Mon, 07 Sep 2020

Package reghelper updated to version 1.0.0 with previous version 0.3.6 dated 2020-04-16

Title: Helper Functions for Regression Analysis
Description: A set of functions used to automate commonly used methods in regression analysis. This includes plotting interactions, and calculating simple slopes, standardized coefficients, regions of significance (Johnson & Neyman, 1936; cf. Spiller et al., 2012), etc. See the reghelper documentation for more information, documentation, and examples.
Author: Jeffrey Hughes [aut, cre]
Maintainer: Jeffrey Hughes <jeff.hughes@gmail.com>

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Package Rdimtools updated to version 1.0.4 with previous version 1.0.3 dated 2020-05-22

Title: Dimension Reduction and Estimation Methods
Description: We provide linear and nonlinear dimension reduction techniques. Intrinsic dimension estimation methods for exploratory analysis are also provided. For more details on the package, see the paper by You (2020) <arXiv:2005.11107>.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>), Changhee Suh [ctb]
Maintainer: Kisung You <kyoustat@gmail.com>

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Package epikit updated to version 0.1.2 with previous version 0.1.1 dated 2020-04-13

Title: Miscellaneous Tools for the 'R4Epis' Project
Description: Contains tools for formatting inline code, renaming redundant columns, aggregating age categories, and calculating proportions with confidence intervals. This is part of the 'R4Epis' project <https://r4epis.netlify.com>.
Author: Zhian N. Kamvar [aut, cre] (<https://orcid.org/0000-0003-1458-7108>), Dirk Schumacher [aut], Alex Spina [ctb], Kate Doyle [ctb]
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>

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Package callr updated to version 3.4.4 with previous version 3.4.3 dated 2020-03-28

Title: Call R from R
Description: It is sometimes useful to perform a computation in a separate R process, without affecting the current R process at all. This packages does exactly that.
Author: Gábor Csárdi [aut, cre, cph] (<https://orcid.org/0000-0001-7098-9676>), Winston Chang [aut], RStudio [cph, fnd], Mango Solutions [cph, fnd]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

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Package BGVAR updated to version 2.1.1 with previous version 2.1.0 dated 2020-09-07

Title: Bayesian Global Vector Autoregressions
Description: Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 <doi:10.1002/jae.2504>. Post-processing functions allow for doing predictions, structurally identify the model with short-run or sign-restrictions and compute impulse response functions, historical decompositions and forecast error variance decompositions. Plotting functions are also available.
Author: Maximilian Boeck [aut, cre] (<https://orcid.org/0000-0001-6024-8305>), Martin Feldkircher [aut] (<https://orcid.org/0000-0002-5511-9215>), Florian Huber [aut] (<https://orcid.org/0000-0002-2896-7921>), Christopher Sims [ctb]
Maintainer: Maximilian Boeck <maximilian.boeck@wu.ac.at>

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Package ActiveDriverWGS updated to version 1.1.0 with previous version 1.0.1 dated 2019-03-22

Title: A Driver Discovery Tool for Cancer Whole Genomes
Description: A method for finding an enrichment of cancer simple somatic mutations (SNVs and Indels) in functional elements across the human genome. 'ActiveDriverWGS' detects coding and noncoding driver elements using whole genome sequencing data. The method is part of the following publication: Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction Networks. Molecular Cell (2020) <doi:10.1016/j.molcel.2019.12.027>.
Author: Juri Reimand [aut, cre], Helen Zhu [aut]
Maintainer: Juri Reimand <juri.reimand@utoronto.ca>

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Package MortalityTables updated to version 2.0.1 with previous version 2.0 dated 2020-08-26

Title: A Framework for Various Types of Mortality / Life Tables
Description: Classes to implement and plot cohort life tables for actuarial calculations. In particular, birth-year dependent mortality tables using a yearly trend to extrapolate from a base year are implemented, as well as period life table, cohort life tables using an age shift, and merged life tables.
Author: Reinhold Kainhofer [aut, cre]
Maintainer: Reinhold Kainhofer <reinhold@kainhofer.com>

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Package GJRM updated to version 0.2-3 with previous version 0.2-2 dated 2020-02-07

Title: Generalised Joint Regression Modelling
Description: Routines for fitting various joint (and univariate) regression models, with several types of covariate effects, in the presence of equations' errors association, endogeneity, non-random sample selection or partial observability.
Author: Giampiero Marra <giampiero.marra@ucl.ac.uk> and Rosalba Radice <rosalba.radice@city.ac.uk>
Maintainer: Giampiero Marra <giampiero.marra@ucl.ac.uk>

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More information about GJRM at CRAN
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Package LabourMarketAreas updated to version 3.2.5 with previous version 3.2.4 dated 2020-03-03

Title: Identification, Tuning, Visualisation and Analysis of Labour Market Areas
Description: Produces Labour Market Areas from commuting flows available at elementary territorial units. It provides tools for automatic tuning based on spatial contiguity. It also allows for statistical analyses and visualisation of the new functional geography.
Author: Daniela Ichim, Luisa Franconi, Michele D'Alo', Guido van den Heuvel
Maintainer: Luisa Franconi <franconi@istat.it>

Diff between LabourMarketAreas versions 3.2.4 dated 2020-03-03 and 3.2.5 dated 2020-09-07

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Package DescTools updated to version 0.99.38 with previous version 0.99.37 dated 2020-07-10

Title: Tools for Descriptive Statistics
Description: A collection of miscellaneous basic statistic functions and convenience wrappers for efficiently describing data. The author's intention was to create a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. The package contains furthermore functions to produce documents using MS Word (or PowerPoint) and functions to import data from Excel. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'BigCamelCase' style was consequently applied to functions borrowed from contributed R packages as well.
Author: Andri Signorell [aut, cre], Ken Aho [ctb], Andreas Alfons [ctb], Nanina Anderegg [ctb], Tomas Aragon [ctb], Chandima Arachchige [ctb], Antti Arppe [ctb], Adrian Baddeley [ctb], Kamil Barton [ctb], Ben Bolker [ctb], Hans W. Borchers [ctb], Frederico Caeiro [ctb], Stephane Champely [ctb], Daniel Chessel [ctb], Leanne Chhay [ctb], Clint Cummins [ctb], Michael Dewey [ctb], Harold C. Doran [ctb], Stephane Dray [ctb], Charles Dupont [ctb], Dirk Eddelbuettel [ctb], Claus Ekstrom [ctb], Martin Elff [ctb], Jeff Enos [ctb], Richard W. Farebrother [ctb], John Fox [ctb], Romain Francois [ctb], Michael Friendly [ctb], Tal Galili [ctb], Matthias Gamer [ctb], Joseph L. Gastwirth [ctb], Vilmantas Gegzna [ctb], Yulia R. Gel [ctb], Juergen Gross [ctb], Gabor Grothendieck [ctb], Frank E. Harrell Jr [ctb], Richard Heiberger [ctb], Michael Hoehle [ctb], Christian W. Hoffmann [ctb], Soeren Hojsgaard [ctb], Torsten Hothorn [ctb], Markus Huerzeler [ctb], Wallace W. Hui [ctb], Pete Hurd [ctb], Rob J. Hyndman [ctb], Christopher Jackson [ctb], Matthias Kohl [ctb], Mikko Korpela [ctb], Max Kuhn [ctb], Detlew Labes [ctb], Friederich Leisch [ctb], Jim Lemon [ctb], Dong Li [ctb], Martin Maechler [ctb], Arni Magnusson [ctb], Ben Mainwaring [ctb], Daniel Malter [ctb], George Marsaglia [ctb], John Marsaglia [ctb], Alina Matei [ctb], David Meyer [ctb], Weiwen Miao [ctb], Giovanni Millo [ctb], Yongyi Min [ctb], David Mitchell [ctb], Franziska Mueller [ctb], Markus Naepflin [ctb], Daniel Navarro [ctb], Henric Nilsson [ctb], Klaus Nordhausen [ctb], Derek Ogle [ctb], Hong Ooi [ctb], Nick Parsons [ctb], Sandrine Pavoine [ctb], Tony Plate [ctb], Luke Prendergast [ctb], Roland Rapold [ctb], William Revelle [ctb], Tyler Rinker [ctb], Brian D. Ripley [ctb], Caroline Rodriguez [ctb], Nathan Russell [ctb], Nick Sabbe [ctb], Venkatraman E. Seshan [ctb], Michael Smithson [ctb], Greg Snow [ctb], Karline Soetaert [ctb], Werner A. Stahel [ctb], Alec Stephenson [ctb], Mark Stevenson [ctb], Ralf Stubner [ctb], Matthias Templ [ctb], Duncan Temple Lang [ctb], Terry Therneau [ctb], Yves Tille [ctb], Luis Torgo [ctb], Adrian Trapletti [ctb], Joshua Ulrich [ctb], Kevin Ushey [ctb], Jeremy VanDerWal [ctb], Bill Venables [ctb], John Verzani [ctb], Pablo J. Villacorta Iglesias [ctb], Gregory R. Warnes [ctb], Stefan Wellek [ctb], Hadley Wickham [ctb], Rand R. Wilcox [ctb], Peter Wolf [ctb], Daniel Wollschlaeger [ctb], Joseph Wood [ctb], Ying Wu [ctb], Thomas Yee [ctb], Achim Zeileis [ctb]
Maintainer: Andri Signorell <andri@signorell.net>

