package.
Author: Bjoern Koneswarakantha [aut, cre] (<https://orcid.org/0000-0003-4585-7799>)
Maintainer: Bjoern Koneswarakantha <datistics@gmail.com>

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Package rminizinc updated to version 0.0.8 with previous version 0.0.7 dated 2021-08-04

Title: R Interface to 'MiniZinc'
Description: Constraint optimization, or constraint programming, is the name given to identifying feasible solutions out of a very large set of candidates, where the problem can be modeled in terms of arbitrary constraints. 'MiniZinc' is a free and open-source constraint modeling language. Constraint satisfaction and discrete optimization problems can be formulated in a high-level modeling language. Models are compiled into an intermediate representation that is understood by a wide range of solvers. 'MiniZinc' itself provides several solvers, for instance 'GeCode'. R users can use the package to solve constraint programming problems without using 'MiniZinc' directly, modify existing 'MiniZinc' models and also create their own models.
Author: Akshit Achara, Lars Kotthoff, Hans W. Borchers, Guido Tack
Maintainer: Akshit Achara <acharaakshit@gmail.com>

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Package coronavirus updated to version 0.3.31 with previous version 0.3.30 dated 2021-09-19

Title: The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset
Description: Provides a daily summary of the Coronavirus (COVID-19) cases by state/province. Data source: Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus <https://systems.jhu.edu/research/public-health/ncov/>.
Author: Rami Krispin [aut, cre], Jarrett Byrnes [aut] (<https://orcid.org/0000-0002-9791-9472>)
Maintainer: Rami Krispin <rami.krispin@gmail.com>

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Package bignum updated to version 0.3.0 with previous version 0.2.2 dated 2021-09-21

Title: Arbitrary-Precision Integer and Floating-Point Mathematics
Description: Classes for storing and manipulating arbitrary-precision integer vectors and high-precision floating-point vectors. These extend the range and precision of the 'integer' and 'double' data types found in R. This package utilizes the 'Boost.Multiprecision' C++ library. It is specifically designed to work well with the 'tidyverse' collection of R packages.
Author: David Hall [aut, cre, cph] (<https://orcid.org/0000-0002-2193-0480>)
Maintainer: David Hall <david.hall.physics@gmail.com>

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Thu, 14 Oct 2021

Package tvem updated to version 1.3.1 with previous version 1.3 dated 2021-08-05

Title: Time-Varying Effect Models
Description: Fits time-varying effect models (TVEM). These are a kind of application of varying-coefficient models in the context of longitudinal data, allowing the strength of linear, logistic, or Poisson regression relationships to change over time. These models are described further in Tan, Shiyko, Li, Li & Dierker (2012) <doi:10.1037/a0025814>. We thank Kaylee Litson, Patricia Berglund, and Yajnaseni Chakraborti for their valuable help with testing the package and documentation. The development of this package was part of a research project supported by National Institutes of Health grants P50 DA039838 from the National Institute of Drug Abuse and 1R01 CA229542-01 from the National Cancer Institute and the NIH Office of Behavioral and Social Science Research. Content is solely the responsibility of the authors and does not necessarily represent the official views of the funding institutions mentioned above. This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
Author: John J. Dziak [aut, cre] (<https://orcid.org/0000-0003-0762-5495>), Donna L. Coffman [aut] (<https://orcid.org/0000-0001-6305-6579>), Runze Li [aut] (<https://orcid.org/0000-0002-0154-2202>), Kaylee Litson [aut] (<https://orcid.org/0000-0003-1296-4811>), Yajnaseni Chakraborti [aut]
Maintainer: John J. Dziak <dziakj1@gmail.com>

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Package textplot updated to version 0.2.1 with previous version 0.2.0 dated 2021-08-18

Title: Text Plots
Description: Visualise complex relations in texts. This is done by providing functionalities for displaying text co-occurrence networks, text correlation networks, dependency relationships as well as text clustering and semantic text 'embeddings'. Feel free to join the effort of providing interesting text visualisations.
Author: Jan Wijffels [aut, cre, cph], BNOSAC [cph], Sacha Epskamp [ctb, cph] (code in R/matrix_reduction.R adapted from the qgraph package version 1.4.0 which is GPL-2 licensed), Ingo Feinerer and Kurt Hornik [ctb, cph] (partial code in R/textplot_corlines.R adapted from the tm package version 0.4 which is GPL-2 licensed)
Maintainer: Jan Wijffels <jwijffels@bnosac.be>

