Mon, 11 Dec 2023

Package eddington updated to version 4.1.1 with previous version 2.1.1 dated 2020-03-24

Title: Compute a Cyclist's Eddington Number
Description: Compute a cyclist's Eddington number, including efficiently computing cumulative E over a vector. A cyclist's Eddington number <https://en.wikipedia.org/wiki/Arthur_Eddington#Eddington_number_for_cycling> is the maximum number satisfying the condition such that a cyclist has ridden E miles or greater on E distinct days. The algorithm in this package is an improvement over the conventional approach because both summary statistics and cumulative statistics can be computed in linear time, since it does not require initial sorting of the data. These functions may also be used for computing h-indices for authors, a metric described by Hirsch (2005) <doi:10.1073/pnas.0507655102>. Both are specific applications of computing the side length of a Durfee square <https://en.wikipedia.org/wiki/Durfee_square>.
Author: Paul Egeler [aut, cre], Tashi Reigle [ctb]
Maintainer: Paul Egeler <paulegeler@gmail.com>

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Package yulab.utils updated to version 0.1.1 with previous version 0.1.0 dated 2023-09-20

Title: Supporting Functions for Packages Maintained by 'YuLab-SMU'
Description: Miscellaneous functions commonly used by 'YuLab-SMU'.
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package simIDM updated to version 0.1.0 with previous version 0.0.5 dated 2023-01-27

Title: Simulating Oncology Trials using an Illness-Death Model
Description: Based on the illness-death model a large number of clinical trials with oncology endpoints progression-free survival (PFS) and overall survival (OS) can be simulated, see Meller, Beyersmann and Rufibach (2019) <doi:10.1002/sim.8295>. The simulation set-up allows for random and event-driven censoring, an arbitrary number of treatment arms, staggered study entry and drop-out. Exponentially, Weibull and piecewise exponentially distributed survival times can be generated. The correlation between PFS and OS can be calculated.
Author: Alexandra Erdmann [aut, cre], Kaspar Rufibach [aut], Holger Loewe [aut], Daniel Sabanes Bove [aut], F. Hoffmann-La Roche AG [cph, fnd], University of Ulm [cph, fnd]
Maintainer: Alexandra Erdmann <alexandra.erdmann@uni-ulm.de>

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Package HMR updated to version 1.0.3 with previous version 1.0.2 dated 2022-05-20

Title: Flux Estimation with Static Chamber Data
Description: Statistical analysis of static chamber concentration data for trace gas flux estimation.
Author: Asger R. Pedersen <asger@clin.au.dk>
Maintainer: Asger R. Pedersen <asger@clin.au.dk>

Diff between HMR versions 1.0.2 dated 2022-05-20 and 1.0.3 dated 2023-12-11

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Package data.validator updated to version 0.2.1 with previous version 0.2.0 dated 2023-05-08

Title: Automatic Data Validation and Reporting
Description: Validate dataset by columns and rows using convenient predicates inspired by 'assertr' package. Generate good looking HTML report or print console output to display in logs of your data processing pipeline.
Author: Marcin Dubel [aut, cre], Pawel Przytula [aut], Jakub Nowicki [aut], Krystian Igras [aut], Dominik Krzeminski [ctb], Servet Ahmet Cizmeli [ctb], Appsilon Sp. z o.o. [cph]
Maintainer: Marcin Dubel <opensource+marcin@appsilon.com>

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Package Rmpi updated to version 0.7-2 with previous version 0.7-1 dated 2023-03-18

Title: Interface (Wrapper) to MPI (Message-Passing Interface)
Description: An interface (wrapper) to MPI. It also provides interactive R manager and worker environment.
Author: Hao Yu [aut]
Maintainer: Hao Yu <hyu@stats.uwo.ca>

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Package tinycodet updated to version 0.3.0 with previous version 0.2.2 dated 2023-11-25

Title: Functions to Help in your Coding Etiquette
Description: Adds some functions to help in your coding etiquette. 'tinycodet' primarily focuses on 4 aspects. 1) Safer decimal (in)equality testing, safer atomic conversions, and other functions for safer coding. 2) A new package import system, that attempts to combine the benefits of using a package without attaching, with the benefits of attaching a package. 3) Extending the string manipulation capabilities of the 'stringi' R package. 4) Reducing repetitive code. 'tinycodet' has only one dependency, namely 'stringi'.
Author: Tony Wilkes [aut, cre, cph]
Maintainer: Tony Wilkes <tony_a_wilkes@outlook.com>

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Package this.path updated to version 2.3.1 with previous version 2.3.0 dated 2023-12-02

Title: Get Executing Script's Path
Description: Determine the path of the executing script. Compatible with a few popular GUIs: 'Rgui', 'RStudio', 'VSCode', 'Jupyter', 'Emacs', and 'Rscript' (shell). Compatible with several functions and packages: 'source()', 'sys.source()', 'debugSource()' in 'RStudio', 'compiler::loadcmp()', 'box::use()', 'knitr::knit()', 'plumber::plumb()', 'shiny::runApp()', 'package:targets', and 'testthat::source_file()'.
Author: Iris Simmons
Maintainer: Iris Simmons <ikwsimmo@gmail.com>

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Package SenSrivastava updated to version 2015.6.25.1 with previous version 2015.6.25 dated 2015-06-26

Title: Datasets from Sen & Srivastava
Description: Collection of datasets from Sen & Srivastava: "Regression Analysis, Theory, Methods and Applications", Springer. Sources for individual data files are more fully documented in the book.
Author: Kjetil B Halvorsen <kjetil1001@gmail.com>
Maintainer: Kjetil B Halvorsen <kjetil1001@gmail.com>

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Package ruminate updated to version 0.2.1 with previous version 0.2.0 dated 2023-12-02

Title: A Pharmacometrics Data Transformation and Analysis Tool
Description: Exploration of pharmacometrics data involves both general tools (transformation and plotting) and specific techniques (non-compartmental analysis). This kind of exploration is generally accomplished by utilizing different packages. The purpose of 'ruminate' is to create a 'shiny' interface to make these tools more broadly available while creating reproducible results.
Author: John Harrold [aut, cre]
Maintainer: John Harrold <john.m.harrold@gmail.com>

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Package rolap updated to version 2.5.0 with previous version 2.4.0 dated 2023-11-14

Title: Obtaining Star Databases from Flat Tables
Description: Data in multidimensional systems is obtained from operational systems and is transformed to adapt it to the new structure. Frequently, the operations to be performed aim to transform a flat table into a ROLAP (Relational On-Line Analytical Processing) star database. The main objective of the package is to allow the definition of these transformations easily. The implementation of the multidimensional database obtained can be exported to work with multidimensional analysis tools on spreadsheets or relational databases.
Author: Jose Samos [aut, cre, cph]
Maintainer: Jose Samos <jsamos@ugr.es>

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Package pleio updated to version 1.9 with previous version 1.6 dated 2018-12-06

Title: Pleiotropy Test for Multiple Traits on a Genetic Marker
Description: Perform tests for pleiotropy of multiple traits of various variable types on genotypes for a genetic marker.
Author: Daniel J Schaid
Maintainer: Jason Sinnwell <sinnwell.jason@mayo.edu>

Diff between pleio versions 1.6 dated 2018-12-06 and 1.9 dated 2023-12-11

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Package normalp updated to version 0.7.2.1 with previous version 0.7.2 dated 2020-02-14

Title: Routines for Exponential Power Distribution
Description: A collection of utilities referred to Exponential Power distribution, also known as General Error Distribution (see Mineo, A.M. and Ruggieri, M. (2005), A software Tool for the Exponential Power Distribution: The normalp package. In Journal of Statistical Software, Vol. 12, Issue 4).
Author: Angelo M. Mineo <angelo.mineo@unipa.it>
Maintainer: Angelo M. Mineo <angelo.mineo@unipa.it>

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Package LiblineaR updated to version 2.10-23 with previous version 2.10-22 dated 2022-12-03

Title: Linear Predictive Models Based on the LIBLINEAR C/C++ Library
Description: A wrapper around the LIBLINEAR C/C++ library for machine learning (available at <https://www.csie.ntu.edu.tw/~cjlin/liblinear/>). LIBLINEAR is a simple library for solving large-scale regularized linear classification and regression. It currently supports L2-regularized classification (such as logistic regression, L2-loss linear SVM and L1-loss linear SVM) as well as L1-regularized classification (such as L2-loss linear SVM and logistic regression) and L2-regularized support vector regression (with L1- or L2-loss). The main features of LiblineaR include multi-class classification (one-vs-the rest, and Crammer & Singer method), cross validation for model selection, probability estimates (logistic regression only) or weights for unbalanced data. The estimation of the models is particularly fast as compared to other libraries.
Author: Thibault Helleputte [cre, aut, cph], Jerome Paul [aut], Pierre Gramme [aut]
Maintainer: Thibault Helleputte <thibault.helleputte@dnalytics.com>

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Package ipw updated to version 1.2.1 with previous version 1.2 dated 2023-01-06

Title: Estimate Inverse Probability Weights
Description: Functions to estimate the probability to receive the observed treatment, based on individual characteristics. The inverse of these probabilities can be used as weights when estimating causal effects from observational data via marginal structural models. Both point treatment situations and longitudinal studies can be analysed. The same functions can be used to correct for informative censoring.
Author: Willem M. van der Wal [aut, cre], Ronald B. Geskus [aut]
Maintainer: Willem M. van der Wal <willem@vanderwalresearch.com>

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Package elections updated to version 1.0.1 with previous version 1.0 dated 2018-03-05

Title: USA Presidential Elections Data
Description: This includes a dataset on the outcomes of the USA presidential elections since 1920, and various predictors, as used in <https://www.vanderwalresearch.com/blog/15-elections>.
Author: Willem M. van der Wal <willem@vanderwalresearch.com>
Maintainer: Willem M. van der Wal <willem@vanderwalresearch.com>

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Package versus updated to version 0.2.1 with previous version 0.2.0 dated 2023-12-10

Title: Compare Data Frames
Description: A toolset for interactively exploring the differences between two data frames.
Author: Ryan Dickerson [aut, cre, cph]
Maintainer: Ryan Dickerson <fresh.tent5866@fastmail.com>

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Package rxode2random updated to version 2.0.12 with previous version 2.0.11 dated 2023-03-28

Title: Random Number Generation Functions for 'rxode2'
Description: Provides the random number generation (in parallel) needed for 'rxode2' (Wang, Hallow and James (2016) <doi:10.1002/psp4.12052>) and 'nlmixr2' (Fidler et al (2019) <doi:10.1002/psp4.12445>). This split will reduce computational burden of recompiling 'rxode2'.
Author: Matthew L. Fidler [aut, cre] , Wenping Wang [ctb], Bill Denney [ctb]
Maintainer: Matthew L. Fidler <matthew.fidler@gmail.com>

Diff between rxode2random versions 2.0.11 dated 2023-03-28 and 2.0.12 dated 2023-12-11

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More information about rxode2random at CRAN
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Package MoEClust updated to version 1.5.2 with previous version 1.5.1 dated 2022-12-20

Title: Gaussian Parsimonious Clustering Models with Covariates and a Noise Component
Description: Clustering via parsimonious Gaussian Mixtures of Experts using the MoEClust models introduced by Murphy and Murphy (2020) <doi:10.1007/s11634-019-00373-8>. This package fits finite Gaussian mixture models with a formula interface for supplying gating and/or expert network covariates using a range of parsimonious covariance parameterisations from the GPCM family via the EM/CEM algorithm. Visualisation of the results of such models using generalised pairs plots and the inclusion of an additional noise component is also facilitated. A greedy forward stepwise search algorithm is provided for identifying the optimal model in terms of the number of components, the GPCM covariance parameterisation, and the subsets of gating/expert network covariates.
Author: Keefe Murphy [aut, cre] , Thomas Brendan Murphy [ctb]
Maintainer: Keefe Murphy <keefe.murphy@mu.ie>

Diff between MoEClust versions 1.5.1 dated 2022-12-20 and 1.5.2 dated 2023-12-11

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More information about MoEClust at CRAN
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Package IncidencePrevalence updated to version 0.6.0 with previous version 0.5.3 dated 2023-11-23

Title: Estimate Incidence and Prevalence using the OMOP Common Data Model
Description: Calculate incidence and prevalence using data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model. Incidence and prevalence can be estimated for the total population in a database or for a stratification cohort.
Author: Edward Burn [aut, cre] , Berta Raventos [aut] , Marti Catala [aut] , Mike Du [ctb] , Yuchen Guo [ctb] , Adam Black [ctb] , Ger Inberg [ctb] , Kim Lopez [ctb]
Maintainer: Edward Burn <edward.burn@ndorms.ox.ac.uk>

Diff between IncidencePrevalence versions 0.5.3 dated 2023-11-23 and 0.6.0 dated 2023-12-11

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Package igraph updated to version 1.6.0 with previous version 1.5.1 dated 2023-08-10

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: Gabor Csardi [aut] , Tamas Nepusz [aut] , Vincent Traag [aut] , Szabolcs Horvat [aut] , Fabio Zanini [aut] , Daniel Noom [aut], Kirill Mueller [aut, cre] , Maelle Salmon [ctb], Chan Zuckerberg Initiative [fnd]
Maintainer: Kirill Mueller <kirill@cynkra.com>

Diff between igraph versions 1.5.1 dated 2023-08-10 and 1.6.0 dated 2023-12-11

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Package gslnls updated to version 1.2.0 with previous version 1.1.2 dated 2023-01-17

Title: GSL Nonlinear Least-Squares Fitting
Description: An R interface to nonlinear least-squares optimization with the GNU Scientific Library (GSL), see M. Galassi et al. (2009, ISBN:0954612078). The available trust region methods include the Levenberg-Marquardt algorithm with and without geodesic acceleration, the Steihaug-Toint conjugate gradient algorithm for large systems and several variants of Powell's dogleg algorithm. The interface includes multi-start optimization using quasi-random samples based on a modified version of algorithm in Hickernell and Yuan (1997, OR Transactions). Bindings are provided to tune a number of parameters affecting the low-level aspects of the trust region algorithms. The interface mimics R's nls() function and returns model objects inheriting from the same class.
Author: Joris Chau [aut, cre]
Maintainer: Joris Chau <joris.chau@openanalytics.eu>

Diff between gslnls versions 1.1.2 dated 2023-01-17 and 1.2.0 dated 2023-12-11

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Package GenTwoArmsTrialSize updated to version 0.0.4.5 with previous version 0.0.4.4 dated 2023-12-08

Title: Generalized Two Arms Clinical Trial Sample Size Calculation
Description: Two arms clinical trials required sample size is calculated in the comprehensive parametric context. The calculation is based on the type of endpoints(continuous/binary/time-to-event/ordinal), design (parallel/crossover), hypothesis tests (equality/noninferiority/superiority/equivalence), trial arms noncompliance rates and expected loss of follow-up. Methods are described in: Chow SC, Shao J, Wang H, Lokhnygina Y (2017) <doi:10.1201/9781315183084>, Wittes, J (2002) <doi:10.1093/epirev/24.1.39>, Sato, T (2000) <doi:10.1002/1097-0258(20001015)19:19%3C2689::aid-sim555%3E3.0.co;2-0>, Lachin J M, Foulkes, M A (1986) <doi:10.2307/2531201>, Whitehead J(1993) <doi:10.1002/sim.4780122404>, Julious SA (2023) <doi:10.1201/9780429503658>.
Author: Mohsen Soltanifar [aut] , Chel Hee Lee [cre, aut]
Maintainer: Chel Hee Lee <chelhee.lee@ucalgary.ca>

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Package duckplyr updated to version 0.3.0 with previous version 0.2.3 dated 2023-11-08

Title: A 'DuckDB'-Backed Version of 'dplyr'
Description: A drop-in replacement for 'dplyr', powered by 'DuckDB' for performance. Also defines a set of generics that provide a low-level implementer's interface for the high-level user interface of 'dplyr'.
Author: Hannes Muehleisen [aut] , Kirill Mueller [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Kirill Mueller <kirill@cynkra.com>

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Package cli updated to version 3.6.2 with previous version 3.6.1 dated 2023-03-23

Title: Helpers for Developing Command Line Interfaces
Description: A suite of tools to build attractive command line interfaces ('CLIs'), from semantic elements: headings, lists, alerts, paragraphs, etc. Supports custom themes via a 'CSS'-like language. It also contains a number of lower level 'CLI' elements: rules, boxes, trees, and 'Unicode' symbols with 'ASCII' alternatives. It support ANSI colors and text styles as well.
Author: Gabor Csardi [aut, cre], Hadley Wickham [ctb], Kirill Mueller [ctb], Salim Brueggemann [ctb] , Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between cli versions 3.6.1 dated 2023-03-23 and 3.6.2 dated 2023-12-11

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Permanent link

Package bigReg updated to version 0.1.5 with previous version 0.1.2 dated 2016-07-25

Title: Generalized Linear Models (GLM) for Large Data Sets
Description: Allows the user to carry out GLM on very large data sets. Data can be created using the data_frame() function and appended to the object with object$append(data); data_frame and data_matrix objects are available that allow the user to store large data on disk. The data is stored as doubles in binary format and any character columns are transformed to factors and then stored as numeric (binary) data while a look-up table is stored in a separate .meta_data file in the same folder. The data is stored in blocks and GLM regression algorithm is modified and carries out a MapReduce- like algorithm to fit the model. The functions bglm(), and summary() and bglm_predict() are available for creating and post-processing of models. The library requires Armadillo installed on your system. It may not function on windows since multi-core processing is done using mclapply() which forks R on Unix/Linux type operating systems.
Author: Chibisi Chima-Okereke <chibisi@active-analytics.com>
Maintainer: Chibisi Chima-Okereke <chibisi@active-analytics.com>

Diff between bigReg versions 0.1.2 dated 2016-07-25 and 0.1.5 dated 2023-12-11

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Package BGVAR updated to version 2.5.4 with previous version 2.5.3 dated 2023-12-08

Title: Bayesian Global Vector Autoregressions
Description: Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 <doi:10.1002/jae.2504>. Post-processing functions allow for doing predictions, structurally identify the model with short-run or sign-restrictions and compute impulse response functions, historical decompositions and forecast error variance decompositions. Plotting functions are also available. The package has a companion paper: Boeck, M., Feldkircher, M. and F. Huber (2022) "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R", Journal of Statistical Software, Vol. 104(9), pp. 1-28 <doi:10.18 [...truncated...]
Author: Maximilian Boeck [aut, cre] , Martin Feldkircher [aut] , Florian Huber [aut] , Darjus Hosszejni [ctb]
Maintainer: Maximilian Boeck <maximilian.boeck@unibocconi.it>

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Package ads updated to version 1.5-10 with previous version 1.5-9 dated 2023-01-17

Title: Spatial Point Patterns Analysis
Description: Perform first- and second-order multi-scale analyses derived from Ripley K-function (Ripley B. D. (1977) <doi:10.1111/j.2517-6161.1977.tb01615.x>), for univariate, multivariate and marked mapped data in rectangular, circular or irregular shaped sampling windows, with tests of statistical significance based on Monte Carlo simulations.
Author: Raphael Pelissier [aut], Francois Goreaud [aut], Dominique Lamonica [cre]
Maintainer: Dominique Lamonica <dominique.lamonica@ird.fr>

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Package ldhmm updated to version 0.6.1 with previous version 0.5.1 dated 2019-12-05

Title: Hidden Markov Model for Financial Time-Series Based on Lambda Distribution
Description: Hidden Markov Model (HMM) based on symmetric lambda distribution framework is implemented for the study of return time-series in the financial market. Major features in the S&P500 index, such as regime identification, volatility clustering, and anti-correlation between return and volatility, can be extracted from HMM cleanly. Univariate symmetric lambda distribution is essentially a location-scale family of exponential power distribution. Such distribution is suitable for describing highly leptokurtic time series obtained from the financial market. It provides a theoretically solid foundation to explore such data where the normal distribution is not adequate. The HMM implementation follows closely the book: "Hidden Markov Models for Time Series", by Zucchini, MacDonald, Langrock (2016).
Author: Stephen H-T. Lihn [aut, cre]
Maintainer: Stephen H-T. Lihn <stevelihn@gmail.com>

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Sun, 10 Dec 2023

Package webfakes updated to version 1.3.0 with previous version 1.2.1 dated 2023-10-01

