Sat, 26 Jan 2019

Package Hmisc updated to version 4.2-0 with previous version 4.1-1 dated 2018-01-03

Title: Harrell Miscellaneous
Description: Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, and recoding variables.
Author: Frank E Harrell Jr <f.harrell@vanderbilt.edu>, with contributions from Charles Dupont and many others.
Maintainer: Frank E Harrell Jr <f.harrell@vanderbilt.edu>

Diff between Hmisc versions 4.1-1 dated 2018-01-03 and 4.2-0 dated 2019-01-26

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Package future updated to version 1.11.1.1 with previous version 1.11.0 dated 2019-01-21

Title: Unified Parallel and Distributed Processing in R for Everyone
Description: The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multiprocess)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers etc. Because of its unified API, there is no need to modify any code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between future versions 1.11.0 dated 2019-01-21 and 1.11.1.1 dated 2019-01-26

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Package BioStatR updated to version 3.0.0 with previous version 2.0.0 dated 2014-08-28

Title: Initiation à La Statistique Avec R
Description: Datasets and functions for the book "Initiation à la Statistique avec R", Dunod, 3eme edition, 2018.
Author: Frederic Bertrand [cre, aut] (<https://orcid.org/0000-0002-0837-8281>), Myriam Maumy-Bertrand [aut] (<https://orcid.org/0000-0002-4615-1512>)
Maintainer: Frederic Bertrand <frederic.bertrand@math.unistra.fr>

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Package irr updated to version 0.84.1 with previous version 0.84 dated 2012-07-16

Title: Various Coefficients of Interrater Reliability and Agreement
Description: Coefficients of Interrater Reliability and Agreement for quantitative, ordinal and nominal data: ICC, Finn-Coefficient, Robinson's A, Kendall's W, Cohen's Kappa, ...
Author: Matthias Gamer <m.gamer@uke.uni-hamburg.de>, Jim Lemon <jim@bitwrit.com.au>, Ian Fellows <ifellows@uscd.edu> Puspendra Singh <puspendra.pusp22@gmail.com>
Maintainer: Matthias Gamer <m.gamer@uke.uni-hamburg.de>

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Package waveslim updated to version 1.7.5.1 with previous version 1.7.5 dated 2015-01-09

Title: Basic Wavelet Routines for One-, Two- And Three-Dimensional Signal Processing
Description: Basic wavelet routines for time series (1D), image (2D) and array (3D) analysis. The code provided here is based on wavelet methodology developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002). All figures in chapters 4-7 of GSW (2001) are reproducible using this package and R code available at the book website(s) below.
Author: Brandon Whitcher
Maintainer: Brandon Whitcher <bwhitcher@gmail.com>

Diff between waveslim versions 1.7.5 dated 2015-01-09 and 1.7.5.1 dated 2019-01-26

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Package RcmdrPlugin.IPSUR updated to version 0.2-1.1 with previous version 0.2-1 dated 2014-09-10

Title: An IPSUR Plugin for the R Commander
Description: Provides an R Commander plugin that accompanies IPSUR, an Introduction to Probability and Statistics Using R.
Author: G. Jay Kerns [aut, cre], Theophilus Boye [ctb], Tyler Drombosky [ctb]
Maintainer: G. Jay Kerns <gkerns@ysu.edu>

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Package muhaz updated to version 1.2.6.1 with previous version 1.2.6 dated 2014-08-09

Title: Hazard Function Estimation in Survival Analysis
Description: Produces a smooth estimate of the hazard function for censored data.
Author: S original by Kenneth Hess, <khess@odin.mdacc.tmc.edu> R port by R. Gentleman
Maintainer: David Winsemius <dwinsemius@comcast.net>

Diff between muhaz versions 1.2.6 dated 2014-08-09 and 1.2.6.1 dated 2019-01-26

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Package mblm updated to version 0.12.1 with previous version 0.12 dated 2013-12-30