Diff between DescTools versions 0.99.37 dated 2020-07-10 and 0.99.38 dated 2020-09-07

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New package SNPassoc with initial version 2.0-0
Package: SNPassoc
Version: 2.0-0
Date: 2020-09-07
Depends: R (>= 4.0.0)
Imports: haplo.stats, mvtnorm, parallel, survival, tidyr, plyr, ggplot2, poisbinom
Suggests: testthat, knitr, BiocStyle, rmarkdown, biomaRt
Title: SNPs-Based Whole Genome Association Studies
Author: Juan R Gonzalez and Victor Moreno
Maintainer: Juan R Gonzalez <juanr.gonzalez@isglobal.org>
Description: Functions to perform most of the common analysis in genome association studies are implemented. These analyses include descriptive statistics and exploratory analysis of missing values, calculation of Hardy-Weinberg equilibrium, analysis of association based on generalized linear models (either for quantitative or binary traits), and analysis of multiple SNPs (haplotype and epistasis analysis). Permutation test and related tests (sum statistic and truncated product) are also implemented. Max-statistic and genetic risk-allele score exact distributions are also possible to be estimated. The methods are described in Gonzalez JR et al. (2007) <doi: 10.1093/bioinformatics/btm025>.
License: GPL (>= 2)
URL: https://brge.isglobal.org
Encoding: latin1
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2020-09-07 13:00:55 UTC; jrgonzalez
Repository: CRAN
Date/Publication: 2020-09-07 16:10:03 UTC

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Package CLA updated to version 0.96-0 with previous version 0.95-1 dated 2019-05-11

Title: Critical Line Algorithm in Pure R
Description: Implements 'Markowitz' Critical Line Algorithm ('CLA') for classical mean-variance portfolio optimization, see Markowitz (1952) <doi:10.2307/2975974>. Care has been taken for correctness in light of previous buggy implementations.
Author: Yanhao Shi <syhelena@163.com>, Martin Maechler <maechler@stat.math.ethz.ch>
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

Diff between CLA versions 0.95-1 dated 2019-05-11 and 0.96-0 dated 2020-09-07

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Package ROCnReg updated to version 1.0-3 with previous version 1.0-2 dated 2020-07-05

Title: ROC Curve Inference with and without Covariates
Description: Estimates the pooled (unadjusted) Receiver Operating Characteristic (ROC) curve, the covariate-adjusted ROC (AROC) curve, and the covariate-specific/conditional ROC (cROC) curve by different methods, both Bayesian and frequentist. Also, it provides functions to obtain ROC-based optimal cutpoints utilizing several criteria. Based on Erkanli, A. et al. (2006) <doi:10.1002/sim.2496>; Faraggi, D. (2003) <doi:10.1111/1467-9884.00350>; Gu, J. et al. (2008) <doi:10.1002/sim.3366>; Inacio de Carvalho, V. et al. (2013) <doi:10.1214/13-BA825>; Inacio de Carvalho, V., and Rodriguez-Alvarez, M.X. (2018) <arXiv:1806.00473>; Janes, H., and Pepe, M.S. (2009) <doi:10.1093/biomet/asp002>; Pepe, M.S. (1998) <http://www.jstor.org/stable/2534001?seq=1>; Rodriguez-Alvarez, M.X. et al. (2011a) <doi:10.1016/j.csda.2010.07.018>; Rodriguez-Alvarez, M.X. et al. (2011a) <doi:10.1007/s11222-010-9184-1>. Please see Rodriguez-Alvarez, M.X. and Inacio, V. (20208) <arXiv:2003.13111> for more details.
Author: Maria Xose Rodriguez-Alvarez [aut, cre] (<https://orcid.org/0000-0002-1329-9238>), Vanda Inacio [aut] (<https://orcid.org/0000-0001-8084-1616>)
Maintainer: Maria Xose Rodriguez-Alvarez <mxrodriguez@bcamath.org>

Diff between ROCnReg versions 1.0-2 dated 2020-07-05 and 1.0-3 dated 2020-09-07

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Package bootComb updated to version 1.0.0 with previous version 0.2.0 dated 2020-08-20

Title: Combine Parameter Estimates via Parametric Bootstrap
Description: Propagate uncertainty from several estimates when combining these estimates via a function. This is done by using the parametric bootstrap to simulate values from the distribution of each estimate to build up an empirical distribution of the combined parameter. Finally either the percentile method is used or the highest density interval is chosen to derive a confidence interval for the combined parameter with the desired coverage. References: Davison and Hinkley (1997,ISBN:0-521-57471-4) for the parametric bootstrap and percentile method, Gelman et al. (2014,ISBN:978-1-4398-4095-5) for the highest density interval, Stockdale et al. (2020)<doi:10.1016/j.jhep.2020.04.008> for an example of combining conditional prevalences.
Author: Marc Henrion [aut, cre] (<https://orcid.org/0000-0003-1242-839X>)
Maintainer: Marc Henrion <mhenrion@mlw.mw>

Diff between bootComb versions 0.2.0 dated 2020-08-20 and 1.0.0 dated 2020-09-07

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Package vader updated to version 0.2.1 with previous version 0.2.0 dated 2020-09-04

Title: Valence Aware Dictionary and sEntiment Reasoner (VADER)
Description: A lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains. Hutto & Gilbert (2014) <https://www.aaai.org/ocs/index.php/ICWSM/ICWSM14/paper/view/8109/8122>.
Author: Katherine Roehrick [aut, cre]
Maintainer: Katherine Roehrick <kr.gitcode@gmail.com>

Diff between vader versions 0.2.0 dated 2020-09-04 and 0.2.1 dated 2020-09-07

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Package pkgdown updated to version 1.6.0 with previous version 1.5.1 dated 2020-04-09

