Tue, 18 Oct 2022

Package QFASA updated to version 1.1.2 with previous version 1.1.1 dated 2021-07-20

Title: Quantitative Fatty Acid Signature Analysis
Description: Accurate estimates of the diets of predators are required in many areas of ecology, but for many species current methods are imprecise, limited to the last meal, and often biased. The diversity of fatty acids and their patterns in organisms, coupled with the narrow limitations on their biosynthesis, properties of digestion in monogastric animals, and the prevalence of large storage reservoirs of lipid in many predators, led to the development of quantitative fatty acid signature analysis (QFASA) to study predator diets.
Author: Connie Stewart [cre, aut, cph], Sara Iverson [aut, cph], Chris Field [aut], Don Bowen [aut], Wade Blanchard [aut], Shelley Lang [aut], Justin Kamerman [aut], Hongchang Bao [ctb], Holly Steeves [aut], Jennifer McNichol [aut], Tyler Rideout [aut]
Maintainer: Connie Stewart <connie.stewart@unb.ca>

Diff between QFASA versions 1.1.1 dated 2021-07-20 and 1.1.2 dated 2022-10-18

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Package networkABC updated to version 0.8-1 with previous version 0.8-0 dated 2021-03-20

Title: Network Reverse Engineering with Approximate Bayesian Computation
Description: We developed an inference tool based on approximate Bayesian computation to decipher network data and assess the strength of the inferred links between network's actors. It is a new multi-level approximate Bayesian computation (ABC) approach. At the first level, the method captures the global properties of the network, such as a scale-free structure and clustering coefficients, whereas the second level is targeted to capture local properties, including the probability of each couple of genes being linked. Up to now, Approximate Bayesian Computation (ABC) algorithms have been scarcely used in that setting and, due to the computational overhead, their application was limited to a small number of genes. On the contrary, our algorithm was made to cope with that issue and has low computational cost. It can be used, for instance, for elucidating gene regulatory network, which is an important step towards understanding the normal cell physiology and complex pathological phenotype. Reverse-eng [...truncated...]
Author: Frederic Bertrand [cre, aut] , Myriam Maumy-Bertrand [aut] , Khadija Musayeva [ctb], Nicolas Jung [ctb], Universite de Strasbourg [cph], CNRS [cph]
Maintainer: Frederic Bertrand <frederic.bertrand@utt.fr>

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Package DT updated to version 0.26 with previous version 0.25 dated 2022-09-12

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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Package tkrplot updated to version 0.0-27 with previous version 0.0-26 dated 2021-10-05

Title: TK Rplot
Description: Simple mechanism for placing R graphics in a Tk widget.
Author: Luke Tierney <luke-tierney@uiowa.edu>
Maintainer: Luke Tierney <luke-tierney@uiowa.edu>

Diff between tkrplot versions 0.0-26 dated 2021-10-05 and 0.0-27 dated 2022-10-18

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Package tidytags updated to version 1.0.3 with previous version 1.0.2 dated 2022-08-23

Title: Importing and Analyzing 'Twitter' Data Collected with 'Twitter Archiving Google Sheets'
Description: The 'tidytags' package coordinates the simplicity of collecting tweets over time with a 'Twitter Archiving Google Sheet' (TAGS; <https://tags.hawksey.info/>) and the utility of the 'rtweet' package (<https://docs.ropensci.org/rtweet/>) for processing and preparing additional 'Twitter' metadata. 'tidytags' also introduces functions developed to facilitate systematic yet flexible analyses of data from 'Twitter'.
Author: K. Bret Staudt Willet [aut, cre] , Joshua M. Rosenberg [aut] , Lluis Revilla Sancho [rev] , Marion Louveaux [rev]
Maintainer: K. Bret Staudt Willet <bret.staudtwillet@fsu.edu>

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Package shrinkTVP updated to version 2.0.6 with previous version 2.0.5 dated 2022-02-03

Title: Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage
Description: Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter models with shrinkage priors. Details on the algorithms used are provided in Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006> and Cadonna et al. (2020) <doi:10.3390/econometrics8020020>. For details on the package, please see Knaus et al. (2021) <doi:10.18637/jss.v100.i13>.
Author: Peter Knaus [aut, cre] , Angela Bitto-Nemling [aut], Annalisa Cadonna [aut] , Sylvia Fruehwirth-Schnatter [aut] , Daniel Winkler [ctb], Kemal Dingic [ctb]
Maintainer: Peter Knaus <peter.knaus@wu.ac.at>

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Package sAIC updated to version 1.0.1 with previous version 1.0 dated 2016-10-05

Title: Akaike Information Criterion for Sparse Estimation
Description: Computes the Akaike information criterion for the generalized linear models (logistic regression, Poisson regression, and Gaussian graphical models) estimated by the lasso.
Author: Shuichi Kawano [aut, cre] , Yoshiyuki Ninomiya [aut]
Maintainer: Shuichi Kawano <skawano@math.kyushu-u.ac.jp>

Diff between sAIC versions 1.0 dated 2016-10-05 and 1.0.1 dated 2022-10-18

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Package rlas updated to version 1.6.1 with previous version 1.6.0 dated 2022-05-26

Title: Read and Write 'las' and 'laz' Binary File Formats Used for Remote Sensing Data
Description: Read and write 'las' and 'laz' binary file formats. The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. The LAS specifications are approved by the American Society for Photogrammetry and Remote Sensing <https://www.asprs.org/divisions-committees/lidar-division/laser-las-file-format-exchange-activities>. The LAZ file format is an open and lossless compression scheme for binary LAS format versions 1.0 to 1.4 <https://laszip.org/>.
Author: Jean-Romain Roussel [aut, cre, cph], Florian De Boissieu [aut, ctb] , Martin Isenburg [cph] , David Auty [ctb] , Pierrick Marie [ctb] , Tiago de Conto [ctb]
Maintainer: Jean-Romain Roussel <jean-romain.roussel.1@ulaval.ca>

Diff between rlas versions 1.6.0 dated 2022-05-26 and 1.6.1 dated 2022-10-18

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Package RcppSimdJson updated to version 0.1.8 with previous version 0.1.7 dated 2022-02-18

Title: 'Rcpp' Bindings for the 'simdjson' Header-Only Library for 'JSON' Parsing
Description: The 'JSON' format is ubiquitous for data interchange, and the 'simdjson' library written by Daniel Lemire (and many contributors) provides a high-performance parser for these files which by relying on parallel 'SIMD' instruction manages to parse these files as faster than disk speed. See the <arXiv:1902.08318> paper for more details about 'simdjson'. This package parses 'JSON' from string, file, or remote URLs under a variety of settings.
Author: Dirk Eddelbuettel, Brendan Knapp, Daniel Lemire
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package np updated to version 0.60-16 with previous version 0.60-15 dated 2022-10-09

Title: Nonparametric Kernel Smoothing Methods for Mixed Data Types
Description: Nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, <https://www.nserc-crsng.gc.ca/>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <https://www.sshrc-crsh.gc.ca/>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <https://sharcnet.ca/>). We would also like to acknowledge the contributions of the GNU GSL authors. In particular, we adapt the GNU GSL B-spline routine gsl_bspline.c adding automated support for quantile knots (in addition to uniform knots), providing missing functionality for derivatives, and for extending the splines beyond their endpoints.
Author: Jeffrey S. Racine [aut, cre], Tristen Hayfield [aut]
Maintainer: Jeffrey S. Racine <racinej@mcmaster.ca>

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Package modeltime.ensemble updated to version 1.0.2 with previous version 1.0.1 dated 2022-06-09

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

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Package mlrCPO updated to version 0.3.7-5 with previous version 0.3.7-4 dated 2022-07-20

Title: Composable Preprocessing Operators and Pipelines for Machine Learning
Description: Toolset that enriches 'mlr' with a diverse set of preprocessing operators. Composable Preprocessing Operators ("CPO"s) are first-class R objects that can be applied to data.frames and 'mlr' "Task"s to modify data, can be attached to 'mlr' "Learner"s to add preprocessing to machine learning algorithms, and can be composed to form preprocessing pipelines.
Author: Martin Binder [aut, cre], Bernd Bischl [ctb], Michel Lang [ctb], Lars Kotthoff [ctb]
Maintainer: Martin Binder <developer.mb706@doublecaret.com>

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Package KoboconnectR updated to version 1.2.1 with previous version 1.2.0 dated 2022-10-16

Title: Download Data from Kobotoolbox to R
Description: Wrapper for 'Kobotoolbox' APIs ver 2 mentioned at <https://support.kobotoolbox.org/api.html>, to download data from 'Kobotoolbox' to R. Small and simple package that adds immense convenience for the data professionals using 'Kobotoolbox'.
Author: Asitav Sen [aut, cre, cph]
Maintainer: Asitav Sen <hello@asitavsen.com>

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Package gridOT updated to version 1.0.1 with previous version 1.0 dated 2022-10-17

Title: Approximate Optimal Transport Between Two-Dimensional Grids
Description: Can be used for optimal transport between two-dimensional grids with respect to separable cost functions of l^p form. It utilizes the Frank-Wolfe algorithm to approximate so-called pivot measures: one-dimensional transport plans that fully describe the full transport, see G. Auricchio (2021) <arXiv:2105.07278>. For these, it offers methods for visualization and to extract the corresponding transport plans and costs. Additionally, related functions for one-dimensional optimal transport are available.
Author: Michel Groppe [aut, cre], Nicholas Bonneel [ctb], Egervary Research Group on Combinatorial Optimization [cph]
Maintainer: Michel Groppe <michel.groppe@stud.uni-goettingen.de>

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Package GA updated to version 3.2.3 with previous version 3.2.2 dated 2021-10-15

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

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Package crs updated to version 0.15-36 with previous version 0.15-35 dated 2022-10-09

Title: Categorical Regression Splines
Description: Regression splines that handle a mix of continuous and categorical (discrete) data often encountered in applied settings. I would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, <https://www.nserc-crsng.gc.ca>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <https://www.sshrc-crsh.gc.ca>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <https://www.sharcnet.ca>). We would also like to acknowledge the contributions of the GNU GSL authors. In particular, we adapt the GNU GSL B-spline routine gsl_bspline.c adding automated support for quantile knots (in addition to uniform knots), providing missing functionality for derivatives, and for extending the splines beyond their endpoints.
Author: Jeffrey S. Racine [aut, cre], Zhenghua Nie [aut], Brian D. Ripley [ctb]
Maintainer: Jeffrey S. Racine <racinej@mcmaster.ca>

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Package bipartite updated to version 2.18 with previous version 2.17 dated 2022-04-20

Title: Visualising Bipartite Networks and Calculating Some (Ecological) Indices
Description: Functions to visualise webs and calculate a series of indices commonly used to describe pattern in (ecological) webs. It focuses on webs consisting of only two levels (bipartite), e.g. pollination webs or predator-prey-webs. Visualisation is important to get an idea of what we are actually looking at, while the indices summarise different aspects of the web's topology.
Author: Carsten F. Dormann [aut, cre] , Jochen Fruend [aut] , Bernd Gruber [aut] , Stephen Beckett [ctb] , Mariano Devoto [ctb] , Gabriel M.F. Felix [ctb] , Jos<e9> M. Iriondo [ctb] , Tore Opsahl [ctb] , Rafael B.P. Pinheiro [ctb] , Rouven Strauss [ctb], Die [...truncated...]
Maintainer: Carsten F. Dormann <carsten.dormann@biom.uni-freiburg.de>

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Package tgp updated to version 2.4-20 with previous version 2.4-19 dated 2022-08-19

Title: Bayesian Treed Gaussian Process Models
Description: Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes (GPs) with jumps to the limiting linear model (LLM). Special cases also implemented include Bayesian linear models, CART, treed linear models, stationary separable and isotropic GPs, and GP single-index models. Provides 1-d and 2-d plotting functions (with projection and slice capabilities) and tree drawing, designed for visualization of tgp-class output. Sensitivity analysis and multi-resolution models are supported. Sequential experimental design and adaptive sampling functions are also provided, including ALM, ALC, and expected improvement. The latter supports derivative-free optimization of noisy black-box functions. For details and tutorials, see Gramacy (2007) <doi:10.18637/jss.v019.i09> and Gramacy & Taddy (2010) <doi:10.18637/jss.v033.i06>.
Author: Robert B. Gramacy <rbg@vt.edu> and Matt A. Taddy
Maintainer: Robert B. Gramacy <rbg@vt.edu>

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Package representr updated to version 0.1.4 with previous version 0.1.3 dated 2022-02-03

Title: Create Representative Records After Entity Resolution
Description: An implementation of Kaplan, Betancourt, Steorts (2022) <doi:10.1080/00031305.2022.2041482> that creates representative records for use in downstream tasks after entity resolution is performed. Multiple methods for creating the representative records (data sets) are provided.
Author: Andee Kaplan [aut, cre], Brenda Betancourt [aut], Rebecca C. Steorts [aut]
Maintainer: Andee Kaplan <andee.kaplan@colostate.edu>

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Package PINstimation updated to version 0.1.1 with previous version 0.1.0 dated 2022-05-27

