Mon, 21 Sep 2020

Package splmm updated to version 1.1 with previous version 1.0 dated 2020-09-21

Title: Simultaneous Penalized Linear Mixed Effects Models
Description: Contains functions that fit linear mixed-effects models for high-dimensional data (p>>n) with penalty for both the fixed effects and random effects for variable selection. The details of the algorithm can be found in Luoying Yang PhD thesis (available soon). The algorithm implementation is based on the R package 'lmmlasso'.
Author: Luoying Yang, Tong Tong Wu
Maintainer: Luoying Yang <lyang19@u.rochester.edu>

Diff between splmm versions 1.0 dated 2020-09-21 and 1.1 dated 2020-09-21

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More information about splmm at CRAN
Permanent link

Package metropolis updated to version 0.1.8 with previous version 0.1.5 dated 2020-01-23

Title: The Metropolis Algorithm
Description: Learning and using the Metropolis algorithm for Bayesian fitting of a generalized linear model. The package vignette includes examples of hand-coding a logistic model using several variants of the Metropolis algorithm. The package also contains R functions for simulating posterior distributions of Bayesian generalized linear model parameters using guided, adaptive, guided-adaptive and random walk Metropolis algorithms. The random walk Metropolis algorithm was originally described in Metropolis et al (1953); <doi:10.1063/1.1699114>.
Author: Alexander Keil [aut, cre]
Maintainer: Alexander Keil <akeil@unc.edu>

Diff between metropolis versions 0.1.5 dated 2020-01-23 and 0.1.8 dated 2020-09-21

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More information about metropolis at CRAN
Permanent link

Package koRpus updated to version 0.13-1 with previous version 0.11-5 dated 2018-10-28

Title: An R Package for Text Analysis
Description: A set of tools to analyze texts. Includes, amongst others, functions for automatic language detection, hyphenation, several indices of lexical diversity (e.g., type token ratio, HD-D/vocd-D, MTLD) and readability (e.g., Flesch, SMOG, LIX, Dale-Chall). Basic import functions for language corpora are also provided, to enable frequency analyses (supports Celex and Leipzig Corpora Collection file formats) and measures like tf-idf. Note: For full functionality a local installation of TreeTagger is recommended. It is also recommended to not load this package directly, but by loading one of the available language support packages from the 'l10n' repository <https://undocumeantit.github.io/repos/l10n/>. 'koRpus' also includes a plugin for the R GUI and IDE RKWard, providing graphical dialogs for its basic features. The respective R package 'rkward' cannot be installed directly from a repository, as it is a part of RKWard. To make full use of this feature, please install RKWard from <https://rkward.kde.org> (plugins are detected automatically). Due to some restrictions on CRAN, the full package sources are only available from the project homepage. To ask for help, report bugs, request features, or discuss the development of the package, please subscribe to the koRpus-dev mailing list (<https://korpusml.reaktanz.de>).
Author: Meik Michalke [aut, cre], Earl Brown [ctb], Alberto Mirisola [ctb], Alexandre Brulet [ctb], Laura Hauser [ctb]
Maintainer: Meik Michalke <meik.michalke@hhu.de>

Diff between koRpus versions 0.11-5 dated 2018-10-28 and 0.13-1 dated 2020-09-21

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More information about koRpus at CRAN
Permanent link

Package freesurferformats updated to version 0.1.13 with previous version 0.1.12 dated 2020-08-26

Title: Read and Write 'FreeSurfer' Neuroimaging File Formats
Description: Provides functions to read and write neuroimaging data in various file formats, with a focus on 'FreeSurfer' <http://freesurfer.net/> formats. This includes, but is not limited to, the following file formats: 1) MGH/MGZ format files, which can contain multi-dimensional images or other data. Typically they contain time-series of three-dimensional brain scans acquired by magnetic resonance imaging (MRI). They can also contain vertex-wise measures of surface morphometry data. The MGH format is named after the Massachusetts General Hospital, and the MGZ format is a compressed version of the same format. 2) 'FreeSurfer' morphometry data files in binary 'curv' format. These contain vertex-wise surface measures, i.e., one scalar value for each vertex of a brain surface mesh. These are typically values like the cortical thickness or brain surface area at each vertex. 3) Annotation file format. This contains a brain surface parcellation derived from a cortical atlas. 4) Surface file format. Contains a brain surface mesh, given by a list of vertices and a list of faces.
Author: Tim Schäfer [aut, cre] (<https://orcid.org/0000-0002-3683-8070>)
Maintainer: Tim Schäfer <ts+code@rcmd.org>