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Package RDP updated to version 0.2.0 with previous version 0.1.8 dated 2021-09-25

Title: The Ramer-Douglas-Peucker Algorithm
Description: Pretty fast implementation of the Ramer-Douglas-Peucker algorithm for reducing the number of points on a 2D curve. Urs Ramer (1972), "An iterative procedure for the polygonal approximation of plane curves" <doi:10.1016/S0146-664X(72)80017-0>. David H. Douglas and Thomas K. Peucker (1973), "Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature" <doi:10.3138/FM57-6770-U75U-7727>.
Author: Robert Dahl Jacobsen [aut, cre]
Maintainer: Robert Dahl Jacobsen <cran@dahl-jacobsen.dk>

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Package VFP updated to version 1.3.1 with previous version 1.3 dated 2020-06-16

Title: Variance Function Program
Description: Variance function estimation for models proposed by W. Sadler in his variance function program ('VFP', <http://www.aacb.asn.au/resources/useful-tools/variance-function-program-v14>). Here, the idea is to fit multiple variance functions to a data set and consequently assess which function reflects the relationship 'Var ~ Mean' best. For 'in-vitro diagnostic' ('IVD') assays modeling this relationship is of great importance when individual test-results are used for defining follow-up treatment of patients.
Author: Andre Schuetzenmeister [cre, aut], Florian Dufey [aut], Andrea Geistanger [ctb]
Maintainer: Andre Schuetzenmeister <andre.schuetzenmeister@roche.com>

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Package UKFE updated to version 0.2.0 with previous version 0.1.9 dated 2021-10-05

Title: UK Flood Estimation
Description: Functions to implement the methods of the Flood Estimation Handbook (FEH), associated updates and the revitalised flood hydrograph model (ReFH). Currently the 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). "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 individual updated to version 0.1.6 with previous version 0.1.4 dated 2021-07-29

Title: Framework for Specifying and Simulating Individual Based Models
Description: A framework which provides users a set of useful primitive elements for specifying individual based simulation models, with special attention models for infectious disease epidemiology. Users build models by specifying variables for each characteristic of individuals in the simulated population by using data structures exposed by the package. The package provides efficient methods for finding subsets of individuals based on these variables, or cohorts. Cohorts can then be targeted for variable updates or scheduled for events. Variable updates queued during a time step are executed at the end of a discrete time step, and the code places no restrictions on how individuals are allowed to interact. These data structures are designed to provide an intuitive way for users to turn their conceptual model of a system into executable code, which is fast and memory efficient.
Author: Giovanni Charles [aut, cre] (<https://orcid.org/0000-0002-7024-1200>), Sean L. Wu [aut] (<https://orcid.org/0000-0002-5781-9493>), Peter Winskill [aut] (<https://orcid.org/0000-0003-3001-4959>), Imperial College of Science, Technology and Medicine [cph]
Maintainer: Giovanni Charles <giovanni.charles@gmail.com>

Diff between individual versions 0.1.4 dated 2021-07-29 and 0.1.6 dated 2021-10-14

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Package spData updated to version 2.0.1 with previous version 0.3.10 dated 2021-06-18

Title: Datasets for Spatial Analysis
Description: Diverse spatial datasets for demonstrating, benchmarking and teaching spatial data analysis. It includes R data of class sf (defined by the package 'sf'), Spatial ('sp'), and nb ('spdep'). Unlike other spatial data packages such as 'rnaturalearth' and 'maps', it also contains data stored in a range of file formats including GeoJSON, ESRI Shapefile and GeoPackage. Some of the datasets are designed to illustrate specific analysis techniques. cycle_hire() and cycle_hire_osm(), for example, is designed to illustrate point pattern analysis techniques.
Author: Roger Bivand [aut] (<https://orcid.org/0000-0003-2392-6140>), Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>), Robin Lovelace [aut] (<https://orcid.org/0000-0001-5679-6536>), Mark Monmonier [ctb] (author of the state.vbm dataset), Greg Snow [ctb] (author of the state.vbm dataset)
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

Diff between spData versions 0.3.10 dated 2021-06-18 and 2.0.1 dated 2021-10-14

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Package parglm updated to version 0.1.7 with previous version 0.1.6 dated 2020-08-10