Title: Estimation of the Probability of Informed Trading
Description: A comprehensive bundle of utilities for the estimation of probability of informed trading models: original PIN in Easley and O'Hara (1992) and Easley et al. (1996); Multilayer PIN (MPIN) in Ersan (2016); Adjusted PIN (AdjPIN) in Duarte and Young (2009); and volume-synchronized PIN (VPIN) in Easley et al. (2011, 2012). Implementations of various estimation methods suggested in the literature are included. Additional compelling features comprise posterior probabilities, an implementation of an expectation-maximization (EM) algorithm, and PIN decomposition into layers, and into bad/good components. Versatile data simulation tools, and trade classification algorithms are among the supplementary utilities. The package provides fast, compact, and precise utilities to tackle the sophisticated, error-prone, and time-consuming estimation procedure of informed trading, and this solely using the raw trade-level data.
Author: Montasser Ghachem [aut, cre, cph] , Oguz Ersan [aut]
Maintainer: Montasser Ghachem <montasser.ghachem@pinstimation.com>

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Package ldsep updated to version 2.1.5 with previous version 2.1.4 dated 2022-02-11

Title: Linkage Disequilibrium Shrinkage Estimation for Polyploids
Description: Estimate haplotypic or composite pairwise linkage disequilibrium (LD) in polyploids, using either genotypes or genotype likelihoods. Support is provided to estimate the popular measures of LD: the LD coefficient D, the standardized LD coefficient D', and the Pearson correlation coefficient r. All estimates are returned with corresponding standard errors. These estimates and standard errors can then be used for shrinkage estimation. The main functions are ldfast(), ldest(), mldest(), sldest(), plot.lddf(), format_lddf(), and ldshrink(). Details of the methods are available in Gerard (2021a) <doi:10.1111/1755-0998.13349> and Gerard (2021b) <doi:10.1038/s41437-021-00462-5>.
Author: David Gerard [aut, cre]
Maintainer: David Gerard <gerard.1787@gmail.com>

Diff between ldsep versions 2.1.4 dated 2022-02-11 and 2.1.5 dated 2022-10-18

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Package IsoplotRgui updated to version 5.1 with previous version 5.0 dated 2022-09-15

Title: Web Interface to 'IsoplotR'
Description: Provides a graphical user interface to the 'IsoplotR' package for radiometric geochronology. The GUI runs in an internet browser and can either be used offline, or hosted on a server to provide online access to the 'IsoplotR' toolbox.
Author: Pieter Vermeesch [aut, cre], Tim Band [ctb]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

Diff between IsoplotRgui versions 5.0 dated 2022-09-15 and 5.1 dated 2022-10-18

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Package xfun updated to version 0.34 with previous version 0.33 dated 2022-09-12

Title: Supporting Functions for Packages Maintained by 'Yihui Xie'
Description: Miscellaneous functions commonly used in other packages maintained by 'Yihui Xie'.
Author: Yihui Xie [aut, cre, cph] , Wush Wu [ctb], Daijiang Li [ctb], Xianying Tan [ctb], Salim Brueggemann [ctb] , Christophe Dervieux [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package bqtl updated to version 1.0-34 with previous version 1.0-33 dated 2021-09-04

Title: Bayesian QTL Mapping Toolkit
Description: QTL mapping toolkit for inbred crosses and recombinant inbred lines. Includes maximum likelihood and Bayesian tools.
Author: Charles C. Berry <cberry@ucsd.edu>
Maintainer: Charles C. Berry <cberry@ucsd.edu>

Diff between bqtl versions 1.0-33 dated 2021-09-04 and 1.0-34 dated 2022-10-18

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Package multimark updated to version 2.1.5 with previous version 2.1.4 dated 2022-03-08

Title: Capture-Mark-Recapture Analysis using Multiple Non-Invasive Marks
Description: Traditional and spatial capture-mark-recapture analysis with multiple non-invasive marks. The models implemented in 'multimark' combine encounter history data arising from two different non-invasive "marks", such as images of left-sided and right-sided pelage patterns of bilaterally asymmetrical species, to estimate abundance and related demographic parameters while accounting for imperfect detection. Bayesian models are specified using simple formulae and fitted using Markov chain Monte Carlo. Addressing deficiencies in currently available software, 'multimark' also provides a user-friendly interface for performing Bayesian multimodel inference using non-spatial or spatial capture-recapture data consisting of a single conventional mark or multiple non-invasive marks. See McClintock (2015) <doi:10.1002/ece3.1676> and Maronde et al. (2020) <doi:10.1002/ece3.6990>.
Author: Brett T. McClintock [aut, cre], Acho Arnold [ctb, cph] , Barry Brown [ctb] , James Lovato [ctb] , John Burkardt [ctb] , Cleve Moler [ctb] , Arjun Gopalaswamy [ctb]
Maintainer: Brett T. McClintock <brett.mcclintock@noaa.gov>

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Package momentuHMM updated to version 1.5.5 with previous version 1.5.4 dated 2021-09-03

Title: Maximum Likelihood Analysis of Animal Movement Behavior Using Multivariate Hidden Markov Models
Description: Extended tools for analyzing telemetry data using generalized hidden Markov models. Features of momentuHMM (pronounced ``momentum'') include data pre-processing and visualization, fitting HMMs to location and auxiliary biotelemetry or environmental data, biased and correlated random walk movement models, hierarchical HMMs, multiple imputation for incorporating location measurement error and missing data, user-specified design matrices and constraints for covariate modelling of parameters, random effects, decoding of the state process, visualization of fitted models, model checking and selection, and simulation. See McClintock and Michelot (2018) <doi:10.1111/2041-210X.12995>.
Author: Brett McClintock, Theo Michelot
Maintainer: Brett McClintock <brett.mcclintock@noaa.gov>

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Package CSHShydRology updated to version 1.2.10 with previous version 1.2.9 dated 2022-09-05

Title: Canadian Hydrological Analyses
Description: A collection of user-submitted functions to aid in the analysis of hydrological data, particularly for users in Canada. The functions focus on the use of Canadian data sets, and are suited to Canadian hydrology, such as the important cold region hydrological processes and will work with Canadian hydrological models. The functions are grouped into several themes, currently including Statistical hydrology, Basic data manipulations, Visualization, and Spatial hydrology. Functions developed by the Floodnet project are also included. CSHShydRology has been developed with the assistance of the Canadian Society for Hydrological Sciences (CSHS) which is an affiliated society of the Canadian Water Resources Association (CWRA). As of version 1.2.6, functions now fail gracefully when attempting to download data from a url which is unavailable.
Author: Kevin Shook [cre, aut], Paul Whitfield [aut], Robert Chlumsky [aut], Daniel Moore [aut], Martin Durocher [aut], Matthew Lemieux [ctb], Jason Chiang [ctb], Joel Trubilowicz [ctb], SJ Kim [ctb]
Maintainer: Kevin Shook <kevin.shook@usask.ca>

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Package CDatanet updated to version 2.0.1 with previous version 1.0.1 dated 2022-04-05

Title: Modeling Count Data with Peer Effects
Description: Likelihood-based estimation and data generation from a class of models used to estimate peer effects on count data by controlling for the network endogeneity. This class includes count data models with social interactions (Houndetoungan 2022; <doi:10.2139/ssrn.3721250>), spatial tobit models (Xu and Lee 2015; <doi:10.1016/j.jeconom.2015.05.004>), and spatial linear-in-means models (Lee 2004; <doi:10.1111/j.1468-0262.2004.00558.x>).
Author: Elysee Aristide Houndetoungan [cre, aut]
Maintainer: Elysee Aristide Houndetoungan <ariel92and@gmail.com>

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Package backbone updated to version 2.1.1 with previous version 2.1.0 dated 2022-06-01

Title: Extracts the Backbone from Graphs
Description: An implementation of methods for extracting an unweighted unipartite graph (i.e. a backbone) from an unweighted unipartite graph, a weighted unipartite graph, the projection of an unweighted bipartite graph , or the projection of a weighted bipartite graph (Neal, 2022 <doi:10.1371/journal.pone.0269137>).
Author: Zachary Neal [aut, cre] , Rachel Domagalski [aut], Bruce Sagan [aut], Karl Godard [ctb]
Maintainer: Zachary Neal <zpneal@msu.edu>

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Package IsoplotR updated to version 5.1 with previous version 5.0 dated 2022-09-15

Title: Statistical Toolbox for Radiometric Geochronology
Description: Plots U-Pb data on Wetherill and Tera-Wasserburg concordia diagrams. Calculates concordia and discordia ages. Performs linear regression of measurements with correlated errors using 'York', 'Titterington' and 'Ludwig' approaches. Generates Kernel Density Estimates (KDEs) and Cumulative Age Distributions (CADs). Produces Multidimensional Scaling (MDS) configurations and Shepard plots of multi-sample detrital datasets using the Kolmogorov-Smirnov distance as a dissimilarity measure. Calculates 40Ar/39Ar ages, isochrons, and age spectra. Computes weighted means accounting for overdispersion. Calculates U-Th-He (single grain and central) ages, logratio plots and ternary diagrams. Processes fission track data using the external detector method and LA-ICP-MS, calculates central ages and plots fission track and other data on radial (a.k.a. 'Galbraith') plots. Constructs total Pb-U, Pb-Pb, Th-Pb, K-Ca, Re-Os, Sm-Nd, Lu-Hf, Rb-Sr and 230Th-U isochrons as well as 230Th-U evolution plots.
Author: Pieter Vermeesch [aut, cre]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

Diff between IsoplotR versions 5.0 dated 2022-09-15 and 5.1 dated 2022-10-18

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Package Ease updated to version 0.1.1 with previous version 0.1.0 dated 2022-09-19

Title: Simulating Explicit Population Genetics Models
Description: Implementation in a simple and efficient way of fully customisable population genetics simulations, considering multiple loci that have epistatic interactions. Specifically suited to the modelling of multilocus nucleocytoplasmic systems (with both diploid and haploid loci), it is nevertheless possible to simulate purely diploid (or purely haploid) genetic models. Examples of models that can be simulated with Ease are numerous, for example models of genetic incompatibilities as presented by Marie-Orleach et al. (2022) <doi:10.1101/2022.07.25.501356>. Many others are conceivable, although few are actually explored, Ease having been developed in particular to provide a solution so that these kinds of models can be simulated simply.
Author: Ehouarn Le Faou <ehouarnlefaou@orange.fr> [aut, cre]
Maintainer: Ehouarn Le Faou <ehouarnlefaou@orange.fr>

Diff between Ease versions 0.1.0 dated 2022-09-19 and 0.1.1 dated 2022-10-18

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Package cartogramR updated to version 1.0-9 with previous version 1.0-8 dated 2022-07-18

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 1.0-8 dated 2022-07-18 and 1.0-9 dated 2022-10-18

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Package n1qn1 updated to version 6.0.1-11 with previous version 6.0.1-10 dated 2020-11-17

Title: Port of the 'Scilab' 'n1qn1' Module for Unconstrained BFGS Optimization
Description: Provides 'Scilab' 'n1qn1'. This takes more memory than traditional L-BFGS. The n1qn1 routine is useful since it allows prespecification of a Hessian. If the Hessian is near enough the truth in optimization it can speed up the optimization problem. The algorithm is described in the 'Scilab' optimization documentation located at <https://www.scilab.org/sites/default/files/optimization_in_scilab.pdf>. This version uses manually modified code from 'f2c' to make this a C only binary.
Author: Matthew Fidler [aut, cre], Wenping Wang [aut], Claude Lemarechal [aut, ctb], Joseph Bonnans [ctb], Jean-Charles Gilbert [ctb], Claudia Sagastizabal [ctb], Stephen L. Campbell, [ctb], Jean-Philippe Chancelier [ctb], Ramine Nikoukhah [ctb], Dirk Eddelb [...truncated...]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

Diff between n1qn1 versions 6.0.1-10 dated 2020-11-17 and 6.0.1-11 dated 2022-10-18

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Package gtreg updated to version 0.2.0 with previous version 0.1.1 dated 2022-08-17

Title: Regulatory Tables for Clinical Research
Description: Creates tables suitable for regulatory agency submission by leveraging the 'gtsummary' package as the back end. Tables can be exported to HTML, Word, PDF and more. Highly customized outputs are available by utilizing existing styling functions from 'gtsummary' as well as custom options designed for regulatory tables.
Author: Shannon Pileggi [aut, cre, cph] , Daniel D. Sjoberg [aut]
Maintainer: Shannon Pileggi <shannon.pileggi@gmail.com>

Diff between gtreg versions 0.1.1 dated 2022-08-17 and 0.2.0 dated 2022-10-18

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Package shinylight updated to version 1.0.0 with previous version 0.7 dated 2022-09-01

Title: Web Interface to 'R' Functions
Description: Web front end for your 'R' functions producing plots or tables. If you have a function or set of related functions, you can make them available over the internet through a web browser. This is the same motivation as the 'shiny' package, but note that the development of 'shinylight' is not in any way linked to that of 'shiny' (beyond the use of the 'httpuv' package). You might prefer 'shinylight' to 'shiny' if you want a lighter weight deployment with easier horizontal scaling, or if you want to develop your front end yourself in JavaScript and HTML just using a lightweight remote procedure call interface to your R code on the server.
Author: Pieter Vermeesch [aut], Tim Band [aut, cre]
Maintainer: Tim Band <t.band@ucl.ac.uk>