Title: Fake Web Apps for HTTP Testing
Description: Create a web app that makes it easier to test web clients without using the internet. It includes a web app framework with path matching, parameters and templates. Can parse various 'HTTP' request bodies. Can send 'JSON' data or files from the disk. Includes a web app that implements the 'httpbin.org' web service.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd], Civetweb contributors [ctb] , Redoc contributors [ctb] , L. Peter Deutsch [ctb] , Martin Purschke [ctb] , Aladdin Enterprises [cph] , Maelle Salmon [ctb]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package usmapdata updated to version 0.1.2 with previous version 0.1.1 dated 2023-10-20

Title: Mapping Data for 'usmap' Package
Description: Provides a container for data used by the 'usmap' package. The data used by 'usmap' has been extracted into this package so that the file size of the 'usmap' package can be reduced greatly. The data in this package will be updated roughly once per year (plus bug fixes) as new shape files are provided by the US Census bureau.
Author: Paolo Di Lorenzo [aut, cre]
Maintainer: Paolo Di Lorenzo <dilorenzo@hey.com>

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Package tpn updated to version 1.8 with previous version 1.7 dated 2023-09-27

Title: Truncated Positive Normal Model and Extensions
Description: Provide data generation and estimation tools for the truncated positive normal (tpn) model discussed in Gomez, Olmos, Varela and Bolfarine (2018) <doi:10.1007/s11766-018-3354-x>, the slash tpn distribution discussed in Gomez, Gallardo and Santoro (2021) <doi:10.3390/sym13112164>, the bimodal tpn distribution discussed in Gomez et al. (2022) <doi:10.3390/sym14040665> and the flexible tpn model.
Author: Diego Gallardo [aut, cre], Hector J. Gomez [aut], Yolanda M. Gomez [aut]
Maintainer: Diego Gallardo <dgallardo@ubiobio.cl>

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Package multibias updated to version 1.3.0 with previous version 1.2.1 dated 2023-10-21

Title: Simultaneous Multi-Bias Adjustment
Description: Quantify the causal effect of a binary exposure on a binary outcome with adjustment for multiple biases. The functions can simultaneously adjust for any combination of uncontrolled confounding, exposure/outcome misclassification, and selection bias. The underlying method generalizes the concept of combining inverse probability of selection weighting with predictive value weighting. Simultaneous multi-bias analysis can be used to enhance the validity and transparency of real-world evidence obtained from observational, longitudinal studies. Based on the work from Paul Brendel, Aracelis Torres, and Onyebuchi Arah (2023) <doi:10.1093/ije/dyad001>.
Author: Paul Brendel [aut, cre, cph]
Maintainer: Paul Brendel <pcbrendel@gmail.com>

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Package FlexParamCurve updated to version 1.5-6 with previous version 1.5-5 dated 2018-11-26

Title: Tools to Fit Flexible Parametric Curves
Description: Model selection tools and 'selfStart' functions to fit parametric curves in 'nls', 'nlsList' and 'nlme' frameworks.
Author: Stephen Oswald [aut, cre]
Maintainer: Stephen Oswald <steve.oswald@psu.edu>

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Package filelock updated to version 1.0.3 with previous version 1.0.2 dated 2018-10-05

Title: Portable File Locking
Description: Place an exclusive or shared lock on a file. It uses 'LockFile' on Windows and 'fcntl' locks on Unix-like systems.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package keypress updated to version 1.3.1 with previous version 1.3.0 dated 2022-10-26

Title: Wait for a Key Press in a Terminal
Description: Wait for a single key press at the 'R' prompt. This works in terminals, but does not currently work in the 'Windows' 'GUI', the 'OS X' 'GUI' ('R.app'), in 'Emacs' 'ESS', in an 'Emacs' shell buffer or in 'R Studio'. In these cases 'keypress' stops with an error message.
Author: Gabor Csardi [aut, cre], Jon Griffiths [aut]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package pak updated to version 0.7.1 with previous version 0.7.0 dated 2023-11-17

Title: Another Approach to Package Installation
Description: The goal of 'pak' is to make package installation faster and more reliable. In particular, it performs all HTTP operations in parallel, so metadata resolution and package downloads are fast. Metadata and package files are cached on the local disk as well. 'pak' has a dependency solver, so it finds version conflicts before performing the installation. This version of 'pak' supports CRAN, 'Bioconductor' and 'GitHub' packages as well.
Author: Gabor Csardi [aut, cre], Jim Hester [aut], Posit Software, PBC [cph, fnd], Winston Chang [ctb] , Mango Solutions [cph, fnd] , Hadley Wickham [ctb, cph] , Jeroen Ooms [ctb] , Maelle Salmon [ctb] , Duncan Temple Lang [ctb] , Lloyd Hilaiel [cph] , Miche [...truncated...]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package keyring updated to version 1.3.2 with previous version 1.3.1 dated 2022-10-27

Title: Access the System Credential Store from R
Description: Platform independent 'API' to access the operating system's credential store. Currently supports: 'Keychain' on 'macOS', Credential Store on 'Windows', the Secret Service 'API' on 'Linux', and simple, platform independent stores implemented with environment variables or encrypted files. Additional storage back-ends can be added easily.
Author: Gabor Csardi [aut, cre], Alec Wong [ctb], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between keyring versions 1.3.1 dated 2022-10-27 and 1.3.2 dated 2023-12-10

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Permanent link

Package pkgdepends updated to version 0.7.1 with previous version 0.7.0 dated 2023-11-10

Title: Package Dependency Resolution and Downloads
Description: Find recursive dependencies of 'R' packages from various sources. Solve the dependencies to obtain a consistent set of packages to install. Download packages, and install them. It supports packages on 'CRAN', 'Bioconductor' and other 'CRAN-like' repositories, 'GitHub', package 'URLs', and local package trees and files. It caches metadata and package files via the 'pkgcache' package, and performs all 'HTTP' requests, downloads, builds and installations in parallel. 'pkgdepends' is the workhorse of the 'pak' package.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between pkgdepends versions 0.7.0 dated 2023-11-10 and 0.7.1 dated 2023-12-10

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Package memisc updated to version 0.99.31.7 with previous version 0.99.31.6 dated 2023-03-10

Title: Management of Survey Data and Presentation of Analysis Results
Description: An infrastructure for the management of survey data including value labels, definable missing values, recoding of variables, production of code books, and import of (subsets of) 'SPSS' and 'Stata' files is provided. Further, the package allows to produce tables and data frames of arbitrary descriptive statistics and (almost) publication-ready tables of regression model estimates, which can be exported to 'LaTeX' and HTML.
Author: Martin Elff
Maintainer: Martin Elff <memisc@elff.eu>

Diff between memisc versions 0.99.31.6 dated 2023-03-10 and 0.99.31.7 dated 2023-12-10

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More information about memisc at CRAN
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Package getPass updated to version 0.2-4 with previous version 0.2-2 dated 2017-07-21

Title: Masked User Input
Description: A micro-package for reading "passwords", i.e. reading user input with masking, so that the input is not displayed as it is typed. Currently we have support for 'RStudio', the command line (every OS), and any platform where 'tcltk' is present.
Author: Drew Schmidt [aut, cre], Wei-Chen Chen [aut], Gabor Csardi [ctb] , Rich FitzJohn [ctb]
Maintainer: Drew Schmidt <wrathematics@gmail.com>

Diff between getPass versions 0.2-2 dated 2017-07-21 and 0.2-4 dated 2023-12-10

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More information about getPass at CRAN
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Package getip updated to version 0.1-4 with previous version 0.1-3 dated 2023-01-25

Title: 'IP' Address 'Lookup'
Description: A micro-package for getting your 'IP' address, either the local/internal or the public/external one. Currently only 'IPv4' addresses are supported.
Author: Drew Schmidt [aut, cre], Wei-Chen Chen [aut]
Maintainer: Drew Schmidt <wrathematics@gmail.com>

Diff between getip versions 0.1-3 dated 2023-01-25 and 0.1-4 dated 2023-12-10

 ChangeLog             |    3 +++
 DESCRIPTION           |    6 +++---
 MD5                   |   12 ++++++------
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 7 files changed, 18 insertions(+), 15 deletions(-)

More information about getip at CRAN
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Package float updated to version 0.3-2 with previous version 0.3-1 dated 2023-02-16

Title: 32-Bit Floats
Description: R comes with a suite of utilities for linear algebra with "numeric" (double precision) vectors/matrices. However, sometimes single precision (or less!) is more than enough for a particular task. This package extends R's linear algebra facilities to include 32-bit float (single precision) data. Float vectors/matrices have half the precision of their "numeric"-type counterparts but are generally faster to numerically operate on, for a performance vs accuracy trade-off. The internal representation is an S4 class, which allows us to keep the syntax identical to that of base R's. Interaction between floats and base types for binary operators is generally possible; in these cases, type promotion always defaults to the higher precision. The package ships with copies of the single precision 'BLAS' and 'LAPACK', which are automatically built in the event they are not available on the system.
Author: Drew Schmidt [aut, cre, cph], Wei-Chen Chen [aut], Dmitriy Selivanov [ctb] , ORNL [cph]
Maintainer: Drew Schmidt <wrathematics@gmail.com>

Diff between float versions 0.3-1 dated 2023-02-16 and 0.3-2 dated 2023-12-10

 ChangeLog        |    3 +++
 DESCRIPTION      |    6 +++---
 MD5              |   12 ++++++------
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More information about float at CRAN
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Package glinvci updated to version 1.2.2 with previous version 1.2.1 dated 2023-08-24

Title: Phylogenetic Comparative Methods with Uncertainty Estimates
Description: A framework for analytically computing the asymptotic confidence intervals and maximum-likelihood estimates of a class of continuous-time Gaussian branching processes defined by Mitov V, Bartoszek K, Asimomitis G, Stadler T (2019) <doi:10.1016/j.tpb.2019.11.005>. The class of model includes the widely used Ornstein-Uhlenbeck and Brownian motion branching processes. The framework is designed to be flexible enough so that the users can easily specify their own sub-models, or re-parameterizations, and obtain the maximum-likelihood estimates and confidence intervals of their own custom models.
Author: Hao Chi Kiang [cre, aut]
Maintainer: Hao Chi Kiang <hello@hckiang.com>

Diff between glinvci versions 1.2.1 dated 2023-08-24 and 1.2.2 dated 2023-12-10

 DESCRIPTION                  |    8 ++++----
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More information about glinvci at CRAN
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Package sylcount updated to version 0.2-6 with previous version 0.2-5 dated 2022-11-04

Title: Syllable Counting and Readability Measurements
Description: An English language syllable counter, plus readability score measure-er. For readability, we support 'Flesch' Reading Ease and 'Flesch-Kincaid' Grade Level ('Kincaid' 'et al'. 1975) <https://stars.library.ucf.edu/cgi/viewcontent.cgi?article=1055&context=istlibrary>, Automated Readability Index ('Senter' and Smith 1967) <https://apps.dtic.mil/sti/citations/AD0667273>, Simple Measure of Gobbledygook (McLaughlin 1969), and 'Coleman-Liau' (Coleman and 'Liau' 1975) <doi:10.1037/h0076540>. The package has been carefully optimized and should be very efficient, both in terms of run time performance and memory consumption. The main methods are 'vectorized' by document, and scores for multiple documents are computed in parallel via 'OpenMP'.
Author: Drew Schmidt [aut, cre]
Maintainer: Drew Schmidt <wrathematics@gmail.com>

Diff between sylcount versions 0.2-5 dated 2022-11-04 and 0.2-6 dated 2023-12-10

 ChangeLog             |    3 +++
 DESCRIPTION           |    9 ++++-----
 MD5                   |    8 ++++----
 README.md             |    2 +-
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 5 files changed, 14 insertions(+), 12 deletions(-)

More information about sylcount at CRAN
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Package rayrender updated to version 0.31.2 with previous version 0.29.6 dated 2023-06-08

Title: Build and Raytrace 3D Scenes
Description: Render scenes using pathtracing. Build 3D scenes out of spheres, cubes, planes, disks, triangles, cones, curves, line segments, cylinders, ellipsoids, and 3D models in the 'Wavefront' OBJ file format or the PLY Polygon File Format. Supports several material types, textures, multicore rendering, and tone-mapping. Based on the "Ray Tracing in One Weekend" book series. Peter Shirley (2018) <https://raytracing.github.io>.
Author: Tyler Morgan-Wall [aut, cph, cre] , Syoyo Fujita [ctb, cph], Melissa O'Neill [ctb, cph], Vilya Harvey [ctb, cph]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

Diff between rayrender versions 0.29.6 dated 2023-06-08 and 0.31.2 dated 2023-12-10

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Package PoPdesign updated to version 1.0.4 with previous version 1.0.3 dated 2022-10-02

Title: Posterior Predictive (PoP) Design for Phase I Clinical Trials
Description: The primary goal of phase I clinical trials is to find the maximum tolerated dose (MTD). To reach this objective, we introduce a new design for phase I clinical trials, the posterior predictive (PoP) design. The PoP design is an innovative model-assisted design that is as simply as the conventional algorithmic designs as its decision rules can be pre-tabulated prior to the onset of trial, but is of more flexibility of selecting diverse target toxicity rates and cohort sizes. The PoP design has desirable properties, such as coherence and consistency. Moreover, the PoP design provides better empirical performance than the BOIN and Keyboard design with respect to high average probabilities of choosing the MTD and slightly lower risk of treating patients at subtherapeutic or overly toxic doses.
Author: Chenqi Fu [aut], Xinying Fang [aut, cre], Shouhao Zhou [aut]
Maintainer: Xinying Fang <fxy950225@gmail.com>

Diff between PoPdesign versions 1.0.3 dated 2022-10-02 and 1.0.4 dated 2023-12-10

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Package ngram updated to version 3.2.3 with previous version 3.2.2 dated 2022-10-31

Title: Fast n-Gram 'Tokenization'
Description: An n-gram is a sequence of n "words" taken, in order, from a body of text. This is a collection of utilities for creating, displaying, summarizing, and "babbling" n-grams. The 'tokenization' and "babbling" are handled by very efficient C code, which can even be built as its own standalone library. The babbler is a simple Markov chain. The package also offers a vignette with complete example 'workflows' and information about the utilities offered in the package.
Author: Drew Schmidt [aut, cre], Christian Heckendorf [aut]
Maintainer: Drew Schmidt <wrathematics@gmail.com>

Diff between ngram versions 3.2.2 dated 2022-10-31 and 3.2.3 dated 2023-12-10

 ChangeLog     |    3 +++
 DESCRIPTION   |    6 +++---
 MD5           |   10 +++++-----
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Package meanr updated to version 0.1-6 with previous version 0.1-5 dated 2022-10-25

Title: Sentiment Analysis Scorer
Description: Sentiment analysis is a popular technique in text mining that attempts to determine the emotional state of some text. We provide a new implementation of a common method for computing sentiment, whereby words are scored as positive or negative according to a dictionary lookup. Then the sum of those scores is returned for the document. We use the 'Hu' and 'Liu' sentiment dictionary ('Hu' and 'Liu', 2004) <doi:10.1145/1014052.1014073> for determining sentiment. The scoring function is 'vectorized' by document, and scores for multiple documents are computed in parallel via 'OpenMP'.
Author: Drew Schmidt [aut, cre]
Maintainer: Drew Schmidt <wrathematics@gmail.com>

Diff between meanr versions 0.1-5 dated 2022-10-25 and 0.1-6 dated 2023-12-10

 ChangeLog                |    3 +++
 DESCRIPTION              |    6 +++---
 MD5                      |   10 +++++-----
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Package versus updated to version 0.2.0 with previous version 0.1.0 dated 2023-11-12

Title: Compare Data Frames
Description: A toolset for interactively exploring the differences between two data frames.
Author: Ryan Dickerson [aut, cre, cph]
Maintainer: Ryan Dickerson <fresh.tent5866@fastmail.com>

Diff between versus versions 0.1.0 dated 2023-11-12 and 0.2.0 dated 2023-12-10

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More information about versus at CRAN
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Package rxode2parse updated to version 2.0.17 with previous version 2.0.16 dated 2023-03-28

Title: Parsing and Code Generation Functions for 'rxode2'
Description: Provides the parsing needed for 'rxode2' (Wang, Hallow and James (2016) <doi:10.1002/psp4.12052>). It also provides the 'stan' based advan linear compartment model solutions with gradients (Carpenter et al (2015), <arXiv:1509.07164>) needed in 'nlmixr2' (Fidler et al (2019) <doi:10.1002/psp4.12445>). This split will reduce computational burden of recompiling 'rxode2'.
Author: Matthew L. Fidler [aut, cre] , Wenping Wang [aut], Richard Upton [ctb], Gabriel Staples [ctb], Goro Fuji [ctb], Morwenn [ctb], Igor Kushnir [ctb], Kevin Ushey [ctb], David Cooley [ctb]
Maintainer: Matthew L. Fidler <matthew.fidler@gmail.com>

Diff between rxode2parse versions 2.0.16 dated 2023-03-28 and 2.0.17 dated 2023-12-10

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Package rrBLUP updated to version 4.6.3 with previous version 4.6.2 dated 2023-01-06

Title: Ridge Regression and Other Kernels for Genomic Selection
Description: Software for genomic prediction with the RR-BLUP mixed model (Endelman 2011, <doi:10.3835/plantgenome2011.08.0024>). One application is to estimate marker effects by ridge regression; alternatively, BLUPs can be calculated based on an additive relationship matrix or a Gaussian kernel.
Author: Jeffrey Endelman
Maintainer: Jeffrey Endelman <endelman@wisc.edu>

Diff between rrBLUP versions 4.6.2 dated 2023-01-06 and 4.6.3 dated 2023-12-10

 DESCRIPTION           |    6 +++---
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Package RmdConcord updated to version 0.3 with previous version 0.2.0 dated 2023-04-29

Title: Concordances for 'R Markdown'
Description: Supports concordances in 'R Markdown' documents. This currently allows the original source location in the '.Rmd' file of errors detected by 'HTML tidy' to be found more easily, and potentially allows forward and reverse search in 'HTML' and 'LaTeX' documents produced from 'R Markdown'. The 'LaTeX' support has been included in the most recent development version of the 'patchDVI' package.
Author: Duncan Murdoch [aut, cre], Heather Turner [ctb]
Maintainer: Duncan Murdoch <murdoch.duncan@gmail.com>

Diff between RmdConcord versions 0.2.0 dated 2023-04-29 and 0.3 dated 2023-12-10

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Package milorGWAS updated to version 0.6 with previous version 0.3 dated 2020-03-25

Title: Mixed Logistic Regression for Genome-Wide Analysis Studies (GWAS)
Description: Fast approximate methods for mixed logistic regression in genome-wide analysis studies (GWAS). Milet et al 2020 <doi:10.1101/2020.01.17.910109>.
Author: Herve Perdry and Jacqueline Milet
Maintainer: Herve Perdry <herve.perdry@universite-paris-saclay.fr>

Diff between milorGWAS versions 0.3 dated 2020-03-25 and 0.6 dated 2023-12-10

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Package crew.cluster updated to version 0.1.4 with previous version 0.1.3 dated 2023-10-17

Title: Crew Launcher Plugins for Traditional High-Performance Computing Clusters
Description: In computationally demanding analysis projects, statisticians and data scientists asynchronously deploy long-running tasks to distributed systems, ranging from traditional clusters to cloud services. The 'crew.cluster' package extends the 'mirai'-powered 'crew' package with worker launcher plugins for traditional high-performance computing systems. Inspiration also comes from packages 'mirai' by Gao (2023) <https://github.com/shikokuchuo/mirai>, 'future' by Bengtsson (2021) <doi:10.32614/RJ-2021-048>, 'rrq' by FitzJohn and Ashton (2023) <https://github.com/mrc-ide/rrq>, 'clustermq' by Schubert (2019) <doi:10.1093/bioinformatics/btz284>), and 'batchtools' by Lang, Bischl, and Surmann (2017). <doi:10.21105/joss.00135>.
Author: William Michael Landau [aut, cre] , Michael Gilbert Levin [aut] , Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau.oss@gmail.com>

Diff between crew.cluster versions 0.1.3 dated 2023-10-17 and 0.1.4 dated 2023-12-10

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Package PMCMRplus updated to version 1.9.10 with previous version 1.9.9 dated 2023-11-26

Title: Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended
Description: For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs multiple comparisons tests (Tukey-Kramer test, Scheffe test, LSD-test) and many-to-one tests (Dunnett test) for normally distributed residuals and equal within variance are available. Furthermore, all-pairs tests (Games-Howell test, Tamhane's T2 test, Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one (Tamhane-Dunnett Test) for normally distributed residuals and heterogeneous variances are provided. Van der Waerden's normal scores test for omnibus, all-pairs and many-to-one tests is provided for non-normally distributed residuals and homogeneous variances. The Kruskal-Wallis, BWS and Anderson-Darling omnibus test and all-pairs tests (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- Fligner test) as well as many-to-one (Nemenyi test, Dunn test, U-test) are given for the analysis of variance by ranks. Non-parametric trend tests (Jonckheere test, Cuzick test, Johnson-Mehr [...truncated...]
Author: Thorsten Pohlert [aut, cre]
Maintainer: Thorsten Pohlert <thorsten.pohlert@gmx.de>