Title: Parallel GLM
Description: Provides a parallel estimation method for generalized linear models without compiling with a multithreaded LAPACK or BLAS.
Author: Benjamin Christoffersen [cre, aut] (<https://orcid.org/0000-0002-7182-1346>), Anthony Williams [cph], Boost developers [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>

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Package mully updated to version 2.1.34 with previous version 2.1.33 dated 2021-06-02

Title: Create, Modify and Visualize Multi-Layered Networks
Description: Allows the user to create graph with multiple layers. The user can also modify the layers, the nodes, and the edges. The graph can also be visualized. Zaynab Hammoud and Frank Kramer (2018) <doi:10.3390/genes9110519>. More about multilayered graphs and their usage can be found in our review paper: Zaynab Hammoud and Frank Kramer (2020) <doi:10.1186/s41044-020-00046-0>.
Author: Zaynab Hammoud
Maintainer: Zaynab Hammoud <zaynabhassanhammoud@gmail.com>

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Package MEDseq updated to version 1.3.1 with previous version 1.3.0 dated 2021-07-15

Title: Mixtures of Exponential-Distance Models with Covariates
Description: Implements a model-based clustering method for categorical life-course sequences relying on mixtures of exponential-distance models introduced by Murphy et al. (2021) <doi:10.1111/rssa.12712>. A range of flexible precision parameter settings corresponding to weighted generalisations of the Hamming distance metric are considered, along with the potential inclusion of a noise component. Gating covariates can be supplied in order to relate sequences to baseline characteristics. Sampling weights are also accommodated. The models are fitted using the EM algorithm and tools for visualising the results are also provided.
Author: Keefe Murphy [aut, cre] (<https://orcid.org/0000-0002-7709-3159>), Thomas Brendan Murphy [ctb] (<https://orcid.org/0000-0002-5668-7046>), Raffaella Piccarreta [ctb], Isobel Claire Gormley [ctb] (<https://orcid.org/0000-0001-7713-681X>)
Maintainer: Keefe Murphy <keefe.murphy@mu.ie>

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Package cvCovEst updated to version 1.0.1 with previous version 1.0.0 dated 2021-07-25

Title: Cross-Validated Covariance Matrix Estimation
Description: An efficient cross-validated approach for covariance matrix estimation, particularly useful in high-dimensional settings. This method relies upon the theory of loss-based estimator selection to identify the optimal estimator of the covariance matrix from among a prespecified set of candidates.
Author: Philippe Boileau [aut, cre, cph] (<https://orcid.org/0000-0002-4850-2507>), Nima Hejazi [aut] (<https://orcid.org/0000-0002-7127-2789>), Brian Collica [aut] (<https://orcid.org/0000-0003-1127-2557>), Jamarcus Liu [ctb], Mark van der Laan [ctb, ths] (<https://orcid.org/0000-0003-1432-5511>), Sandrine Dudoit [ctb, ths] (<https://orcid.org/0000-0002-6069-8629>)
Maintainer: Philippe Boileau <philippe_boileau@berkeley.edu>

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Package comat updated to version 0.9.2 with previous version 0.9.1 dated 2021-04-19

Title: Creates Co-Occurrence Matrices of Spatial Data
Description: Builds co-occurrence matrices based on spatial raster data. It includes creation of weighted co-occurrence matrices (wecoma) and integrated co-occurrence matrices (incoma; Vadivel et al. (2007) <doi:10.1016/j.patrec.2007.01.004>).
Author: Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>), Maximillian H.K. Hesselbarth [ctb] (Co-author of underlying C++ code for get_class_index_map(), get_unique_values(), and rcpp_get_coma() functions), Marco Sciaini [ctb] (Co-author of underlying C++ code for get_class_index_map(), get_unique_values(), and rcpp_get_coma() functions), Sebastian Hanss [ctb] (Co-author of underlying C++ code for get_class_index_map(), get_unique_values(), and rcpp_get_coma() functions)
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

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Package chillR updated to version 0.72.5 with previous version 0.72.4 dated 2021-05-13