Diff between shinylight versions 0.7 dated 2022-09-01 and 1.0.0 dated 2022-10-18

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Package Rmixmod updated to version 2.1.7 with previous version 2.1.6 dated 2021-11-24

Title: Classification with Mixture Modelling
Description: Interface of 'MIXMOD' software for supervised, unsupervised and semi-supervised classification with mixture modelling <doi: 10.18637/jss.v067.i06>.
Author: Florent Langrognet [aut], Remi Lebret [aut], Christian Poli [aut], Serge Iovleff [aut], Benjamin Auder [aut], Parmeet Bhatia [ctb], Anwuli Echenim [ctb], Serge Iovleff [aut], Christophe Biernacki [ctb], Gilles Celeux [ctb], Gerard Govaert [ctb], Quen [...truncated...]
Maintainer: Quentin Grimonprez <quentingrim@yahoo.fr>

Diff between Rmixmod versions 2.1.6 dated 2021-11-24 and 2.1.7 dated 2022-10-18

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Package ParBayesianOptimization updated to version 1.2.6 with previous version 1.2.4 dated 2021-02-11

Title: Parallel Bayesian Optimization of Hyperparameters
Description: Fast, flexible framework for implementing Bayesian optimization of model hyperparameters according to the methods described in Snoek et al. <arXiv:1206.2944>. The package allows the user to run scoring function in parallel, save intermediary results, and tweak other aspects of the process to fully utilize the computing resources available to the user.
Author: Samuel Wilson [aut, cre]
Maintainer: Samuel Wilson <samwilson303@gmail.com>

Diff between ParBayesianOptimization versions 1.2.4 dated 2021-02-11 and 1.2.6 dated 2022-10-18

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Package MLEcens updated to version 0.1-7 with previous version 0.1-5 dated 2022-03-31

Title: Computation of the MLE for Bivariate Interval Censored Data
Description: We provide functions to compute the nonparametric maximum likelihood estimator (MLE) for the bivariate distribution of (X,Y), when realizations of (X,Y) cannot be observed directly. To be more precise, we consider the situation where we observe a set of rectangles in R^2 that are known to contain the unobservable realizations of (X,Y). We compute the MLE based on such a set of rectangles. The methods can also be used for univariate censored data (see data set 'cosmesis'), and for censored data with competing risks (see data set 'menopause'). We also provide functions to visualize the observed data and the MLE.
Author: Marloes Maathuis [aut, cre]
Maintainer: Marloes Maathuis <marloesmaathuis@gmail.com>

Diff between MLEcens versions 0.1-5 dated 2022-03-31 and 0.1-7 dated 2022-10-18

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Package Runuran updated to version 0.37 with previous version 0.36 dated 2022-05-05

Title: R Interface to the 'UNU.RAN' Random Variate Generators
Description: Interface to the 'UNU.RAN' library for Universal Non-Uniform RANdom variate generators. Thus it allows to build non-uniform random number generators from quite arbitrary distributions. In particular, it provides an algorithm for fast numerical inversion for distribution with given density function. In addition, the package contains densities, distribution functions and quantiles from a couple of distributions.
Author: Josef Leydold [aut, cre], Wolfgang H"ormann [aut]
Maintainer: Josef Leydold <josef.leydold@wu.ac.at>

Diff between Runuran versions 0.36 dated 2022-05-05 and 0.37 dated 2022-10-18

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Package RAppArmor updated to version 3.2.3 with previous version 3.2.2 dated 2020-12-11

Title: Bindings to AppArmor and Security Related Linux Tools
Description: Bindings to kernel methods for enforcing security restrictions. AppArmor can apply mandatory access control (MAC) policies on a given task (process) via security profiles with detailed ACL definitions. In addition this package implements bindings for setting process resource limits (rlimit), uid, gid, affinity and priority. The high level R function 'eval.secure' builds on these methods to perform dynamic sandboxing: it evaluates a single R expression within a temporary fork which acts as a sandbox by enforcing fine grained restrictions without affecting the main R process. A portable version of this function is now available in the 'unix' package.
Author: Jeroen Ooms [aut, cre]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between RAppArmor versions 3.2.2 dated 2020-12-11 and 3.2.3 dated 2022-10-18

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Package PRECAST updated to version 1.3 with previous version 1.2 dated 2022-07-11

Title: Embedding and Clustering with Alignment for Spatial Datasets
Description: An efficient data integration method is provided for multiple spatial transcriptomics data with non-cluster-relevant effects such as the complex batch effects. It unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, requiring only partially shared cell/domain clusters across datasets. More details can be referred to Wei Liu, et al. (2022) <doi:10.1101/2022.06.26.497672>.
Author: Wei Liu [aut, cre], Yi Yang [aut], Jin Liu [aut]
Maintainer: Wei Liu <wei.liu@duke-nus.edu.sg>

Diff between PRECAST versions 1.2 dated 2022-07-11 and 1.3 dated 2022-10-18

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Package breakfast updated to version 2.3 with previous version 2.2 dated 2021-06-11

Title: Methods for Fast Multiple Change-Point Detection and Estimation
Description: A developing software suite for multiple change-point detection/estimation (data segmentation) in data sequences.
Author: Andreas Anastasiou [aut], Yining Chen [aut, cre], Haeran Cho [aut], Piotr Fryzlewicz [aut]
Maintainer: Yining Chen <y.chen101@lse.ac.uk>

Diff between breakfast versions 2.2 dated 2021-06-11 and 2.3 dated 2022-10-18

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Package unix updated to version 1.5.5 with previous version 1.5.4 dated 2021-11-16

Title: POSIX System Utilities
Description: Bindings to system utilities found in most Unix systems such as POSIX functions which are not part of the Standard C Library.
Author: Jeroen Ooms [aut, cre]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between unix versions 1.5.4 dated 2021-11-16 and 1.5.5 dated 2022-10-18

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Package sys updated to version 3.4.1 with previous version 3.4 dated 2020-07-23

Title: Powerful and Reliable Tools for Running System Commands in R
Description: Drop-in replacements for the base system2() function with fine control and consistent behavior across platforms. Supports clean interruption, timeout, background tasks, and streaming STDIN / STDOUT / STDERR over binary or text connections. Arguments on Windows automatically get encoded and quoted to work on different locales.
Author: Jeroen Ooms [aut, cre] , Gabor Csardi [ctb]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between sys versions 3.4 dated 2020-07-23 and 3.4.1 dated 2022-10-18

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Package stfit updated to version 0.99.9 with previous version 0.99.8 dated 2020-10-02

Title: Spatio-Temporal Functional Imputation Tool
Description: A general spatiotemporal satellite image imputation method based on sparse functional data analytic techniques. The imputation method applies and extends the Functional Principal Analysis by Conditional Estimation (PACE). The underlying idea for the proposed procedure is to impute a missing pixel by borrowing information from temporally and spatially contiguous pixels based on the best linear unbiased prediction.
Author: Weicheng Zhu [aut, cre]
Maintainer: Weicheng Zhu <mingsnu@gmail.com>

Diff between stfit versions 0.99.8 dated 2020-10-02 and 0.99.9 dated 2022-10-18

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New package PolygonSoup with initial version 1.0.0
Package: PolygonSoup
Title: Mesh from Polygon Soup
Version: 1.0.0
Maintainer: Stephane Laurent <laurent_step@outlook.fr>
Description: Allows to get a consistent 3D mesh from a polygon soup, that is an unorganized set of polygons. The mesh can be triangulated and its exterior edges are computed.
License: GPL-3
URL: https://github.com/stla/PolygonSoup
BugReports: https://github.com/stla/PolygonSoup/issues
Depends: R (>= 2.10)
Imports: data.table, gmp, Rcpp (>= 1.0.9), rgl
Suggests: misc3d
LinkingTo: BH, Rcpp, RcppCGAL, RcppEigen
Encoding: UTF-8
LazyData: true
SystemRequirements: C++ 14, gmp, mpfr
NeedsCompilation: yes
Packaged: 2022-10-18 07:34:25 UTC; stla
Author: Stephane Laurent [aut, cre]
Repository: CRAN
Date/Publication: 2022-10-18 12:17:55 UTC

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Package mSimCC updated to version 0.0.2 with previous version 0.0.1 dated 2019-06-03

Title: Micro Simulation Model for Cervical Cancer Prevention
Description: Micro simulation model to reproduce natural history of cervical cancer and cost-effectiveness evaluation of prevention strategies. See Georgalis L, de Sanjose S, Esnaola M, Bosch F X, Diaz M (2016) <doi:10.1097/CEJ.0000000000000202> for more details.
Author: David Morina , Pedro Puig and Mireia Diaz
Maintainer: David Morina Soler <dmorina@ub.edu>

Diff between mSimCC versions 0.0.1 dated 2019-06-03 and 0.0.2 dated 2022-10-18

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Package modeltime updated to version 1.2.3 with previous version 1.2.2 dated 2022-06-07

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

Diff between modeltime versions 1.2.2 dated 2022-06-07 and 1.2.3 dated 2022-10-18

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Package mmrm updated to version 0.1.5 with previous version 0.1.3 dated 2022-10-18

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 and Schnell (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 adjusted degrees of freedom, 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], Ya Wang [aut], Craig Gower-Page [ctb], Boehringer Ingelheim Ltd. [cph, fnd], Gilead Sciences, Inc. [cph, fnd], F. [...truncated...]
Maintainer: Daniel Sabanes Bove <daniel.sabanes_bove@roche.com>

Diff between mmrm versions 0.1.3 dated 2022-10-18 and 0.1.5 dated 2022-10-18

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Package kdevine updated to version 0.4.4 with previous version 0.4.3 dated 2021-05-11

Title: Multivariate Kernel Density Estimation with Vine Copulas
Description: Implements the vine copula based kernel density estimator of Nagler and Czado (2016) <doi:10.1016/j.jmva.2016.07.003>. The estimator does not suffer from the curse of dimensionality and is therefore well suited for high-dimensional applications.
Author: Thomas Nagler [aut, cre]
Maintainer: Thomas Nagler <mail@tnagler.com>

Diff between kdevine versions 0.4.3 dated 2021-05-11 and 0.4.4 dated 2022-10-18

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New package linkedInadsR with initial version 0.1.0
Package: linkedInadsR
Title: Access to 'LinkedIn' Ads via the 'Windsor.ai' API
Version: 0.1.0
Description: Collect marketing data from 'LinkedIn' Ads using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.
License: GPL-3
URL: https://windsor.ai/
Depends: R (>= 3.5.0)
Imports: jsonlite (>= 1.7.2)
Suggests: knitr, rmarkdown, dplyr, ggplot2, tidyr, curl
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2022-10-14 14:17:34 UTC; pablo
Author: Pablo Sanchez [cre, aut], Windsor.ai [cph]
Maintainer: Pablo Sanchez <pablosama@outlook.es>
Repository: CRAN
Date/Publication: 2022-10-18 12:00:02 UTC

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New package FunctanSNP with initial version 0.1.0
Package: FunctanSNP
Title: Functional Analysis (with Interactions) for Dense SNP Data
Version: 0.1.0
Maintainer: Rui Ren <xmurr@stu.xmu.edu.cn>
Description: An implementation of revised functional regression models for multiple genetic variation data, such as single nucleotide polymorphism (SNP) data, which provides revised functional linear regression models, partially functional interaction regression analysis with penalty-based techniques and corresponding drawing functions, etc.(Ruzong Fan, Yifan Wang, James L. Mills, Alexander F. Wilson, Joan E. Bailey-Wilson, and Momiao Xiong (2013) <doi:10.1002/gepi.21757>).
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: caret, glmnet, lava, MASS, stats, fda, funData, graphics
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-10-18 09:02:10 UTC; renrui
Author: Rui Ren [aut, cre], Kuangnan Fang [aut], Qingzhao Zhang [aut], Shuangge Ma [aut]
Repository: CRAN
Date/Publication: 2022-10-18 12:28:03 UTC

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Package EMMIXSSL updated to version 1.1.1 with previous version 1.1.0 dated 2022-02-08

Title: Semi-Supervised Gaussian Mixture Model with a Missing-Data Mechanism
Description: The algorithm of semi-supervised learning based on finite Gaussian mixture models with a missing-data mechanism is designed for a fitting g-class Gaussian mixture model via maximum likelihood (ML). It is proposed to treat the labels of the unclassified features as missing-data and to introduce a framework for their missing as in the pioneering work of Rubin (1976) for missing in incomplete data analysis. This dependency in the missingness pattern can be leveraged to provide additional information about the optimal classifier as specified by Bayes’ rule.
Author: Ziyang Lyu, Daniel Ahfock, Geoffrey J. McLachlan
Maintainer: Ziyang Lyu <ziyang.lyu@unsw.edu.au>

Diff between EMMIXSSL versions 1.1.0 dated 2022-02-08 and 1.1.1 dated 2022-10-18

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Package jsmodule updated to version 1.3.3 with previous version 1.3.2 dated 2022-09-12