Title: Make Static HTML Documentation for a Package
Description: Generate an attractive and useful website from a source package. 'pkgdown' converts your documentation, vignettes, 'README', and more to 'HTML' making it easy to share information about your package online.
Author: Hadley Wickham [aut, cre] (<https://orcid.org/0000-0003-4757-117X>), Jay Hesselberth [aut] (<https://orcid.org/0000-0002-6299-179X>), RStudio [cph, fnd]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package MCAvariants updated to version 2.5 with previous version 2.2 dated 2019-01-21

Title: Multiple Correspondence Analysis Variants
Description: Provides two variants of multiple correspondence analysis (ca): multiple ca and ordered multiple ca via orthogonal polynomials of Emerson.
Author: Rosaria Lombardo and Eric J Beh
Maintainer: Rosaria Lombardo <rosaria.lombardo@unicampania.it>

Diff between MCAvariants versions 2.2 dated 2019-01-21 and 2.5 dated 2020-09-07

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Package inspectdf updated to version 0.0.9 with previous version 0.0.8 dated 2020-06-25

Title: Inspection, Comparison and Visualisation of Data Frames
Description: A collection of utilities for columnwise summary, comparison and visualisation of data frames. Functions report missingness, categorical levels, numeric distribution, correlation, column types and memory usage.
Author: Alastair Rushworth [aut, cre], David Wilkins [ctb]
Maintainer: Alastair Rushworth <alastairmrushworth@gmail.com>

Diff between inspectdf versions 0.0.8 dated 2020-06-25 and 0.0.9 dated 2020-09-07

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Package extraDistr updated to version 1.9.1 with previous version 1.8.11 dated 2019-06-10

Title: Additional Univariate and Multivariate Distributions
Description: Density, distribution function, quantile function and random generation for a number of univariate and multivariate distributions. This package implements the following distributions: Bernoulli, beta-binomial, beta-negative binomial, beta prime, Bhattacharjee, Birnbaum-Saunders, bivariate normal, bivariate Poisson, categorical, Dirichlet, Dirichlet-multinomial, discrete gamma, discrete Laplace, discrete normal, discrete uniform, discrete Weibull, Frechet, gamma-Poisson, generalized extreme value, Gompertz, generalized Pareto, Gumbel, half-Cauchy, half-normal, half-t, Huber density, inverse chi-squared, inverse-gamma, Kumaraswamy, Laplace, location-scale t, logarithmic, Lomax, multivariate hypergeometric, multinomial, negative hypergeometric, non-standard beta, normal mixture, Poisson mixture, Pareto, power, reparametrized beta, Rayleigh, shifted Gompertz, Skellam, slash, triangular, truncated binomial, truncated normal, truncated Poisson, Tukey lambda, Wald, zero-inflated binomial, zero-inflated negative binomial, zero-inflated Poisson.
Author: Tymoteusz Wolodzko
Maintainer: Tymoteusz Wolodzko <twolodzko+extraDistr@gmail.com>

Diff between extraDistr versions 1.8.11 dated 2019-06-10 and 1.9.1 dated 2020-09-07

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Package censusapi updated to version 0.7.0 with previous version 0.6.0 dated 2019-04-13

Title: Retrieve Data from the Census APIs
Description: A wrapper for the U.S. Census Bureau APIs that returns data frames of Census data and metadata. Available datasets include the Decennial Census, American Community Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, Population Estimates and Projections, and more.
Author: Hannah Recht [aut, cre]
Maintainer: Hannah Recht <censusapi.rstats@gmail.com>

Diff between censusapi versions 0.6.0 dated 2019-04-13 and 0.7.0 dated 2020-09-07

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Package BioVenn updated to version 1.0.1 with previous version 1.0.0 dated 2020-09-01

Title: Create Area-Proportional Venn Diagrams from Biological Lists
Description: Creates an area-proportional Venn diagram of 2 or 3 circles. 'BioVenn' is the only R package that can automatically generate an accurate area-proportional Venn diagram by having only lists of (biological) identifiers as input. Also offers the option to map Entrez and/or Affymetrix IDs to Ensembl IDs. In SVG mode, text and numbers can be dragged and dropped. Based on the BioVenn web interface available at <https://www.biovenn.nl>. Hulsen et al. (2008) <doi:10.1186/1471-2164-9-488>.
Author: Tim Hulsen [aut, cre] (<https://orcid.org/0000-0002-0208-8443>)
Maintainer: Tim Hulsen <thulsen@gmail.com>

Diff between BioVenn versions 1.0.0 dated 2020-09-01 and 1.0.1 dated 2020-09-07

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More information about BioVenn at CRAN
Permanent link

New package BASS with initial version 1.2.2
Package: BASS
Version: 1.2.2
Date: 2020-08-31
Title: Bayesian Adaptive Spline Surfaces
Description: Bayesian fitting and sensitivity analysis methods for adaptive spline surfaces described in <doi:10.18637/jss.v094.i08>. Built to handle continuous and categorical inputs as well as functional or scalar output. An extension of the methodology in Denison, Mallick and Smith (1998) <doi:10.1023/A:1008824606259>.
Authors@R: c(person("Devin", "Francom", role = c("aut", "cre"), email = "devinfrancom@gmail.com"), person("Bruno", "Sanso", role = "ths"))
License: GPL-3
Suggests: knitr, testthat (>= 2.1.0), parallel, MASS, formatR
VignetteBuilder: knitr
Imports: truncdist, hypergeo
RoxygenNote: 7.1.0
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-08-31 15:03:13 UTC; dfrancom
Author: Devin Francom [aut, cre], Bruno Sanso [ths]
Maintainer: Devin Francom <devinfrancom@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-07 13:20:03 UTC

More information about BASS at CRAN
Permanent link

Package tgp updated to version 2.4-16 with previous version 2.4-14 dated 2016-02-07

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.
Author: Robert B. Gramacy <rbg@vt.edu> and Matt A. Taddy <mataddy@amazon.com>
Maintainer: Robert B. Gramacy <rbg@vt.edu>

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More information about tgp at CRAN
Permanent link

Package shiny.semantic updated to version 0.4.0 with previous version 0.3.0 dated 2020-03-13

Title: 'FomanticUI' Support for Shiny
Description: Creating a great user interface for your Shiny apps can be a hassle, especially if you want to work purely in R and don't want to use, for instance HTML templates. This package adds support for a powerful UI library 'FomanticUI' - <https://fomantic-ui.com/> (before: Semantic). It also supports universal UI input binding that works with various DOM elements.
Author: Filip Stachura [aut], Dominik Krzeminski [cre], Krystian Igras [aut], Adam Forys [aut], Paweł Przytuła [aut], Jakub Chojna [aut], Olga Mierzwa-Sulima [aut], Ashley Baldry [ctb], Jakub Chojna [ctb], Olga Mierzwa-Sulima [ctb], Pedro Manuel Coutinho da Silva [ctb], Paweł Przytuła [ctb], Kamil Żyła [ctb], Appsilon Sp. z o.o. [cph]
Maintainer: Dominik Krzeminski <dominik@appsilon.com>

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More information about shiny.semantic at CRAN
Permanent link

Package rpact updated to version 3.0.0 with previous version 2.0.6 dated 2019-12-12

Title: Confirmatory Adaptive Clinical Trial Design and Analysis
Description: Design and analysis of confirmatory adaptive clinical trials with continuous, binary, and survival endpoints according to the methods described in the monograph by Wassmer and Brannath (2016) <doi:10.1007/978-3-319-32562-0>. This includes classical group sequential as well as multi-stage adaptive hypotheses tests that are based on the combination testing principle.
Author: Gernot Wassmer [aut], Friedrich Pahlke [aut, cre]
Maintainer: Friedrich Pahlke <friedrich.pahlke@rpact.com>

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Package pagemap updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-04