Diff between PMCMRplus versions 1.9.9 dated 2023-11-26 and 1.9.10 dated 2023-12-10

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Package formods updated to version 0.1.3 with previous version 0.1.2 dated 2023-11-26

Title: 'Shiny' Modules for General Tasks
Description: 'Shiny' apps can often make use of the same key elements, this package provides modules for common tasks (data upload, wrangling data, figure generation and saving the app state). These modules can react and interact as well as generate code to create reproducible analyses.
Author: John Harrold [aut, cre]
Maintainer: John Harrold <john.m.harrold@gmail.com>

Diff between formods versions 0.1.2 dated 2023-11-26 and 0.1.3 dated 2023-12-10

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Package clustMixType updated to version 0.3-14 with previous version 0.3-9 dated 2022-12-14

Title: k-Prototypes Clustering for Mixed Variable-Type Data
Description: Functions to perform k-prototypes partitioning clustering for mixed variable-type data according to Z.Huang (1998): Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Variables, Data Mining and Knowledge Discovery 2, 283-304.
Author: Gero Szepannek [aut, cre], Rabea Aschenbruck [aut]
Maintainer: Gero Szepannek <gero.szepannek@web.de>

Diff between clustMixType versions 0.3-9 dated 2022-12-14 and 0.3-14 dated 2023-12-10

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Package pingr updated to version 2.0.3 with previous version 2.0.2 dated 2022-10-26

Title: Check if a Remote Computer is Up
Description: Check if a remote computer is up. It can either just call the system ping command, or check a specified TCP port.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between pingr versions 2.0.2 dated 2022-10-26 and 2.0.3 dated 2023-12-10

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Package pkgsearch updated to version 3.1.3 with previous version 3.1.2 dated 2022-10-26

Title: Search and Query CRAN R Packages
Description: Search CRAN metadata about packages by keyword, popularity, recent activity, package name and more. Uses the 'R-hub' search server, see <https://r-pkg.org> and the CRAN metadata database, that contains information about CRAN packages. Note that this is _not_ a CRAN project.
Author: Gabor Csardi [aut, cre], Maelle Salmon [aut] , R Consortium [fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between pkgsearch versions 3.1.2 dated 2022-10-26 and 3.1.3 dated 2023-12-10

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Package pkgcache updated to version 2.2.1 with previous version 2.2.0 dated 2023-07-18

Title: Cache 'CRAN'-Like Metadata and R Packages
Description: Metadata and package cache for CRAN-like repositories. This is a utility package to be used by package management tools that want to take advantage of caching.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package pkgbuild updated to version 1.4.3 with previous version 1.4.2 dated 2023-06-26

Title: Find Tools Needed to Build R Packages
Description: Provides functions used to build R packages. Locates compilers needed to build R packages on various platforms and ensures the PATH is configured appropriately so R can use them.
Author: Hadley Wickham [aut], Jim Hester [aut], Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between pkgbuild versions 1.4.2 dated 2023-06-26 and 1.4.3 dated 2023-12-10

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Package lpSolve updated to version 5.6.20 with previous version 5.6.19 dated 2023-09-13

Title: Interface to 'Lp_solve' v. 5.5 to Solve Linear/Integer Programs
Description: Lp_solve is freely available (under LGPL 2) software for solving linear, integer and mixed integer programs. In this implementation we supply a "wrapper" function in C and some R functions that solve general linear/integer problems, assignment problems, and transportation problems. This version calls lp_solve version 5.5.
Author: Michel Berkelaar and others
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between lpSolve versions 5.6.19 dated 2023-09-13 and 5.6.20 dated 2023-12-10

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Package BayesFluxR updated to version 0.1.3 with previous version 0.1.2 dated 2023-10-06

Title: Implementation of Bayesian Neural Networks
Description: Implementation of 'BayesFlux.jl' for R; It extends the famous 'Flux.jl' machine learning library to Bayesian Neural Networks. The goal is not to have the fastest production ready library, but rather to allow more people to be able to use and research on Bayesian Neural Networks.
Author: Enrico Wegner [aut, cre]
Maintainer: Enrico Wegner <e.wegner@student.maastrichtuniversity.nl>

Diff between BayesFluxR versions 0.1.2 dated 2023-10-06 and 0.1.3 dated 2023-12-10

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Package processx updated to version 3.8.3 with previous version 3.8.2 dated 2023-06-30

Title: Execute and Control System Processes
Description: Tools to run system processes in the background. It can check if a background process is running; wait on a background process to finish; get the exit status of finished processes; kill background processes. It can read the standard output and error of the processes, using non-blocking connections. 'processx' can poll a process for standard output or error, with a timeout. It can also poll several processes at once.
Author: Gabor Csardi [aut, cre, cph] , Winston Chang [aut], Posit Software, PBC [cph, fnd], Mango Solutions [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between processx versions 3.8.2 dated 2023-06-30 and 3.8.3 dated 2023-12-10

 DESCRIPTION             |   19 +++++++++----------
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 src/create-time.c       |    2 +-
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 8 files changed, 32 insertions(+), 23 deletions(-)

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Package desc updated to version 1.4.3 with previous version 1.4.2 dated 2022-09-08

Title: Manipulate DESCRIPTION Files
Description: Tools to read, write, create, and manipulate DESCRIPTION files. It is intended for packages that create or manipulate other packages.
Author: Gabor Csardi [aut, cre], Kirill Mueller [aut], Jim Hester [aut], Maelle Salmon [ctb] , Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between desc versions 1.4.2 dated 2022-09-08 and 1.4.3 dated 2023-12-10

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Package pbdMPI updated to version 0.5-1 with previous version 0.5-0 dated 2023-09-10

Title: R Interface to MPI for HPC Clusters (Programming with Big Data Project)
Description: A simplified, efficient, interface to MPI for HPC clusters. It is a derivation and rethinking of the Rmpi package. pbdMPI embraces the prevalent parallel programming style on HPC clusters. Beyond the interface, a collection of functions for global work with distributed data and resource-independent RNG reproducibility is included. It is based on S4 classes and methods.
Author: Wei-Chen Chen [aut, cre], George Ostrouchov [aut], Drew Schmidt [aut], Pragneshkumar Patel [aut], Hao Yu [aut], Christian Heckendorf [ctb] , Brian Ripley [ctb] , R Core team [ctb] , Sebastien Lamy de la Chapelle [aut]
Maintainer: Wei-Chen Chen <wccsnow@gmail.com>

Diff between pbdMPI versions 0.5-0 dated 2023-09-10 and 0.5-1 dated 2023-12-10

 ChangeLog                     |    3 +++
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Package networkDynamic updated to version 0.11.4 with previous version 0.11.3 dated 2023-02-16

Title: Dynamic Extensions for Network Objects
Description: Simple interface routines to facilitate the handling of network objects with complex intertemporal data. This is a part of the "statnet" suite of packages for network analysis.
Author: Carter T. Butts [aut], Ayn Leslie-Cook [aut], Pavel N. Krivitsky [aut], Skye Bender-deMoll [aut, cre], Zack Almquist [ctb], David R. Hunter [ctb], Li Wang [ctb], Kirk Li [ctb], Steven M. Goodreau [ctb], Jeffrey Horner [ctb], Martina Morris [ctb]
Maintainer: Skye Bender-deMoll <skyebend@uw.edu>

Diff between networkDynamic versions 0.11.3 dated 2023-02-16 and 0.11.4 dated 2023-12-10

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Package brio updated to version 1.1.4 with previous version 1.1.3 dated 2021-11-30

Title: Basic R Input Output
Description: Functions to handle basic input output, these functions always read and write UTF-8 (8-bit Unicode Transformation Format) files and provide more explicit control over line endings.
Author: Jim Hester [aut] , Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between brio versions 1.1.3 dated 2021-11-30 and 1.1.4 dated 2023-12-10

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Package s2 updated to version 1.1.5 with previous version 1.1.4 dated 2023-05-17

Title: Spherical Geometry Operators Using the S2 Geometry Library
Description: Provides R bindings for Google's s2 library for geometric calculations on the sphere. High-performance constructors and exporters provide high compatibility with existing spatial packages, transformers construct new geometries from existing geometries, predicates provide a means to select geometries based on spatial relationships, and accessors extract information about geometries.
Author: Dewey Dunnington [aut] , Edzer Pebesma [aut, cre] , Ege Rubak [aut], Jeroen Ooms [ctb] , Google, Inc. [cph]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

Diff between s2 versions 1.1.4 dated 2023-05-17 and 1.1.5 dated 2023-12-10

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Package grove updated to version 1.1.1 with previous version 1.1 dated 2018-01-07

Title: Wavelet Functional ANOVA Through Markov Groves
Description: Functional denoising and functional ANOVA through wavelet-domain Markov groves. Fore more details see: Ma L. and Soriano J. (2018) Efficient functional ANOVA through wavelet-domain Markov groves. <arXiv:1602.03990v2 [stat.ME]>.
Author: Jacopo Soriano and Li Ma
Maintainer: Li Ma <li.ma@duke.edu>

Diff between grove versions 1.1 dated 2018-01-07 and 1.1.1 dated 2023-12-10

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Package vote updated to version 2.4-3 with previous version 2.3-2 dated 2022-02-04

Title: Election Vote Counting
Description: Counting election votes and determining election results by different methods, including the single transferable vote or ranked choice, approval, score, plurality, condorcet and two-round runoff methods (Raftery et al., 2021 <doi:10.32614/RJ-2021-086>).
Author: Hana Sevcikova, Bernard Silverman, Adrian Raftery
Maintainer: Hana Sevcikova<hanas@uw.edu>

Diff between vote versions 2.3-2 dated 2022-02-04 and 2.4-3 dated 2023-12-10

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Package RCLabels updated to version 0.1.8 with previous version 0.1.7 dated 2023-12-01

Title: Manipulate Matrix Row and Column Labels with Ease
Description: Functions to assist manipulation of matrix row and column labels for all types of matrix mathematics where row and column labels are to be respected.
Author: Matthew Heun [aut, cre]
Maintainer: Matthew Heun <matthew.heun@me.com>

Diff between RCLabels versions 0.1.7 dated 2023-12-01 and 0.1.8 dated 2023-12-10

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Package rayvertex updated to version 0.10.3 with previous version 0.7.9 dated 2023-06-08

Title: 3D Software Rasterizer
Description: Rasterize images using a 3D software renderer. 3D scenes are created either by importing external files, building scenes out of the included objects, or by constructing meshes manually. Supports point and directional lights, anti-aliased lines, shadow mapping, transparent objects, translucent objects, multiple materials types, reflection, refraction, environment maps, multicore rendering, bloom, tone-mapping, and screen-space ambient occlusion.
Author: Tyler Morgan-Wall [aut, cph, cre] , Syoyo Fujita [ctb, cph], Vilya Harvey [ctb, cph], G-Truc Creation [ctb, cph], Sean Barrett [ctb, cph]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

Diff between rayvertex versions 0.7.9 dated 2023-06-08 and 0.10.3 dated 2023-12-10

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Package ggside updated to version 0.2.3 with previous version 0.2.2 dated 2022-12-04

Title: Side Grammar Graphics
Description: The grammar of graphics as shown in 'ggplot2' has provided an expressive API for users to build plots. 'ggside' extends 'ggplot2' by allowing users to add graphical information about one of the main panel's axis using a familiar 'ggplot2' style API with tidy data. This package is particularly useful for visualizing metadata on a discrete axis, or summary graphics on a continuous axis such as a boxplot or a density distribution.
Author: Justin Landis [aut, cre]
Maintainer: Justin Landis <jtlandis314@gmail.com>

Diff between ggside versions 0.2.2 dated 2022-12-04 and 0.2.3 dated 2023-12-10

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Sat, 09 Dec 2023

Package matsindf updated to version 0.4.6 with previous version 0.4.5 dated 2023-12-02

Title: Matrices in Data Frames
Description: Provides functions to collapse a tidy data frame into matrices in a data frame and expand a data frame of matrices into a tidy data frame.
Author: Matthew Heun [aut, cre]
Maintainer: Matthew Heun <matthew.heun@me.com>

Diff between matsindf versions 0.4.5 dated 2023-12-02 and 0.4.6 dated 2023-12-09

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Package RcppAlgos updated to version 2.8.3 with previous version 2.8.2 dated 2023-10-02

Title: High Performance Tools for Combinatorics and Computational Mathematics
Description: Provides optimized functions and flexible combinatorial iterators implemented in C++ for solving problems in combinatorics and computational mathematics. Utilizes the RMatrix class from 'RcppParallel' for thread safety. There are combination/permutation functions with constraint parameters that allow for generation of all results of a vector meeting specific criteria (e.g. generating integer partitions/compositions or finding all combinations such that the sum is between two bounds). Capable of generating specific combinations/permutations (e.g. retrieve only the nth lexicographical result) which sets up nicely for parallelization as well as random sampling. Gmp support permits exploration where the total number of results is large (e.g. comboSample(10000, 500, n = 4)). Additionally, there are several high performance number theoretic functions that are useful for problems common in computational mathematics. Some of these functions make use of the fast integer division library 'libdiv [...truncated...]
Author: Joseph Wood
Maintainer: Joseph Wood <jwood000@gmail.com>

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Package MRS updated to version 1.2.5 with previous version 1.2.4 dated 2018-01-23

Title: Multi-Resolution Scanning for Cross-Sample Differences
Description: An implementation of the MRS algorithm for comparison across distributions, as described in Jacopo Soriano, Li Ma (2017) <doi:10.1111/rssb.12180>. The model is based on a nonparametric process taking the form of a Markov model that transitions between a "null" and an "alternative" state on a multi-resolution partition tree of the sample space. MRS effectively detects and characterizes a variety of underlying differences. These differences can be visualized using several plotting functions.
Author: Jacopo Soriano and Li Ma
Maintainer: Li Ma <li.ma@duke.edu>

Diff between MRS versions 1.2.4 dated 2018-01-23 and 1.2.5 dated 2023-12-09

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Package cdgd updated to version 0.3.3 with previous version 0.3.2 dated 2023-06-30

Title: Causal Decomposition of Group Disparities
Description: The framework of causal decomposition of group disparities developed by Yu and Elwert (2023) <arXiv:2306.16591>. This package implements the decomposition estimators that are based on efficient influence functions. For the nuisance functions of the estimators, both parametric and nonparametric options are provided, as well as manual options in case the default models are not satisfying.
Author: Ang Yu [aut, cre, cph]
Maintainer: Ang Yu <ang_yu@outlook.com>

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Package bigalgebra updated to version 1.1.1 with previous version 1.1.0 dated 2022-04-08

Title: 'BLAS' and 'LAPACK' Routines for Native R Matrices and 'big.matrix' Objects
Description: Provides arithmetic functions for R matrix and 'big.matrix' objects as well as functions for QR factorization, Cholesky factorization, General eigenvalue, and Singular value decomposition (SVD). A method matrix multiplication and an arithmetic method -for matrix addition, matrix difference- allows for mixed type operation -a matrix class object and a big.matrix class object- and pure type operation for two big.matrix class objects.
Author: Frederic Bertrand [cre, ctb] , Michael J. Kane [aut], Bryan Lewis [aut], John W. Emerson [aut]
Maintainer: Frederic Bertrand <frederic.bertrand@utt.fr>

Diff between bigalgebra versions 1.1.0 dated 2022-04-08 and 1.1.1 dated 2023-12-09

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Package cmfrec updated to version 3.5.1-3 with previous version 3.5.1-2 dated 2023-11-28

Title: Collective Matrix Factorization for Recommender Systems
Description: Collective matrix factorization (a.k.a. multi-view or multi-way factorization, Singh, Gordon, (2008) <doi:10.1145/1401890.1401969>) tries to approximate a (potentially very sparse or having many missing values) matrix 'X' as the product of two low-dimensional matrices, optionally aided with secondary information matrices about rows and/or columns of 'X', which are also factorized using the same latent components. The intended usage is for recommender systems, dimensionality reduction, and missing value imputation. Implements extensions of the original model (Cortes, (2018) <arXiv:1809.00366>) and can produce different factorizations such as the weighted 'implicit-feedback' model (Hu, Koren, Volinsky, (2008) <doi:10.1109/ICDM.2008.22>), the 'weighted-lambda-regularization' model, (Zhou, Wilkinson, Schreiber, Pan, (2008) <doi:10.1007/978-3-540-68880-8_32>), or the enhanced model with 'implicit features' (Rendle, Zhang, Koren, (2019) <arXiv:1905.01395>), with [...truncated...]
Author: David Cortes [aut, cre, cph], Jorge Nocedal [cph] , Naoaki Okazaki [cph] , David Blackman [cph] , Sebastiano Vigna [cph] , NumPy Developers [cph]
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

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Package BGLR updated to version 1.1.1 with previous version 1.1.0 dated 2022-05-11

Title: Bayesian Generalized Linear Regression
Description: Bayesian Generalized Linear Regression.
Author: Gustavo de los Campos, Paulino Perez Rodriguez
Maintainer: Paulino Perez Rodriguez <perpdgo@colpos.mx>

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Package marginaleffects updated to version 0.17.0 with previous version 0.16.0 dated 2023-10-19

Title: Predictions, Comparisons, Slopes, Marginal Means, and Hypothesis Tests
Description: Compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference.
Author: Vincent Arel-Bundock [aut, cre, cph] , Marcio Augusto Diniz [ctb] , Noah Greifer [ctb] , Etienne Bacher [ctb]
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>

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Package cccp updated to version 0.3-1 with previous version 0.2-9 dated 2022-09-09

Title: Cone Constrained Convex Problems
Description: Routines for solving convex optimization problems with cone constraints by means of interior-point methods. The implemented algorithms are partially ported from CVXOPT, a Python module for convex optimization (see <https://cvxopt.org> for more information).
Author: Bernhard Pfaff [aut, cre], Lieven Vandenberghe [cph] , Martin Andersen [cph] , Joachim Dahl [cph]
Maintainer: Bernhard Pfaff <bernhard@pfaffikus.de>

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Package new.dist updated to version 0.1.1 with previous version 0.1.0 dated 2023-11-07

Title: Alternative Continuous and Discrete Distributions
Description: The aim is to develop an R package, which is the 'new.dist' package, for the probability (density) function, the distribution function, the quantile function and the associated random number generation function for discrete and continuous distributions, which have recently been proposed in the literature. This package implements the following distributions: The Power Muth Distribution, a Bimodal Weibull Distribution, the Discrete Lindley Distribution, The Gamma-Lomax Distribution, Weighted Geometric Distribution, a Power Log-Dagum Distribution, Kumaraswamy Distribution, Lindley Distribution, the Unit-Inverse Gaussian Distribution, EP Distribution, Akash Distribution, Ishita Distribution, Maxwell Distribution, the Standard Omega Distribution, Slashed Generalized Rayleigh Distribution, Two-Parameter Rayleigh Distribution, Muth Distribution, Uniform-Geometric Distribution, Discrete Weibull Distribution.
Author: Ramazan Akman [cre, ctb] , Coskun Kus [aut, ctb] , Ihab Abusaif [aut, ctb]
Maintainer: Ramazan Akman <ramazanakman12345@gmail.com>

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Package mvMORPH updated to version 1.1.9 with previous version 1.1.8 dated 2023-11-29

Title: Multivariate Comparative Tools for Fitting Evolutionary Models to Morphometric Data
Description: Fits multivariate (Brownian Motion, Early Burst, ACDC, Ornstein-Uhlenbeck and Shifts) models of continuous traits evolution on trees and time series. 'mvMORPH' also proposes high-dimensional multivariate comparative tools (linear models using Generalized Least Squares and multivariate tests) based on penalized likelihood. See Clavel et al. (2015) <DOI:10.1111/2041-210X.12420>, Clavel et al. (2019) <DOI:10.1093/sysbio/syy045>, and Clavel & Morlon (2020) <DOI:10.1093/sysbio/syaa010>.
Author: Julien Clavel, with contributions from Aaron King, and Emmanuel Paradis
Maintainer: Julien Clavel <julien.clavel@hotmail.fr>

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Package huxtable updated to version 5.5.3 with previous version 5.5.2 dated 2022-12-16