Title: 'RStudio' Addins and 'Shiny' Modules for Medical Research
Description: 'RStudio' addins and 'Shiny' modules for descriptive statistics, regression and survival analysis.
Author: Jinseob Kim [aut, cre] , Zarathu [cph, fnd], Hyunki Lee [aut], Changwoo Lim [aut]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

Diff between jsmodule versions 1.3.2 dated 2022-09-12 and 1.3.3 dated 2022-10-18

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Package writexl updated to version 1.4.1 with previous version 1.4.0 dated 2021-04-20

Title: Export Data Frames to Excel 'xlsx' Format
Description: Zero-dependency data frame to xlsx exporter based on 'libxlsxwriter'. Fast and no Java or Excel required.
Author: Jeroen Ooms [aut, cre] , John McNamara [cph] )
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between writexl versions 1.4.0 dated 2021-04-20 and 1.4.1 dated 2022-10-18

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Package ssh updated to version 0.8.2 with previous version 0.8.1 dated 2022-09-24

Title: Secure Shell (SSH) Client for R
Description: Connect to a remote server over SSH to transfer files via SCP, setup a secure tunnel, or run a command or script on the host while streaming stdout and stderr directly to the client.
Author: Jeroen Ooms [aut, cre]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between ssh versions 0.8.1 dated 2022-09-24 and 0.8.2 dated 2022-10-18

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Package scuba updated to version 1.11-1 with previous version 1.11-0 dated 2021-05-14

Title: Diving Calculations and Decompression Models
Description: Code for describing and manipulating scuba diving profiles (depth-time curves) and decompression models, for calculating the predictions of decompression models, for calculating maximum no-decompression time and decompression tables, and for performing mixed gas calculations.
Author: Adrian Baddeley [aut, cre], Vittorio Broglio [ctb, dtc], Pedro Antonio Neves [ctb, dtc], Andrew Bassom [ctb], Peter Buzzacott [ctb], Aren Leishman [ctb]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

Diff between scuba versions 1.11-0 dated 2021-05-14 and 1.11-1 dated 2022-10-18

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Package rsvg updated to version 2.3.2 with previous version 2.3.1 dated 2022-04-20

Title: Render SVG Images into PDF, PNG, (Encapsulated) PostScript, or Bitmap Arrays
Description: Renders vector-based svg images into high-quality custom-size bitmap arrays using 'librsvg2'. The resulting bitmap can be written to e.g. png, jpeg or webp format. In addition, the package can convert images directly to various formats such as pdf or postscript.
Author: Jeroen Ooms [aut, cre] , Salim Brueggemann [ctb]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between rsvg versions 2.3.1 dated 2022-04-20 and 2.3.2 dated 2022-10-18

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Package RMySQL updated to version 0.10.24 with previous version 0.10.23 dated 2021-12-14

Title: Database Interface and 'MySQL' Driver for R
Description: Legacy 'DBI' interface to 'MySQL' / 'MariaDB' based on old code ported from S-PLUS. A modern 'MySQL' client based on 'Rcpp' is available from the 'RMariaDB' package.
Author: Jeroen Ooms [aut, cre] , David James [aut], Saikat DebRoy [aut], Hadley Wickham [aut], Jeffrey Horner [aut], RStudio [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between RMySQL versions 0.10.23 dated 2021-12-14 and 0.10.24 dated 2022-10-18

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Package date updated to version 1.2-40 with previous version 1.2-39 dated 2020-02-05

Title: Functions for Handling Dates
Description: Functions for handling dates.
Author: Terry Therneau [aut], Thomas Lumley [trl] , Kjetil Halvorsen [trl] , Kurt Hornik [trl, ctb, cre] , R Core Team [ctb]
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

Diff between date versions 1.2-39 dated 2020-02-05 and 1.2-40 dated 2022-10-18

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Package yaml updated to version 2.3.6 with previous version 2.3.5 dated 2022-02-21

Title: Methods to Convert R Data to YAML and Back
Description: Implements the 'libyaml' 'YAML' 1.1 parser and emitter (<https://pyyaml.org/wiki/LibYAML>) for R.
Author: Shawn P Garbett [aut], Jeremy Stephens [aut, cre], Kirill Simonov [aut], Yihui Xie [ctb], Zhuoer Dong [ctb], Hadley Wickham [ctb], Jeffrey Horner [ctb], reikoch [ctb], Will Beasley [ctb], Brendan O'Connor [ctb], Gregory R. Warnes [ctb], Michael Quinn [...truncated...]
Maintainer: Shawn Garbett <shawn.garbett@vumc.org>

Diff between yaml versions 2.3.5 dated 2022-02-21 and 2.3.6 dated 2022-10-18

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More information about yaml at CRAN
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Package updog updated to version 2.1.3 with previous version 2.1.2 dated 2022-01-24

Title: Flexible Genotyping for Polyploids
Description: Implements empirical Bayes approaches to genotype polyploids from next generation sequencing data while accounting for allele bias, overdispersion, and sequencing error. The main functions are flexdog() and multidog(), which allow the specification of many different genotype distributions. Also provided are functions to simulate genotypes, rgeno(), and read-counts, rflexdog(), as well as functions to calculate oracle genotyping error rates, oracle_mis(), and correlation with the true genotypes, oracle_cor(). These latter two functions are useful for read depth calculations. Run browseVignettes(package = "updog") in R for example usage. See Gerard et al. (2018) <doi:10.1534/genetics.118.301468> and Gerard and Ferrao (2020) <doi:10.1093/bioinformatics/btz852> for details on the implemented methods.
Author: David Gerard [aut, cre]
Maintainer: David Gerard <gerard.1787@gmail.com>

Diff between updog versions 2.1.2 dated 2022-01-24 and 2.1.3 dated 2022-10-18

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Package unrtf updated to version 1.4.2 with previous version 1.4.1 dated 2021-12-09

Title: Extract Text from Rich Text Format (RTF) Documents
Description: Wraps the 'unrtf' utility to extract text from RTF files. Supports document conversion to HTML, LaTeX or plain text. Output in HTML is recommended because 'unrtf' has limited support for converting between character encodings.
Author: Jeroen Ooms [aut, cre], Free Software Foundation, Inc [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between unrtf versions 1.4.1 dated 2021-12-09 and 1.4.2 dated 2022-10-18

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Package soilDB updated to version 2.7.5 with previous version 2.7.4 dated 2022-09-30

Title: Soil Database Interface
Description: A collection of functions for reading data from USDA-NCSS soil databases.
Author: Dylan Beaudette [aut], Jay Skovlin [aut], Stephen Roecker [aut], Andrew Brown [aut, cre]
Maintainer: Andrew Brown <andrew.g.brown@usda.gov>

Diff between soilDB versions 2.7.4 dated 2022-09-30 and 2.7.5 dated 2022-10-18

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Package Pursuit updated to version 1.0.3 with previous version 1.0.2 dated 2021-01-10

Title: Projection Pursuit
Description: Package for projection pursuit (PP) with 17 methods and grand tour with 3 methods. Being that projection pursuit searches for low-dimensional linear projections in high-dimensional data structures, while grand tour is a technique used to explore multivariate statistical data through animation.
Author: Paulo Cesar Ossani <ossanipc@hotmail.com> Marcelo Angelo Cirillo <macufla@des.ufla.br>
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>

Diff between Pursuit versions 1.0.2 dated 2021-01-10 and 1.0.3 dated 2022-10-18

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Package lsirm12pl updated to version 1.1.0 with previous version 1.0.2 dated 2022-10-11

Title: Latent Space Item Response Model
Description: Analysis of dichotomous and continuous response data using latent factor by both 1PL LSIRM and 2PL LSIRM as described in Jeon et al. (2021) <doi:10.1007/s11336-021-09762-5>. It includes original 1PL LSIRM and 2PL LSIRM provided for binary response data and its extension for continuous response data. Bayesian model selection with spike-and-slab prior and method for dealing data with missing value under missing at random, missing completely at random are also supported. Various diagnostic plots are available to inspect the latent space and summary of estimated parameters.
Author: Dongyoung Go [aut], Gwanghee Kim [aut], Jina Park [aut, cre], Ickhoon Jin [ctb], Minjeong Jeon [ctb]
Maintainer: Jina Park <pja0707@yonsei.ac.kr>

Diff between lsirm12pl versions 1.0.2 dated 2022-10-11 and 1.1.0 dated 2022-10-18

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Package image.dlib updated to version 0.1.1 with previous version 0.1.0 dated 2020-07-27

Title: Image Processing Functionality using the 'dlib' Package
Description: Facility wrappers around the image processing functionality of 'dlib'. 'Dlib' <http://dlib.net> is a 'C++' toolkit containing machine learning algorithms and computer vision tools. Currently the package allows to find feature descriptors of digital images, in particular 'SURF' and 'HOG' descriptors.
Author: Jan Wijffels [aut, cre, cph] , BNOSAC [cph] , Davis E. King [ctb, cph] , dlib authors [ctb, cph]
Maintainer: Jan Wijffels <jwijffels@bnosac.be>

Diff between image.dlib versions 0.1.0 dated 2020-07-27 and 0.1.1 dated 2022-10-18