Title: Create Mini Map for Web Pages
Description: Quickly and easily add a mini map to your 'rmarkdown' html documents.
Author: Wei Su [aut, cre], Lars Jung [aut, cph] (pagemap library in htmlwidgets/lib, https://github.com/lrsjng/pagemap)
Maintainer: Wei Su <swsoyee@gmail.com>

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Package officer updated to version 0.3.14 with previous version 0.3.13 dated 2020-08-29

Title: Manipulation of Microsoft Word and PowerPoint Documents
Description: Access and manipulate 'Microsoft Word' and 'Microsoft PowerPoint' documents from R. The package focuses on tabular and graphical reporting from R; it also provides two functions that let users get document content into data objects. A set of functions lets add and remove images, tables and paragraphs of text in new or existing documents. When working with 'PowerPoint' presentations, slides can be added or removed; shapes inside slides can also be added or removed. When working with 'Word' documents, a cursor can be used to help insert or delete content at a specific location in the document. The package does not require any installation of Microsoft products to be able to write Microsoft files.
Author: David Gohel [aut, cre], Frank Hangler [ctb] (function body_replace_all_text), Liz Sander [ctb] (several documentation fixes), Anton Victorson [ctb] (fixes xml structures), Jon Calder [ctb] (update vignettes), John Harrold [ctb] (fuction annotate_base), John Muschelli [ctb] (google doc compatibility)
Maintainer: David Gohel <david.gohel@ardata.fr>

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Package lacunaritycovariance updated to version 1.1-0 with previous version 1.0-13 dated 2020-01-31

Title: Gliding Box Lacunarity and Other Metrics for 2D Random Closed Sets
Description: Functions for estimating the gliding box lacunarity (GBL), covariance, and pair-correlation of a random closed set (RACS) in 2D from a binary coverage map (e.g. presence-absence land cover maps). Contains a number of newly-developed covariance-based estimators of GBL (Hingee et al., 2019) <doi:10.1007/s13253-019-00351-9> and balanced estimators, proposed by Picka (2000) <http://www.jstor.org/stable/1428408>, for covariance, centred covariance, and pair-correlation. Also contains methods for estimating contagion-like properties of RACS and simulating 2D Boolean models. Binary coverage maps are usually represented as raster images with pixel values of TRUE, FALSE or NA, with NA representing unobserved pixels. A demo for extracting such a binary map from a geospatial data format is provided. Binary maps may also be represented using polygonal sets as the foreground, however for most computations such maps are converted into raster images. The package is based on research conducted during the author's PhD studies.
Author: Kassel Liam Hingee
Maintainer: Kassel Liam Hingee <kassel.hingee@gmail.com>

Diff between lacunaritycovariance versions 1.0-13 dated 2020-01-31 and 1.1-0 dated 2020-09-07

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Package ggpmisc updated to version 0.3.6 with previous version 0.3.5 dated 2020-06-01

Title: Miscellaneous Extensions to 'ggplot2'
Description: Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Specialization of method ggplot(): accept and convert on the fly time series data. Geom: "table", "plot" and "grob" add insets to plots using native data coordinates, while "table_npc", "plot_npc" and "grob_npc" do the same using "npc" coordinates through new aesthetics "npcx" and "npcy". Statistics: locate and tag peaks and valleys; count observations in different quadrants of a plot; select observations based on 2D density; label with the equation of a polynomial fitted with lm() or other types of models; labels with P-value, R^2 or adjusted R^2 or information criteria for fitted models; label with ANOVA table for fitted models; label with summary for fitted models. Model fit classes for which suitable methods are provided by package 'broom' are supported. Scales and stats to build volcano and quadrant plots based on outcomes, fold changes, p-values and false discovery rates.
Author: Pedro J. Aphalo [aut, cre] (<https://orcid.org/0000-0003-3385-972X>), Kamil Slowikowski [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

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New package incidence2 with initial version 0.1.0
Package: incidence2
Type: Package
Title: Compute, Handle and Plot Incidence of Dated Events
Version: 0.1.0
Authors@R: c( person("Tim", "Taylor", role = c("aut", "cre"), email = "tim.taylor@hiddenelephants.co.uk", comment = c(ORCID = "0000-0002-8587-7113")), person("Thibaut", "Jombart", role = c("aut"), email = "thibautjombart@gmail.com"), person("Zhian N.", "Kamvar", role = "aut", email = "zkamvar@gmail.com", comment = c(ORCID = "0000-0003-1458-7108")), person("Rich", "FitzJohn", role = "aut", email = "rich.fitzjohn@gmail.com"), person("Jun", "Cai", role = "ctb", email = "cai-j12@mails.tsinghua.edu.cn", comment = c(ORCID = "0000-0001-9495-1226")), person("Sangeeta", "Bhatia", role = "ctb", email = "sangeetabhatia03@gmail.com"), person("Jakob", "Schumacher", role = "ctb"), person("Juliet R.C.", "Pulliam", role = "ctb", email = "pulliam@sun.ac.za", comment = c(ORCID = "0000-0003-3314-8223")) )
Description: Provides functions and classes to compute, handle and visualise incidence from dated events for a defined time interval. Dates can be provided in various standard formats. The class 'incidence2' is used to store computed incidence and can be easily manipulated, subsetted, and plotted. This package is part of the RECON (<https://www.repidemicsconsortium.org/>) toolkit for outbreak analysis.
Encoding: UTF-8
License: MIT + file LICENSE
URL: https://github.com/reconhub/incidence2
BugReports: https://github.com/reconhub/incidence2/issues
RoxygenNote: 7.1.1
Imports: ggplot2, aweek (>= 0.2.0), rlang, dplyr (>= 1.0.0), tibble, ellipsis, vctrs, magrittr, pillar
Suggests: outbreaks, testthat, knitr, rmarkdown, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-08-27 07:22:47 UTC; tim
Author: Tim Taylor [aut, cre] (<https://orcid.org/0000-0002-8587-7113>), Thibaut Jombart [aut], Zhian N. Kamvar [aut] (<https://orcid.org/0000-0003-1458-7108>), Rich FitzJohn [aut], Jun Cai [ctb] (<https://orcid.org/0000-0001-9495-1226>), Sangeeta Bhatia [ctb], Jakob Schumacher [ctb], Juliet R.C. Pulliam [ctb] (<https://orcid.org/0000-0003-3314-8223>)
Maintainer: Tim Taylor <tim.taylor@hiddenelephants.co.uk>
Repository: CRAN
Date/Publication: 2020-09-07 12:40:15 UTC

More information about incidence2 at CRAN
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Package gensvm updated to version 0.1.4 with previous version 0.1.3 dated 2019-12-02

Title: A Generalized Multiclass Support Vector Machine
Description: The GenSVM classifier is a generalized multiclass support vector machine (SVM). This classifier aims to find decision boundaries that separate the classes with as wide a margin as possible. In GenSVM, the loss function is very flexible in the way that misclassifications are penalized. This allows the user to tune the classifier to the dataset at hand and potentially obtain higher classification accuracy than alternative multiclass SVMs. Moreover, this flexibility means that GenSVM has a number of other multiclass SVMs as special cases. One of the other advantages of GenSVM is that it is trained in the primal space, allowing the use of warm starts during optimization. This means that for common tasks such as cross validation or repeated model fitting, GenSVM can be trained very quickly. Based on: G.J.J. van den Burg and P.J.F. Groenen (2018) <https://www.jmlr.org/papers/v17/14-526.html>.
Author: Gertjan van den Burg [aut, cre], Patrick Groenen [ctb]
Maintainer: Gertjan van den Burg <gertjanvandenburg@gmail.com>

Diff between gensvm versions 0.1.3 dated 2019-12-02 and 0.1.4 dated 2020-09-07

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Package BGVAR updated to version 2.1.0 with previous version 2.0.1 dated 2020-06-24