Title: Easily Create and Style Tables for LaTeX, HTML and Other Formats
Description: Creates styled tables for data presentation. Export to HTML, LaTeX, RTF, 'Word', 'Excel', and 'PowerPoint'. Simple, modern interface to manipulate borders, size, position, captions, colours, text styles and number formatting. Table cells can span multiple rows and/or columns. Includes a 'huxreg' function for creation of regression tables, and 'quick_*' one-liners to print data to a new document.
Author: David Hugh-Jones [aut, cre]
Maintainer: David Hugh-Jones <davidhughjones@gmail.com>

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Package gdtools updated to version 0.3.5 with previous version 0.3.4 dated 2023-10-15

Title: Utilities for Graphical Rendering and Fonts Management
Description: Tools are provided to compute metrics of formatted strings and to check the availability of a font. Another set of functions is provided to support the collection of fonts from 'Google Fonts' in a cache. Their use is simple within 'R Markdown' documents and 'shiny' applications but also with graphic productions generated with the 'ggiraph', 'ragg' and 'svglite' packages or with tabular productions from the 'flextable' package.
Author: David Gohel [aut, cre], Hadley Wickham [aut], Lionel Henry [aut], Jeroen Ooms [aut] , Yixuan Qiu [ctb], R Core Team [cph] , ArData [cph], RStudio [cph]
Maintainer: David Gohel <david.gohel@ardata.fr>

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Package ast2ast updated to version 0.3.2 with previous version 0.3.1 dated 2023-04-11

Title: Translates an R Function to a C++ Function
Description: Enable translation of a tiny subset of R to C++. The user has to define a R function which gets translated. For a full list of possible functions check the documentation. After translation an R function is returned which is a shallow wrapper around the C++ code. Alternatively an external pointer to the C++ function is returned to the user. The intention of the package is to generate fast functions which can be used as ode-system or during optimization.
Author: Kraemer Konrad [aut, cre]
Maintainer: Kraemer Konrad <konrad_kraemer@yahoo.de>

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Package ggiraph updated to version 0.8.8 with previous version 0.8.7 dated 2023-03-17

Title: Make 'ggplot2' Graphics Interactive
Description: Create interactive 'ggplot2' graphics using 'htmlwidgets'.
Author: David Gohel [aut, cre], Panagiotis Skintzos [aut], Mike Bostock [cph] , Speros Kokenes [cph] , Eric Shull [cph] , Lee Thomason [cph] , Vladimir Agafonkin [cph] , Eric Book [ctb]
Maintainer: David Gohel <david.gohel@ardata.fr>

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Package frechet updated to version 0.3.0 with previous version 0.2.0 dated 2020-12-16

Title: Statistical Analysis for Random Objects and Non-Euclidean Data
Description: Provides implementation of statistical methods for random objects lying in various metric spaces, which are not necessarily linear spaces. The core of this package is Fréchet regression for random objects with Euclidean predictors, which allows one to perform regression analysis for non-Euclidean responses under some mild conditions. Examples include distributions in 2-Wasserstein space, covariance matrices endowed with power metric (with Frobenius metric as a special case), Cholesky and log-Cholesky metrics, spherical data. References: Petersen, A., & Müller, H.-G. (2019) <doi:10.1214/17-AOS1624>.
Author: Yaqing Chen [aut, cre], Yidong Zhou [aut], Han Chen [aut], Alvaro Gajardo [aut], Jianing Fan [aut], Qixian Zhong [aut], Paromita Dubey [aut], Kyunghee Han [aut], Satarupa Bhattacharjee [aut], Changbo Zhu [ctb], Su I Iao [ctb], Poorbita Kundu [ctb], P [...truncated...]
Maintainer: Yaqing Chen <yqchen@stat.rutgers.edu>

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Package rayimage updated to version 0.10.0 with previous version 0.9.1 dated 2023-01-16

Title: Image Processing for Simulated Cameras
Description: Uses convolution-based techniques to generate simulated camera bokeh, depth of field, and other camera effects, using an image and an optional depth map. Accepts both filename inputs and in-memory array representations of images and matrices. Includes functions to perform 2D convolutions, reorient and resize images/matrices, add image overlays, generate camera vignette effects, and add titles to images.
Author: Tyler Morgan-Wall [aut, cph, cre] , Sean Barrett [ctb, cph]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

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Package plume updated to version 0.2.1 with previous version 0.2.0 dated 2023-11-30

Title: A Simple Author Handler for Scientific Writing
Description: Handles and formats author information in scientific writing in 'R Markdown' and 'Quarto'. 'plume' provides easy-to-use and flexible tools for injecting author metadata in 'YAML' headers as well as generating author and contribution lists (among others) as strings from tabular data.
Author: Arnaud Gallou [aut, cre, cph]
Maintainer: Arnaud Gallou <arangacas@gmail.com>

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Package RcppInt64 updated to version 0.0.4 with previous version 0.0.3 dated 2023-09-19

Title: 'Rcpp'-Based Helper Functions to Pass 'Int64' and 'nanotime' Values Between 'R' and 'C++'
Description: 'Int64' values can be created and accessed via the 'bit64' package and its 'integer64' class which package the 'int64' representation cleverly into a 'double'. The 'nanotime' packages builds on this to support nanosecond-resolution timestamps. This packages helps conversions between 'R' and 'C++' via several helper functions provided via a single header file. A complete example client package is included as an illustration.
Author: Dirk Eddelbuettel [aut, cre]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppInt64 versions 0.0.3 dated 2023-09-19 and 0.0.4 dated 2023-12-09

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Package HomomorphicEncryption updated to version 0.3.0 with previous version 0.2.0 dated 2023-11-11

Title: BFV, BGV, CKKS Schema for Fully Homomorphic Encryption
Description: Implements the Brakerski-Fan-Vercauteren (BFV, 2012) <https://eprint.iacr.org/2012/144>, Brakerski-Gentry-Vaikuntanathan (BGV, 2014) <doi:10.1145/2633600>, and Cheon-Kim-Kim-Song (CKKS, 2016) <https://eprint.iacr.org/2016/421.pdf> schema for Fully Homomorphic Encryption, as well as several helper functions.
Author: Bastiaan Quast [aut, cre]
Maintainer: Bastiaan Quast <bquast@gmail.com>

Diff between HomomorphicEncryption versions 0.2.0 dated 2023-11-11 and 0.3.0 dated 2023-12-09

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Package Directional updated to version 6.4 with previous version 6.3 dated 2023-10-11

Title: A Collection of Functions for Directional Data Analysis
Description: A collection of functions for directional data (including massive data, with millions of observations) analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000). Other references include a) Phillip J. Paine, Simon P. Preston Michail Tsagris and Andrew T. A. Wood (2018). "An elliptically symmetric angular Gaussian distribution". Statistics and Computing 28(3): 689-697. <doi:10.1007/s11222-017-9756-4>. b) Tsagris M. and Alenazi A. (2019). "Comparison of discriminant analysis methods on the sphere". Communications in Statistics: Case Studies, Data Analysis and Applications 5(4):467--491. <doi:10.1080/23737484.2019.1684854>. c) P. J. Paine, S. P. Preston, M. Tsagris and Andrew T. A. Wood (2020). "Spherical regression models with general covariates and anisotropic errors". Statistics and Computing 30(1): 153--165. <d [...truncated...]
Author: Michail Tsagris, Giorgos Athineou, Christos Adam, Anamul Sajib, Eli Amson, Micah J. Waldstein
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package Compositional updated to version 6.6 with previous version 6.5 dated 2023-10-23

Title: Compositional Data Analysis
Description: Regression, classification, contour plots, hypothesis testing and fitting of distributions for compositional data are some of the functions included. We further include functions for percentages (or proportions). The standard textbook for such data is John Aitchison's (1986) "The statistical analysis of compositional data". Relevant papers include: a) Tsagris M.T., Preston S. and Wood A.T.A. (2011). "A data-based power transformation for compositional data". Fourth International International Workshop on Compositional Data Analysis. b) Tsagris M. (2014). "The k-NN algorithm for compositional data: a revised approach with and without zero values present". Journal of Data Science, 12(3): 519--534. c) Tsagris M. (2015). "A novel, divergence based, regression for compositional data". Proceedings of the 28th Panhellenic Statistics Conference, 15-18 April 2015, Athens, Greece, 430--444. d) Tsagris M. (2015). "Regression analysis with compositional data containing zero values". Chilean Journa [...truncated...]
Author: Michail Tsagris [aut, cre], Giorgos Athineou [aut], Abdulaziz Alenazi [ctb], Christos Adam [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package DDIwR updated to version 0.17 with previous version 0.16 dated 2023-10-01

Title: DDI with R
Description: Useful functions for various DDI (Data Documentation Initiative) related inputs and outputs. Converts data files to and from DDI, SPSS, Stata, SAS, R and Excel, including user declared missing values.
Author: Adrian Dusa [aut, cre, cph]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

Diff between DDIwR versions 0.16 dated 2023-10-01 and 0.17 dated 2023-12-09

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Package influential updated to version 2.2.9 with previous version 2.2.8 dated 2023-11-19

Title: Identification and Classification of the Most Influential Nodes
Description: Contains functions for the classification and ranking of top candidate features, reconstruction of networks from adjacency matrices and data frames, analysis of the topology of the network and calculation of centrality measures, and identification of the most influential nodes. Also, a function is provided for running SIRIR model, which is the combination of leave-one-out cross validation technique and the conventional SIR model, on a network to unsupervisedly rank the true influence of vertices. Additionally, some functions have been provided for the assessment of dependence and correlation of two network centrality measures as well as the conditional probability of deviation from their corresponding means in opposite direction. Fred Viole and David Nawrocki (2013, ISBN:1490523995). Csardi G, Nepusz T (2006). "The igraph software package for complex network research." InterJournal, Complex Systems, 1695. Adopted algorithms and sources are referenced in function document.
Author: Abbas Salavaty [aut, cre], Mirana Ramialison [ths], Peter D. Currie [ths]
Maintainer: Adrian Salavaty <abbas.salavaty@gmail.com>

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Package DSjobtracker updated to version 2.0.0 with previous version 0.1.1 dated 2020-12-14

Title: What Skills and Qualifications are Required for Data Science Related Jobs?
Description: Dataset containing information about job listings for data science job roles.
Author: Thiyanga S. Talagala [aut, cre] , Janith C. Wanniarachchi [aut], Hansani Piyumika [ctb], HLS Perera [ctb], S Dissanayake [ctb], MB Senanayake [ctb], T Wickramrathne [ctb]
Maintainer: Thiyanga S. Talagala <ttalagala@sjp.ac.lk>

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Package DT updated to version 0.31 with previous version 0.30 dated 2023-10-05

Title: A Wrapper of the JavaScript Library 'DataTables'
Description: Data objects in R can be rendered as HTML tables using the JavaScript library 'DataTables' (typically via R Markdown or Shiny). The 'DataTables' library has been included in this R package. The package name 'DT' is an abbreviation of 'DataTables'.
Author: Yihui Xie [aut, cre], Joe Cheng [aut], Xianying Tan [aut], JJ Allaire [ctb], Maximilian Girlich [ctb], Greg Freedman Ellis [ctb], Johannes Rauh [ctb], SpryMedia Limited [ctb, cph] , Brian Reavis [ctb, cph] , Leon Gersen [ctb, cph] , Bartek Szopka [ct [...truncated...]
Maintainer: Yihui Xie <xie@yihui.name>

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 R/package.R                                                                                   |    2 
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 build/vignette.rds                                                                            |binary
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 tests/testit/test-sort.R                                                                      |only
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Fri, 08 Dec 2023

Package mmrm updated to version 0.3.7 with previous version 0.3.6 dated 2023-11-17

Title: Mixed Models for Repeated Measures
Description: Mixed models for repeated measures (MMRM) are a popular choice for analyzing longitudinal continuous outcomes in randomized clinical trials and beyond; see Cnaan, Laird and Slasor (1997) <doi:10.1002/(SICI)1097-0258(19971030)16:20%3C2349::AID-SIM667%3E3.0.CO;2-E> for a tutorial and Mallinckrodt, Lane, Schnell, Peng and Mancuso (2008) <doi:10.1177/009286150804200402> for a review. This package implements MMRM based on the marginal linear model without random effects using Template Model Builder ('TMB') which enables fast and robust model fitting. Users can specify a variety of covariance matrices, weight observations, fit models with restricted or standard maximum likelihood inference, perform hypothesis testing with Satterthwaite or Kenward-Roger adjustment, and extract least square means estimates by using 'emmeans'.
Author: Daniel Sabanes Bove [aut, cre], Julia Dedic [aut], Doug Kelkhoff [aut], Kevin Kunzmann [aut], Brian Matthew Lang [aut], Liming Li [aut], Christian Stock [aut], Ya Wang [aut], Craig Gower-Page [ctb], Dan James [aut], Jonathan Sidi [aut], Daniel Leibov [...truncated...]
Maintainer: Daniel Sabanes Bove <daniel.sabanes_bove@roche.com>

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Permanent link

Package fastTextR updated to version 2.1.0 with previous version 2.0.1 dated 2022-10-31

Title: An Interface to the 'fastText' Library
Description: An interface to the 'fastText' library <https://github.com/facebookresearch/fastText>. The package can be used for text classification and to learn word vectors. An example how to use 'fastTextR' can be found in the 'README' file.
Author: Florian Schwendinger [aut], Emil Hvitfeldt [aut, cre]
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>

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Package CohortAlgebra updated to version 0.1.0 with previous version 0.0.4 dated 2023-09-13

Title: Use of Interval Algebra to Create New Cohort(s) from Existing Cohorts
Description: This software tool is designed to generate new cohorts utilizing data from previously instantiated cohorts. It employs interval algebra operators such as UNION, INTERSECT, and MINUS to manipulate the data within the instantiated cohorts and create new cohorts.
Author: Gowtham Rao [aut, cre], Observational Health Data Science and Informatics [cph]
Maintainer: Gowtham Rao <rao@ohdsi.org>

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Package bbmle updated to version 1.0.25.1 with previous version 1.0.25 dated 2022-05-11

Title: Tools for General Maximum Likelihood Estimation
Description: Methods and functions for fitting maximum likelihood models in R. This package modifies and extends the 'mle' classes in the 'stats4' package.
Author: Ben Bolker [aut, cre] , R Development Core Team [aut], Iago Gine-Vazquez [ctb]
Maintainer: Ben Bolker <bolker@mcmaster.ca>

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Package ebirdst updated to version 3.2022.1 with previous version 3.2022.0 dated 2023-11-15

Title: Access and Analyze eBird Status and Trends Data Products
Description: Tools for accessing and analyzing eBird Status and Trends Data Products (<https://science.ebird.org/en/status-and-trends>). eBird (<https://ebird.org/home>) is a global database of bird observations collected by member of the public. eBird Status and Trends uses these data to model global bird distributions, abundances, and population trends at a high spatial and temporal resolution.
Author: Matthew Strimas-Mackey [aut, cre] , Shawn Ligocki [aut], Tom Auer [aut] , Daniel Fink [aut] , Cornell Lab of Ornithology [cph]
Maintainer: Matthew Strimas-Mackey <mes335@cornell.edu>

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Package BGVAR updated to version 2.5.3 with previous version 2.5.2 dated 2022-10-26

Title: Bayesian Global Vector Autoregressions
Description: Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 <doi:10.1002/jae.2504>. Post-processing functions allow for doing predictions, structurally identify the model with short-run or sign-restrictions and compute impulse response functions, historical decompositions and forecast error variance decompositions. Plotting functions are also available. The package has a companion paper: Boeck, M., Feldkircher, M. and F. Huber (2022) "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R", Journal of Statistical Software, Vol. 104(9), pp. 1-28 <doi:10.18 [...truncated...]
Author: Maximilian Boeck [aut, cre] , Martin Feldkircher [aut] , Florian Huber [aut] , Darjus Hosszejni [ctb]
Maintainer: Maximilian Boeck <maximilian.boeck@unibocconi.it>

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Package mlr3pipelines updated to version 0.5.0-2 with previous version 0.5.0 dated 2023-05-22

Title: Preprocessing Operators and Pipelines for 'mlr3'
Description: Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.
Author: Martin Binder [aut, cre], Florian Pfisterer [aut] , Lennart Schneider [aut] , Bernd Bischl [aut] , Michel Lang [aut] , Sebastian Fischer [ctb] , Susanne Dandl [aut]
Maintainer: Martin Binder <mlr.developer@mb706.com>

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Package mmap updated to version 0.6-22 with previous version 0.6-21 dated 2023-01-29

Title: Map Pages of Memory
Description: R interface to POSIX mmap and Window's MapViewOfFile.
Author: Jeffrey A. Ryan
Maintainer: Jeffrey A. Ryan <jeff.a.ryan@gmail.com>

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Package ldt updated to version 0.5.1 with previous version 0.5.0 dated 2023-11-07

Title: Automated Uncertainty Analysis
Description: Methods and tools for model selection and multi-model inference (Burnham and Anderson (2002) <doi:10.1007/b97636>, among others). 'SUR' (for parameter estimation), 'logit'/'probit' (for binary classification), and 'VARMA' (for time-series forecasting) are implemented. Evaluations are both in-sample and out-of-sample. It is designed to be efficient in terms of CPU usage and memory consumption.
Author: Ramin Mojab [aut, cre], Stephen Becker [cph] by Ciyou Zhu . L-BFGS-B Version 3.0 is an algorithmic update from 2011, with coding changes by J. L. Morales)
Maintainer: Ramin Mojab <rmojab63@gmail.com>

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Package handwriter updated to version 2.0.3 with previous version 2.0.2 dated 2023-10-13

Title: Handwriting Analysis in R
Description: Perform statistical writership analysis of scanned handwritten documents. Webpage provided at: <https://csafe-isu.github.io/handwriter/index.html>.
Author: Iowa State University of Science and Technology on behalf of its Center for Statistics and Applications in Forensic Evidence [aut, cph, fnd], Nick Berry [aut], Stephanie Reinders [aut, cre], James Taylor [aut], Felix Baez-Santiago [ctb], Jon Gonzalez [...truncated...]
Maintainer: Stephanie Reinders <srein@iastate.edu>

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Package fourierin updated to version 0.2.5 with previous version 0.2.4 dated 2019-04-07

Title: Computes Numeric Fourier Integrals
Description: Computes Fourier integrals of functions of one and two variables using the Fast Fourier transform. The Fourier transforms must be evaluated on a regular grid for fast evaluation.
Author: Guillermo Basulto-Elias
Maintainer: Guillermo Basulto-Elias <guillermobasulto@gmail.com>

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Package empichar updated to version 1.0.1 with previous version 1.0.0 dated 2019-05-08

Title: Evaluates the Empirical Characteristic Function for Multivariate Samples
Description: Evaluates the empirical characteristic function of univariate and multivariate samples. This package uses 'RcppArmadillo' for fast evaluation. It is also possible to export the code to be used in other packages at 'C++' level.
Author: Guillermo Basulto-Elias [aut, cre]
Maintainer: Guillermo Basulto-Elias <guillermobasulto@gmail.com>

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Package httk updated to version 2.3.0 with previous version 2.2.2 dated 2023-02-20

Title: High-Throughput Toxicokinetics
Description: Pre-made models that can be rapidly tailored to various chemicals and species using chemical-specific in vitro data and physiological information. These tools allow incorporation of chemical toxicokinetics ("TK") and in vitro-in vivo extrapolation ("IVIVE") into bioinformatics, as described by Pearce et al. (2017) (<doi:10.18637/jss.v079.i04>). Chemical-specific in vitro data characterizing toxicokinetics have been obtained from relatively high-throughput experiments. The chemical-independent ("generic") physiologically-based ("PBTK") and empirical (for example, one compartment) "TK" models included here can be parameterized with in vitro data or in silico predictions which are provided for thousands of chemicals, multiple exposure routes, and various species. High throughput toxicokinetics ("HTTK") is the combination of in vitro data and generic models. We establish the expected accuracy of HTTK for chemicals without in vivo data through statistical evaluation of HTTK predicti [...truncated...]
Author: John Wambaugh [aut, cre] , Sarah Davidson-Fritz [aut] , Robert Pearce [aut] , Caroline Ring [aut] , Greg Honda [aut] , Mark Sfeir [aut], Matt Linakis [aut] , Dustin Kapraun [aut] , Nathan Pollesch [ctb] , Miyuki Breen [ctb] , Shannon Bell [ctb] , Xia [...truncated...]
Maintainer: John Wambaugh <wambaugh.john@epa.gov>

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Package blatent updated to version 0.1.2 with previous version 0.1.1 dated 2020-12-15