Title: Statistical Methods for Phenology Analysis in Temperate Fruit Trees
Description: The phenology of plants (i.e. the timing of their annual life phases) depends on climatic cues. For temperate trees and many other plants, spring phases, such as leaf emergence and flowering, have been found to result from the effects of both cool (chilling) conditions and heat. Fruit tree scientists (pomologists) have developed some metrics to quantify chilling and heat (e.g. see Luedeling (2012) <doi:10.1016/j.scienta.2012.07.011>). 'chillR' contains functions for processing temperature records into chilling (Chilling Hours, Utah Chill Units and Chill Portions) and heat units (Growing Degree Hours). Regarding chilling metrics, Chill Portions are often considered the most promising, but they are difficult to calculate. This package makes it easy. 'chillR' also contains procedures for conducting a PLS analysis relating phenological dates (e.g. bloom dates) to either mean temperatures or mean chill and heat accumulation rates, based on long-term weather and phenology records (Luedeling and Gassner (2012) <doi:10.1016/j.agrformet.2011.10.020>). As of version 0.65, it also includes functions for generating weather scenarios with a weather generator, for conducting climate change analyses for temperature-based climatic metrics and for plotting results from such analyses. Since version 0.70, 'chillR' contains a function for interpolating hourly temperature records.
Author: Eike Luedeling [aut, cre] (<https://orcid.org/0000-0002-7316-3631>)
Maintainer: Eike Luedeling <eike@eikeluedeling.com>

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Package rSPDE updated to version 0.6.3 with previous version 0.6.2 dated 2021-02-23

Title: Rational Approximations of Fractional Stochastic Partial Differential Equations
Description: Functions that compute rational approximations of fractional elliptic stochastic partial differential equations. The package also contains functions for common statistical usage of these approximations. The main reference for the methods is Bolin and Kirchner (2020) <doi:10.1080/10618600.2019.1665537>, which can be generated by the citation function in R.
Author: David Bolin [cre, aut]
Maintainer: David Bolin <davidbolin@gmail.com>

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Package PPforest updated to version 0.1.2 with previous version 0.1.1 dated 2018-06-11

Title: Projection Pursuit Classification Forest
Description: Implements projection pursuit forest algorithm for supervised classification.
Author: Natalia da Silva, Eun-Kyung Lee, Di Cook
Maintainer: Natalia da Silva <natalia.dasilva@fcea.edu.uy>

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Package DSMolgenisArmadillo updated to version 1.3.7 with previous version 1.3.6 dated 2021-10-12

Title: 'DataSHIELD' Client for 'MOLGENIS Armadillo'
Description: 'DataSHIELD' is an infrastructure and series of R packages that enables the remote and 'non-disclosive' analysis of sensitive research data. This package is the 'DataSHIELD' interface implementation to analyze data shared on a 'MOLGENIS Armadillo' server. 'MOLGENIS Armadillo' is a light-weight 'DataSHIELD' server using a file store and an 'RServe' server.
Author: Sido Haakma [aut, cre] (<https://orcid.org/0000-0003-1278-9144>), Tommy de Boer [aut] (<https://orcid.org/0000-0002-4492-7225>), Fleur Kelpin [aut] (<https://orcid.org/0000-0003-1527-5130>), MOLGENIS org [cph, fnd]
Maintainer: Sido Haakma <s.haakma@rug.nl>

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Package cmsafops updated to version 1.2.1 with previous version 1.2.0 dated 2021-09-06

Title: Tools for CM SAF NetCDF Data
Description: The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (<http://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The 'cmsafops' R-package provides a collection of R-operators for the analysis and manipulation of CM SAF NetCDF formatted data. Other CF conform NetCDF data with time, longitude and latitude dimension should be applicable, but there is no guarantee for an error-free application. CM SAF climate data records are provided for free via (<https://wui.cmsaf.eu/safira>). Detailed information and test data are provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox>).
Author: Steffen Kothe [aut, cre], Danny Parsons [ctb]
Maintainer: Steffen Kothe <Steffen.Kothe@dwd.de>

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More information about cmsafops at CRAN
Permanent link

Package cmsaf updated to version 3.3.0 with previous version 3.2.0 dated 2021-09-06