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 inst/dlib-19.20/dlib/assert.h                                                            |  434 
 inst/dlib-19.20/dlib/base64.h                                                            |   18 
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 inst/dlib-19.20/dlib/cmd_line_parser/cmd_line_parser_print_1.h                           |  410 
 inst/dlib-19.20/dlib/cmd_line_parser/get_option.h                                        |  362 
 inst/dlib-19.20/dlib/cmd_line_parser/get_option_abstract.h                               |  292 
 inst/dlib-19.20/dlib/config.h                                                            |   62 
 inst/dlib-19.20/dlib/config_reader.h                                                     |   78 
 inst/dlib-19.20/dlib/config_reader/config_reader_kernel_1.h                              | 1476 -
 inst/dlib-19.20/dlib/config_reader/config_reader_kernel_abstract.h                       |  726 
 inst/dlib-19.20/dlib/config_reader/config_reader_thread_safe_1.h                         |  912 
 inst/dlib-19.20/dlib/config_reader/config_reader_thread_safe_abstract.h                  |   90 
 inst/dlib-19.20/dlib/console_progress_indicator.h                                        |  414 
 inst/dlib-19.20/dlib/dir_nav.h                                                           |   42 
 inst/dlib-19.20/dlib/dir_nav/dir_nav_extensions.cpp                                      |  242 
 inst/dlib-19.20/dlib/dir_nav/dir_nav_extensions.h                                        |  344 
 inst/dlib-19.20/dlib/dir_nav/dir_nav_extensions_abstract.h                               |  406 
 inst/dlib-19.20/dlib/dir_nav/dir_nav_kernel_1.cpp                                        |  516 
 inst/dlib-19.20/dlib/dir_nav/dir_nav_kernel_1.h                                          | 1268 -
 inst/dlib-19.20/dlib/dir_nav/dir_nav_kernel_2.cpp                                        |  508 
 inst/dlib-19.20/dlib/dir_nav/dir_nav_kernel_2.h                                          | 1318 -
 inst/dlib-19.20/dlib/dir_nav/dir_nav_kernel_abstract.h                                   | 1030 -
 inst/dlib-19.20/dlib/dir_nav/posix.h                                                     |   12 
 inst/dlib-19.20/dlib/dir_nav/windows.h                                                   |   12 
 inst/dlib-19.20/dlib/enable_if.h                                                         |  124 
 inst/dlib-19.20/dlib/entropy_decoder.h                                                   |   88 
 inst/dlib-19.20/dlib/entropy_decoder/entropy_decoder_kernel_1.cpp                        |  440 
 inst/dlib-19.20/dlib/entropy_decoder/entropy_decoder_kernel_1.h                          |  264 
 inst/dlib-19.20/dlib/entropy_decoder/entropy_decoder_kernel_2.cpp                        |  448 
 inst/dlib-19.20/dlib/entropy_decoder/entropy_decoder_kernel_2.h                          |  254 
 inst/dlib-19.20/dlib/entropy_decoder/entropy_decoder_kernel_abstract.h                   |  414 
 inst/dlib-19.20/dlib/entropy_decoder/entropy_decoder_kernel_c.h                          |  246 
 inst/dlib-19.20/dlib/entropy_encoder.h                                                   |   86 
 inst/dlib-19.20/dlib/entropy_encoder/entropy_encoder_kernel_1.cpp                        |  478 
 inst/dlib-19.20/dlib/entropy_encoder/entropy_encoder_kernel_1.h                          |  238 
 inst/dlib-19.20/dlib/entropy_encoder/entropy_encoder_kernel_2.cpp                        |  466 
 inst/dlib-19.20/dlib/entropy_encoder/entropy_encoder_kernel_2.h                          |  224 
 inst/dlib-19.20/dlib/entropy_encoder/entropy_encoder_kernel_abstract.h                   |  322 
 inst/dlib-19.20/dlib/entropy_encoder/entropy_encoder_kernel_c.h                          |  224 
 inst/dlib-19.20/dlib/error.h                                                             |  898 
 inst/dlib-19.20/dlib/float_details.h                                                     |  322 
 inst/dlib-19.20/dlib/general_hash/count_bits.h                                           |  164 
 inst/dlib-19.20/dlib/general_hash/count_bits_abstract.h                                  |   96 
 inst/dlib-19.20/dlib/general_hash/general_hash.h                                         |  160 
 inst/dlib-19.20/dlib/general_hash/hash.h                                                 |  284 
 inst/dlib-19.20/dlib/general_hash/hash_abstract.h                                        |  364 
 inst/dlib-19.20/dlib/general_hash/murmur_hash3.h                                         | 1052 -
 inst/dlib-19.20/dlib/general_hash/murmur_hash3_abstract.h                                |  250 
 inst/dlib-19.20/dlib/general_hash/random_hashing.h                                       | 1754 -
 inst/dlib-19.20/dlib/general_hash/random_hashing_abstract.h                              |  116 
 inst/dlib-19.20/dlib/geometry.h                                                          |   30 
 inst/dlib-19.20/dlib/geometry/border_enumerator.h                                        |  372 
 inst/dlib-19.20/dlib/geometry/border_enumerator_abstract.h                               |  252 
 inst/dlib-19.20/dlib/geometry/drectangle.h                                               | 1004 -
 inst/dlib-19.20/dlib/geometry/drectangle_abstract.h                                      | 1284 -
 inst/dlib-19.20/dlib/geometry/line.h                                                     |  472 
 inst/dlib-19.20/dlib/geometry/line_abstract.h                                            |  484 
 inst/dlib-19.20/dlib/geometry/point_transforms.h                                         | 1982 +-
 inst/dlib-19.20/dlib/geometry/point_transforms_abstract.h                                | 1594 -
 inst/dlib-19.20/dlib/geometry/rectangle.h                                                | 1688 -
 inst/dlib-19.20/dlib/geometry/rectangle_abstract.h                                       | 1702 -
 inst/dlib-19.20/dlib/geometry/vector.h                                                   | 2772 +-
 inst/dlib-19.20/dlib/geometry/vector_abstract.h                                          | 1038 -
 inst/dlib-19.20/dlib/graph_utils.h                                                       |   24 
 inst/dlib-19.20/dlib/graph_utils/edge_list_graphs.h                                      | 1186 -
 inst/dlib-19.20/dlib/graph_utils/edge_list_graphs_abstract.h                             |  716 
 inst/dlib-19.20/dlib/graph_utils/find_k_nearest_neighbors_lsh.h                          |  434 
 inst/dlib-19.20/dlib/graph_utils/find_k_nearest_neighbors_lsh_abstract.h                 |  204 
 inst/dlib-19.20/dlib/graph_utils/function_objects.h                                      |  258 
 inst/dlib-19.20/dlib/graph_utils/function_objects_abstract.h                             |  418 
 inst/dlib-19.20/dlib/graph_utils/graph_utils.h                                           | 2454 +-
 inst/dlib-19.20/dlib/graph_utils/graph_utils_abstract.h                                  |  904 
 inst/dlib-19.20/dlib/graph_utils/ordered_sample_pair.h                                   |  250 
 inst/dlib-19.20/dlib/graph_utils/ordered_sample_pair_abstract.h                          |  256 
 inst/dlib-19.20/dlib/graph_utils/sample_pair.h                                           |  358 
 inst/dlib-19.20/dlib/graph_utils/sample_pair_abstract.h                                  |  384 
 inst/dlib-19.20/dlib/hash.h                                                              |   28 
 inst/dlib-19.20/dlib/image_keypoint.h                                                    |   32 
 inst/dlib-19.20/dlib/image_keypoint/binned_vector_feature_image.h                        |  866 
 inst/dlib-19.20/dlib/image_keypoint/binned_vector_feature_image_abstract.h               |  574 
 inst/dlib-19.20/dlib/image_keypoint/build_separable_poly_filters.h                       |  372 
 inst/dlib-19.20/dlib/image_keypoint/draw_surf_points.h                                   |   80 
 inst/dlib-19.20/dlib/image_keypoint/draw_surf_points_abstract.h                          |   60 
 inst/dlib-19.20/dlib/image_keypoint/fine_hog_image.h                                     |  756 
 inst/dlib-19.20/dlib/image_keypoint/fine_hog_image_abstract.h                            |  552 
 inst/dlib-19.20/dlib/image_keypoint/hashed_feature_image.h                               | 1036 -
 inst/dlib-19.20/dlib/image_keypoint/hashed_feature_image_abstract.h                      |  606 
 inst/dlib-19.20/dlib/image_keypoint/hessian_pyramid.h                                    | 1062 -
 inst/dlib-19.20/dlib/image_keypoint/hessian_pyramid_abstract.h                           |  488 
 inst/dlib-19.20/dlib/image_keypoint/hog.h                                                | 1028 -
 inst/dlib-19.20/dlib/image_keypoint/hog_abstract.h                                       |  670 
 inst/dlib-19.20/dlib/image_keypoint/nearest_neighbor_feature_image.h                     |  816 
 inst/dlib-19.20/dlib/image_keypoint/nearest_neighbor_feature_image_abstract.h            |  508 
 inst/dlib-19.20/dlib/image_keypoint/poly_image.h                                         | 1298 -
 inst/dlib-19.20/dlib/image_keypoint/poly_image_abstract.h                                |  670 
 inst/dlib-19.20/dlib/image_keypoint/surf.h                                               |  590 
 inst/dlib-19.20/dlib/image_keypoint/surf_abstract.h                                      |  326 
 inst/dlib-19.20/dlib/image_processing.h                                                  |   56 
 inst/dlib-19.20/dlib/image_processing/box_overlap_testing.h                              |  430 
 inst/dlib-19.20/dlib/image_processing/box_overlap_testing_abstract.h                     |  402 
 inst/dlib-19.20/dlib/image_processing/correlation_tracker.h                              |  808 
 inst/dlib-19.20/dlib/image_processing/correlation_tracker_abstract.h                     |  324 
 inst/dlib-19.20/dlib/image_processing/detection_template_tools.h                         |  226 
 inst/dlib-19.20/dlib/image_processing/detection_template_tools_abstract.h                |  190 
 inst/dlib-19.20/dlib/image_processing/frontal_face_detector.h                            | 4746 ++---
 inst/dlib-19.20/dlib/image_processing/frontal_face_detector_abstract.h                   |   50 
 inst/dlib-19.20/dlib/image_processing/full_object_detection.h                            |  382 
 inst/dlib-19.20/dlib/image_processing/full_object_detection_abstract.h                   |  406 
 inst/dlib-19.20/dlib/image_processing/generic_image.h                                    | 1134 -
 inst/dlib-19.20/dlib/image_processing/object_detector.h                                  | 1252 -
 inst/dlib-19.20/dlib/image_processing/object_detector_abstract.h                         |  808 
 inst/dlib-19.20/dlib/image_processing/remove_unobtainable_rectangles.h                   |  634 
 inst/dlib-19.20/dlib/image_processing/remove_unobtainable_rectangles_abstract.h          |  112 
 inst/dlib-19.20/dlib/image_processing/render_face_detections.h                           |  198 
 inst/dlib-19.20/dlib/image_processing/render_face_detections_abstract.h                  |  118 
 inst/dlib-19.20/dlib/image_processing/scan_fhog_pyramid.h                                | 2696 +-
 inst/dlib-19.20/dlib/image_processing/scan_fhog_pyramid_abstract.h                       | 1568 -
 inst/dlib-19.20/dlib/image_processing/scan_image.h                                       | 1012 -
 inst/dlib-19.20/dlib/image_processing/scan_image_abstract.h                              |  566 
 inst/dlib-19.20/dlib/image_processing/scan_image_boxes.h                                 | 1260 -
 inst/dlib-19.20/dlib/image_processing/scan_image_boxes_abstract.h                        |  788 
 inst/dlib-19.20/dlib/image_processing/scan_image_custom.h                                |  802 
 inst/dlib-19.20/dlib/image_processing/scan_image_custom_abstract.h                       |  780 
 inst/dlib-19.20/dlib/image_processing/scan_image_pyramid.h                               | 2202 +-
 inst/dlib-19.20/dlib/image_processing/scan_image_pyramid_abstract.h                      |  990 -
 inst/dlib-19.20/dlib/image_processing/scan_image_pyramid_tools.h                         |  360 
 inst/dlib-19.20/dlib/image_processing/scan_image_pyramid_tools_abstract.h                |  236 
 inst/dlib-19.20/dlib/image_processing/setup_hashed_features.h                            |  438 
 inst/dlib-19.20/dlib/image_processing/setup_hashed_features_abstract.h                   |  420 
 inst/dlib-19.20/dlib/image_processing/shape_predictor.h                                  | 1048 -
 inst/dlib-19.20/dlib/image_processing/shape_predictor_abstract.h                         |  390 
 inst/dlib-19.20/dlib/image_processing/shape_predictor_trainer.h                          | 1766 -
 inst/dlib-19.20/dlib/image_processing/shape_predictor_trainer_abstract.h                 |  894 
 inst/dlib-19.20/dlib/image_transforms.h                                                  |   62 
 inst/dlib-19.20/dlib/image_transforms/assign_image.h                                     |  770 
 inst/dlib-19.20/dlib/image_transforms/assign_image_abstract.h                            |  392 
 inst/dlib-19.20/dlib/image_transforms/colormaps.h                                        |  538 
 inst/dlib-19.20/dlib/image_transforms/colormaps_abstract.h                               |  304 
 inst/dlib-19.20/dlib/image_transforms/draw.h                                             |  792 
 inst/dlib-19.20/dlib/image_transforms/draw_abstract.h                                    |  300 
 inst/dlib-19.20/dlib/image_transforms/edge_detector.h                                    | 1476 -
 inst/dlib-19.20/dlib/image_transforms/edge_detector_abstract.h                           | 1108 -
 inst/dlib-19.20/dlib/image_transforms/equalize_histogram.h                               |  364 
 inst/dlib-19.20/dlib/image_transforms/equalize_histogram_abstract.h                      |  244 
 inst/dlib-19.20/dlib/image_transforms/fhog.h                                             | 2808 +-
 inst/dlib-19.20/dlib/image_transforms/fhog_abstract.h                                    |  692 
 inst/dlib-19.20/dlib/image_transforms/hough_transform.h                                  | 1180 -
 inst/dlib-19.20/dlib/image_transforms/hough_transform_abstract.h                         |  742 
 inst/dlib-19.20/dlib/image_transforms/image_pyramid.h                                    | 2476 +-
 inst/dlib-19.20/dlib/image_transforms/image_pyramid_abstract.h                           |  768 
 inst/dlib-19.20/dlib/image_transforms/integral_image.h                                   |  380 
 inst/dlib-19.20/dlib/image_transforms/integral_image_abstract.h                          |  338 
 inst/dlib-19.20/dlib/image_transforms/interpolation.h                                    | 4314 ++--
 inst/dlib-19.20/dlib/image_transforms/interpolation_abstract.h                           | 3064 +--
 inst/dlib-19.20/dlib/image_transforms/label_connected_blobs.h                            |  718 
 inst/dlib-19.20/dlib/image_transforms/label_connected_blobs_abstract.h                   |  558 
 inst/dlib-19.20/dlib/image_transforms/lbp.h                                              |  614 
 inst/dlib-19.20/dlib/image_transforms/lbp_abstract.h                                     |  278 
 inst/dlib-19.20/dlib/image_transforms/morphological_operations.h                         | 1860 -
 inst/dlib-19.20/dlib/image_transforms/morphological_operations_abstract.h                |  740 
 inst/dlib-19.20/dlib/image_transforms/random_color_transform.h                           |  314 
 inst/dlib-19.20/dlib/image_transforms/random_color_transform_abstract.h                  |  188 
 inst/dlib-19.20/dlib/image_transforms/random_cropper.h                                   |  722 
 inst/dlib-19.20/dlib/image_transforms/random_cropper_abstract.h                          |  692 
 inst/dlib-19.20/dlib/image_transforms/segment_image.h                                    | 1960 +-
 inst/dlib-19.20/dlib/image_transforms/segment_image_abstract.h                           |  336 
 inst/dlib-19.20/dlib/image_transforms/spatial_filtering.h                                | 3160 +--
 inst/dlib-19.20/dlib/image_transforms/spatial_filtering_abstract.h                       |  974 -
 inst/dlib-19.20/dlib/image_transforms/thresholding.h                                     | 1360 -
 inst/dlib-19.20/dlib/image_transforms/thresholding_abstract.h                            |  398 
 inst/dlib-19.20/dlib/interfaces/cmd_line_parser_option.h                                 |  214 
 inst/dlib-19.20/dlib/interfaces/enumerable.h                                             |  260 
 inst/dlib-19.20/dlib/interfaces/map_pair.h                                               |  148 
 inst/dlib-19.20/dlib/interfaces/remover.h                                                |  440 
 inst/dlib-19.20/dlib/is_kind.h                                                           |  324 
 inst/dlib-19.20/dlib/linker.h                                                            |   18 
 inst/dlib-19.20/dlib/linker/linker_kernel_1.cpp                                          |  714 
 inst/dlib-19.20/dlib/linker/linker_kernel_1.h                                            |  282 
 inst/dlib-19.20/dlib/linker/linker_kernel_abstract.h                                     |  282 
 inst/dlib-19.20/dlib/logger.h                                                            |   22 
 inst/dlib-19.20/dlib/logger/extra_logger_headers.cpp                                     |   80 
 inst/dlib-19.20/dlib/logger/extra_logger_headers.h                                       |   82 
 inst/dlib-19.20/dlib/logger/logger_config_file.cpp                                       |  428 
 inst/dlib-19.20/dlib/logger/logger_config_file.h                                         |  270 
 inst/dlib-19.20/dlib/logger/logger_kernel_1.cpp                                          |  996 -
 inst/dlib-19.20/dlib/logger/logger_kernel_1.h                                            | 1374 -
 inst/dlib-19.20/dlib/logger/logger_kernel_abstract.h                                     |  858 
 inst/dlib-19.20/dlib/lsh.h                                                               |   28 
 inst/dlib-19.20/dlib/lsh/create_random_projection_hash.h                                 |  464 
 inst/dlib-19.20/dlib/lsh/create_random_projection_hash_abstract.h                        |  296 
 inst/dlib-19.20/dlib/lsh/hashes.h                                                        |  438 
 inst/dlib-19.20/dlib/lsh/hashes_abstract.h                                               |  572 
 inst/dlib-19.20/dlib/lsh/projection_hash.h                                               |  236 
 inst/dlib-19.20/dlib/lsh/projection_hash_abstract.h                                      |  238 
 inst/dlib-19.20/dlib/map.h                                                               |  118 
 inst/dlib-19.20/dlib/map/map_kernel_1.h                                                  |  872 
 inst/dlib-19.20/dlib/map/map_kernel_abstract.h                                           |  470 
 inst/dlib-19.20/dlib/map/map_kernel_c.h                                                  |  496 
 inst/dlib-19.20/dlib/matrix.h                                                            |   48 
 inst/dlib-19.20/dlib/matrix/cblas_constants.h                                            |   64 
 inst/dlib-19.20/dlib/matrix/lapack/fortran_id.h                                          |  124 
 inst/dlib-19.20/dlib/matrix/lapack/gees.h                                                |  528 
 inst/dlib-19.20/dlib/matrix/lapack/geev.h                                                |  468 
 inst/dlib-19.20/dlib/matrix/lapack/geqrf.h                                               |  336 
 inst/dlib-19.20/dlib/matrix/lapack/gesdd.h                                               |  728 
 inst/dlib-19.20/dlib/matrix/lapack/gesvd.h                                               |  646 
 inst/dlib-19.20/dlib/matrix/lapack/getrf.h                                               |  264 
 inst/dlib-19.20/dlib/matrix/lapack/ormqr.h                                               |  448 
 inst/dlib-19.20/dlib/matrix/lapack/pbtrf.h                                               |  356 
 inst/dlib-19.20/dlib/matrix/lapack/potrf.h                                               |  348 
 inst/dlib-19.20/dlib/matrix/lapack/syev.h                                                |  436 
 inst/dlib-19.20/dlib/matrix/lapack/syevr.h                                               |  890 
 inst/dlib-19.20/dlib/matrix/matrix.h                                                     | 4350 ++--
 inst/dlib-19.20/dlib/matrix/matrix_abstract.h                                            | 1744 -
 inst/dlib-19.20/dlib/matrix/matrix_assign.h                                              | 1956 +-
 inst/dlib-19.20/dlib/matrix/matrix_assign_fwd.h                                          |  826 
 inst/dlib-19.20/dlib/matrix/matrix_blas_bindings.h                                       | 3278 +--
 inst/dlib-19.20/dlib/matrix/matrix_cholesky.h                                            |  558 
 inst/dlib-19.20/dlib/matrix/matrix_conj_trans.h                                          |  142 
 inst/dlib-19.20/dlib/matrix/matrix_conv.h                                                |  716 
 inst/dlib-19.20/dlib/matrix/matrix_conv_abstract.h                                       |  316 
 inst/dlib-19.20/dlib/matrix/matrix_data_layout.h                                         | 2682 +-
 inst/dlib-19.20/dlib/matrix/matrix_data_layout_abstract.h                                |   80 
 inst/dlib-19.20/dlib/matrix/matrix_default_mul.h                                         |  268 
 inst/dlib-19.20/dlib/matrix/matrix_eigenvalue.h                                          | 2758 +-
 inst/dlib-19.20/dlib/matrix/matrix_exp.h                                                 |  550 
 inst/dlib-19.20/dlib/matrix/matrix_exp_abstract.h                                        |  420 
 inst/dlib-19.20/dlib/matrix/matrix_expressions.h                                         |  560 
 inst/dlib-19.20/dlib/matrix/matrix_fft.h                                                 | 1692 -
 inst/dlib-19.20/dlib/matrix/matrix_fft_abstract.h                                        |  236 
 inst/dlib-19.20/dlib/matrix/matrix_fwd.h                                                 |   62 
 inst/dlib-19.20/dlib/matrix/matrix_generic_image.h                                       |  220 
 inst/dlib-19.20/dlib/matrix/matrix_la.h                                                  | 3614 +--
 inst/dlib-19.20/dlib/matrix/matrix_la_abstract.h                                         | 2010 +-
 inst/dlib-19.20/dlib/matrix/matrix_lu.h                                                  |  722 
 inst/dlib-19.20/dlib/matrix/matrix_mat.h                                                 | 1466 -
 inst/dlib-19.20/dlib/matrix/matrix_mat_abstract.h                                        |  486 
 inst/dlib-19.20/dlib/matrix/matrix_math_functions.h                                      |  896 
 inst/dlib-19.20/dlib/matrix/matrix_math_functions_abstract.h                             | 1190 -
 inst/dlib-19.20/dlib/matrix/matrix_op.h                                                  |  958 -
 inst/dlib-19.20/dlib/matrix/matrix_qr.h                                                  |  932 
 inst/dlib-19.20/dlib/matrix/matrix_read_from_istream.h                                   |  216 
 inst/dlib-19.20/dlib/matrix/matrix_subexp.h                                              | 3148 +--
 inst/dlib-19.20/dlib/matrix/matrix_subexp_abstract.h                                     | 1140 -
 inst/dlib-19.20/dlib/matrix/matrix_trsm.h                                                | 1308 -
 inst/dlib-19.20/dlib/matrix/matrix_utilities.h                                           | 9394 +++++-----
 inst/dlib-19.20/dlib/matrix/matrix_utilities_abstract.h                                  | 3828 ++--
 inst/dlib-19.20/dlib/matrix/symmetric_matrix_cache.h                                     |  928 
 inst/dlib-19.20/dlib/matrix/symmetric_matrix_cache_abstract.h                            |  126 
 inst/dlib-19.20/dlib/md5.h                                                               |    6 
 inst/dlib-19.20/dlib/md5/md5_kernel_1.cpp                                                | 1234 -
 inst/dlib-19.20/dlib/md5/md5_kernel_1.h                                                  |  100 
 inst/dlib-19.20/dlib/md5/md5_kernel_abstract.h                                           |  166 
 inst/dlib-19.20/dlib/member_function_pointer.h                                           |   20 
 inst/dlib-19.20/dlib/member_function_pointer/make_mfp.h                                  |  358 
 inst/dlib-19.20/dlib/member_function_pointer/make_mfp_abstract.h                         |  414 
 inst/dlib-19.20/dlib/member_function_pointer/member_function_pointer_kernel_1.h          | 1018 -
 inst/dlib-19.20/dlib/member_function_pointer/member_function_pointer_kernel_abstract.h   |  966 -
 inst/dlib-19.20/dlib/memory_manager.h                                                    |  146 
 inst/dlib-19.20/dlib/memory_manager/memory_manager_kernel_1.h                            |  610 
 inst/dlib-19.20/dlib/memory_manager/memory_manager_kernel_2.h                            |  506 
 inst/dlib-19.20/dlib/memory_manager/memory_manager_kernel_3.h                            |  770 
 inst/dlib-19.20/dlib/memory_manager/memory_manager_kernel_abstract.h                     |  292 
 inst/dlib-19.20/dlib/memory_manager_stateless.h                                          |  144 
 inst/dlib-19.20/dlib/memory_manager_stateless/memory_manager_stateless_kernel_1.h        |  202 
 inst/dlib-19.20/dlib/memory_manager_stateless/memory_manager_stateless_kernel_2.h        |  238 
 inst/dlib-19.20/dlib/memory_manager_stateless/memory_manager_stateless_kernel_abstract.h |  346 
 inst/dlib-19.20/dlib/misc_api.h                                                          |   40 
 inst/dlib-19.20/dlib/misc_api/misc_api_kernel_1.cpp                                      |  298 
 inst/dlib-19.20/dlib/misc_api/misc_api_kernel_1.h                                        |  220 
 inst/dlib-19.20/dlib/misc_api/misc_api_kernel_2.cpp                                      |  246 
 inst/dlib-19.20/dlib/misc_api/misc_api_kernel_2.h                                        |  162 
 inst/dlib-19.20/dlib/misc_api/misc_api_kernel_abstract.h                                 |  318 
 inst/dlib-19.20/dlib/misc_api/misc_api_shared.h                                          |  114 
 inst/dlib-19.20/dlib/misc_api/posix.h                                                    |   12 
 inst/dlib-19.20/dlib/misc_api/windows.h                                                  |   12 
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 inst/dlib-19.20/dlib/pixel.h                                                             | 3432 +--
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 inst/dlib-19.20/dlib/server.h                                                            |   24 
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 inst/dlib-19.20/dlib/sockets.h                                                           |   40 
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Package gunit updated to version 1.0.2 with previous version 1.0.0 dated 2019-05-03