Title: Bayesian Latent Variable Models
Description: Estimation of latent variable models using Bayesian methods. Currently estimates the loglinear cognitive diagnosis model of Henson, Templin, and Willse (2009) <doi:10.1007/s11336-008-9089-5>.
Author: Jonathan Templin [aut, cre]
Maintainer: Jonathan Templin <jonathan-templin@uiowa.edu>

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Permanent link

Package admisc updated to version 0.34 with previous version 0.33 dated 2023-06-30

Title: Adrian Dusa's Miscellaneous
Description: Contains functions used across packages 'DDIwR', 'QCA' and 'venn'. Interprets and translates, factorizes and negates SOP - Sum of Products expressions, for both binary and multi-value crisp sets, and extracts information (set names, set values) from those expressions. Other functions perform various other checks if possibly numeric (even if all numbers reside in a character vector) and coerce to numeric, or check if the numbers are whole. It also offers, among many others, a highly versatile recoding routine and some more flexible alternatives to the base functions 'with()' and 'within()'. SOP simplification functions in this package use related minimization from package 'QCA', which is recommended to be installed despite not being listed in the Imports field, due to circular dependency issues.
Author: Adrian Dusa [aut, cre, cph]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package pfr updated to version 1.0.1 with previous version 1.0.0 dated 2023-08-15

Title: Interface to the 'C++' Library 'Pf'
Description: Builds and runs 'c++' code for classes that encapsulate state space model, particle filtering algorithm pairs. Algorithms include the Bootstrap Filter from Gordon et al. (1993) <doi:10.1049/ip-f-2.1993.0015>, the generic SISR filter, the Auxiliary Particle Filter from Pitt et al (1999) <doi:10.2307/2670179>, and a variety of Rao-Blackwellized particle filters inspired by Andrieu et al. (2002) <doi:10.1111/1467-9868.00363>. For more details on the 'c++' library 'pf', see Brown (2020) <doi:10.21105/joss.02599>.
Author: Taylor Brown [aut, cre]
Maintainer: Taylor Brown <trb5me@virginia.edu>

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Package GABB updated to version 0.3.7 with previous version 0.3.5 dated 2023-11-27

Title: Facilitation of Data Preparation and Plotting Procedures for RDA and PCA Analyses
Description: Help to the occasional R user for synthesis and enhanced graphical visualization of redundancy analysis (RDA) and principal component analysis (PCA) methods and objects. Inputs are : data frame, RDA (package 'vegan') and PCA (package 'FactoMineR') objects. Outputs are : synthesized results of RDA, displayed in console and saved in tables ; displayed and saved objects of PCA graphic visualization of individuals and variables projections with multiple graphic parameters.
Author: Gregoire Bianchetti [aut, cre]
Maintainer: Gregoire Bianchetti <auguste.blam@gmail.com>

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Package tern updated to version 0.9.3 with previous version 0.9.0 dated 2023-09-01

Title: Create Common TLGs Used in Clinical Trials
Description: Table, Listings, and Graphs (TLG) library for common outputs used in clinical trials.
Author: Joe Zhu [aut, cre], Daniel Sabanes Bove [aut], Jana Stoilova [aut], Heng Wang [aut], Francois Collin [aut], Adrian Waddell [aut], Pawel Rucki [aut], Chendi Liao [aut], Jennifer Li [aut], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Joe Zhu <joe.zhu@roche.com>

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More information about tern at CRAN
Permanent link

Package svglite updated to version 2.1.3 with previous version 2.1.2 dated 2023-10-11

Title: An 'SVG' Graphics Device
Description: A graphics device for R that produces 'Scalable Vector Graphics'. 'svglite' is a fork of the older 'RSvgDevice' package.
Author: Hadley Wickham [aut], Lionel Henry [aut], Thomas Lin Pedersen [cre, aut] , T Jake Luciani [aut], Matthieu Decorde [aut], Vaudor Lise [aut], Tony Plate [ctb] , David Gohel [ctb] , Yixuan Qiu [ctb] , Hakon Malmedal [ctb] , Posit, PBC [cph, fnd]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@posit.co>

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Package spacyr updated to version 1.3.0 with previous version 1.2.1 dated 2020-03-04

Title: Wrapper to the 'spaCy' 'NLP' Library
Description: An R wrapper to the 'Python' 'spaCy' 'NLP' library, from <https://spacy.io>.
Author: Kenneth Benoit [cre, aut, cph] , Akitaka Matsuo [aut] , Johannes Gruber [ctb] , European Research Council [fnd]
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

Diff between spacyr versions 1.2.1 dated 2020-03-04 and 1.3.0 dated 2023-12-08

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 spacyr-1.3.0/spacyr/tests/testthat/test-2-spacy_parse.R          |   26 
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 spacyr-1.3.0/spacyr/tests/testthat/test-4-entity-functions.R     |  487 ++--
 spacyr-1.3.0/spacyr/tests/testthat/test-5-nounphrase-functions.R |  567 ++---
 spacyr-1.3.0/spacyr/tests/testthat/test-6-quanteda-methods.R     |    3 
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 49 files changed, 2234 insertions(+), 2880 deletions(-)

More information about spacyr at CRAN
Permanent link

Package dataset updated to version 0.2.7 with previous version 0.2.1 dated 2023-03-18

Title: Create Data Frames that are Easier to Exchange and Reuse
Description: The aim of the 'dataset' package is to make tidy datasets easier to release, exchange and reuse. It organizes and formats data frame 'R' objects into well-referenced, well-described, interoperable datasets into release and reuse ready form. A subjective interpretation of the W3C DataSet recommendation and the datacube model <https://www.w3.org/TR/vocab-data-cube/>, which is also used in the global Statistical Data and Metadata eXchange standards, the application of the connected Dublin Core <https://www.dublincore.org/specifications/dublin-core/dcmi-terms/> and DataCite <https://support.datacite.org/docs/datacite-metadata-schema-44/> standards preferred by European open science repositories to improve the findability, accessibility, interoperability and reusability of the datasets.
Author: Daniel Antal [aut, cre] , Marcelo Perlin [rev]
Maintainer: Daniel Antal <daniel.antal@dataobservatory.eu>

Diff between dataset versions 0.2.1 dated 2023-03-18 and 0.2.7 dated 2023-12-08

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 152 files changed, 6874 insertions(+), 7910 deletions(-)

More information about dataset at CRAN
Permanent link

Package stan4bart updated to version 0.0-7 with previous version 0.0-6 dated 2023-02-03

Title: Bayesian Additive Regression Trees with Stan-Sampled Parametric Extensions
Description: Fits semiparametric linear and multilevel models with non-parametric additive Bayesian additive regression tree (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) components and Stan (Stan Development Team (2021) <https://mc-stan.org/>) sampled parametric ones. Multilevel models can be expressed using 'lme4' syntax (Bates, Maechler, Bolker, and Walker (2015) <doi:10.18637/jss.v067.i01>).
Author: Vincent Dorie [aut, cre] , Ben Goodrich [ctb] , Jonah Gabry [ctb] , Imad Ali [ctb] , Sam Brilleman [ctb] , Paul-Christian Burkner [ctb] , Joshua Pritikin [ctb] , Andrew Gelman [ctb] , Bob Carpenter [ctb] , Matt Hoffman [ctb] , Daniel Lee [ctb] , Mich [...truncated...]
Maintainer: Vincent Dorie <vdorie@gmail.com>

Diff between stan4bart versions 0.0-6 dated 2023-02-03 and 0.0-7 dated 2023-12-08

 DESCRIPTION                         |    8 +++---
 MD5                                 |   22 +++++++++---------
 R/generics.R                        |   12 +++++++--
 R/lme4_functions.R                  |   18 +++++++++-----
 R/misc.R                            |   25 ++++++++++++++++++++
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 inst/NEWS.Rd                        |   10 ++++++++
 src/include/rstan/io/r_ostream.hpp  |    4 +--
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 src/stan_sampler.cpp                |   44 ++++++++++++++++++++++--------------
 tests/testthat/test-01-continuous.R |   24 +++++++++++++++++++
 12 files changed, 172 insertions(+), 65 deletions(-)

More information about stan4bart at CRAN
Permanent link

Package seqinr updated to version 4.2-36 with previous version 4.2-30 dated 2023-04-05

Title: Biological Sequences Retrieval and Analysis
Description: Exploratory data analysis and data visualization for biological sequence (DNA and protein) data. Seqinr includes utilities for sequence data management under the ACNUC system described in Gouy, M. et al. (1984) Nucleic Acids Res. 12:121-127 <doi:10.1093/nar/12.1Part1.121>.
Author: Delphine Charif [aut], Olivier Clerc [ctb], Carolin Frank [ctb], Jean R. Lobry [aut, cph], Anamaria Necsulea [ctb], Leonor Palmeira [ctb], Simon Penel [cre], Guy Perriere [ctb]
Maintainer: Simon Penel <simon.penel@univ-lyon1.fr>

Diff between seqinr versions 4.2-30 dated 2023-04-05 and 4.2-36 dated 2023-12-08

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 MD5                        |  236 ++++++++++++------------
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Package r2sundials updated to version 6.5.0-4 with previous version 6.5.0-3 dated 2023-03-24

Title: Wrapper for 'SUNDIALS' Solving ODE and Sensitivity Problem
Description: Wrapper for widely used 'SUNDIALS' software (SUite of Nonlinear and DIfferential/ALgebraic Equation Solvers) and more precisely to its 'CVODES' solver. It is aiming to solve ordinary differential equations (ODE) and optionally pending forward sensitivity problem. The wrapper is made 'R' friendly by allowing to pass custom parameters to user's callback functions. Such functions can be both written in 'R' and in 'C++' ('RcppArmadillo' flavor). In case of 'C++', performance is greatly improved so this option is highly advisable when performance matters. If provided, Jacobian matrix can be calculated either in dense or sparse format. In the latter case 'rmumps' package is used to solve corresponding linear systems. Root finding and pending event management are optional and can be specified as 'R' or 'C++' functions too. This makes them a very flexible tool for controlling the ODE system during the time course simulation. 'SUNDIALS' library was published in Hindmarsh et al. (2005) <doi:1 [...truncated...]
Author: Serguei Sokol [cre, aut], Carol S. Woodward [ctb], Daniel R. Reynolds [ctb], Alan C. Hindmarsh [ctb], David J. Gardner [ctb], Cody J. Balos [ctb], Radu Serban [ctb], Scott D. Cohen [ctb], Peter N. Brown [ctb], George Byrne [ctb], Allan G. Taylor [ctb [...truncated...]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

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Package psbcSpeedUp updated to version 2.0.5 with previous version 2.0.4 dated 2023-10-12

Title: Penalized Semiparametric Bayesian Cox Models
Description: Algorithms to speed up the Bayesian Lasso Cox model (Lee et al., Int J Biostat, 2011 <doi:10.2202/1557-4679.1301>) and the Bayesian Lasso Cox with mandatory variables (Zucknick et al. Biometrical J, 2015 <doi:10.1002/bimj.201400160>).
Author: Zhi Zhao [aut, cre], Manuela Zucknick [aut], Maral Saadati [aut], Axel Benner [aut]
Maintainer: Zhi Zhao <zhi.zhao@medisin.uio.no>

Diff between psbcSpeedUp versions 2.0.4 dated 2023-10-12 and 2.0.5 dated 2023-12-08

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Package oeli updated to version 0.3.1 with previous version 0.3.0 dated 2023-12-02

Title: My Utilities for Developing Data Science Software
Description: Some general utilities (helper functions) that I and maybe others find useful when developing data science software. Functionality includes argument validation, density calculation, sampling, matrix printing, user interaction, storage helpers and more. The vignettes illustrate use cases.
Author: Lennart Oelschlaeger [aut, cre]
Maintainer: Lennart Oelschlaeger <oelschlaeger.lennart@gmail.com>

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Package mrgsim.sa updated to version 0.2.0 with previous version 0.1.0 dated 2020-11-30

Title: Sensitivity Analysis with 'mrgsolve'
Description: Perform sensitivity analysis on ordinary differential equation based models, including ad-hoc graphical analyses based on structured sequences of parameters as well as local sensitivity analysis. Functions are provided for creating inputs, simulating scenarios and plotting outputs.
Author: Kyle Baron [aut, cre]
Maintainer: Kyle Baron <kylebtwin@imap.cc>

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Package ichimoku updated to version 1.4.11 with previous version 1.4.10 dated 2023-10-28

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] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

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Package HEtools updated to version 1.0.0 with previous version 0.2.0 dated 2023-11-11

Title: Homomorphic Encryption Polynomials
Description: Homomorphic encryption (Brakerski and Vaikuntanathan (2014) <doi:10.1137/120868669>) using Ring Learning with Errors (Lyubashevsky et al. (2012) <https://eprint.iacr.org/2012/230>) is a form of Learning with Errors (Regev (2005) <doi:10.1145/1060590.1060603>) using polynomial rings over finite fields. Functions to generate the required polynomials (using 'polynom'), with various distributions of coefficients are provided. Additionally, functions to generate and take coefficient modulo are provided.
Author: Bastiaan Quast [aut, cre]
Maintainer: Bastiaan Quast <bquast@gmail.com>

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Package bayescount updated to version 0.9.99-9 with previous version 0.9.99-8 dated 2022-05-07

Title: Power Calculations and Bayesian Analysis of Count Distributions and FECRT Data using MCMC
Description: A set of functions to allow analysis of count data (such as faecal egg count data) using Bayesian MCMC methods. Returns information on the possible values for mean count, coefficient of variation and zero inflation (true prevalence) present in the data. A complete faecal egg count reduction test (FECRT) model is implemented, which returns inference on the true efficacy of the drug from the pre- and post-treatment data provided, using non-parametric bootstrapping as well as using Bayesian MCMC. Functions to perform power analyses for faecal egg counts (including FECRT) are also provided.
Author: Matthew Denwood [aut, cre]
Maintainer: Matthew Denwood <md@sund.ku.dk>

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Package mizer updated to version 2.5.0 with previous version 2.4.1 dated 2023-04-26

Title: Dynamic Multi-Species Size Spectrum Modelling
Description: A set of classes and methods to set up and run multi-species, trait based and community size spectrum ecological models, focused on the marine environment.
Author: Gustav Delius [cre, aut, cph] , Finlay Scott [aut, cph], Julia Blanchard [aut, cph] , Ken Andersen [aut, cph] , Richard Southwell [ctb, cph]
Maintainer: Gustav Delius <gustav.delius@york.ac.uk>

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Package lpridge updated to version 1.1-0 with previous version 1.0-8 dated 2018-06-12

Title: Local Polynomial (Ridge) Regression
Description: Local Polynomial Regression with Ridging.
Author: Burkhardt Seifert <seifert@ifspm.unizh.ch> ; Packaged for R by Martin Maechler
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

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Package lightgbm updated to version 4.2.0 with previous version 3.3.5 dated 2023-01-16

Title: Light Gradient Boosting Machine
Description: Tree based algorithms can be improved by introducing boosting frameworks. 'LightGBM' is one such framework, based on Ke, Guolin et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>. This package offers an R interface to work with it. It is designed to be distributed and efficient with the following advantages: 1. Faster training speed and higher efficiency. 2. Lower memory usage. 3. Better accuracy. 4. Parallel learning supported. 5. Capable of handling large-scale data. In recognition of these advantages, 'LightGBM' has been widely-used in many winning solutions of machine learning competitions. Comparison experiments on public datasets suggest that 'LightGBM' can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, 'LightGBM' can achieve a linear speed-up in training time by using multiple m [...truncated...]
Author: Yu Shi [aut], Guolin Ke [aut], Damien Soukhavong [aut], James Lamb [aut, cre], Qi Meng [aut], Thomas Finley [aut], Taifeng Wang [aut], Wei Chen [aut], Weidong Ma [aut], Qiwei Ye [aut], Tie-Yan Liu [aut], Nikita Titov [aut], Yachen Yan [ctb], Microsof [...truncated...]
Maintainer: James Lamb <jaylamb20@gmail.com>