Title: A Toolbox for CM SAF NetCDF Data
Description: The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground segment of the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities. The CM SAF contributes to the sustainable monitoring of the climate system by providing essential climate variables related to the energy and water cycle of the atmosphere (<http://www.cmsaf.eu>). It is a joint cooperation of eight National Meteorological and Hydrological Services. The 'cmsaf' R-package includes a 'shiny' based interface for an easy application of the 'cmsafops' and 'cmsafvis' packages - the CM SAF R Toolbox. The Toolbox offers an easy way to prepare, manipulate, analyse and visualize CM SAF NetCDF formatted data. Other CF conform NetCDF data with time, longitude and latitude dimension should be applicable, but there is no guarantee for an error-free application. CM SAF climate data records are provided for free via (<https://wui.cmsaf.eu/safira>). Detailed information and test data are provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox>).
Author: Steffen Kothe [aut, cre], Danny Parsons [ctb]
Maintainer: Steffen Kothe <Steffen.Kothe@dwd.de>

Diff between cmsaf versions 3.2.0 dated 2021-09-06 and 3.3.0 dated 2021-10-14

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More information about cmsaf at CRAN
Permanent link

Package pdynmc updated to version 0.9.6 with previous version 0.9.5 dated 2021-08-13

Title: Moment Condition Based Estimation of Linear Dynamic Panel Data Models
Description: Linear dynamic panel data modeling based on linear and nonlinear moment conditions as proposed by Holtz-Eakin, Newey, and Rosen (1988) <doi:10.2307/1913103>, Ahn and Schmidt (1995) <doi:10.1016/0304-4076(94)01641-C>, and Arellano and Bover (1995) <doi:10.1016/0304-4076(94)01642-D>. Estimation of the model parameters relies on the Generalized Method of Moments (GMM), numerical optimization (when nonlinear moment conditions are employed) and the computation of closed form solutions (when estimation is based on linear moment conditions). One-step, two-step and iterated estimation is available. of closed form solutions. For inference and specification testing, Windmeijer (2005) <doi:10.1016/j.jeconom.2004.02.005> and doubly corrected standard errors (Hwang, Kang, Lee, 2021 <doi:10.1016/j.jeconom.2020.09.010>) are available. Additionally, serial correlation tests, tests for overidentification, and Wald tests are provided. Functions for visualizing panel data structures and modeling results obtained from GMM estimation are also available. The plot methods include functions to plot unbalanced panel structure, coefficient ranges and coefficient paths across GMM iterations (the latter is implemented according to the plot shown in Hansen and Lee, 2021 <doi:10.3982/ECTA16274>).
Author: Markus Fritsch [aut, cre], Joachim Schnurbus [aut], Andrew Adrian Yu Pua [aut]
Maintainer: Markus Fritsch <Markus.Fritsch@uni-Passau.de>

Diff between pdynmc versions 0.9.5 dated 2021-08-13 and 0.9.6 dated 2021-10-14

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More information about pdynmc at CRAN
Permanent link

Package lingtypology updated to version 1.1.6 with previous version 1.1.5 dated 2021-05-15

Title: Linguistic Typology and Mapping
Description: Provides R with the Glottolog database <https://glottolog.org/> and some more abilities for purposes of linguistic mapping. The Glottolog database contains the catalogue of languages of the world. This package helps researchers to make a linguistic maps, using philosophy of the Cross-Linguistic Linked Data project <https://clld.org/>, which allows for while at the same time facilitating uniform access to the data across publications. A tutorial for this package is available on GitHub pages <https://docs.ropensci.org/lingtypology/> and package vignette. Maps created by this package can be used both for the investigation and linguistic teaching. In addition, package provides an ability to download data from typological databases such as WALS, AUTOTYP and some others and to create your own database website.
Author: George Moroz [aut, cre] (<https://orcid.org/0000-0003-1990-6083>), Kirill Koncha [ctb] (<https://orcid.org/0000-0003-0676-2658>), Mikhail Leonov [ctb], Anna Smirnova [ctb]
Maintainer: George Moroz <agricolamz@gmail.com>

Diff between lingtypology versions 1.1.5 dated 2021-05-15 and 1.1.6 dated 2021-10-14

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More information about lingtypology at CRAN
Permanent link

Package BayesMallows updated to version 1.0.3 with previous version 1.0.2 dated 2021-06-04