Title: Bayesian Global Vector Autoregressions
Description: Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 <doi:10.1002/jae.2504>. Post-processing functions allow for doing predictions, structurally identify the model with short-run or sign-restrictions and compute impulse response functions, historical decompositions and forecast error variance decompositions. Plotting functions are also available.
Author: Maximilian Boeck [aut, cre] (<https://orcid.org/0000-0001-6024-8305>), Martin Feldkircher [aut] (<https://orcid.org/0000-0002-5511-9215>), Florian Huber [aut] (<https://orcid.org/0000-0002-2896-7921>), Christopher Sims [ctb]
Maintainer: Maximilian Boeck <maximilian.boeck@wu.ac.at>

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Package rgeos updated to version 0.5-5 with previous version 0.5-3 dated 2020-05-08

Title: Interface to Geometry Engine - Open Source ('GEOS')
Description: Interface to Geometry Engine - Open Source ('GEOS') using the C 'API' for topology operations on geometries. The 'GEOS' library is external to the package, and, when installing the package from source, must be correctly installed first. Windows and Mac Intel OS X binaries are provided on 'CRAN'. ('rgeos' >= 0.5-1): Up to and including 'GEOS' 3.7.1, topological operations succeeded with some invalid geometries for which the same operations fail from and including 'GEOS' 3.7.2. The 'checkValidity=' argument defaults and structure have been changed, from default FALSE to integer default '0L' for 'GEOS' < 3.7.2 (no check), '1L' 'GEOS' >= 3.7.2 (check and warn). A value of '2L' is also provided that may be used, assigned globally using 'set_RGEOS_CheckValidity(2L)', or locally using the 'checkValidity=2L' argument, to attempt zero-width buffer repair if invalid geometries are found. The previous default (FALSE, now '0L') is fastest and used for 'GEOS' < 3.7.2, but will not warn users of possible problems before the failure of topological operations that previously succeeded. From 'GEOS' 3.8.0, repair of geometries may also be attempted using 'gMakeValid()', which may, however, return a collection of geometries of different types.
Author: Roger Bivand [cre, aut] (<https://orcid.org/0000-0003-2392-6140>), Colin Rundel [aut], Edzer Pebesma [ctb], Rainer Stuetz [ctb], Karl Ove Hufthammer [ctb], Patrick Giraudoux [ctb], Martin Davis [cph, ctb], Sandro Santilli [cph, ctb]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

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Package PoissonBinomial updated to version 1.1.3 with previous version 1.1.2 dated 2020-09-01

Title: Efficient Computation of Ordinary and Generalized Poisson Binomial Distributions
Description: Efficient implementations of multiple exact and approximate methods as described in Hong (2013) <doi:10.1016/j.csda.2012.10.006>, Biscarri, Zhao & Brunner (2018) <doi:10.1016/j.csda.2018.01.007> and Zhang, Hong & Balakrishnan (2018) <doi:10.1080/00949655.2018.1440294> for computing the probability mass, cumulative distribution and quantile functions, as well as generating random numbers for both the ordinary and generalized Poisson binomial distribution.
Author: Florian Junge [aut, cre]
Maintainer: Florian Junge <florian.junge@h-da.de>

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Package vivo updated to version 0.2.1 with previous version 0.2.0 dated 2020-07-02

Title: Variable Importance via Oscillations
Description: Provides an easy to calculate local variable importance measure based on Ceteris Paribus profile and global variable importance measure based on Partial Dependence Profiles.
Author: Anna Kozak [aut, cre], Przemyslaw Biecek [aut, ths]
Maintainer: Anna Kozak <anna1993kozak@gmail.com>

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Package Seurat updated to version 3.2.1 with previous version 3.2.0 dated 2020-07-16

Title: Tools for Single Cell Genomics
Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031> for more details.
Author: Rahul Satija [aut] (<https://orcid.org/0000-0001-9448-8833>), Andrew Butler [aut] (<https://orcid.org/0000-0003-3608-0463>), Paul Hoffman [aut, cre] (<https://orcid.org/0000-0002-7693-8957>), Tim Stuart [aut] (<https://orcid.org/0000-0002-3044-0897>), Jeff Farrell [ctb], Shiwei Zheng [ctb] (<https://orcid.org/0000-0001-6682-6743>), Christoph Hafemeister [ctb] (<https://orcid.org/0000-0001-6365-8254>), Patrick Roelli [ctb], Yuhan Hao [ctb] (<https://orcid.org/0000-0002-1810-0822>)
Maintainer: Paul Hoffman <nygcSatijalab@nygenome.org>

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Package RcmdrPlugin.BWS1 updated to version 0.1-3 with previous version 0.1-2 dated 2020-06-19

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

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Package prioritylasso updated to version 0.2.4 with previous version 0.2.3 dated 2019-12-17

Title: Analyzing Multiple Omics Data with an Offset Approach
Description: Fits successive Lasso models for several blocks of (omics) data with different priorities and takes the predicted values as an offset for the next block.
Author: Simon Klau, Roman Hornung, Alina Bauer
Maintainer: Roman Hornung <hornung@ibe.med.uni-muenchen.de>

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Package OpenRepGrid.ic updated to version 0.3.1 with previous version 0.3.0 dated 2020-07-30

Title: Interpretive Clustering for Repertory Grids
Description: Shiny UI to identify cliques of related constructs in repertory grid data. See Burr, King, & Heckmann (2020) <doi:10.1080/14780887.2020.1794088> for a description of the interpretive clustering (IC) method.
Author: Mark Heckmann [aut, cre, cph] (<https://orcid.org/0000-0002-0736-7417>), Viv Burr [aut], Nigel King [aut]
Maintainer: Mark Heckmann <heckmann.mark@gmail.com>

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Package insight updated to version 0.9.5 with previous version 0.9.1 dated 2020-08-26

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

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Package HH updated to version 3.1-42 with previous version 3.1-40 dated 2020-03-03

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

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More information about HH at CRAN
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Package FCPS updated to version 1.2.4 with previous version 1.2.3 dated 2020-06-26

Title: Fundamental Clustering Problems Suite
Description: Many conventional clustering algorithms are provided in this package with consistent input and output, which enables the user to try out algorithms swiftly. Additionally, 26 statistical approaches for the estimation of the number of clusters as well as the the mirrored density plot (MD-plot) of clusterability are implemented. Moreover, the fundamental clustering problems suite (FCPS) offers a variety of clustering challenges any algorithm should handle when facing real world data, see Thrun, M.C., Ultsch A.: "Clustering Benchmark Datasets Exploiting the Fundamental Clustering Problems" (2020), Data in Brief, <DOI:10.1016/j.dib.2020.105501>.
Author: Michael Thrun [aut, cre, cph] (<https://orcid.org/0000-0001-9542-5543>), Peter Nahrgang [ctr, ctb], Felix Pape [ctr, ctb], Vasyl Pihur [ctb], Guy Brock [ctb], Susmita Datta [ctb], Somnath Datta [ctb], Luis Winckelmann [com], Alfred Ultsch [dtc, ctb], Quirin Stier [ctb, rev]
Maintainer: Michael Thrun <m.thrun@gmx.net>

Diff between FCPS versions 1.2.3 dated 2020-06-26 and 1.2.4 dated 2020-09-07

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Package estimatr updated to version 0.26.0 with previous version 0.24.0 dated 2020-09-02

Title: Fast Estimators for Design-Based Inference
Description: Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regression, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>.
Author: Graeme Blair [aut, cre], Jasper Cooper [aut], Alexander Coppock [aut], Macartan Humphreys [aut], Luke Sonnet [aut], Neal Fultz [ctb], Lily Medina [ctb], Russell Lenth [ctb]
Maintainer: Graeme Blair <graeme.blair@ucla.edu>