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 lightgbm-4.2.0/lightgbm/R/saveRDS.lgb.Booster.R                                                 |   57 
 lightgbm-4.2.0/lightgbm/R/utils.R                                                               |  151 
 lightgbm-4.2.0/lightgbm/README.md                                                               |  102 
 lightgbm-4.2.0/lightgbm/build                                                                   |only
 lightgbm-4.2.0/lightgbm/configure                                                               |  738 -
 lightgbm-4.2.0/lightgbm/configure.ac                                                            |   12 
 lightgbm-4.2.0/lightgbm/configure.win                                                           |   38 
 lightgbm-4.2.0/lightgbm/demo/basic_walkthrough.R                                                |    1 
 lightgbm-4.2.0/lightgbm/demo/boost_from_prediction.R                                            |    5 
 lightgbm-4.2.0/lightgbm/demo/early_stopping.R                                                   |    1 
 lightgbm-4.2.0/lightgbm/demo/leaf_stability.R                                                   |    6 
 lightgbm-4.2.0/lightgbm/demo/multiclass.R                                                       |   14 
 lightgbm-4.2.0/lightgbm/demo/multiclass_custom_objective.R                                      |    4 
 lightgbm-4.2.0/lightgbm/demo/weight_param.R                                                     |   25 
 lightgbm-4.2.0/lightgbm/inst                                                                    |only
 lightgbm-4.2.0/lightgbm/man/dim.Rd                                                              |    6 
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 lightgbm-4.2.0/lightgbm/man/get_field.Rd                                                        |    2 
 lightgbm-4.2.0/lightgbm/man/lgb.Dataset.Rd                                                      |   12 
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 lightgbm-4.2.0/lightgbm/man/lgb.Dataset.create.valid.Rd                                         |   13 
 lightgbm-4.2.0/lightgbm/man/lgb.Dataset.save.Rd                                                 |    2 
 lightgbm-4.2.0/lightgbm/man/lgb.Dataset.set.categorical.Rd                                      |    2 
 lightgbm-4.2.0/lightgbm/man/lgb.Dataset.set.reference.Rd                                        |    2 
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 lightgbm-4.2.0/lightgbm/man/lgb.dump.Rd                                                         |    3 
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 lightgbm-4.2.0/lightgbm/man/lgb.importance.Rd                                                   |    3 
 lightgbm-4.2.0/lightgbm/man/lgb.interprete.Rd                                                   |    3 
 lightgbm-4.2.0/lightgbm/man/lgb.load.Rd                                                         |    5 
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 lightgbm-4.2.0/lightgbm/man/lgb.model.dt.tree.Rd                                                |    3 
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 lightgbm-4.2.0/lightgbm/man/lgb.plot.interpretation.Rd                                          |    3 
 lightgbm-4.2.0/lightgbm/man/lgb.restore_handle.Rd                                               |only
 lightgbm-4.2.0/lightgbm/man/lgb.save.Rd                                                         |    3 
 lightgbm-4.2.0/lightgbm/man/lgb.train.Rd                                                        |   31 
 lightgbm-4.2.0/lightgbm/man/lgb_shared_dataset_params.Rd                                        |    4 
 lightgbm-4.2.0/lightgbm/man/lgb_shared_params.Rd                                                |   30 
 lightgbm-4.2.0/lightgbm/man/lightgbm.Rd                                                         |   78 
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 lightgbm-4.2.0/lightgbm/man/print.lgb.Booster.Rd                                                |only
 lightgbm-4.2.0/lightgbm/man/readRDS.lgb.Booster.Rd                                              |   10 
 lightgbm-4.2.0/lightgbm/man/saveRDS.lgb.Booster.Rd                                              |   11 
 lightgbm-4.2.0/lightgbm/man/setLGBMThreads.Rd                                                   |only
 lightgbm-4.2.0/lightgbm/man/set_field.Rd                                                        |    2 
 lightgbm-4.2.0/lightgbm/man/slice.Rd                                                            |    8 
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 lightgbm-4.2.0/lightgbm/src/Makevars.in                                                         |    6 
 lightgbm-4.2.0/lightgbm/src/Makevars.win.in                                                     |    8 
 lightgbm-4.2.0/lightgbm/src/application/predictor.hpp                                           |    8 
 lightgbm-4.2.0/lightgbm/src/boosting/bagging.hpp                                                |only
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 lightgbm-4.2.0/lightgbm/src/boosting/cuda                                                       |only
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 lightgbm-4.2.0/lightgbm/src/boosting/gbdt.h                                                     |  125 
 lightgbm-4.2.0/lightgbm/src/boosting/gbdt_model_text.cpp                                        |   35 
 lightgbm-4.2.0/lightgbm/src/boosting/goss.hpp                                                   |  168 
 lightgbm-4.2.0/lightgbm/src/boosting/rf.hpp                                                     |   45 
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 lightgbm-4.2.0/lightgbm/src/boosting/score_updater.hpp                                          |   22 
 lightgbm-4.2.0/lightgbm/src/c_api.cpp                                                           |  525 
 lightgbm-4.2.0/lightgbm/src/cuda                                                                |only
 lightgbm-4.2.0/lightgbm/src/include/Eigen/Cholesky                                              |    1 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/Core                                                  |   19 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/Eigenvalues                                           |    1 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/Geometry                                              |    5 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/Householder                                           |    1 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/Jacobi                                                |    1 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/LU                                                    |    7 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/QR                                                    |    1 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/SVD                                                   |    1 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Cholesky/LDLT.h                                   |   10 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Cholesky/LLT.h                                    |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Array.h                                      |   32 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/ArrayWrapper.h                               |   42 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/AssignEvaluator.h                            |  120 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/BandMatrix.h                                 |   32 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Block.h                                      |   72 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/BooleanRedux.h                               |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/CoreEvaluators.h                             |  253 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/CwiseBinaryOp.h                              |   24 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/CwiseNullaryOp.h                             |   89 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/CwiseUnaryOp.h                               |   12 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/CwiseUnaryView.h                             |   20 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/DenseBase.h                                  |   82 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/DenseCoeffsBase.h                            |   34 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/DenseStorage.h                               |  158 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Diagonal.h                                   |   34 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Dot.h                                        |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/EigenBase.h                                  |   16 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/ForceAlignedAccess.h                         |   12 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/GeneralProduct.h                             |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/GenericPacketMath.h                          |  629 -
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/GlobalFunctions.h                            |    5 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Inverse.h                                    |   16 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Map.h                                        |    8 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/MapBase.h                                    |    8 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/MathFunctions.h                              |  477 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/MathFunctionsImpl.h                          |   98 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Matrix.h                                     |   36 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/NestByValue.h                                |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/NumTraits.h                                  |   94 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/PartialReduxEvaluator.h                      |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/PlainObjectBase.h                            |   61 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Product.h                                    |   44 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/ProductEvaluators.h                          |  167 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Random.h                                     |   36 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Redux.h                                      |   22 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Ref.h                                        |  137 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Replicate.h                                  |   12 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Reshaped.h                                   |    7 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/ReturnByValue.h                              |   10 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Reverse.h                                    |   14 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Select.h                                     |   14 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/SelfAdjointView.h                            |   36 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Solve.h                                      |   24 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/SolveTriangular.h                            |   24 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/StableNorm.h                                 |   57 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/StlIterators.h                               |   19 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Stride.h                                     |   13 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Transpose.h                                  |   12 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Transpositions.h                             |   32 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/TriangularMatrix.h                           |  112 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/VectorwiseOp.h                               |   26 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Visitor.h                                    |  150 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX/Complex.h                           |  102 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX/MathFunctions.h                     |   79 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX/PacketMath.h                        |  390 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX/TypeCasting.h                       |   48 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX512/Complex.h                        |   70 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX512/MathFunctions.h                  |  237 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX512/PacketMath.h                     |  401 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX512/TypeCasting.h                    |   16 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AltiVec/Complex.h                       |  235 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AltiVec/MatrixProduct.h                 | 3080 ++++-
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AltiVec/MatrixProductCommon.h           |only
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AltiVec/MatrixProductMMA.h              |only
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AltiVec/PacketMath.h                    |  484 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/CUDA/Complex.h                          |  315 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/Default/BFloat16.h                      |  150 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/Default/ConjHelper.h                    |  116 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/Default/GenericPacketMathFunctions.h    | 1140 +
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/Default/GenericPacketMathFunctionsFwd.h |   51 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/Default/Half.h                          |  510 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/GPU/PacketMath.h                        |  459 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/MSA/Complex.h                           |   72 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/MSA/PacketMath.h                        |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/NEON/Complex.h                          |  109 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/NEON/MathFunctions.h                    |   24 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/NEON/PacketMath.h                       | 1758 ++
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/NEON/TypeCasting.h                      |    8 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SSE/Complex.h                           |  178 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SSE/MathFunctions.h                     |   33 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SSE/PacketMath.h                        |  389 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SSE/TypeCasting.h                       |    7 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SVE                                     |only
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SYCL/InteropHeaders.h                   |    3 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SYCL/MathFunctions.h                    |   18 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/ZVector/MathFunctions.h                 |   10 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/ZVector/PacketMath.h                    |   56 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/functors/BinaryFunctors.h                    |  173 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/functors/NullaryFunctors.h                   |    6 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/functors/UnaryFunctors.h                     |   62 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h           |  201 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/products/GeneralMatrixMatrix.h               |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/products/Parallelizer.h                      |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/products/SelfadjointRank2Update.h            |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/products/TriangularSolverMatrix.h            |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/BlasUtil.h                              |  201 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/ConfigureVectorization.h                |   62 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/Constants.h                             |   21 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/DisableStupidWarnings.h                 |    3 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/ForwardDeclarations.h                   |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/IndexedViewHelper.h                     |   12 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/IntegralConstant.h                      |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/Macros.h                                |  287 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/Memory.h                                |   59 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/Meta.h                                  |  255 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/StaticAssert.h                          |    5 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/SymbolicIndex.h                         |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/XprHelper.h                             |   50 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Eigenvalues/HessenbergDecomposition.h             |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h              |   97 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Eigenvalues/Tridiagonalization.h                  |   30 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/AlignedBox.h                             |  102 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/AngleAxis.h                              |    8 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/EulerAngles.h                            |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/Homogeneous.h                            |   26 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/ParametrizedLine.h                       |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/Quaternion.h                             |   22 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/Rotation2D.h                             |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/Scaling.h                                |    2 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Jacobi/Jacobi.h                                   |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/LU/FullPivLU.h                                    |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/LU/InverseImpl.h                                  |   31 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/LU/PartialPivLU.h                                 |   13 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/SVD/BDCSVD.h                                      |   34 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/SVD/JacobiSVD.h                                   |   33 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/SVD/SVDBase.h                                     |   42 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/plugins/ArrayCwiseUnaryOps.h                      |   52 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/plugins/BlockMethods.h                            |    3 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/plugins/CommonCwiseUnaryOps.h                     |   43 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/plugins/MatrixCwiseBinaryOps.h                    |    8 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/plugins/MatrixCwiseUnaryOps.h                     |   10 
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 lightgbm-4.2.0/lightgbm/src/include/LightGBM/boosting.h                                         |    4 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/c_api.h                                            |  267 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/config.h                                           |  156 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_algorithms.hpp                           |only
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Package grattan updated to version 2023.1.2 with previous version 2023.1.1 dated 2023-09-04

Title: Australian Tax Policy Analysis
Description: Utilities to cost and evaluate Australian tax policy, including fast projections of personal income tax collections, high-performance tax and transfer calculators, and an interface to common indices from the Australian Bureau of Statistics. Written to support Grattan Institute's Australian Perspectives program, and related projects. Access to the Australian Taxation Office's sample files of personal income tax returns is assumed.
Author: Hugh Parsonage [aut, cre], Tim Cameron [aut], Brendan Coates [aut], Matthew Katzen [aut], William Young [aut], Ittima Cherastidtham [dtc], W. Karsten [ctb], M. Enrique Garcia [ctb], Matt Cowgill [aut]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

Diff between grattan versions 2023.1.1 dated 2023-09-04 and 2023.1.2 dated 2023-12-08

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Package data.table updated to version 1.14.10 with previous version 1.14.8 dated 2023-02-17

Title: Extension of `data.frame`
Description: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
Author: Tyson Barrett [aut, cre], Matt Dowle [aut], Arun Srinivasan [aut], Jan Gorecki [ctb], Michael Chirico [ctb], Pasha Stetsenko [ctb], Tom Short [ctb], Steve Lianoglou [ctb], Eduard Antonyan [ctb], Markus Bonsch [ctb], Hugh Parsonage [ctb], Scott Ritchi [...truncated...]
Maintainer: Tyson Barrett <t.barrett88@gmail.com>

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Package symengine updated to version 0.2.3 with previous version 0.2.2 dated 2022-10-23

Title: Interface to the 'SymEngine' Library
Description: Provides an R interface to 'SymEngine' <https://github.com/symengine/>, a standalone 'C++' library for fast symbolic manipulation. The package has functionalities for symbolic computation like calculating exact mathematical expressions, solving systems of linear equations and code generation.
Author: Jialin Ma [cre, aut], Isuru Fernando [aut], Xin Chen [aut]
Maintainer: Jialin Ma <marlin@inventati.org>

Diff between symengine versions 0.2.2 dated 2022-10-23 and 0.2.3 dated 2023-12-08

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Package rtables updated to version 0.6.6 with previous version 0.6.3 dated 2023-08-30

Title: Reporting Tables
Description: Reporting tables often have structure that goes beyond simple rectangular data. The 'rtables' package provides a framework for declaring complex multi-level tabulations and then applying them to data. This framework models both tabulation and the resulting tables as hierarchical, tree-like objects which support sibling sub-tables, arbitrary splitting or grouping of data in row and column dimensions, cells containing multiple values, and the concept of contextual summary computations. A convenient pipe-able interface is provided for declaring table layouts and the corresponding computations, and then applying them to data.
Author: Gabriel Becker [aut] , Adrian Waddell [aut], Daniel Sabanes Bove [ctb], Maximilian Mordig [ctb], Davide Garolini [ctb], Emily de la Rua [ctb], Abinaya Yogasekaram [ctb], Joe Zhu [ctb, cre], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Joe Zhu <joe.zhu@roche.com>

Diff between rtables versions 0.6.3 dated 2023-08-30 and 0.6.6 dated 2023-12-08

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More information about rtables at CRAN
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Package Rbeast updated to version 1.0.0 with previous version 0.9.9 dated 2023-05-14

Title: Bayesian Change-Point Detection and Time Series Decomposition
Description: Interpretation of time series data is affected by model choices. Different models can give different or even contradicting estimates of patterns, trends, and mechanisms for the same data--a limitation alleviated by the Bayesian estimator of abrupt change,seasonality, and trend (BEAST) of this package. BEAST seeks to improve time series decomposition by forgoing the "single-best-model" concept and embracing all competing models into the inference via a Bayesian model averaging scheme. It is a flexible tool to uncover abrupt changes (i.e., change-points), cyclic variations (e.g., seasonality), and nonlinear trends in time-series observations. BEAST not just tells when changes occur but also quantifies how likely the detected changes are true. It detects not just piecewise linear trends but also arbitrary nonlinear trends. BEAST is applicable to real-valued time series data of all kinds, be it for remote sensing, economics, climate sciences, ecology, and hydrology. Example applications in [...truncated...]
Author: Tongxi Hu [aut], Yang Li [aut], Xuesong Zhang [aut], Kaiguang Zhao [aut, cre], Jack Dongarra [ctb], Cleve Moler [ctb]
Maintainer: Kaiguang Zhao <zhao.1423@osu.edu>

Diff between Rbeast versions 0.9.9 dated 2023-05-14 and 1.0.0 dated 2023-12-08

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 src/abc_sort.c                          |  143 ++
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More information about Rbeast at CRAN
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Package plugdensity updated to version 0.8-5 with previous version 0.8-4 dated 2022-02-23

Title: Plug-in Kernel Density Estimation
Description: Kernel density estimation with global bandwidth selection via "plug-in".
Author: Eva Herrmann <eherrmann@mathematik.tu-darmstadt.de> ; R interface etc by Martin Maechler
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

Diff between plugdensity versions 0.8-4 dated 2022-02-23 and 0.8-5 dated 2023-12-08

 ChangeLog   |    4 ++++
 DESCRIPTION |   14 ++++++--------
 MD5         |    4 ++--
 3 files changed, 12 insertions(+), 10 deletions(-)

More information about plugdensity at CRAN
Permanent link

Package GenTwoArmsTrialSize updated to version 0.0.4.4 with previous version 0.0.4.3 dated 2023-12-07

Title: Generalized Two Arms Clinical Trial Sample Size Calculation
Description: Two arms clinical trials required sample size is calculated in the comprehensive parametric context. The calculation is based on the type of endpoints(continuous/binary/time-to-event/ordinal), design (parallel/crossover), hypothesis tests (equality/noninferiority/superiority/equivalence), trial arms noncompliance rates and expected loss of follow-up. Methods are described in: Chow SC, Shao J, Wang H, Lokhnygina Y (2017) <doi:10.1201/9781315183084>, Wittes, J (2002) <doi:10.1093/epirev/24.1.39>, Sato, T (2000) <doi:10.1002/1097-0258(20001015)19:19%3C2689::aid-sim555%3E3.0.co;2-0>, Lachin J M, Foulkes, M A (1986) <doi:10.2307/2531201>, Whitehead J(1993) <doi:10.1002/sim.4780122404>, Julious SA (2023) <doi:10.1201/9780429503658>.
Author: Mohsen Soltanifar [aut] , Chel Hee Lee [cre, aut]
Maintainer: Chel Hee Lee <chelhee.lee@ucalgary.ca>

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Package blaise updated to version 1.3.11 with previous version 1.3.10 dated 2023-08-18

Title: Read and Write FWF Files in the 'Blaise' Format
Description: Can be used to read and write a fwf with an accompanying 'Blaise' datamodel. Blaise is the software suite built by Statistics Netherlands (CBS). It is essentially a way to write and collect surveys and perform statistical analysis on the data. It stores its data in fixed width format with an accompanying metadata file, this is the Blaise format. The package automatically interprets this metadata and reads the file into an R dataframe. When supplying a datamodel for writing, the dataframe will be automatically converted to that format and checked for compatibility. Supports dataframes, tibbles and LaF objects. For more information about 'Blaise', see <https://blaise.com/products/general-information>.
Author: Sjoerd Ophof [aut, cre]
Maintainer: Sjoerd Ophof <sjoerd.ophof@gmail.com>

Diff between blaise versions 1.3.10 dated 2023-08-18 and 1.3.11 dated 2023-12-08

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Package collinear updated to version 1.1.1 with previous version 1.1.0 dated 2023-11-30

Title: Seamless Multicollinearity Management
Description: System for seamless management of multicollinearity in data frames with numeric and/or categorical variables for statistical analysis and machine learning modeling. The package combines bivariate correlation (Pearson, Spearman, and Cramer's V) with variance inflation factor analysis, target encoding to transform categorical variables into numeric (Micci-Barreca, D. 2001 <DOI:10.1145/507533.507538>), and a flexible feature prioritization method, to deliver a comprehensive multicollinearity management tool covering a wide range of use cases.
Author: Blas M. Benito [aut, cre, cph]
Maintainer: Blas M. Benito <blasbenito@gmail.com>

Diff between collinear versions 1.1.0 dated 2023-11-30 and 1.1.1 dated 2023-12-08

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Package curl updated to version 5.2.0 with previous version 5.1.0 dated 2023-10-02

Title: A Modern and Flexible Web Client for R
Description: The curl() and curl_download() functions provide highly configurable drop-in replacements for base url() and download.file() with better performance, support for encryption (https, ftps), gzip compression, authentication, and other 'libcurl' goodies. The core of the package implements a framework for performing fully customized requests where data can be processed either in memory, on disk, or streaming via the callback or connection interfaces. Some knowledge of 'libcurl' is recommended; for a more-user-friendly web client see the 'httr' package which builds on this package with http specific tools and logic.
Author: Jeroen Ooms [aut, cre] , Hadley Wickham [ctb], RStudio [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between curl versions 5.1.0 dated 2023-10-02 and 5.2.0 dated 2023-12-08

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Package KnockoffTrio updated to version 1.0.2 with previous version 1.0.1 dated 2022-10-17

Title: Trio Data Analysis with Knockoff Statistics for FDR Control
Description: Identification of putative causal variants in genome-wide association studies with the trio design. The package implements the methods in the paper: Yang, Y., Wang, C., Liu, L., Buxbaum, J., He, Z., & Ionita-Laza, I. (2022). KnockoffTrio: A knockoff framework for the identification of putative causal variants in genome-wide association studies with trio design. The American Journal of Human Genetics, 109(10), 1761-1776.
Author: Yi Yang [aut, cre]
Maintainer: Yi Yang <yi.yang@cityu.edu.hk>

Diff between KnockoffTrio versions 1.0.1 dated 2022-10-17 and 1.0.2 dated 2023-12-08

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Package GaSP updated to version 1.0.5 with previous version 1.0.4 dated 2023-05-18

Title: Train and Apply a Gaussian Stochastic Process Model
Description: Train a Gaussian stochastic process model of an unknown function, possibly observed with error, via maximum likelihood or maximum a posteriori (MAP) estimation, run model diagnostics, and make predictions, following Sacks, J., Welch, W.J., Mitchell, T.J., and Wynn, H.P. (1989) "Design and Analysis of Computer Experiments", Statistical Science, <doi:10.1214/ss/1177012413>. Perform sensitivity analysis and visualize low-order effects, following Schonlau, M. and Welch, W.J. (2006), "Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization", <doi:10.1007/0-387-28014-6_14>.
Author: William J. Welch [aut, cre, cph] , Yilin Yang [aut]
Maintainer: William J. Welch <will@stat.ubc.ca>

Diff between GaSP versions 1.0.4 dated 2023-05-18 and 1.0.5 dated 2023-12-08

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Package onbrand updated to version 1.0.4 with previous version 1.0.3 dated 2023-07-16

Title: Templated Reporting Workflows in Word and PowerPoint
Description: Automated reporting in Word and PowerPoint can require customization for each organizational template. This package works around this by adding standard reporting functions and an abstraction layer to facilitate automated reporting workflows that can be replicated across different organizational templates.
Author: John Harrold [aut, cre] , Bryan Smith [aut]
Maintainer: John Harrold <john.m.harrold@gmail.com>

Diff between onbrand versions 1.0.3 dated 2023-07-16 and 1.0.4 dated 2023-12-08

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Package Canek updated to version 0.2.5 with previous version 0.2.4 dated 2023-11-05

Title: Batch Correction of Single Cell Transcriptome Data
Description: Non-linear/linear hybrid method for batch-effect correction that uses Mutual Nearest Neighbors (MNNs) to identify similar cells between datasets. Reference: Loza M. et al. (NAR Genomics and Bioinformatics, 2020) <doi:10.1093/nargab/lqac022>.
Author: Martin Loza [aut, cre] , Diego Diez [aut]
Maintainer: Martin Loza <martin.loza.lopez@gmail.com>

Diff between Canek versions 0.2.4 dated 2023-11-05 and 0.2.5 dated 2023-12-08

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Package ASGS.foyer updated to version 0.3.3 with previous version 0.3.1 dated 2021-03-21

Title: Interface to the Australian Statistical Geography Standard
Description: The Australian Statistical Geography Standard ('ASGS') is a set of shapefiles by the Australian Bureau of Statistics. This package provides an interface to those shapefiles, as well as methods for converting coordinates to shapefiles.
Author: Hugh Parsonage [aut, cre]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

Diff between ASGS.foyer versions 0.3.1 dated 2021-03-21 and 0.3.3 dated 2023-12-08

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Thu, 07 Dec 2023

Package omnibus updated to version 1.2.8 with previous version 1.2.7 dated 2023-08-21

Title: Helper Tools for Managing Data, Dates, Missing Values, and Text
Description: An assortment of helper functions for managing data (e.g., rotating values in matrices by a user-defined angle, switching from row- to column-indexing), dates (e.g., intuiting year from messy date strings), handling missing values (e.g., removing elements/rows across multiple vectors or matrices if any have an NA), text (e.g., flushing reports to the console in real-time); and combining data frames with different schema (copying, filling, or concatenating columns or applying functions before combining).
Author: Adam B. Smith [cre, aut]
Maintainer: Adam B. Smith <adam.smith@mobot.org>

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Package nanoarrow updated to version 0.3.0.1 with previous version 0.3.0 dated 2023-09-29

Title: Interface to the 'nanoarrow' 'C' Library
Description: Provides an 'R' interface to the 'nanoarrow' 'C' library and the 'Apache Arrow' application binary interface. Functions to import and export 'ArrowArray', 'ArrowSchema', and 'ArrowArrayStream' 'C' structures to and from 'R' objects are provided alongside helpers to facilitate zero-copy data transfer among 'R' bindings to libraries implementing the 'Arrow' 'C' data interface.
Author: Dewey Dunnington [aut, cre] , Apache Arrow [aut, cph], Apache Software Foundation [cph]
Maintainer: Dewey Dunnington <dewey@dunnington.ca>

Diff between nanoarrow versions 0.3.0 dated 2023-09-29 and 0.3.0.1 dated 2023-12-07

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Package vetr updated to version 0.2.16 with previous version 0.2.15 dated 2023-01-06