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Package SuperGauss updated to version 2.0.0 with previous version 1.0.2 dated 2020-02-27

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

Diff between SuperGauss versions 1.0.2 dated 2020-02-27 and 2.0.0 dated 2020-09-21

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Package mc.heterogeneity updated to version 0.1.2 with previous version 0.1.1 dated 2020-06-24

Title: A Monte Carlo Based Heterogeneity Test for Meta-Analysis
Description: Implements a Monte Carlo Based Heterogeneity Test for standardized mean differences (d), Fisher-transformed Pearson's correlations (r), and natural-logarithm-transformed odds ratio (OR) in Meta-Analysis Studies. Depending on the presence of moderators, this Monte Carlo Based Test can be implemented in the random or mixed-effects model. This package uses rma() function from the R package 'metafor' to obtain parameter estimates and likelihood, so installation of R package 'metafor' is required. This approach refers to the studies of Hedges (1981) <doi:10.3102/10769986006002107>, Hedges & Olkin (1985, ISBN:978-0123363800), Silagy, Lancaster, Stead, Mant, & Fowler (2004) <doi:10.1002/14651858.CD000146.pub2>, Viechtbauer (2010) <doi:10.18637/jss.v036.i03>, and Zuckerman (1994, ISBN:978-0521432009).
Author: Han Du [aut], Ge Jiang [aut, cre], Zijun Ke [ctb]
Maintainer: Ge Jiang <gejiang2@illinois.edu>

Diff between mc.heterogeneity versions 0.1.1 dated 2020-06-24 and 0.1.2 dated 2020-09-21

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Package wedge (with last version 1.0-3) was removed from CRAN

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

2019-09-04 1.0-3
2019-06-27 1.0-2
2019-05-01 1.0-1

Permanent link
Package periscope updated to version 0.5.2 with previous version 0.5.1 dated 2020-07-03

Title: Enterprise Streamlined 'Shiny' Application Framework
Description: An enterprise-targeted scalable and UI-standardized 'shiny' framework including a variety of developer convenience functions with the goal of both streamlining robust application development while assisting with creating a consistent user experience regardless of application or developer.
Author: Constance Brett [aut, cre], Isaac Neuhaus [aut] (canvasXpress JavaScript Library Maintainer), Ger Inberg [ctb], Bristol-Meyers Squibb (BMS) [cph]
Maintainer: Constance Brett <connie@aggregate-genius.com>

Diff between periscope versions 0.5.1 dated 2020-07-03 and 0.5.2 dated 2020-09-21

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New package tidystats with initial version 0.5
Package: tidystats
Type: Package
Title: Save Output of Statistical Tests
Version: 0.5
Author: Willem Sleegers
Maintainer: Willem Sleegers <w.sleegers@me.com>
Description: Save the output of statistical tests in an organized file that can be shared with others or used to report statistics in scientific papers.
URL: https://willemsleegers.github.io/tidystats/
BugReports: https://github.com/WillemSleegers/tidystats/issues
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.1.1
LazyData: true
Depends: R (>= 3.2.0)
Imports: dplyr, tidyr, purrr, stringr, readr, jsonlite, tibble
Suggests: knitr, rmarkdown, testthat, BayesFactor, lme4, lmerTest
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-21 10:07:04 UTC; willem
Repository: CRAN
Date/Publication: 2020-09-21 16:50:02 UTC

More information about tidystats at CRAN
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Package SmallCountRounding updated to version 0.5.0 with previous version 0.4.0 dated 2019-10-17

Title: Small Count Rounding of Tabular Data
Description: A statistical disclosure control tool to protect frequency tables in cases where small values are sensitive. The function PLSrounding() performs small count rounding of necessary inner cells so that all small frequencies of cross-classifications to be published (publishable cells) are rounded. This is equivalent to changing micro data since frequencies of unique combinations are changed. Thus, additivity and consistency are guaranteed. The methodology is described in Langsrud and Heldal (2018) <https://www.researchgate.net/publication/327768398_An_Algorithm_for_Small_Count_Rounding_of_Tabular_Data>.
Author: Øyvind Langsrud [aut, cre], Johan Heldal [aut]
Maintainer: Øyvind Langsrud <oyl@ssb.no>

Diff between SmallCountRounding versions 0.4.0 dated 2019-10-17 and 0.5.0 dated 2020-09-21

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Permanent link

Package parameters updated to version 0.8.6 with previous version 0.8.5 dated 2020-09-12