Diff between estimatr versions 0.24.0 dated 2020-09-02 and 0.26.0 dated 2020-09-07

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Package DALEXtra updated to version 2.0 with previous version 1.3.2 dated 2020-07-28

Title: Extension for 'DALEX' Package
Description: Provides wrapper of various machine learning models. In applied machine learning, there is a strong belief that we need to strike a balance between interpretability and accuracy. However, in field of the interpretable machine learning, there are more and more new ideas for explaining black-box models, that are implemented in 'R'. 'DALEXtra' creates 'DALEX' Biecek (2018) <arXiv:1806.08915> explainer for many type of models including those created using 'python' 'scikit-learn' and 'keras' libraries, and 'java' 'h2o' library. Important part of the package is Champion-Challenger analysis and innovative approach to model performance across subsets of test data presented in Funnel Plot. Third branch of 'DALEXtra' package is aspect importance analysis that provides instance-level explanations for the groups of explanatory variables.
Author: Szymon Maksymiuk [aut, cre] (<https://orcid.org/0000-0002-3120-1601>), Przemyslaw Biecek [aut] (<https://orcid.org/0000-0001-8423-1823>), Anna Kozak [ctb], Hubert Baniecki [ctb]
Maintainer: Szymon Maksymiuk <sz.maksymiuk@gmail.com>

Diff between DALEXtra versions 1.3.2 dated 2020-07-28 and 2.0 dated 2020-09-07

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New package SteinerNet with initial version 3.1.0
Package: SteinerNet
Type: Package
Version: 3.1.0
Date: 2020-08-21
Title: Steiner Tree Approach for Graph Analysis
Description: A set of functions for finding and analysing Steiner trees. It has applications in biological pathway network analysis. Sadeghi (2013) <doi:10.1186/1471-2105-14-144>.
Author: Afshin Sadeghi <sadeghi.afshin@gmail.com>
Maintainer: Aleksei Krasikov <krasikov.as@phystech.edu>
URL: https://github.com/krashkov/SteinerNet
BugReports: https://github.com/krashkov/SteinerNet/issues
Depends: R (>= 3.1.0), igraph (>= 0.6.0)
Imports: grDevices, stats, utils, graphics
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
License: GPL-3
Repository: CRAN
NeedsCompilation: no
Encoding: UTF-8
RoxygenNote: 7.1.1
Packaged: 2020-09-05 01:47:32 UTC; krashkov
Date/Publication: 2020-09-07 09:50:08 UTC

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Package RcppEnsmallen updated to version 0.2.14.2.1 with previous version 0.2.14.1.1 dated 2020-08-27

Title: Header-Only C++ Mathematical Optimization Library for 'Armadillo'
Description: 'Ensmallen' is a templated C++ mathematical optimization library (by the 'MLPACK' team) that provides a simple set of abstractions for writing an objective function to optimize. Provided within are various standard and cutting-edge optimizers that include full-batch gradient descent techniques, small-batch techniques, gradient-free optimizers, and constrained optimization. The 'RcppEnsmallen' package includes the header files from the 'Ensmallen' library and pairs the appropriate header files from 'armadillo' through the 'RcppArmadillo' package. Therefore, users do not need to install 'Ensmallen' nor 'Armadillo' to use 'RcppEnsmallen'. Note that 'Ensmallen' is licensed under 3-Clause BSD, 'Armadillo' starting from 7.800.0 is licensed under Apache License 2, 'RcppArmadillo' (the 'Rcpp' bindings/bridge to 'Armadillo') is licensed under the GNU GPL version 2 or later. Thus, 'RcppEnsmallen' is also licensed under similar terms. Note that 'Ensmallen' requires a compiler that supports 'C++11' and 'Armadillo' 8.400 or later.
Author: James Joseph Balamuta [aut, cre, cph] (<https://orcid.org/0000-0003-2826-8458>), Dirk Eddelbuettel [aut, cph] (<https://orcid.org/0000-0001-6419-907X>)
Maintainer: James Joseph Balamuta <balamut2@illinois.edu>

Diff between RcppEnsmallen versions 0.2.14.1.1 dated 2020-08-27 and 0.2.14.2.1 dated 2020-09-07

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Package gradeR updated to version 1.0.9 with previous version 1.0.8 dated 2020-09-03

Title: Helps Grade Assignment Submissions that are R Scripts
Description: After being given the location of your students' submissions and a test file, the function runs each .R file, and evaluates the results from all the given tests. Results are neatly returned in a data frame that has a row for each student, and a column for each test.
Author: Taylor Brown [aut, cre]
Maintainer: Taylor Brown <trb5me@virginia.edu>

Diff between gradeR versions 1.0.8 dated 2020-09-03 and 1.0.9 dated 2020-09-07

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Package dynsurv updated to version 0.4-2 with previous version 0.4-1 dated 2020-08-28

Title: Dynamic Models for Survival Data
Description: Time-varying coefficient models for interval censored and right censored survival data including 1) Bayesian Cox model with time-independent, time-varying or dynamic coefficients for right censored and interval censored data studied by Sinha et al. (1999) <doi:10.1111/j.0006-341X.1999.00585.x> and Wang et al. (2013) <doi:10.1007/s10985-013-9246-8>, 2) Spline based time-varying coefficient Cox model for right censored data proposed by Perperoglou et al. (2006) <doi:10.1016/j.cmpb.2005.11.006>, and 3) Transformation model with time-varying coefficients for right censored data using estimating equations proposed by Peng and Huang (2007) <doi:10.1093/biomet/asm058>.
Author: Wenjie Wang [aut, cre] (<https://orcid.org/0000-0003-0363-3180>), Ming-Hui Chen [aut], Xiaojing Wang [aut], Jun Yan [aut] (<https://orcid.org/0000-0003-4401-7296>)
Maintainer: Wenjie Wang <wang@wwenjie.org>

Diff between dynsurv versions 0.4-1 dated 2020-08-28 and 0.4-2 dated 2020-09-07

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Package chemmodlab updated to version 1.1.0 with previous version 1.0.0 dated 2017-04-21

Title: A Cheminformatics Modeling Laboratory for Fitting and Assessing Machine Learning Models
Description: Contains a set of methods for fitting models and methods for validating the resulting models. The statistical methodologies comprise a comprehensive collection of approaches whose validity and utility have been accepted by experts in the Cheminformatics field. As promising new methodologies emerge from the statistical and data-mining communities, they will be incorporated into the laboratory. These methods are aimed at discovering quantitative structure-activity relationships (QSARs). However, the user can directly input their own choices of descriptors and responses, so the capability for comparing models is effectively unlimited.
Author: Jacqueline Hughes-Oliver [aut], Jeremy Ash [aut, cre], Atina Brooks [aut]
Maintainer: Jeremy Ash <jrash@ncsu.edu>

Diff between chemmodlab versions 1.0.0 dated 2017-04-21 and 1.1.0 dated 2020-09-07

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More information about chemmodlab at CRAN
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Package cgwtools updated to version 3.2 with previous version 3.0.1 dated 2019-02-12

Title: Miscellaneous Tools
Description: Functions for performing quick observations or evaluations of data, including a variety of ways to list objects by size, class, etc. In addition, functions which mimic Unix shell commands, including 'head', 'tail' ,'pushd' ,and 'popd'. The functions 'seqle' and 'reverse.seqle' mimic the base 'rle' but can search for linear sequences. The function 'splatnd' allows the user to generate zero-argument commands without the need for 'makeActiveBinding' .
Author: Carl Witthoft
Maintainer: Carl Witthoft <carl@witthoft.com>