Title: Trust, but Verify
Description: Declarative template-based framework for verifying that objects meet structural requirements, and auto-composing error messages when they do not.
Author: Brodie Gaslam [aut, cre], Paxdiablo [cph] , R Core Team [cph]
Maintainer: Brodie Gaslam <brodie.gaslam@yahoo.com>

Diff between vetr versions 0.2.15 dated 2023-01-06 and 0.2.16 dated 2023-12-07

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Package fansi updated to version 1.0.6 with previous version 1.0.5 dated 2023-10-08

Title: ANSI Control Sequence Aware String Functions
Description: Counterparts to R string manipulation functions that account for the effects of ANSI text formatting control sequences.
Author: Brodie Gaslam [aut, cre], Elliott Sales De Andrade [ctb], R Core Team [cph]
Maintainer: Brodie Gaslam <brodie.gaslam@yahoo.com>

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Package blackbox updated to version 1.1.46 with previous version 1.1.43 dated 2023-05-03

Title: Black Box Optimization and Exploration of Parameter Space
Description: Performs prediction of a response function from simulated response values, allowing black-box optimization of functions estimated with some error. Includes a simple user interface for such applications, as well as more specialized functions designed to be called by the Migraine software (Rousset and Leblois, 2012 <doi:10.1093/molbev/MSR262>; Leblois et al., 2014 <doi:10.1093/molbev/msu212>; and see URL). The latter functions are used for prediction of likelihood surfaces and implied likelihood ratio confidence intervals, and for exploration of predictor space of the surface. Prediction of the response is based on ordinary Kriging (with residual error) of the input. Estimation of smoothing parameters is performed by generalized cross-validation.
Author: Francois Rousset [aut, cre, cph] , Raphael Leblois [ctb]
Maintainer: Francois Rousset <francois.rousset@umontpellier.fr>

Diff between blackbox versions 1.1.43 dated 2023-05-03 and 1.1.46 dated 2023-12-07

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Package vcfR updated to version 1.15.0 with previous version 1.14.0 dated 2023-02-10

Title: Manipulate and Visualize VCF Data
Description: Facilitates easy manipulation of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices of data. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file (*.vcf.gz). It also may be converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and familiar R software.
Author: Brian J. Knaus [cre, aut] , Niklaus J. Grunwald [aut] , Eric C. Anderson [ctb] , David J. Winter [ctb], Zhian N. Kamvar [ctb] , Javier F. Tabima [ctb]
Maintainer: Brian J. Knaus <briank.lists@gmail.com>

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Package RSQLite updated to version 2.3.4 with previous version 2.3.3 dated 2023-11-04

Title: SQLite Interface for R
Description: Embeds the SQLite database engine in R and provides an interface compliant with the DBI package. The source for the SQLite engine and for various extensions in a recent version is included. System libraries will never be consulted because this package relies on static linking for the plugins it includes; this also ensures a consistent experience across all installations.
Author: Kirill Mueller [aut, cre] , Hadley Wickham [aut], David A. James [aut], Seth Falcon [aut], D. Richard Hipp [ctb] , Dan Kennedy [ctb] , Joe Mistachkin [ctb] , SQLite Authors [ctb] , Liam Healy [ctb] , R Consortium [fnd], RStudio [cph]
Maintainer: Kirill Mueller <kirill@cynkra.com>

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Package rotations updated to version 1.6.5 with previous version 1.6.4 dated 2022-06-24

Title: Working with Rotation Data
Description: Tools for working with rotational data, including simulation from the most commonly used distributions on SO(3), methods for different Bayes, mean and median type estimators for the central orientation of a sample, confidence/credible regions for the central orientation based on those estimators and a novel visualization technique for rotation data. Most recently, functions to identify potentially discordant (outlying) values have been added. References: Bingham, Melissa A. and Nordman, Dan J. and Vardeman, Steve B. (2009), Bingham, Melissa A and Vardeman, Stephen B and Nordman, Daniel J (2009), Bingham, Melissa A and Nordman, Daniel J and Vardeman, Stephen B (2010), Leon, C.A. and Masse, J.C. and Rivest, L.P. (2006), Hartley, R and Aftab, K and Trumpf, J. (2011), Stanfill, Bryan and Genschel, Ulrike and Hofmann, Heike (2013), Maonton, Jonathan (2004), Mardia, KV and Jupp, PE (2000, ISBN:9780471953333), Rancourt, D. and Rivest, L.P. and Asselin, J. (2000), Chang, Ted and Rivest, Loui [...truncated...]
Author: Bryan Stanfill [aut, cre], Heike Hofmann [aut], Ulrike Genschel [aut], Aymeric Stamm [ctb] , Luciano Selzer [ctb]
Maintainer: Bryan Stanfill <bstanfill2003@gmail.com>

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Package rnndescent updated to version 0.1.3 with previous version 0.1.1 dated 2023-11-27

Title: Nearest Neighbor Descent Method for Approximate Nearest Neighbors
Description: The Nearest Neighbor Descent method for finding approximate nearest neighbors by Dong and co-workers (2010) <doi:10.1145/1963405.1963487>. Based on the 'Python' package 'PyNNDescent' <https://github.com/lmcinnes/pynndescent>.
Author: James Melville [aut, cre, cph], Vitalie Spinu [ctb]
Maintainer: James Melville <jlmelville@gmail.com>

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Package rBDAT updated to version 1.0.0 with previous version 0.10.0 dated 2022-10-14

Title: Implementation of BDAT Tree Taper Fortran Functions
Description: Implementing the BDAT tree taper Fortran routines, which were developed for the German National Forest Inventory (NFI), to calculate diameters, volume, assortments, double bark thickness and biomass for different tree species based on tree characteristics and sorting information. See Kublin (2003) <doi:10.1046/j.1439-0337.2003.00183.x> for details.
Author: Christian Vonderach [aut, cre], Edgar Kublin [aut], Bernhard Boesch [aut], Gerald Kaendler [aut], Dominik Cullmann [ctb]
Maintainer: Christian Vonderach <christian.vonderach@forst.bwl.de>

Diff between rBDAT versions 0.10.0 dated 2022-10-14 and 1.0.0 dated 2023-12-07

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More information about rBDAT at CRAN
Permanent link

Package matRiks updated to version 0.1.2 with previous version 0.1.1 dated 2023-11-20

Title: Generates Raven-Like Matrices According to Rules
Description: Generates Raven like matrices according to different rules and the response list associated to the matrix. The package can generate matrices composed of 4 or 9 cells, along with a response list of 11 elements (the correct response + 10 incorrect responses). The matrices can be generated according to both logical rules (i.e., the relationships between the elements in the matrix are manipulated to create the matrix) and visual-spatial rules (i.e., the visual or spatial characteristics of the elements are manipulated to generate the matrix). The graphical elements of this package are based on the 'DescTools' package. This package has been developed within the PRIN2020 Project (Prot. 20209WKCLL) titled "Computerized, Adaptive and Personalized Assessment of Executive Functions and Fluid Intelligence" and founded by the Italian Ministry of Education and Research.
Author: Andrea Brancaccio [aut, ctb, cph], Ottavia M. Epifania [aut, ctb, com], Debora de Chiusole [ctb]
Maintainer: Andrea Brancaccio <andrea.brancaccio@unipd.it>

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More information about matRiks at CRAN
Permanent link

Package dparser updated to version 1.3.1-11 with previous version 1.3.1-10 dated 2023-03-16

Title: Port of 'Dparser' Package
Description: A Scannerless GLR parser/parser generator. Note that GLR standing for "generalized LR", where L stands for "left-to-right" and R stands for "rightmost (derivation)". For more information see <https://en.wikipedia.org/wiki/GLR_parser>. This parser is based on the Tomita (1987) algorithm. (Paper can be found at <https://aclanthology.org/P84-1073.pdf>). The original 'dparser' package documentation can be found at <https://dparser.sourceforge.net/>. This allows you to add mini-languages to R (like rxode2's ODE mini-language Wang, Hallow, and James 2015 <DOI:10.1002/psp4.12052>) or to parse other languages like 'NONMEM' to automatically translate them to R code. To use this in your code, add a LinkingTo dparser in your DESCRIPTION file and instead of using #include <dparse.h> use #include <dparser.h>. This also provides a R-based port of the make_dparser <https://dparser.sourceforge.net/d/make_dparser.cat> command called mkdparser(). Addition [...truncated...]
Author: Matthew Fidler [aut, cre], John Plevyak [aut, cph]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

Diff between dparser versions 1.3.1-10 dated 2023-03-16 and 1.3.1-11 dated 2023-12-07

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Permanent link

Package cartogramR updated to version 1.0-10 with previous version 1.0-9 dated 2022-10-18

Title: Continuous Cartogram
Description: Procedures for making continuous cartogram. Procedures available are: flow based cartogram (Gastner & Newman (2004) <doi:10.1073/pnas.0400280101>), fast flow based cartogram (Gastner, Seguy & More (2018) <doi:10.1073/pnas.1712674115>), rubber band based cartogram (Dougenik et al. (1985) <doi:10.1111/j.0033-0124.1985.00075.x>).
Author: Pierre-Andre Cornillon [aut, cre], Florent Demoraes [aut], Flow-Based-Cartograms [cph]
Maintainer: Pierre-Andre Cornillon <pierre-andre.cornillon@univ-rennes2.fr>

Diff between cartogramR versions 1.0-9 dated 2022-10-18 and 1.0-10 dated 2023-12-07

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Permanent link

Package TDApplied updated to version 3.0.0 with previous version 2.0.4 dated 2023-01-25

Title: Machine Learning and Inference for Topological Data Analysis
Description: Topological data analysis is a powerful tool for finding non-linear global structure in whole datasets. The main tool of topological data analysis is persistent homology, which computes a topological shape descriptor of a dataset called a persistence diagram. 'TDApplied' provides useful and efficient methods for analyzing groups of persistence diagrams with machine learning and statistical inference, and these functions can also interface with other data science packages to form flexible and integrated topological data analysis pipelines.
Author: Shael Brown [aut, cre], Dr. Reza Farivar [aut, fnd]
Maintainer: Shael Brown <shaelebrown@gmail.com>

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Package clustermq updated to version 0.9.2 with previous version 0.9.1 dated 2023-11-21

Title: Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque)
Description: Evaluate arbitrary function calls using workers on HPC schedulers in single line of code. All processing is done on the network without accessing the file system. Remote schedulers are supported via SSH.
Author: Michael Schubert [aut, cre, cph] , ZeroMQ authors [aut, cph]
Maintainer: Michael Schubert <mschu.dev@gmail.com>

Diff between clustermq versions 0.9.1 dated 2023-11-21 and 0.9.2 dated 2023-12-07

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 clustermq-0.9.2/clustermq/src/libzmq/src/io_object.cpp                                           |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/io_object.hpp                                           |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/io_thread.cpp                                           |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/io_thread.hpp                                           |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ip.cpp                                                  |   32 
 clustermq-0.9.2/clustermq/src/libzmq/src/ip.hpp                                                  |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ip_resolver.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ipc_address.cpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ipc_address.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ipc_connecter.cpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ipc_connecter.hpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ipc_listener.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ipc_listener.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/kqueue.cpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/kqueue.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/lb.cpp                                                  |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/lb.hpp                                                  |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/likely.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mailbox.cpp                                             |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mailbox.hpp                                             |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mailbox_safe.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mailbox_safe.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mechanism.cpp                                           |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mechanism.hpp                                           |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mechanism_base.cpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mechanism_base.hpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/metadata.cpp                                            |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/metadata.hpp                                            |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/msg.cpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/msg.hpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mtrie.cpp                                               |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mtrie.hpp                                               |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/mutex.hpp                                               |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/norm_engine.cpp                                         |   72 
 clustermq-0.9.2/clustermq/src/libzmq/src/null_mechanism.cpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/null_mechanism.hpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/object.cpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/object.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/options.cpp                                             |  148 
 clustermq-0.9.2/clustermq/src/libzmq/src/options.hpp                                             |   41 
 clustermq-0.9.2/clustermq/src/libzmq/src/own.cpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/own.hpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pair.cpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pair.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/peer.cpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/peer.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pgm_receiver.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pgm_receiver.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pgm_sender.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pgm_sender.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pgm_socket.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pgm_socket.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pipe.cpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pipe.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/plain_client.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/plain_client.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/plain_common.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/plain_server.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/plain_server.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/platform.hpp.in                                         |   12 
 clustermq-0.9.2/clustermq/src/libzmq/src/poll.cpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/poll.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/poller.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/poller_base.cpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/poller_base.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/polling_util.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/polling_util.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pollset.cpp                                             |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pollset.hpp                                             |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/precompiled.cpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/precompiled.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/proxy.cpp                                               |  398 +-
 clustermq-0.9.2/clustermq/src/libzmq/src/proxy.hpp                                               |   38 
 clustermq-0.9.2/clustermq/src/libzmq/src/pub.cpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pub.hpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pull.cpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/pull.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/push.cpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/push.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/radio.cpp                                               |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/radio.hpp                                               |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/radix_tree.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/radix_tree.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/random.cpp                                              |  116 
 clustermq-0.9.2/clustermq/src/libzmq/src/random.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/raw_decoder.cpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/raw_decoder.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/raw_encoder.cpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/raw_encoder.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/raw_engine.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/raw_engine.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/reaper.cpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/reaper.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/rep.cpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/rep.hpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/req.cpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/req.hpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/router.cpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/router.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/scatter.cpp                                             |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/scatter.hpp                                             |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/secure_allocator.hpp                                    |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/select.cpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/select.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/server.cpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/server.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/session_base.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/session_base.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/signaler.cpp                                            |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/signaler.hpp                                            |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/socket_base.cpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/socket_base.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/socket_poller.cpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/socket_poller.hpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/socks.cpp                                               |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/socks.hpp                                               |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/socks_connecter.cpp                                     |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/socks_connecter.hpp                                     |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/stdint.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/stream.cpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/stream.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/stream_connecter_base.cpp                               |   78 
 clustermq-0.9.2/clustermq/src/libzmq/src/stream_connecter_base.hpp                               |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/stream_engine_base.cpp                                  |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/stream_engine_base.hpp                                  |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/stream_listener_base.cpp                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/stream_listener_base.hpp                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/sub.cpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/sub.hpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tcp.cpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tcp.hpp                                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tcp_address.cpp                                         |   31 
 clustermq-0.9.2/clustermq/src/libzmq/src/tcp_address.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tcp_connecter.cpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tcp_connecter.hpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tcp_listener.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tcp_listener.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/thread.cpp                                              |   46 
 clustermq-0.9.2/clustermq/src/libzmq/src/thread.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/timers.cpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/timers.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tipc_address.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tipc_address.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tipc_connecter.cpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tipc_connecter.hpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tipc_listener.cpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/tipc_listener.hpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/trie.cpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/trie.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/udp_address.cpp                                         |   31 
 clustermq-0.9.2/clustermq/src/libzmq/src/udp_address.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/udp_engine.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/v1_decoder.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/v1_decoder.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/v1_encoder.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/v1_encoder.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/v2_decoder.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/v2_decoder.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/v2_encoder.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/v2_encoder.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/v2_protocol.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/v3_1_encoder.cpp                                        |   35 
 clustermq-0.9.2/clustermq/src/libzmq/src/v3_1_encoder.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/vmci.cpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/vmci.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/vmci_address.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/vmci_address.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/vmci_connecter.cpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/vmci_connecter.hpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/vmci_listener.cpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/vmci_listener.hpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/windows.hpp                                             |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/wire.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_address.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_address.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_connecter.cpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_connecter.hpp                                        |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_decoder.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_decoder.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_encoder.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_encoder.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_engine.cpp                                           |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_engine.hpp                                           |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_listener.cpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_listener.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ws_protocol.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/wss_address.cpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/wss_address.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/wss_engine.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/wss_engine.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/xpub.cpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/xpub.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/xsub.cpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/xsub.hpp                                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ypipe.hpp                                               |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ypipe_base.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/ypipe_conflate.hpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/yqueue.hpp                                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/zap_client.cpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/zap_client.hpp                                          |   29 
 clustermq-0.9.2/clustermq/src/libzmq/src/zmq.cpp                                                 |   38 
 clustermq-0.9.2/clustermq/src/libzmq/src/zmq_draft.h                                             |   44 
 clustermq-0.9.2/clustermq/src/libzmq/src/zmq_utils.cpp                                           |   37 
 clustermq-0.9.2/clustermq/src/libzmq/src/zmtp_engine.cpp                                         |   32 
 clustermq-0.9.2/clustermq/src/libzmq/src/zmtp_engine.hpp                                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/CMakeLists.txt                                        |   13 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_abstract_ipc.cpp                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_address_tipc.cpp                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_ancillaries.cpp                                  |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_app_meta.cpp                                     |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_atomics.cpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_base85.cpp                                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_bind_after_connect_tcp.cpp                       |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_bind_curve_fuzzer.cpp                            |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_bind_fuzzer.cpp                                  |   32 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_bind_null_fuzzer.cpp                             |   31 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_bind_src_address.cpp                             |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_bind_stream_fuzzer.cpp                           |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_bind_ws_fuzzer.cpp                               |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_busy_poll.cpp                                    |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_capabilities.cpp                                 |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_channel.cpp                                      |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_client_server.cpp                                |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_conflate.cpp                                     |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_connect_curve_fuzzer.cpp                         |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_connect_delay_tipc.cpp                           |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_connect_fuzzer.cpp                               |   32 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_connect_null_fuzzer.cpp                          |   32 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_connect_resolve.cpp                              |   29 
 clustermq-0.9.2/clustermq/src/libzmq/tests/test_connect_rid.cpp                                  |   29 
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Package TPmsm updated to version 1.2.12 with previous version 1.2.7 dated 2023-01-13

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] , Javier Roca-Pardinas [aut] , Luis Meira-Machado [aut]
Maintainer: Artur Araujo <artur.stat@gmail.com>

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Package RFpredInterval updated to version 1.0.8 with previous version 1.0.7 dated 2023-03-06

Title: Prediction Intervals with Random Forests and Boosted Forests
Description: Implements various prediction interval methods with random forests and boosted forests. The package has two main functions: pibf() produces prediction intervals with boosted forests (PIBF) as described in Alakus et al. (2022) <doi:10.32614/RJ-2022-012> and rfpi() builds 15 distinct variations of prediction intervals with random forests (RFPI) proposed by Roy and Larocque (2020) <doi:10.1177/0962280219829885>.
Author: Cansu Alakus [aut, cre], Denis Larocque [aut], Aurelie Labbe [aut], Hemant Ishwaran [ctb] , Udaya B. Kogalur [ctb]
Maintainer: Cansu Alakus <cansu.alakus@hec.ca>

Diff between RFpredInterval versions 1.0.7 dated 2023-03-06 and 1.0.8 dated 2023-12-07

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Package pcaPP updated to version 2.0-4 with previous version 2.0-3 dated 2022-10-24

Title: Robust PCA by Projection Pursuit
Description: Provides functions for robust PCA by projection pursuit. The methods are described in Croux et al. (2006) <doi:10.2139/ssrn.968376>, Croux et al. (2013) <doi:10.1080/00401706.2012.727746>, Todorov and Filzmoser (2013) <doi:10.1007/978-3-642-33042-1_31>.
Author: Peter Filzmoser, Heinrich Fritz, Klaudius Kalcher
Maintainer: Valentin Todorov <valentin.todorov@chello.at>

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Package tclust updated to version 1.5-5 with previous version 1.5-4 dated 2023-03-24

Title: Robust Trimmed Clustering
Description: Provides functions for robust trimmed clustering. The methods are described in Garcia-Escudero (2008) <doi:10.1214/07-AOS515>, Fritz et al. (2012) <doi:10.18637/jss.v047.i12>, Garcia-Escudero et al. (2011) <doi:10.1007/s11222-010-9194-z> and others.
Author: Agustin Mayo Iscar, Luis Angel Garcia Escudero, Heinrich Fritz
Maintainer: Valentin Todorov <valentin.todorov@chello.at>

Diff between tclust versions 1.5-4 dated 2023-03-24 and 1.5-5 dated 2023-12-07

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Package mmirestriktor updated to version 0.2.0 with previous version 0.1.0 dated 2023-10-12