Title: Bayesian Preference Learning with the Mallows Rank Model
Description: An implementation of the Bayesian version of the Mallows rank model (Vitelli et al., Journal of Machine Learning Research, 2018 <https://jmlr.org/papers/v18/15-481.html>; Crispino et al., Annals of Applied Statistics, 2019 <doi:10.1214/18-AOAS1203>). Both Cayley, footrule, Hamming, Kendall, Spearman, and Ulam distances are supported in the models. The rank data to be analyzed can be in the form of complete rankings, top-k rankings, partially missing rankings, as well as consistent and inconsistent pairwise preferences. Several functions for plotting and studying the posterior distributions of parameters are provided. The package also provides functions for estimating the partition function (normalizing constant) of the Mallows rank model, both with the importance sampling algorithm of Vitelli et al. and asymptotic approximation with the IPFP algorithm (Mukherjee, Annals of Statistics, 2016 <doi:10.1214/15-AOS1389>).
Author: Oystein Sorensen [aut, cre] (<https://orcid.org/0000-0003-0724-3542>), Valeria Vitelli [aut] (<https://orcid.org/0000-0002-6746-0453>), Marta Crispino [aut], Qinghua Liu [aut], Cristina Mollica [aut], Luca Tardella [aut]
Maintainer: Oystein Sorensen <oystein.sorensen.1985@gmail.com>

Diff between BayesMallows versions 1.0.2 dated 2021-06-04 and 1.0.3 dated 2021-10-14

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Permanent link

Package RPEIF updated to version 1.2.4 with previous version 1.2.3 dated 2021-06-09

Title: Computation and Plots of Influence Functions for Risk and Performance Measures
Description: Computes the influence functions time series of the returns for the risk and performance measures as mentioned in Chen and Martin (2018) <https://www.ssrn.com/abstract=3085672>, as well as in Zhang et al. (2019) <https://www.ssrn.com/abstract=3415903>. Also evaluates estimators influence functions at a set of parameter values and plots them to display the shapes of the influence functions.
Author: Anthony Christidis <anthony.christidis@stat.ubc.ca>, Shengyu Zhang <syzhang@uw.edu>, Douglas Martin <doug@amath.washington.edu>
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>

Diff between RPEIF versions 1.2.3 dated 2021-06-09 and 1.2.4 dated 2021-10-14

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More information about RPEIF at CRAN
Permanent link

Package mapSpain updated to version 0.4.0 with previous version 0.3.1 dated 2021-09-10

Title: Administrative Boundaries of Spain
Description: Administrative Boundaries of Spain at several levels (Autonomous Communities, Provinces, Municipalities) based on the 'GISCO' 'Eurostat' database <https://ec.europa.eu/eurostat/web/gisco> and 'CartoBase SIANE' from 'Instituto Geografico Nacional' <https://www.ign.es/>. It also provides a 'leaflet' plugin and the ability of downloading and processing static tiles.
Author: Diego Hernangómez [aut, cre, cph] (<https://orcid.org/0000-0001-8457-4658>, rOpenSpain)
Maintainer: Diego Hernangómez <diego.hernangomezherrero@gmail.com>

Diff between mapSpain versions 0.3.1 dated 2021-09-10 and 0.4.0 dated 2021-10-14

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More information about mapSpain at CRAN
Permanent link

Package growthPheno updated to version 1.0-34 with previous version 1.0-30 dated 2020-12-12

Title: Plotting, Smoothing and Growth Trait Extraction for Longitudinal Data
Description: Assists in producing longitudinal or profile plots of measured traits. These allow checks to be made for anomalous data and growth patterns in the data to be explored. Smoothing of growth trends for individual plants using smoothing splines is available for removing transient effects. There are tools for diagnosing the adequacy of trait smoothing, either using this package or other packages, such as those that fit nonlinear growth models. A range of per-unit (pot, plant, plot) growth traits can be extracted from longitudinal data, including single time-point smoothed trait values and their growth rates, interval growth rates and other growth statistics, such as maximum growth. The package is particularly suited to preparing data from high-throughput phenotyping facilities, such as imaging data from a Lemna-Tec Scananalyzer 3D (see <https://www.youtube.com/watch?v=MRAF_mAEa7E/> for more information). The package 'growthPheno' can also be installed from <http://chris.brien.name/rpackages/>.
Author: Chris Brien [aut, cre] (<https://orcid.org/0000-0003-0581-1817>)
Maintainer: Chris Brien <chris.brien@adelaide.edu.au>

Diff between growthPheno versions 1.0-30 dated 2020-12-12 and 1.0-34 dated 2021-10-14

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Package RGtk2 updated to version 2.20.36.2 with previous version 2.20.36.1 dated 2021-10-11