Title: Median-Based Linear Models
Description: Provides linear models based on Theil-Sen single median and Siegel repeated medians. They are very robust (29 or 50 percent breakdown point, respectively), and if no outliers are present, the estimators are very similar to OLS.
Author: Lukasz Komsta <lukasz.komsta@umlub.pl>
Maintainer: Lukasz Komsta <lukasz.komsta@umlub.pl>

Diff between mblm versions 0.12 dated 2013-12-30 and 0.12.1 dated 2019-01-26

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Package dfcrm updated to version 0.2-2.1 with previous version 0.2-2 dated 2013-08-02

Title: Dose-Finding by the Continual Reassessment Method
Description: Provides functions to run the CRM and TITE-CRM in phase I trials and calibration tools for trial planning purposes.
Author: Ken Cheung <yc632@columbia.edu>
Maintainer: Jimmy Duong <jkd2108@columbia.edu>

Diff between dfcrm versions 0.2-2 dated 2013-08-02 and 0.2-2.1 dated 2019-01-26

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Package aod updated to version 1.3.1 with previous version 1.3 dated 2012-04-10

Title: Analysis of Overdispersed Data
Description: Provides a set of functions to analyse overdispersed counts or proportions. Most of the methods are already available elsewhere but are scattered in different packages. The proposed functions should be considered as complements to more sophisticated methods such as generalized estimating equations (GEE) or generalized linear mixed effect models (GLMM).
Author: Matthieu Lesnoff <matthieu.lesnoff@cirad.fr> and Renaud Lancelot <renaud.lancelot@cirad.fr>
Maintainer: Renaud Lancelot <renaud.lancelot@cirad.fr>

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Package weibulltools updated to version 1.0.0 with previous version 0.5.4 dated 2018-07-25

Title: Statistical Methods for Life Data Analysis
Description: Contains methods for examining bench test or field data using the well-known Weibull Analysis. It includes Monte Carlo simulation for estimating the life span of products that have not failed, taking account of registering and reporting delays as stated in (Verband der Automobilindustrie e.V. (VDA), 2016, <ISSN:0943-9412>). If the products looked upon are vehicles, the covered mileage can be estimated as well. It also provides non-parametric estimators like Median Ranks, Kaplan-Meier (Abernethy, 2006, <ISBN:978-0-9653062-3-2>), Johnson (Johnson, 1964, <ISBN:978-0444403223>), and Nelson-Aalen for failure probability estimation within samples that contain failures as well as censored data. Methods for estimating the parameters of lifetime distributions, like Maximum Likelihood and Median-Rank Regression, (Genschel and Meeker, 2010, <DOI:10.1080/08982112.2010.503447>) as well as the computation of confidence intervals of quantiles and probabilities using the delta method related to Fisher's confidence intervals (Meeker and Escobar, 1998, <ISBN:9780471673279>) and the beta-binomial confidence bounds are also included. If desired, the data can automatically be divided into subgroups using segmented regression. And if the number of subgroups in a Weibull Mixture Model is known, data can be analyzed using the EM-Algorithm. Besides the calculation, methods for interactive visualization of the edited data using *plotly* are provided as well. These visualizations include the layout of a probability plot for a specified distribution, the graphical technique of probability plotting and the possibility of adding regression lines and confidence bounds to existing plots.
Author: Hensel Tim-Gunnar [aut, cre]
Maintainer: Hensel Tim-Gunnar <tim-gunnar.hensel@tu-berlin.de>

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Package pkgnet updated to version 0.3.2 with previous version 0.3.1 dated 2019-01-20

Title: Get Network Representation of an R Package
Description: Tools from the domain of graph theory can be used to quantify the complexity and vulnerability to failure of a software package. That is the guiding philosophy of this package. 'pkgnet' provides tools to analyze the dependencies between functions in an R package and between its imported packages.
Author: Brian Burns [aut, cre], James Lamb [aut], Patrick Boueri [ctb], Jay Qi [aut]
Maintainer: Brian Burns <brian.burns@uptake.com>