Title: Informative Hypothesis Testing Web Applications
Description: Offering enhanced statistical power compared to traditional hypothesis testing methods, informative hypothesis testing allows researchers to explicitly model their expectations regarding the relationships among parameters. An important software tool for this framework is 'restriktor'. The 'mmirestriktor' package provides 'shiny' web applications to implement some of the basic functionality of 'restriktor'. The mmirestriktor() function launches a 'shiny' application for fitting and analyzing models with constraints. The FbarCards() function launches a card game application which can help build intuition about informative hypothesis testing. The iht_interpreter() helps interpret informative hypothesis testing results based on guidelines in Vanbrabant and Rosseel (2020) <doi:10.4324/9780429273872-14>.
Author: Mackson Ncube [aut, cre], mightymetrika, LLC [cph, fnd]
Maintainer: Mackson Ncube <macksonncube.stats@gmail.com>

Diff between mmirestriktor versions 0.1.0 dated 2023-10-12 and 0.2.0 dated 2023-12-07

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Package fastmatrix updated to version 0.5-77 with previous version 0.5-7 dated 2023-10-12

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 several procedures), omnibus tests for univariate normality, functions to compute the multivariate skewness, kurtosis, the Mahalanobis distance (checking the positive defineteness), and t [...truncated...]
Author: Felipe Osorio [aut, cre] , Alonso Ogueda [aut]
Maintainer: Felipe Osorio <felipe.osorios@usm.cl>

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Package vctsfr updated to version 0.1.1 with previous version 0.1.0 dated 2023-03-30

Title: Visualizing Collections of Time Series Forecasts
Description: A way of visualizing collections of time series and, optionally their future values, forecasts for their future values and prediction intervals for the forecasts. A web-based GUI can be used to display the information in a collection of time series.
Author: Maria Pilar Frias-Bustamante [aut] , Francisco Martinez [aut, cre, cph]
Maintainer: Francisco Martinez <fmartin@ujaen.es>

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Package lares updated to version 5.2.4 with previous version 5.2.3 dated 2023-11-04

Title: Analytics & Machine Learning Sidekick
Description: Auxiliary package for better/faster analytics, visualization, data mining, and machine learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling, Exploratory, API, and Scrapper, it helps the analyst or data scientist to get quick and robust results, without the need of repetitive coding or extensive R programming skills.
Author: Bernardo Lares [aut, cre]
Maintainer: Bernardo Lares <laresbernardo@gmail.com>

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Package dbarts updated to version 0.9-25 with previous version 0.9-23 dated 2023-01-23

Title: Discrete Bayesian Additive Regression Trees Sampler
Description: Fits Bayesian additive regression trees (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) while allowing the updating of predictors or response so that BART can be incorporated as a conditional model in a Gibbs/Metropolis-Hastings sampler. Also serves as a drop-in replacement for package 'BayesTree'.
Author: Vincent Dorie [aut, cre] , Hugh Chipman [aut], Robert McCulloch [aut], Armon Dadgar [ctb] , R Core Team [ctb] , Guido U Draheim [ctb] , Maarten Bosmans [ctb] , Christophe Tournayre [ctb] , Michael Petch [ctb] , Rafael de Lucena Valle [ctb] , Steven G [...truncated...]
Maintainer: Vincent Dorie <vdorie@gmail.com>

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Package Unicode updated to version 15.1.0-1 with previous version 15.0.0-1 dated 2022-09-30

Title: Unicode Data and Utilities
Description: Data from Unicode 15.1.0 and related utilities.
Author: Kurt Hornik [aut, cre]
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

Diff between Unicode versions 15.0.0-1 dated 2022-09-30 and 15.1.0-1 dated 2023-12-07

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Package traj updated to version 2.0.1 with previous version 2.0.0 dated 2023-12-04

Title: Clustering of Functional Data Based on Measures of Change
Description: Implements the three-step procedure proposed by Leffondree et al. (2004) to identify clusters of individual longitudinal trajectories. The procedure involves (1) calculating a number of measures of change capturing various features of the trajectories; (2) using a Principal Component Analysis based dimension reduction algorithm to select a subset of measures and (3) using the K-means clustering algorithm to identify clusters of trajectories.
Author: Marie-Pierre Sylvestre [aut], Laurence Boulanger [aut, cre], Gillis Delmas Tchouangue Dinkou [ctb], Dan Vatnik [ctb]
Maintainer: Laurence Boulanger <laurence.boulanger@umontreal.ca>

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Package refund updated to version 0.1-34 with previous version 0.1-33 dated 2023-11-14

Title: Regression with Functional Data
Description: Methods for regression for functional data, including function-on-scalar, scalar-on-function, and function-on-function regression. Some of the functions are applicable to image data.
Author: Jeff Goldsmith [aut], Fabian Scheipl [aut], Lei Huang [aut], Julia Wrobel [aut, cre], Chongzhi Di [aut], Jonathan Gellar [aut], Jaroslaw Harezlak [aut], Mathew W. McLean [aut], Bruce Swihart [aut], Luo Xiao [aut], Ciprian Crainiceanu [aut], Philip T. [...truncated...]
Maintainer: Julia Wrobel <julia.wrobel@emory.edu>

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Package PoissonMultinomial updated to version 1.1 with previous version 1.0 dated 2022-01-13

Title: The Poisson-Multinomial Distribution
Description: Implementation of the exact, normal approximation, and simulation-based methods for computing the probability mass function (pmf) and cumulative distribution function (cdf) of the Poisson-Multinomial distribution, together with a random number generator for the distribution. The exact method is based on multi-dimensional fast Fourier transformation (FFT) of the characteristic function of the Poisson-Multinomial distribution. The normal approximation method uses a multivariate normal distribution to approximate the pmf of the distribution based on central limit theorem. The simulation method is based on the law of large numbers. Details about the methods are available in Lin, Wang, and Hong (2022) <DOI:10.1007/s00180-022-01299-0>.
Author: Yili Hong [aut, cre], Zhengzhi Lin [aut, ctb], Yueyao Wang [aut, ctb], Florian Junge [aut, ctb]
Maintainer: Yili Hong <yilihong@vt.edu>

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Package mboost updated to version 2.9-9 with previous version 2.9-8 dated 2023-09-06

Title: Model-Based Boosting
Description: Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data. Models and algorithms are described in <doi:10.1214/07-STS242>, a hands-on tutorial is available from <doi:10.1007/s00180-012-0382-5>. The package allows user-specified loss functions and base-learners.
Author: Torsten Hothorn [cre, aut] , Peter Buehlmann [aut] , Thomas Kneib [aut] , Matthias Schmid [aut] , Benjamin Hofner [aut] , Fabian Otto-Sobotka [ctb] , Fabian Scheipl [ctb] , Andreas Mayr [ctb]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package ISOcodes updated to version 2023.12.07 with previous version 2022.09.29 dated 2022-09-30

Title: Selected ISO Codes
Description: ISO language, territory, currency, script and character codes. Provides ISO 639 language codes, ISO 3166 territory codes, ISO 4217 currency codes, ISO 15924 script codes, and the ISO 8859 character codes as well as the UN M.49 area codes.
Author: Christian Buchta [aut], Kurt Hornik [aut, cre]
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

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Package discFA updated to version 1.0.1 with previous version 1.0.0 dated 2023-12-04

Title: Discrete Factor Analysis
Description: Discrete factor analysis for dependent Poisson and negative binomial models with truncation, zero inflation, and zero inflated truncation.
Author: Yasin Asar [aut] , Reza A. Belaghi [aut, cre] , Rolf Larsson [aut]
Maintainer: Reza A. Belaghi <rezaarabi11@gmail.com>

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Package copula updated to version 1.1-3 with previous version 1.1-2 dated 2023-01-25

Title: Multivariate Dependence with Copulas
Description: Classes (S4) of commonly used elliptical, Archimedean, extreme-value and other copula families, as well as their rotations, mixtures and asymmetrizations. Nested Archimedean copulas, related tools and special functions. Methods for density, distribution, random number generation, bivariate dependence measures, Rosenblatt transform, Kendall distribution function, perspective and contour plots. Fitting of copula models with potentially partly fixed parameters, including standard errors. Serial independence tests, copula specification tests (independence, exchangeability, radial symmetry, extreme-value dependence, goodness-of-fit) and model selection based on cross-validation. Empirical copula, smoothed versions, and non-parametric estimators of the Pickands dependence function.
Author: Marius Hofert [aut] , Ivan Kojadinovic [aut] , Martin Maechler [aut, cre] , Jun Yan [aut] , Johanna G. Neslehova [ctb] , <https://orcid.org/0000-0001-9634-4796>), Rebecca Morger [ctb] : code for free mixCopula weight parameters)
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

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Package skpr updated to version 1.6.1 with previous version 1.4.0 dated 2023-06-16

Title: Design of Experiments Suite: Generate and Evaluate Optimal Designs
Description: Generates and evaluates D, I, A, Alias, E, T, and G optimal designs. Supports generation and evaluation of blocked and split/split-split/.../N-split plot designs. Includes parametric and Monte Carlo power evaluation functions, and supports calculating power for censored responses. Provides a framework to evaluate power using functions provided in other packages or written by the user. Includes a Shiny graphical user interface that displays the underlying code used to create and evaluate the design to improve ease-of-use and make analyses more reproducible. For details, see Morgan-Wall et al. (2021) <doi:10.18637/jss.v099.i01>.
Author: Tyler Morgan-Wall [aut, cre], George Khoury [aut]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

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Package rgraph6 updated to version 2.0-3 with previous version 2.0-2 dated 2022-08-25

Title: Representing Graphs as 'graph6', 'digraph6' or 'sparse6' Strings
Description: Encode network data as strings of printable ASCII characters. Implemented functions include encoding and decoding adjacency matrices, edgelists, igraph, and network objects to/from formats 'graph6', 'sparse6', and 'digraph6'. The formats and methods are described in McKay, B.D. and Piperno, A (2014) <doi:10.1016/j.jsc.2013.09.003>.
Author: Michal Bojanowski [aut, cre] , David Schoch [aut]
Maintainer: Michal Bojanowski <michal2992@gmail.com>

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Package dagitty updated to version 0.3-4 with previous version 0.3-1 dated 2021-01-21

Title: Graphical Analysis of Structural Causal Models
Description: A port of the web-based software 'DAGitty', available at <https://dagitty.net>, for analyzing structural causal models (also known as directed acyclic graphs or DAGs). This package computes covariate adjustment sets for estimating causal effects, enumerates instrumental variables, derives testable implications (d-separation and vanishing tetrads), generates equivalent models, and includes a simple facility for data simulation.
Author: Johannes Textor, Benito van der Zander, Ankur Ankan
Maintainer: Johannes Textor <johannes.textor@gmx.de>

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Package WGCNA updated to version 1.72-5 with previous version 1.72-1 dated 2023-01-18

Title: Weighted Correlation Network Analysis
Description: Functions necessary to perform Weighted Correlation Network Analysis on high-dimensional data as originally described in Horvath and Zhang (2005) <doi:10.2202/1544-6115.1128> and Langfelder and Horvath (2008) <doi:10.1186/1471-2105-9-559>. Includes functions for rudimentary data cleaning, construction of correlation networks, module identification, summarization, and relating of variables and modules to sample traits. Also includes a number of utility functions for data manipulation and visualization.
Author: Peter Langfelder <Peter.Langfelder@gmail.com> and Steve Horvath <SHorvath@mednet.ucla.edu> with contributions by Chaochao Cai, Jun Dong, Jeremy Miller, Lin Song, Andy Yip, and Bin Zhang
Maintainer: Peter Langfelder <Peter.Langfelder@gmail.com>

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Package sMSROC updated to version 0.1.2 with previous version 0.1.1 dated 2023-09-29

Title: Assessment of Diagnostic and Prognostic Markers
Description: Provides estimations of the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) based on the two-stages mixed-subjects ROC curve estimator (Diaz-Coto et al. (2020) <doi:10.1515/ijb-2019-0097> and Diaz-Coto et al. (2020) <doi:10.1080/00949655.2020.1736071>).
Author: Susana Diaz-Coto [aut], Susana Diaz-Coto [cre]
Maintainer: Susana Diaz-Coto <susanacoto@gmail.com>

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Package round updated to version 0.21-0.1 with previous version 0.21-0 dated 2023-10-12

Title: Rounding to Decimal Digits
Description: Decimal rounding is non-trivial in binary arithmetic. ISO standard round to even is more rare than typically assumed as most decimal fractions are not exactly representable in binary. Our 'roundX()' versions explore differences between current and potential future versions of round() in R. Further, provides (some partly related) C99 math lib functions not in base R.
Author: Martin Maechler [aut, cre] , R-core [ctb]
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

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Package lokern updated to version 1.1-10.1 with previous version 1.1-10 dated 2023-02-21

Title: Kernel Regression Smoothing with Local or Global Plug-in Bandwidth
Description: Kernel regression smoothing with adaptive local or global plug-in bandwidth selection.
Author: Eva Herrmann <eherrmann@mathematik.tu-darmstadt.de> ; Packaged for R and enhanced by Martin Maechler
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

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Package codecountR updated to version 0.0.4.0 with previous version 0.0.3.1 dated 2023-09-27

Title: Counting Codes in a Text and Preparing Data for Analysis
Description: Data analysis frequently requires coding, in particular when data are collected by interviews, by observations or even by questionnaires. Therefore, code counting and data preparation are necessary phases to carry out the analysis. Thus, the analysts will wish to count the codes inserted in a text (tokenization and counting of a list of pre-established codes) and to carry out the preparation of the data (feature scaling min-max normalization, Zscore, Box and Cox transformation, non parametric bootstrap). For Box and Cox (1964) <https://www.jstor.org/stable/2984418> transformation, optimal Lambda is calculated by log-likelihood. Non parametric bootstrap is based on randomly sampling data with replacement. Package for educational purposes.
Author: Philippe Cohard [aut, cre]
Maintainer: Philippe Cohard <p.cohard@laposte.net>

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Package gpbStat updated to version 0.4.3 with previous version 0.4.2 dated 2023-10-31

Title: Comprehensive Statistical Analysis of Plant Breeding Experiments
Description: Performs statistical data analysis of various Plant Breeding experiments. Contains functions for Line by Tester analysis as per Arunachalam, V.(1974) <http://repository.ias.ac.in/89299/> and Diallel analysis as per Griffing, B. (1956) <https://www.publish.csiro.au/bi/pdf/BI9560463>.
Author: Nandan Patil [cre, aut] , Lakshmi R. Gangavati [aut, ctb]
Maintainer: Nandan Patil <tryanother609@gmail.com>

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Package tidytransit updated to version 1.6.1 with previous version 1.6.0 dated 2023-06-23

Title: Read, Validate, Analyze, and Map GTFS Feeds
Description: Read General Transit Feed Specification (GTFS) zipfiles into a list of R dataframes. Perform validation of the data structure against the specification. Analyze the headways and frequencies at routes and stops. Create maps and perform spatial analysis on the routes and stops. Please see the GTFS documentation here for more detail: <https://gtfs.org/>.
Author: Flavio Poletti [aut, cre], Daniel Herszenhut [aut] , Mark Padgham [aut], Tom Buckley [aut], Danton Noriega-Goodwin [aut], Angela Li [ctb], Elaine McVey [ctb], Charles Hans Thompson [ctb], Michael Sumner [ctb], Patrick Hausmann [ctb], Bob Rudis [ctb], [...truncated...]
Maintainer: Flavio Poletti <flavio.poletti@hotmail.ch>

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Package lolog updated to version 1.3.1 with previous version 1.3 dated 2021-07-01

Title: Latent Order Logistic Graph Models
Description: Estimation of Latent Order Logistic (LOLOG) Models for Networks. LOLOGs are a flexible and fully general class of statistical graph models. This package provides functions for performing MOM, GMM and variational inference. Visual diagnostics and goodness of fit metrics are provided. See Fellows (2018) <arXiv:1804.04583> for a detailed description of the methods.
Author: Ian E. Fellows [aut, cre], Mark S. Handcock [ctb]
Maintainer: Ian E. Fellows <ian@fellstat.com>

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Package collapse updated to version 2.0.7 with previous version 2.0.6 dated 2023-11-12

Title: Advanced and Fast Data Transformation
Description: A C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, robust and programmer friendly. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), and efficient data manipulation functions. The package also provides a flexible and rigorous approach to time series and panel data in R. It further includes fast functions for common statistical procedures, detailed (grouped, weighted) summary statistics, powerful tools to work with nested data, fast data object conversions, functions for memory efficient R programming, and helpers to effectively deal with variable labels, attributes, and missing data. It is well integrated with base R classes, 'dplyr'/' [...truncated...]
Author: Sebastian Krantz [aut, cre] , Matt Dowle [ctb], Arun Srinivasan [ctb], Morgan Jacob [ctb], Dirk Eddelbuettel [ctb], Laurent Berge [ctb], Kevin Tappe [ctb], R Core Team and contributors worldwide [ctb], Martyn Plummer [cph], 1999-2016 The R Core Team [...truncated...]
Maintainer: Sebastian Krantz <sebastian.krantz@graduateinstitute.ch>

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Package Rtsne updated to version 0.17 with previous version 0.16 dated 2022-04-17

Title: T-Distributed Stochastic Neighbor Embedding using a Barnes-Hut Implementation
Description: An R wrapper around the fast T-distributed Stochastic Neighbor Embedding implementation by Van der Maaten (see <https://github.com/lvdmaaten/bhtsne/> for more information on the original implementation).
Author: Jesse Krijthe [aut, cre], Laurens van der Maaten [cph]
Maintainer: Jesse Krijthe <jkrijthe@gmail.com>

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Package report updated to version 0.5.8 with previous version 0.5.7 dated 2023-03-22

Title: Automated Reporting of Results and Statistical Models
Description: The aim of the 'report' package is to bridge the gap between R’s output and the formatted results contained in your manuscript. This package converts statistical models and data frames into textual reports suited for publication, ensuring standardization and quality in results reporting.
Author: Dominique Makowski [aut] , Daniel Luedecke [aut] , Indrajeet Patil [aut] , Remi Theriault [aut, cre] , Mattan S. Ben-Shachar [aut] , Brenton M. Wiernik [aut] , Rudolf Siegel [ctb] , Camden Bock [ctb]
Maintainer: Remi Theriault <remi.theriault@mail.mcgill.ca>

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Package PWEXP updated to version 0.4.2 with previous version 0.4.1 dated 2023-09-14

Title: Piecewise Exponential Distribution Prediction Model
Description: Build piecewise exponential survival model for study design (planning) and event/timeline prediction.
Author: Tianchen Xu [aut, cre]
Maintainer: Tianchen Xu <zjph602xutianchen@gmail.com>

Diff between PWEXP versions 0.4.1 dated 2023-09-14 and 0.4.2 dated 2023-12-07

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Package mirai updated to version 0.11.3 with previous version 0.11.2 dated 2023-11-15

Title: Minimalist Async Evaluation Framework for R
Description: Lightweight parallel code execution and distributed computing. Designed for simplicity, a 'mirai' evaluates an R expression asynchronously, on local or network resources, resolving automatically upon completion. Efficient scheduling over fast inter-process communications or secure TLS connections over TCP/IP, built on 'nanonext' and 'NNG' (Nanomsg Next Gen).
Author: Charlie Gao [aut, cre] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

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Package DiceDesign updated to version 1.10 with previous version 1.9 dated 2021-02-12

Title: Designs of Computer Experiments
Description: Space-Filling Designs and space-filling criteria (distance-based and uniformity-based), with emphasis to computer experiments; <doi:10.18637/jss.v065.i11>.
Author: Jessica Franco, Delphine Dupuy, Olivier Roustant, Patrice Kiener, Guillaume Damblin and Bertrand Iooss.
Maintainer: Celine Helbert <Celine.Helbert@ec-lyon.fr>

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Package declared updated to version 0.24 with previous version 0.23 dated 2023-10-01

Title: Functions for Declared Missing Values
Description: A zero dependency package containing functions to declare labels and missing values, coupled with associated functions to create (weighted) tables of frequencies and various other summary measures. Some of the base functions have been rewritten to make use of the specific information about the missing values, most importantly to distinguish between empty NA and declared NA values. Some functions have similar functionality with the corresponding ones from packages "haven" and "labelled". The aim is to ensure as much compatibility as possible with these packages, while offering an alternative in the objects of class "declared".
Author: Adrian Dusa [aut, cre, cph] , Daniel Antal [ctb]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package zCompositions updated to version 1.5 with previous version 1.4.1 dated 2023-08-23

Title: Treatment of Zeros, Left-Censored and Missing Values in Compositional Data Sets
Description: Principled methods for the imputation of zeros, left-censored and missing data in compositional data sets (Palarea-Albaladejo and Martin-Fernandez (2015) <doi:10.1016/j.chemolab.2015.02.019>).
Author: Javier Palarea-Albaladejo [cre, aut] , Josep Antoni Martin-Fernandez [aut]
Maintainer: Javier Palarea-Albaladejo <javier.palarea@udg.edu>

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