Diff between cgwtools versions 3.0.1 dated 2019-02-12 and 3.2 dated 2020-09-07

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New package bmscstan with initial version 1.0.0
Package: bmscstan
Type: Package
Title: Bayesian Multilevel Single Case Models using 'Stan'
Version: 1.0.0
Authors@R: person("Michele", "Scandola", email = "michele.scandola@univr.it", role = c("aut", "cre"))
Description: Analyse single case analyses against a control group. Its purpose is to provide a flexible, with good power and low first type error approach that can manage at the same time controls' and patient's data. The use of Bayesian statistics allows to test both the alternative and null hypothesis. Scandola, M., & Romano, D. (2020, August 3). <doi:10.31234/osf.io/sajdq>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), rstan, logspline, bayesplot, LaplacesDemon, ggplot2
Imports: coda
VignetteBuilder: knitr
Suggests: reshape2, gridExtra, loo, mcmcse, bridgesampling, testthat, knitr, rmarkdown
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-01 08:48:27 UTC; michele
Author: Michele Scandola [aut, cre]
Maintainer: Michele Scandola <michele.scandola@univr.it>
Repository: CRAN
Date/Publication: 2020-09-07 09:30:02 UTC

More information about bmscstan at CRAN
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New package swfscAirDAS with initial version 0.2.1
Package: swfscAirDAS
Title: Southwest Fisheries Science Center Aerial DAS Data Processing
Version: 0.2.1
Authors@R: person("Sam", "Woodman", email = "sam.woodman@noaa.gov", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-6071-8186"))
Description: Process and summarize aerial survey 'DAS' data (AirDAS) <https://swfsc-publications.fisheries.noaa.gov/publications/TM/SWFSC/NOAA-TM-NMFS-SWFSC-185.PDF> collected using an aerial survey program from the Southwest Fisheries Science Center (SWFSC) <https://www.fisheries.noaa.gov/west-coast/science-data/california-current-marine-mammal-assessment-program>. PDF files detailing the relevant AirDAS data formats are included in this package.
URL: https://smwoodman.github.io/swfscAirDAS/, https://github.com/smwoodman/swfscAirDAS/
BugReports: https://github.com/smwoodman/swfscAirDAS/issues/
Depends: R (>= 3.5.0)
Imports: dplyr, lubridate, magrittr, methods, parallel, readr, rlang, stringr, swfscDAS (>= 0.3.0), swfscMisc, tidyr
Suggests: knitr, rmarkdown, testthat (>= 2.1.0), tibble
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-08-31 22:49:18 UTC; sam.woodman
Author: Sam Woodman [aut, cre] (<https://orcid.org/0000-0001-6071-8186>)
Maintainer: Sam Woodman <sam.woodman@noaa.gov>
Repository: CRAN
Date/Publication: 2020-09-07 08:40:03 UTC

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New package ONEST with initial version 0.0.1
Package: ONEST
Title: Observers Needed to Evaluate Subjective Tests
Version: 0.0.1
Authors@R: c(person("Gang", "Han", role = c("aut", "cre"), email = "hangang.true@gmail.com"), person("Baihong", "Guo", role = "aut", email = "ragerguo1023@gmail.com"))
Author: Gang Han [aut, cre], Baihong Guo [aut]
Maintainer: Gang Han <hangang.true@gmail.com>
URL: https://github.com/hangangtrue/ONEST
BugReports: https://github.com/hangangtrue/ONEST/issues
Description: This ONEST software implements the method of assessing the pathologist agreement in reading PD-L1 assays (Reisenbichler et al. (2020 <doi:10.1038/s41379-020-0544-x>)), to determine the minimum number of evaluators needed to estimate agreement involving a large number of raters. Input to the program should be binary(1/0) pathology data, where “0” may stand for negative and “1” for positive. Additional examples were given using the data from Rimm et al. (2017 <doi:10.1001/jamaoncol.2017.0013>).
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-08-31 17:45:22 UTC; Guo
Repository: CRAN
Date/Publication: 2020-09-07 08:20:03 UTC

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New package CruzPlot with initial version 1.4.2
Package: CruzPlot
Title: Plot Shipboard DAS Data
Version: 1.4.2
Authors@R: c(person("Samuel", "Woodman", role = c("aut", "cre"), email = "sam.woodman@noaa.gov", comment = c(ORCID = "0000-0001-6071-8186")), person("Tim", "Gerrodette", role = c("aut")))
Description: A utility program oriented to create maps, plot data, and do basic data summaries of 'DAS' data <https://swfsc-publications.fisheries.noaa.gov/publications/TM/SWFSC/NOAA-TM-NMFS-SWFSC-305.PDF> produced by 'WinCruz' from the Southwest Fisheries Science Center. <https://www.fisheries.noaa.gov/west-coast/science-data/california-current-marine-mammal-assessment-program>.
URL: https://smwoodman.github.io/CruzPlot/, https://github.com/smwoodman/CruzPlot/
BugReports: https://github.com/smwoodman/CruzPlot/issues/
Imports: dplyr, DT, geosphere, mapdata, marmap, maps, shiny, shinydashboard, shinyjs, stringr, swfscDAS (>= 0.3.0)
Suggests: httr, testthat
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-08-31 22:45:51 UTC; sam.woodman
Author: Samuel Woodman [aut, cre] (<https://orcid.org/0000-0001-6071-8186>), Tim Gerrodette [aut]
Maintainer: Samuel Woodman <sam.woodman@noaa.gov>
Repository: CRAN
Date/Publication: 2020-09-07 08:30:08 UTC

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New package catmaply with initial version 0.9.0
Package: catmaply
Title: Heatmap for Categorical Data using 'plotly'
Version: 0.9.0
Authors@R: c( person("Yves", "Mauron", email="ypmauron@gmail.com", role=c("aut", "cre")), person("Aron", "Weller", role="ctb"), person(given="Trivadis AG", role="cph") )
Maintainer: Yves Mauron <ypmauron@gmail.com>
Description: Methods and plotting functions for displaying categorical data on an interactive heatmap using 'plotly'. Provides functionality for strictly categorical heatmaps, heatmaps illustrating categorized continuous data and annotated heatmaps. Also, there are various options to interact with the x-axis to prevent overlapping axis labels, e.g. via simple sliders or range sliders. Besides the viewer pane, resulting plots can be saved as a standalone HTML file, embedded in 'R Markdown' documents or in a 'Shiny' app.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Imports: plotly, tidyverse, dplyr, lubridate, magrittr, rlang
Suggests: testthat, viridis, knitr
VignetteBuilder: knitr
RoxygenNote: 7.1.0
URL: https://github.com/VerkehrsbetriebeZuerich/catmaply
BugReports: https://github.com/VerkehrsbetriebeZuerich/catmaply/issues
NeedsCompilation: no
Packaged: 2020-08-31 16:25:31 UTC; yves
Author: Yves Mauron [aut, cre], Aron Weller [ctb], Trivadis AG [cph]
Repository: CRAN
Date/Publication: 2020-09-07 08:30:03 UTC

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Package diyar (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:

2020-06-13 0.1.0
2019-12-08 0.0.3
2019-11-11 0.0.2
2019-10-06 0.0.1

Permanent link
Package RMPSS (with last version 1.1.1) was removed from CRAN

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

2020-08-12 1.1.1

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Package tidycwl (with last version 1.0.4) was removed from CRAN

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

2019-12-06 1.0.4
2019-11-28 1.0.3

Permanent link
Package RNifti updated to version 1.2.2 with previous version 1.2.1 dated 2020-09-01