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Package littler updated to version 0.3.6 with previous version 0.3.5 dated 2018-10-04

Title: R at the Command-Line via 'r'
Description: A scripting and command-line front-end is provided by 'r' (aka 'littler') as a lightweight binary wrapper around the GNU R language and environment for statistical computing and graphics. While R can be used in batch mode, the r binary adds full support for both 'shebang'-style scripting (i.e. using a hash-mark-exclamation-path expression as the first line in scripts) as well as command-line use in standard Unix pipelines. In other words, r provides the R language without the environment.
Author: Dirk Eddelbuettel and Jeff Horner
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package SVMMaj updated to version 0.2.9 with previous version 0.2-8 dated 2018-02-25

Title: Implementation of the SVM-Maj Algorithm
Description: Implements the SVM-Maj algorithm to train data with support vector machine as described in Groenen et al. (2008) <doi:10.1007/s11634-008-0020-9>. This algorithm uses two efficient updates, one for linear kernel and one for the nonlinear kernel.
Author: Hoksan Yip, Patrick J.F. Groenen, Georgi Nalbantov
Maintainer: Hok San Yip <hoksan@gmail.com>

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Package JFE updated to version 2.0 with previous version 1.3 dated 2018-11-14

Title: A Menu-Driven GUI for Analyzing Data of Just Finance and Econometrics
Description: Support the decision analysis of international assets selection and portfolio backtesting.
Author: Ho Tsung-wu
Maintainer: Ho Tsung-wu <tsungwu@ntnu.edu.tw>

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Package strider updated to version 1.2 with previous version 1.1 dated 2018-01-10

Title: Strided Iterator and Range
Description: The strided iterator adapts multidimensional buffers to work with the C++ standard library and range-based for-loops. Given a pointer or iterator into a multidimensional data buffer, one can generate an iterator range using make_strided to construct strided versions of the standard library's begin and end. For constructing range-based for-loops, a strided_range class is provided. These help authors to avoid integer-based indexing, which in some cases can impede algorithm performance and introduce indexing errors. This library exists primarily to expose the header file to other R projects.
Author: Tim Keitt [aut, cre]
Maintainer: Tim Keitt <tkeitt@gmail.com>

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Package seqHMM updated to version 1.0.10 with previous version 1.0.9 dated 2018-11-06

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

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Package secrdesign updated to version 2.5.6 with previous version 2.5.5 dated 2018-12-07

Title: Sampling Design for Spatially Explicit Capture-Recapture
Description: Tools for designing spatially explicit capture-recapture studies of animal populations. This is primarily a simulation manager for package 'secr'. Extensions in version 2.5.0 include costing and evaluation of detector spacing.
Author: Murray Efford
Maintainer: Murray Efford <murray.efford@otago.ac.nz>

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Package DeclareDesign updated to version 0.16.0 with previous version 0.14.0 dated 2019-01-07

Title: Declare and Diagnose Research Designs
Description: Researchers can characterize and learn about the properties of research designs before implementation using `DeclareDesign`. Ex ante declaration and diagnosis of designs can help researchers clarify the strengths and limitations of their designs and to improve their properties, and can help readers evaluate a research strategy prior to implementation and without access to results. It can also make it easier for designs to be shared, replicated, and critiqued.
Author: Graeme Blair [aut, cre] (<https://orcid.org/0000-0001-9164-2102>), Jasper Cooper [aut] (<https://orcid.org/0000-0002-8639-3188>), Alexander Coppock [aut] (<https://orcid.org/0000-0002-5733-2386>), Macartan Humphreys [aut] (<https://orcid.org/0000-0001-7029-2326>), Neal Fultz [aut]
Maintainer: Graeme Blair <graeme.blair@ucla.edu>

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