Title: Converts Conductance Units
Description: For plant physiologists, converts conductance (e.g. stomatal conductance) to different units: m/s, mol/m^2/s, and umol/m^2/s/Pa.
Author: Chris Muir [aut, cre]
Maintainer: Chris Muir <cdmuir@hawaii.edu>

Diff between gunit versions 1.0.0 dated 2019-05-03 and 1.0.2 dated 2022-10-18

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Package gRbase updated to version 1.8.8 with previous version 1.8.7 dated 2022-04-02

Title: A Package for Graphical Modelling in R
Description: The 'gRbase' package provides graphical modelling features used by e.g. the packages 'gRain', 'gRim' and 'gRc'. 'gRbase' implements graph algorithms including (i) maximum cardinality search (for marked and unmarked graphs). (ii) moralization, (iii) triangulation, (iv) creation of junction tree. 'gRbase' facilitates array operations, 'gRbase' implements functions for testing for conditional independence. 'gRbase' illustrates how hierarchical log-linear models may be implemented and describes concept of graphical meta data. The facilities of the package are documented in the book by Højsgaard, Edwards and Lauritzen (2012, <doi:10.1007/978-1-4614-2299-0>) and in the paper by Dethlefsen and Højsgaard, (2005, <doi:10.18637/jss.v014.i17>). Please see 'citation("gRbase")' for citation details. NOTICE 'gRbase' requires that the packages graph, 'Rgraphviz' and 'RBGL' are installed from 'bioconductor'; for installation instructions please refer to the web page given below.
Author: Soeren Hoejsgaard <sorenh@math.aau.dk>
Maintainer: Soeren Hoejsgaard <sorenh@math.aau.dk>

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Package golem updated to version 0.3.5 with previous version 0.3.4 dated 2022-09-26

Title: A Framework for Robust Shiny Applications
Description: An opinionated framework for building a production-ready 'Shiny' application. This package contains a series of tools for building a robust 'Shiny' application from start to finish.
Author: Colin Fay [cre, aut] , Vincent Guyader [aut] , Sebastien Rochette [aut] , Cervan Girard [aut] , Novica Nakov [ctb], David Granjon [ctb], Arthur Breant [ctb], Antoine Languillaume [ctb], ThinkR [cph]
Maintainer: Colin Fay <contact@colinfay.me>

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Package gllm updated to version 0.38 with previous version 0.37 dated 2018-11-27

Title: Generalised log-Linear Model
Description: Routines for log-linear models of incomplete contingency tables, including some latent class models, via EM and Fisher scoring approaches. Allows bootstrapping. See Espeland and Hui (1987) <doi:10.2307/2531553> for general approach.
Author: David Duffy <David.Duffy@qimr.edu.au>. C code in emgllmfitter by Andreas Borg <borg@imbei.uni-mainz.de>
Maintainer: David Duffy <David.Duffy@qimrberghofer.edu.au>

Diff between gllm versions 0.37 dated 2018-11-27 and 0.38 dated 2022-10-18

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Package GLDEX updated to version 2.0.0.9.1 with previous version 2.0.0.9 dated 2022-05-17

Title: Fitting Single and Mixture of Generalised Lambda Distributions
Description: The fitting algorithms considered in this package have two major objectives. One is to provide a smoothing device to fit distributions to data using the weight and unweighted discretised approach based on the bin width of the histogram. The other is to provide a definitive fit to the data set using the maximum likelihood and quantile matching estimation. Other methods such as moment matching, starship method, L moment matching are also provided. Diagnostics on goodness of fit can be done via qqplots, KS-resample tests and comparing mean, variance, skewness and kurtosis of the data with the fitted distribution. References include the following: Karvanen and Nuutinen (2008) "Characterizing the generalized lambda distribution by L-moments" <doi:10.1016/j.csda.2007.06.021>, King and MacGillivray (1999) "A starship method for fitting the generalised lambda distributions" <doi:10.1111/1467-842X.00089>, Su (2005) "A Discretized Approach to Flexibly Fit Generalized Lambda Distribut [...truncated...]
Author: Steve Su [aut, cre, cph] , Martin Maechler [aut], Juha Karvanen [aut], Robert King [aut], Benjamin Dean [ctb], R Core Team [aut]
Maintainer: Steve Su <allegro.su@gmail.com>