Title: Fast R and C++ Access to NIfTI Images
Description: Provides very fast read and write access to images stored in the NIfTI-1, NIfTI-2 and ANALYZE-7.5 formats, with seamless synchronisation of in-memory image objects between compiled C and interpreted R code. Also provides a simple image viewer, and a C/C++ API that can be used by other packages. Not to be confused with 'RNiftyReg', which performs image registration and applies spatial transformations.
Author: Jon Clayden [cre, aut] (<https://orcid.org/0000-0002-6608-0619>), Bob Cox [aut], Mark Jenkinson [aut], Matt Hall [ctb], Rick Reynolds [ctb], Kate Fissell [ctb], Jean-loup Gailly [cph], Mark Adler [cph]
Maintainer: Jon Clayden <code@clayden.org>

Diff between RNifti versions 1.2.1 dated 2020-09-01 and 1.2.2 dated 2020-09-07

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Package EFAutilities updated to version 2.1.0 with previous version 2.0.0 dated 2019-02-06

Title: Utility Functions for Exploratory Factor Analysis
Description: A number of utility function for exploratory factor analysis are included in this package. In particular, it computes standard errors for parameter estimates and factor correlations under a variety of conditions.
Author: Guangjian Zhang, Ge Jiang, Minami Hattori, Lauren Trichtinger
Maintainer: Guangjian Zhang <gzhang3@nd.edu>

Diff between EFAutilities versions 2.0.0 dated 2019-02-06 and 2.1.0 dated 2020-09-07

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New package drord with initial version 1.0.0
Package: drord
Title: Doubly-Robust Estimators for Ordinal Outcomes
Version: 1.0.0
Authors@R: c( person("David", "Benkeser", email = "benkeser@emory.edu", role = c("aut", "cre","cph"), comment = c(ORCID = "0000-0002-1019-8343")) )
Description: Efficient covariate-adjusted estimators of quantities that are useful for establishing the effects of treatments on ordinal outcomes.
Depends: R (>= 3.5.0)
Imports: MASS, VGAM, ordinal, ggplot2
Suggests: testthat, knitr, rmarkdown, ggsci
License: MIT + file LICENSE
URL: https://github.com/benkeser/drord
BugReports: https://github.com/benkeser/drord/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-08-31 16:18:24 UTC; dbenkes
Author: David Benkeser [aut, cre, cph] (<https://orcid.org/0000-0002-1019-8343>)
Maintainer: David Benkeser <benkeser@emory.edu>
Repository: CRAN
Date/Publication: 2020-09-07 07:30:03 UTC

More information about drord at CRAN
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New package covid19us with initial version 0.1.7
Package: covid19us
Title: Cases of COVID-19 in the United States
Version: 0.1.7
Authors@R: person(given = "Amanda", family = "Dobbyn", role = c("aut", "cre"), email = "amanda.e.dobbyn@gmail.com")
Description: A wrapper around the 'COVID Tracking Project API' <https://covidtracking.com/api/> providing data on cases of COVID-19 in the US.
License: MIT + file LICENSE
Imports: curl (>= 4.3), dplyr (>= 0.8.3), glue (>= 1.3.1), httr (>= 1.4.1), lubridate (>= 1.7.4), magrittr (>= 1.5), purrr (>= 0.3.3), snakecase (>= 0.11.0), stringr (>= 1.4.0), tibble (>= 2.1.3), tidyr (>= 1.0.2)
Suggests: covr (>= 3.4.0), testthat (>= 2.1.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-08-31 15:06:21 UTC; amanda
Author: Amanda Dobbyn [aut, cre]
Maintainer: Amanda Dobbyn <amanda.e.dobbyn@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-07 07:20:03 UTC

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Package jsonlite updated to version 1.7.1 with previous version 1.7.0 dated 2020-06-25

Title: A Simple and Robust JSON Parser and Generator for R
Description: A reasonably fast JSON parser and generator, optimized for statistical data and the web. Offers simple, flexible tools for working with JSON in R, and is particularly powerful for building pipelines and interacting with a web API. The implementation is based on the mapping described in the vignette (Ooms, 2014). In addition to converting JSON data from/to R objects, 'jsonlite' contains functions to stream, validate, and prettify JSON data. The unit tests included with the package verify that all edge cases are encoded and decoded consistently for use with dynamic data in systems and applications.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>), Duncan Temple Lang [ctb], Lloyd Hilaiel [cph] (author of bundled libyajl)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package Haplin updated to version 7.2.3 with previous version 7.2.2 dated 2020-01-07

Title: Analyzing Case-Parent Triad and/or Case-Control Data with SNP Haplotypes
Description: Performs genetic association analyses of case-parent triad (trio) data with multiple markers. It can also incorporate complete or incomplete control triads, for instance independent control children. Estimation is based on haplotypes, for instance SNP haplotypes, even though phase is not known from the genetic data. 'Haplin' estimates relative risk (RR + conf.int.) and p-value associated with each haplotype. It uses maximum likelihood estimation to make optimal use of data from triads with missing genotypic data, for instance if some SNPs has not been typed for some individuals. 'Haplin' also allows estimation of effects of maternal haplotypes and parent-of-origin effects, particularly appropriate in perinatal epidemiology. 'Haplin' allows special models, like X-inactivation, to be fitted on the X-chromosome. A GxE analysis allows testing interactions between environment and all estimated genetic effects. The models were originally described in Gjessing, HK and Lie, RT (2006) <doi:10.1111/j.1529-8817.2005.00218.x>.
Author: Hakon K. Gjessing [aut, cre], Miriam Gjerdevik [ctb] (functions 'lineByLine', 'cbindFiles', 'rbindFiles', 'snpPower', 'snpSampleSize', 'hapSim', 'hapRun', 'hapPower', 'hapPowerAsymp', and 'hapRelEff'), Julia Romanowska [ctb] (<https://orcid.org/0000-0001-6733-1953>, new data format, parallelisation, new documentation), Oivind Skare [ctb] (TDT tests)
Maintainer: Hakon K. Gjessing <hakon.gjessing@uib.no>

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Package glca updated to version 1.0.0 with previous version 0.1.1 dated 2020-05-30

Title: Latent Class Analysis with Group Variable
Description: Fits latent class analysis (LCA) including group variable and covariates. The group variable can be handled either by multilevel LCA described in Vermunt (2003) <DOI:10.1111/j.0081-1750.2003.t01-1-00131.x> or standard LCA at each level of group variable. The covariates can be incorporated in the form of logistic regression (Bandeen-Roche et al. (1997) <DOI:10.1080/01621459.1997.10473658>).
Author: Youngsun Kim [aut, cre], Hwan Chung [aut]
Maintainer: Youngsun Kim <kim0sun@korea.ac.kr>

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Package FarmTest updated to version 2.2.0 with previous version 2.1.0 dated 2020-04-28

Title: Factor-Adjusted Robust Multiple Testing
Description: Performs robust multiple testing for means in the presence of known and unknown latent factors presented in Fan et al.(2019) "FarmTest: Factor-Adjusted Robust Multiple Testing With Approximate False Discovery Control" <doi:10.1080/01621459.2018.1527700>. Implements a series of adaptive Huber methods combined with fast data-drive tuning schemes proposed in Ke et al.(2019) "User-Friendly Covariance Estimation for Heavy-Tailed Distributions" <doi:10.1214/19-STS711> to estimate model parameters and construct test statistics that are robust against heavy-tailed and/or asymmetric error distributions. Extensions to two-sample simultaneous mean comparison problems are also included. As by-products, this package contains functions that compute adaptive Huber mean, covariance and regression estimators that are of independent interest.
Author: Xiaoou Pan [aut, cre], Yuan Ke [aut], Wen-Xin Zhou [aut]
Maintainer: Xiaoou Pan <xip024@ucsd.edu>

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