Title: R Bindings for Gtk 2.8.0 and Above
Description: Facilities in the R language for programming graphical interfaces using Gtk, the Gimp Tool Kit.
Author: Michael Lawrence <michafla@gene.com> and Duncan Temple Lang <duncan@wald.ucdavis.edu>
Maintainer: ORPHANED

Diff between RGtk2 versions 2.20.36.1 dated 2021-10-11 and 2.20.36.2 dated 2021-10-14

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Package REddyProc updated to version 1.3.0 with previous version 1.2.2 dated 2020-03-18

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>

Diff between REddyProc versions 1.2.2 dated 2020-03-18 and 1.3.0 dated 2021-10-14

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Package MTA updated to version 0.4.0 with previous version 0.3.0 dated 2021-01-20

Title: Multiscalar Territorial Analysis
Description: Build multiscalar territorial analysis based on various contexts.
Author: Ronan Ysebaert [aut], Nicolas Lambert [aut], Timothée Giraud [aut, cre]
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>

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Package simplevis updated to version 4.6.0 with previous version 4.5.0 dated 2021-08-06

Title: Simple 'ggplot2' Visualisation with Less Brainpower
Description: Wrapper functions to make 'ggplot2' and 'leaflet' visualisation easier with less brainpower required.
Author: David Hodge [aut, cre] (<https://orcid.org/0000-0002-3868-7501>), Statistics New Zealand [cph]
Maintainer: David Hodge <davidhodge931@gmail.com>

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Package gcKrig updated to version 1.1.7 with previous version 1.1.6 dated 2021-06-22

Title: Analysis of Geostatistical Count Data using Gaussian Copulas
Description: Provides a variety of functions to analyze and model geostatistical count data with Gaussian copulas, including 1) data simulation and visualization; 2) correlation structure assessment (here also known as the Normal To Anything); 3) calculate multivariate normal rectangle probabilities; 4) likelihood inference and parallel prediction at predictive locations. Description of the method is available from: Han and DeOliveira (2018) <doi:10.18637/jss.v087.i13>.
Author: Zifei Han
Maintainer: Zifei Han <hanzifei1@gmail.com>

Diff between gcKrig versions 1.1.6 dated 2021-06-22 and 1.1.7 dated 2021-10-14

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Package DoubleML updated to version 0.4.0 with previous version 0.3.1 dated 2021-08-02

Title: Double Machine Learning in R
Description: Implementation of the double/debiased machine learning framework of Chernozhukov et al. (2018) <doi:10.1111/ectj.12097> for partially linear regression models, partially linear instrumental variable regression models, interactive regression models and interactive instrumental variable regression models. 'DoubleML' allows estimation of the nuisance parts in these models by machine learning methods and computation of the Neyman orthogonal score functions. 'DoubleML' is built on top of 'mlr3' and the 'mlr3' ecosystem. The object-oriented implementation of 'DoubleML' based on the 'R6' package is very flexible.
Author: Philipp Bach [aut], Victor Chernozhukov [aut], Malte S. Kurz [aut, cre], Martin Spindler [aut]
Maintainer: Malte S. Kurz <malte.simon.kurz@uni-hamburg.de>

Diff between DoubleML versions 0.3.1 dated 2021-08-02 and 0.4.0 dated 2021-10-14

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Package hagis updated to version 3.1.3 with previous version 3.1.2 dated 2021-09-30

Title: Analysis of Plant Pathogen Pathotype Complexities, Distributions and Diversity
Description: Analysis of plant pathogen pathotype survey data. Functions provided calculate distribution of susceptibilities, distribution of complexities with statistics, pathotype frequency distribution, as well as diversity indices for pathotypes. This package is meant to be a direct replacement for Herrmann, Löwer and Schachtel's (1999) <doi:10.1046/j.1365-3059.1999.00325.x> Habgood-Gilmour Spreadsheet, 'HaGiS', previously used for pathotype analysis.
Author: Austin G. McCoy [aut, ccp] (<https://orcid.org/0000-0003-2483-4184>), Zachary Noel [aut, ccp] (<https://orcid.org/0000-0001-6375-8300>), Adam H. Sparks [aut, cre] (<https://orcid.org/0000-0002-0061-8359>), Martin Chilvers [aut, ths] (<https://orcid.org/0000-0001-8832-1666>), Zhian N. Kamvar [ctb, rev] (<https://orcid.org/0000-0003-1458-7108>), Michigan Soybean Promotion Committee [fnd], Project GREEEN [fnd], North Central Soybean Research Program [fnd], GRDC Project DAQ00186 [fnd]
Maintainer: Adam H. Sparks <adamhsparks@gmail.com>