Diff between GLDEX versions 2.0.0.9 dated 2022-05-17 and 2.0.0.9.1 dated 2022-10-18

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Package effectsize updated to version 0.8.1 with previous version 0.8.0 dated 2022-10-09

Title: Indices of Effect Size
Description: Provide utilities to work with indices of effect size for a wide variety of models and hypothesis tests (see list of supported models using the function 'insight::supported_models()'), allowing computation of and conversion between indices such as Cohen's d, r, odds, etc. References: Ben-Shachar et al. (2020) <doi:10.21105/joss.02815>.
Author: Mattan S. Ben-Shachar [aut, cre] , Dominique Makowski [aut] , Daniel Luedecke [aut] , Indrajeet Patil [aut] , Brenton M. Wiernik [aut] , Ken Kelley [ctb], David Stanley [ctb], Jessica Burnett [rev] , Johannes Karreth [rev]
Maintainer: Mattan S. Ben-Shachar <mattansb@msbstats.info>

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Package digest updated to version 0.6.30 with previous version 0.6.29 dated 2021-12-01

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

Diff between digest versions 0.6.29 dated 2021-12-01 and 0.6.30 dated 2022-10-18

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Package clue updated to version 0.3-62 with previous version 0.3-61 dated 2022-05-30

Title: Cluster Ensembles
Description: CLUster Ensembles.
Author: Kurt Hornik [aut, cre] , Walter Boehm [ctb]
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

Diff between clue versions 0.3-61 dated 2022-05-30 and 0.3-62 dated 2022-10-18

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Package adobeanalyticsr updated to version 0.3.3 with previous version 0.3.2 dated 2022-04-05

Title: R Client for 'Adobe Analytics' API 2.0
Description: Connect to the 'Adobe Analytics' API v2.0 <https://github.com/AdobeDocs/analytics-2.0-apis> which powers 'Analysis Workspace'. The package was developed with the analyst in mind, and it will continue to be developed with the guiding principles of iterative, repeatable, timely analysis.
Author: Ben Woodard [aut, cre], Tim Wilson [aut, ctb], Charles Gallagher [ctb], Mark Edmondson [ctb]
Maintainer: Ben Woodard <benrwoodard@gmail.com>

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Package mockthat (with last version 0.2.6) was removed from CRAN

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

2021-04-23 0.2.6
2020-12-09 0.2.4

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

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2016-02-07 0.6
2015-04-01 0.5
2014-11-30 0.4
2012-12-08 0.3
2009-10-29 0.2
2009-10-27 0.1

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Package Rdca (with last version 0.1.0) was removed from CRAN

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

2020-06-02 0.1.0

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Package Rpvt (with last version 0.1.1) was removed from CRAN

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

2020-05-17 0.1.1
2020-05-08 0.1.0

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Package BCEE updated to version 1.3.1 with previous version 1.3.0 dated 2020-04-01

Title: The Bayesian Causal Effect Estimation Algorithm
Description: A Bayesian model averaging approach to causal effect estimation based on the BCEE algorithm. Currently supports binary or continuous exposures and outcomes. For more details, see Talbot et al. (2015) <doi:10.1515/jci-2014-0035> Talbot and Beaudoin (2020) <arXiv:2003.11588>.

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Package bamp updated to version 2.1.3 with previous version 2.1.1 dated 2022-05-05

Title: Bayesian Age-Period-Cohort Modeling and Prediction
Description: Bayesian Age-Period-Cohort Modeling and Prediction using efficient Markov Chain Monte Carlo Methods. This is the R version of the previous BAMP software as described in Volker Schmid and Leonhard Held (2007) <DOI:10.18637/jss.v021.i08> Bayesian Age-Period-Cohort Modeling and Prediction - BAMP, Journal of Statistical Software 21:8. This package includes checks of convergence using Gelman's R.
Author: Volker Schmid [aut, cre], Florian Geressen [ctb], Leonhard Held [ctb], Evi Rainer [ctb]
Maintainer: Volker Schmid <volker.schmid@lmu.de>

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Package signnet updated to version 0.8.1 with previous version 0.8.0 dated 2022-02-13

Title: Methods to Analyse Signed Networks
Description: Methods for the analysis of signed networks. This includes several measures for structural balance as introduced by Cartwright and Harary (1956) <doi:10.1037/h0046049>, blockmodeling algorithms from Doreian (2008) <doi:10.1016/j.socnet.2008.03.005>, various centrality indices, and projections of signed two-mode networks introduced by Schoch (2020) <doi:10.1080/0022250X.2019.1711376>.
Author: David Schoch [aut, cre]
Maintainer: David Schoch <david@schochastics.net>

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Package s2dv updated to version 1.3.0 with previous version 1.2.0 dated 2022-06-23

Title: A Set of Common Tools for Seasonal to Decadal Verification
Description: The advanced version of package 's2dverification'. It is intended for 'seasonal to decadal' (s2d) climate forecast verification, but it can also be used in other kinds of forecasts or general climate analysis. This package is specially designed for the comparison between the experimental and observational datasets. The functionality of the included functions covers from data retrieval, data post-processing, skill scores against observation, to visualization. Compared to 's2dverification', 's2dv' is more compatible with the package 'startR', able to use multiple cores for computation and handle multi-dimensional arrays with a higher flexibility. The CDO version used in development is 1.9.8.
Author: BSC-CNS [aut, cph], An-Chi Ho [aut, cre], Nuria Perez-Zanon [aut], Roberto Bilbao [ctb], Josep Cos [ctb], Carlos Delgado [ctb], Llorenc Lledo [ctb], Andrea Manrique [ctb], Deborah Verfaillie [ctb], Eva Rifà [ctb]
Maintainer: An-Chi Ho <an.ho@bsc.es>

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Package RDSsamplesize updated to version 0.2.0 with previous version 0.1.0 dated 2022-07-04

Title: RDS Sample Size Estimation and Power Calculation
Description: Provides functionality for carrying out sample size estimation and power calculation in Respondent-Driven Sampling.
Author: Yibo Wang [aut, cre], Michael R. Elliott [aut], Sunghee Lee [aut]
Maintainer: Yibo Wang <wangyb@umich.edu>

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New package RCT2 with initial version 0.0.1
Package: RCT2
Version: 0.0.1
Date: 2022-10-16
Title: Designing and Analyzing Two-Stage Randomized Experiments
Maintainer: Kosuke Imai <imai@harvard.edu>
Depends: R (>= 3.1.0)
Description: Provides various statistical methods for designing and analyzing two-stage randomized controlled trials using the methods developed by Imai, Jiang, and Malani (2021) <doi:10.1080/01621459.2020.1775612> and (2022+) <doi:10.48550/arXiv.2011.07677>. The package enables the estimation of direct and spillover effects, conduct hypotheses tests, and conduct sample size calculation for two-stage randomized controlled trials.
License: GPL (>= 2)
URL: https://github.com/kosukeimai/RCT2
BugReports: https://github.com/kosukeimai/RCT2/issues
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
Imports: sandwich, AER, stats, quadprog
NeedsCompilation: no
Packaged: 2022-10-18 03:04:05 UTC; kosukeimai
Author: Karissa Huang [aut], Zhichao Jiang [aut], Kosuke Imai [aut, cre]
Repository: CRAN
Date/Publication: 2022-10-18 07:05:17 UTC

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Package pvar updated to version 2.2.7 with previous version 2.2.5 dated 2018-11-15

Title: Calculation and Application of p-Variation
Description: The calculation of p-variation of the finite sample data. This package is a realisation of the procedure described in Butkus, V. & Norvaisa, R. Lith Math J (2018). <doi: 10.1007/s10986-018-9414-3> The formal definitions and reference into literature are given in vignette.
Author: Vygantas Butkus
Maintainer: Vygantas Butkus <Vygantas.Butkus@gmail.com>

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Package pirouette updated to version 1.6.5 with previous version 1.6.4 dated 2022-10-06

Title: Create a Bayesian Posterior from a Phylogeny
Description: Theoretical biologists are interested in measuring the extent at which we can measure the truth. This package allows to create a Bayesian posterior from a phylogeny that depicts the true evolutionary relationships. The given and true phylogeny can than be compared to the posterior phylogenies. Richèl J. C. Bilderbeek, Giovanni Laudanno, Rampal S. Etienne (2020) "Quantifying the impact of an inference model in Bayesian phylogenetics" <doi:10.1111/2041-210X.13514>.
Author: Richel J.C. Bilderbeek [aut, cre] , Giovanni Laudanno [aut], Thijs Janzen [ctb]
Maintainer: Richel J.C. Bilderbeek <richel@richelbilderbeek.nl>

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Package pedgene updated to version 3.6 with previous version 3.3 dated 2020-02-19

Title: Gene-Level Variant Association Tests for Pedigree Data
Description: Gene-level variant association tests with disease status for pedigree data: kernel and burden association statistics.
Author: Schaid Daniel [aut], Visconti Alessia [ctb], Jason Sinnwell [aut, cre]
Maintainer: Jason Sinnwell <sinnwell.jason@mayo.edu>

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Package PCICt updated to version 0.5-4.3 with previous version 0.5-4.2 dated 2022-10-16

Title: Implementation of POSIXct Work-Alike for 365 and 360 Day Calendars
Description: Provides a work-alike to R's POSIXct class which implements 360- and 365-day calendars in addition to the gregorian calendar.
Author: David Bronaugh <bronaugh@uvic.ca> for the Pacific Climate Impacts Consortium ; portions based on code written by the R-Core team and Ulrich Drepper.
Maintainer: James Hiebert <hiebert@uvic.ca>

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Package neatRanges updated to version 0.1.4 with previous version 0.1.3 dated 2020-03-29

Title: Tidy Up Date/Time Ranges
Description: Collapse, partition, combine, fill gaps in and expand date/time ranges.
Author: Aljaz Jelenko [aut, cre], Patrik Punco [aut]
Maintainer: Aljaz Jelenko <aljaz.jelenko@amis.net>

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Package microsimulation updated to version 1.4.1 with previous version 1.3.7 dated 2022-04-04

Title: Discrete Event Simulation in R and C++, with Tools for Cost-Effectiveness Analysis
Description: Discrete event simulation using both R and C++ (Karlsson et al 2016; <doi:10.1109/eScience.2016.7870915>). The C++ code is adapted from the SSIM library <https://www.inf.usi.ch/carzaniga/ssim/>, allowing for event-oriented simulation. The code includes a SummaryReport class for reporting events and costs by age and other covariates. The C++ code is available as a static library for linking to other packages. A priority queue implementation is given in C++ together with an S3 closure and a reference class implementation. Finally, some tools are provided for cost-effectiveness analysis.
Author: Mark Clements [aut, cre, cph], Alexandra Jauhiainen [aut], Andreas Karlsson [aut], Antonio Carzaniga [cph], University of Colorado [cph], Pierre L'Ecuyer [cph]
Maintainer: Mark Clements <mark.clements@ki.se>

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More information about microsimulation at CRAN
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Package MantaID updated to version 1.0.2 with previous version 1.0.1 dated 2022-10-17

Title: A Machine-Learning Based Tool to Automate the Identification of Biological Database IDs
Description: The number of biological databases is growing rapidly, but different databases use different IDs to refer to the same biological entity. The inconsistency in IDs impedes the integration of various types of biological data. To resolve the problem, we developed 'MantaID', a data-driven, machine-learning based approach that automates identifying IDs on a large scale. The 'MantaID' model's prediction accuracy was proven to be 99%, and it correctly and effectively predicted 100,000 ID entries within two minutes. 'MantaID' supports the discovery and exploitation of ID patterns from large quantities of databases. (e.g., up to 542 biological databases). An easy-to-use freely available open-source software R package, a user-friendly web application, and APIs were also developed for 'MantaID' to improve applicability. To our knowledge, 'MantaID' is the first tool that enables an automatic, quick, accurate, and comprehensive identification of large quantities of IDs, and can therefore be used as [...truncated...]
Author: Zeng Zhengpeng [aut, cre, ctb] , Mao Longfei [aut] , Yu Feng [aut]
Maintainer: Zeng Zhengpeng <molaison@foxmail.com>

Diff between MantaID versions 1.0.1 dated 2022-10-17 and 1.0.2 dated 2022-10-18

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Package krm updated to version 2022.10-17 with previous version 2020.5-20 dated 2020-05-21

Title: Kernel Based Regression Models
Description: Implements several methods for testing the variance component parameter in regression models that contain kernel-based random effects, including a maximum of adjusted scores test. Several kernels are supported, including a profile hidden Markov model mutual information kernel for protein sequence. This package is described in Fong et al. (2015) <DOI:10.1093/biostatistics/kxu056>.
Author: Youyi Fong [cre], Saheli Datta [aut], Krisztian Sebestyen [aut], Steve Park [ctb], Dave Geyer [ctb]
Maintainer: Youyi Fong <youyifong@gmail.com>

Diff between krm versions 2020.5-20 dated 2020-05-21 and 2022.10-17 dated 2022-10-18

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Package isqg updated to version 1.4 with previous version 1.3 dated 2020-06-02

Title: In Silico Quantitative Genetics
Description: Accomplish high performance simulations in quantitative genetics. The molecular genetic components are represented by R6/C++ classes and methods. The core computational algorithm is implemented using bitsets according to <doi:10.1534/g3.119.400373>. A mix between low and high level interfaces provides great flexibility and allows user defined extensions and a wide range of applications.
Author: Fernando H. Toledo [aut, cre] International Maize and Wheat Improvement Center [cph]
Maintainer: Fernando H. Toledo <f.toledo@cgiar.org>

Diff between isqg versions 1.3 dated 2020-06-02 and 1.4 dated 2022-10-18

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Package FDX updated to version 1.0.6 with previous version 1.0.5 dated 2022-10-16

Title: False Discovery Exceedance Controlling Multiple Testing Procedures
Description: Multiple testing procedures for heterogeneous and discrete tests as described in Döhler and Roquain (2019) <arXiv:1912.04607v1>. The main algorithms of the paper are available as continuous, discrete and weighted versions.
Author: Sebastian Doehler [aut], Florian Junge [aut, cre], Etienne Roquain [ctb]
Maintainer: Florian Junge <florian.junge@h-da.de>

Diff between FDX versions 1.0.5 dated 2022-10-16 and 1.0.6 dated 2022-10-18

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Package DTSEA updated to version 0.0.2 with previous version 0.0.1 dated 2022-10-12

Title: Drug Target Set Enrichment Analysis
Description: It is a novel tool used to identify the candidate drugs against a particular disease based on a drug target set enrichment analysis. It assumes the most effective drugs are those with a closer affinity in the protein-protein interaction network to the specified disease. (See Gómez-Carballa et al. (2022) <doi: 10.1016/j.envres.2022.112890> and Feng et al. (2022) <doi: 10.7150/ijms.67815> for disease expression profiles; see Wishart et al. (2018) <doi: 10.1093/nar/gkx1037> and Gaulton et al. (2017) <doi: 10.1093/nar/gkw1074> for drug target information; see Kanehisa et al. (2021) <doi: 10.1093/nar/gkaa970> for the details of KEGG database.)
Author: Junwei Han [aut, cre, cph], Yinchun Su [aut]
Maintainer: Junwei Han <hanjunwei1981@163.com>

Diff between DTSEA versions 0.0.1 dated 2022-10-12 and 0.0.2 dated 2022-10-18

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Package DBItest updated to version 1.7.3 with previous version 1.7.2 dated 2021-12-17

Title: Testing DBI Backends
Description: A helper that tests DBI back ends for conformity to the interface.
Author: Kirill Mueller [aut, cre] , RStudio [cph], R Consortium [fnd]
Maintainer: Kirill Mueller <kirill@cynkra.com>

Diff between DBItest versions 1.7.2 dated 2021-12-17 and 1.7.3 dated 2022-10-18

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New package VIGoR with initial version 1.1.1
Package: VIGoR
Title: Variational Bayesian Inference for Genome-Wide Regression
Version: 1.1.1
Date: 2022-10-11
Description: Conducts linear regression using variational Bayesian inference, particularly optimized for genome-wide association mapping and whole-genome prediction which use a number of DNA markers as the explanatory variables. Provides seven regression models which select the important variables (i.e., the variables related to response variables) among the given explanatory variables in different ways (i.e., model structures).
License: MIT + file LICENSE
NeedsCompilation: yes
Packaged: 2022-10-17 13:22:57 UTC; lbds202001
Author: Akio Onogi [aut, cre, cph], R Core Team [ctb] , Hiroyoshi Iwata [cph], Takuji Nishimura [ctb] , Makoto Matsumoto [ctb] , STRUCTURE software contributors [ctb] , Alan Miller [ctb] , Peter Beerli [ctb]
Maintainer: Akio Onogi <onogiakio@gmail.com>
Repository: CRAN
Date/Publication: 2022-10-18 06:22:32 UTC

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New package tiktokadsR with initial version 0.1.0
Package: tiktokadsR
Title: Access to TikTok Ads via the 'Windsor.ai' API
Version: 0.1.0
Description: Collect marketing data from TikTok Ads using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.
License: GPL-3
URL: https://windsor.ai/
Depends: R (>= 3.5.0)
Imports: jsonlite (>= 1.7.2)
Suggests: knitr, rmarkdown, dplyr, ggplot2, tidyr, curl
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2022-10-17 16:31:23 UTC; pablo
Author: Pablo Sanchez [cre, aut], Windsor.ai [cph]
Maintainer: Pablo Sanchez <pablosama@outlook.es>
Repository: CRAN
Date/Publication: 2022-10-18 06:40:02 UTC

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New package Sysrecon with initial version 0.1.0
Package: Sysrecon
Title: Systematical Metabolic Reconstruction
Version: 0.1.0
Description: Visualize the steps, transformation information, databases used in a metabolic reconstruction, by inputting an article in the form of txt.
License: GPL-3
Imports: ape, dplyr, ggplot2, ggtree, methods, patchwork, plyr, RColorBrewer, readr, readxl, rlang, SnowballC, stats, stringr, tidyverse, tm
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2022-10-17 14:57:48 UTC; lenovo
Author: Shilin Ouyang [aut, cre], Zihao Li [aut], Jiamin Hu [aut], Miyuan Cao [aut], Feng Yu [aut], Longfei Mao [aut], RStudio [cph, fnd]
Maintainer: Shilin Ouyang <ouyangshilin@hnu.edu.cn>
Repository: CRAN
Date/Publication: 2022-10-18 06:42:46 UTC

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New package simuclustfactor with initial version 0.0.3
Package: simuclustfactor
Title: Simultaneous Clustering and Factorial Decomposition of Three-Way Datasets
Version: 0.0.3
Maintainer: Prosper Ablordeppey <pablordeppey@ua.pt>
Description: Implements two iterative techniques called T3Clus and 3Fkmeans, aimed at simultaneously clustering objects and a factorial dimensionality reduction of variables and occasions on three-mode datasets developed by Vichi et al. (2007) <doi:10.1007/s00357-007-0006-x>. Also, we provide a convex combination of these two simultaneous procedures called CT3Clus and based on a hyperparameter alpha (alpha in [0,1], with 3FKMeans for alpha=0 and T3Clus for alpha= 1) also developed by Vichi et al. (2007) <doi:10.1007/s00357-007-0006-x>. Furthermore, we implemented the traditional tandem procedures of T3Clus (TWCFTA) and 3FKMeans (TWFCTA) for sequential clustering-factorial decomposition (TWCFTA), and vice-versa (TWFCTA) proposed by P. Arabie and L. Hubert (1996) <doi:10.1007/978-3-642-79999-0_1>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 2.10)
Imports: methods, stats, Rdpack
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2022-10-17 16:54:46 UTC; iCETEE
Author: Prosper Ablordeppey [aut, cre] , Adelaide Freitas [ctb] , Giorgia Zaccaria [ctb]
Repository: CRAN
Date/Publication: 2022-10-18 06:40:05 UTC

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New package Qardl with initial version 0.1.0
Package: Qardl
Title: Quantile Autoregressive Distributed Lag Model
Version: 0.1.0
Author: Taha Zaghdoudi
Maintainer: Taha Zaghdoudi <zedtaha@gmail.com>
Description: Fit the quantile autoregressive distributed lag model proposed by ( Cho et al. (2015) <doi:10.1016/j.jeconom.2015.05.003>).
Depends: R (>= 3.5)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: stats, dplyr, pbapply, quantreg, MASS
NeedsCompilation: no
Packaged: 2022-10-17 15:46:22 UTC; TAHA
Repository: CRAN
Date/Publication: 2022-10-18 06:45:33 UTC

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New package mmrm with initial version 0.1.3
Package: mmrm
Title: Mixed Models for Repeated Measures
Version: 0.1.3
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<2349::AID-SIM667>3.0.CO;2-E> for a tutorial and Mallinckrodt, Lane and Schnell (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 adjusted degrees of freedom, and extract least square means estimates by using 'emmeans'.
License: Apache License 2.0
URL: https://github.com/openpharma/mmrm/
BugReports: https://github.com/openpharma/mmrm/issues
Depends: R (>= 4.0)
Imports: checkmate (>= 2.0), lifecycle, methods, nlme, numDeriv, parallel, Rdpack, stats, stringr, TMB (>= 1.9.1)
Suggests: emmeans (>= 1.6), estimability, knitr, rmarkdown, testthat (>= 3.0.0), xml2
LinkingTo: RcppEigen, testthat, TMB
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: yes
Packaged: 2022-10-17 16:44:36 UTC; sabanesd
Author: Daniel Sabanes Bove [aut, cre], Julia Dedic [aut], Doug Kelkhoff [aut], Kevin Kunzmann [aut], Brian Matthew Lang [aut], Liming Li [aut], Ya Wang [aut], Craig Gower-Page [ctb], Boehringer Ingelheim Ltd. [cph, fnd], Gilead Sciences, Inc. [cph, fnd], F. [...truncated...]
Maintainer: Daniel Sabanes Bove <daniel.sabanes_bove@roche.com>
Repository: CRAN
Date/Publication: 2022-10-18 06:40:09 UTC

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New package instagramadsR with initial version 0.1.0
Package: instagramadsR
Title: Access to Instagram Ads via the 'Windsor.ai' API
Version: 0.1.0
Description: Collect marketing data from Instagram Ads using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.
License: GPL-3
URL: https://windsor.ai/
Depends: R (>= 3.5.0)
Imports: jsonlite (>= 1.7.2)
Suggests: knitr, rmarkdown, dplyr, ggplot2, tidyr, curl
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2022-10-17 15:14:46 UTC; pablo
Author: Pablo Sanchez [cre, aut], Windsor.ai [cph]
Maintainer: Pablo Sanchez <pablosama@outlook.es>
Repository: CRAN
Date/Publication: 2022-10-18 06:42:43 UTC

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New package CRE with initial version 0.1.0
Package: CRE
Title: Interpretable Subgroups Identification Through Ensemble Learning of Causal Rules
Version: 0.1.0
Maintainer: Naeem Khoshnevis <nkhoshnevis@g.harvard.edu>
Description: Provides an interpretable identification of subgroups with heterogeneous causal effect. The heterogeneous subgroups are discovered through ensemble learning of causal rules. Causal rules are highly interpretable if-then statement that recursively partition the features space into heterogeneous subgroups. A small number of significant causal rules are selected through Stability Selection to control for family-wise error rate in the finite sample setting. It proposes various estimation methods for the conditional causal effects for each discovered causal rule. It is highly flexible and multiple causal estimands and imputation methods are implemented. Lee, K., Bargagli-Stoffi, F. J., & Dominici, F. (2020). Causal rule ensemble: Interpretable inference of heterogeneous treatment effects. arXiv preprint <arXiv:2009.09036>.
License: GPL-3
URL: https://github.com/NSAPH-Software/CRE
BugReports: https://github.com/NSAPH-Software/CRE/issues
Depends: R (>= 3.5.0)
Imports: MASS, stats, logger, gbm, randomForest, methods, xgboost, RRF, data.table, xtable, glmnet, bartCause, stabs, stringr, SuperLearner, dplyr, magrittr, ggplot2, bcf, inTrees
Suggests: baggr, grf, BART, gnm, covr, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Copyright: Harvard University
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2022-10-17 14:20:18 UTC; nak443
Author: Naeem Khoshnevis [aut, cre] , Daniela Maria Garcia [aut] , Riccardo Cadei [aut] , Kwonsang Lee [aut] , Falco Joannes Bargagli Stoffi [aut]
Repository: CRAN
Date/Publication: 2022-10-18 06:35:16 UTC

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Package rayvertex updated to version 0.4.11 with previous version 0.3.3 dated 2021-10-10

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 0.3.3 dated 2021-10-10 and 0.4.11 dated 2022-10-18

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Package PSweight updated to version 1.1.8 with previous version 1.1.7 dated 2022-05-11

Title: Propensity Score Weighting for Causal Inference with Observational Studies and Randomized Trials
Description: Supports propensity score weighting analysis of observational studies and randomized trials. Enables the estimation and inference of average causal effects with binary and multiple treatments using overlap weights (ATO), inverse probability of treatment weights (ATE), average treatment effect among the treated weights (ATT), matching weights (ATM) and entropy weights (ATEN), with and without propensity score trimming. These weights are members of the family of balancing weights introduced in Li, Morgan and Zaslavsky (2018) <doi:10.1080/01621459.2016.1260466> and Li and Li (2019) <doi:10.1214/19-AOAS1282>.
Author: Tianhui Zhou [aut, cre], Guangyu Tong [aut], Fan Li [aut], Laine Thomas [aut], Fan Li [aut]
Maintainer: Tianhui Zhou <thuizhou@outlook.com>

Diff between PSweight versions 1.1.7 dated 2022-05-11 and 1.1.8 dated 2022-10-18

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More information about PSweight at CRAN
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