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Package recometrics updated to version 0.1.5-2 with previous version 0.1.5 dated 2021-09-02

Title: Evaluation Metrics for Implicit-Feedback Recommender Systems
Description: Calculates evaluation metrics for implicit-feedback recommender systems that are based on low-rank matrix factorization models, given the fitted model matrices and data, thus allowing to compare models from a variety of libraries. Metrics include P@K (precision-at-k, for top-K recommendations), R@K (recall at k), AP@K (average precision at k), NDCG@K (normalized discounted cumulative gain at k), Hit@K (from which the 'Hit Rate' is calculated), RR@K (reciprocal rank at k, from which the 'MRR' or 'mean reciprocal rank' is calculated), ROC-AUC (area under the receiver-operating characteristic curve), and PR-AUC (area under the precision-recall curve). These are calculated on a per-user basis according to the ranking of items induced by the model, using efficient multi-threaded routines. Also provides functions for creating train-test splits for model fitting and evaluation.
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

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Package readsparse updated to version 0.1.5-1 with previous version 0.1.5 dated 2021-09-07

Title: Read and Write Sparse Matrices in 'SVMLight' and 'LibSVM' Formats
Description: Read and write labelled sparse matrices in text format as used by software such as 'SVMLight', 'LibSVM', 'ThunderSVM', 'LibFM', 'xLearn', 'XGBoost', 'LightGBM', and others. Supports labelled data for regression, classification (binary, multi-class, multi-label), and ranking (with 'qid' field), and can handle header metadata and comments in files.
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

Diff between readsparse versions 0.1.5 dated 2021-09-07 and 0.1.5-1 dated 2021-10-14

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Package paleopop updated to version 2.1.2 with previous version 2.1.1 dated 2021-04-23

Title: Pattern-Oriented Modeling Framework for Coupled Niche-Population Paleo-Climatic Models
Description: This extension of the poems pattern-oriented modeling (POM) framework provides a collection of modules and functions customized for paleontological time-scales, and optimized for single-generation transitions and large populations, across multiple generations.
Author: Sean Haythorne [aut], Julia Pilowsky [aut, cre] (<https://orcid.org/0000-0002-6376-2585>), Stuart Brown [aut] (<https://orcid.org/0000-0002-0669-1418>), Damien Fordham [aut] (<https://orcid.org/0000-0003-2137-5592>)
Maintainer: Julia Pilowsky <julia.pilowsky@adelaide.edu.au>

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More information about paleopop at CRAN
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Package mlr3viz updated to version 0.5.7 with previous version 0.5.6 dated 2021-09-14

Title: Visualizations for 'mlr3'
Description: Provides visualizations for 'mlr3' objects such as tasks, predictions, resample results or benchmark results via the autoplot() generic of 'ggplot2'. The returned 'ggplot' objects are intended to provide sensible defaults, yet can easily be customized to create camera-ready figures. Visualizations include barplots, boxplots, histograms, ROC curves, and Precision-Recall curves.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Raphael Sonabend [aut] (<https://orcid.org/0000-0001-9225-4654>), Marc Becker [aut] (<https://orcid.org/0000-0002-8115-0400>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Damir Pulatov [ctb]
Maintainer: Michel Lang <michellang@gmail.com>

Diff between mlr3viz versions 0.5.6 dated 2021-09-14 and 0.5.7 dated 2021-10-14

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Package mixreg updated to version 2.0-10 with previous version 0.0-6 dated 2018-03-31

Title: Functions to Fit Mixtures of Regressions
Description: Fits mixtures of (possibly multivariate) regressions (which has been described as doing ANCOVA when you don't know the levels). Turner (2000) <doi:10.1111/1467-9876.00198>.
Author: Rolf Turner <r.turner@auckland.ac.nz>
Maintainer: Rolf Turner <r.turner@auckland.ac.nz>

Diff between mixreg versions 0.0-6 dated 2018-03-31 and 2.0-10 dated 2021-10-14

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More information about mixreg at CRAN
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