Title: Processing of Model Parameters
Description: Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see support list of insight; Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut] (<https://orcid.org/0000-0001-5375-9967>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Indrajeet Patil [aut] (<https://orcid.org/0000-0003-1995-6531>), Søren Højsgaard [aut], Zen J. Lau [ctb]
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between parameters versions 0.8.5 dated 2020-09-12 and 0.8.6 dated 2020-09-21

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Package mlt.docreg updated to version 1.0-8 with previous version 1.0-7 dated 2020-08-31

Title: Most Likely Transformations: Documentation and Regression Tests
Description: Additional documentation, a package vignette and regression tests for package mlt.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between mlt.docreg versions 1.0-7 dated 2020-08-31 and 1.0-8 dated 2020-09-21

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Package labelled updated to version 2.7.0 with previous version 2.6.0 dated 2020-08-27

Title: Manipulating Labelled Data
Description: Work with labelled data imported from 'SPSS' or 'Stata' with 'haven' or 'foreign'. This package provides useful functions to deal with "haven_labelled" and "haven_labelled_spss" classes introduced by 'haven' package.
Author: Joseph Larmarange [aut, cre] (<https://orcid.org/0000-0001-7097-700X>), Daniel Ludecke [ctb], Hadley Wickham [ctb], Michal Bojanowski [ctb], François Briatte [ctb]
Maintainer: Joseph Larmarange <joseph@larmarange.net>

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Package image.textlinedetector updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-15

Title: Segment Images in Text Lines and Words
Description: Find text lines in scanned images and segment the lines into words. Includes implementations of the paper 'Novel A* Path Planning Algorithm for Line Segmentation of Handwritten Documents' by Surinta O. et al (2014) <doi:10.1109/ICFHR.2014.37> available at <https://github.com/smeucci/LineSegm>, an implementation of 'A Statistical approach to line segmentation in handwritten documents' by Arivazhagan M. et al (2007) <doi:10.1117/12.704538>, and a wrapper for an image segmentation technique to detect words in text lines as described in the paper 'Scale Space Technique for Word Segmentation in Handwritten Documents' by Manmatha R. and Srimal N. (1999) paper at <doi:10.1007/3-540-48236-9_3>, wrapper for code available at <https://github.com/arthurflor23/text-segmentation>.
Author: Jan Wijffels [aut, cre, cph] (R wrapper), Vrije Universiteit Brussel - DIGI: Brussels Platform for Digital Humanities [cph] (R wrapper), Jeroen Ooms [ctb, cph] (More details in LICENSE.note file), Arthur Flôr [ctb, cph] (More details in LICENSE.note file), Saverio Meucci [ctb, cph] (More details in LICENSE.note file), Yeara Kozlov [ctb, cph] (More details in LICENSE.note file), Tino Weinkauf [ctb, cph] (More details in LICENSE.note file)
Maintainer: Jan Wijffels <jan.wijffels@vub.be>

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Package HSAUR3 updated to version 1.0-10 with previous version 1.0-9 dated 2018-05-28

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

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Package fairmodels updated to version 0.2.2 with previous version 0.1.1 dated 2020-08-20

Title: Flexible Tool for Bias Detection, Visualization, and Mitigation
Description: Measure fairness metrics in one place for many models. Check how big is model's bias towards different races, sex, nationalities etc. Use measures such as Statistical Parity, Equal odds to detect the discrimination against unprivileged groups. Visualize the bias using heatmap, radar plot, biplot, bar chart (and more!). There are various pre-processing and post-processing bias mitigation algorithms implemented.
Author: Jakub Wiśniewski [aut, cre], Przemysław Biecek [aut] (<https://orcid.org/0000-0001-8423-1823>)
Maintainer: Jakub Wiśniewski <jakwisn@gmail.com>

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New package diseq with initial version 0.0.13
Package: diseq
Title: Estimation Methods for Markets in Disequilibrium
Version: 0.0.13
Date: 2020-09-14
Authors@R: person( "Pantelis", "Karapanagiotis", email = "pikappa.devel@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9871-1908"))
Description: Provides estimation methods for markets in equilibrium and disequilibrium. Specifically, it supports the estimation of an equilibrium and four disequilibrium models with both correlated and independent shocks. It also provides post-estimation analysis tools, such as aggregation and marginal effects calculations. The estimation methods are based on full information maximum likelihood techniques given in Maddala and Nelson (1974) <doi:10.2307/1914215>. They are implemented using the analytic derivative expressions calculated in Karapanagiotis (2020) <doi:10.2139/ssrn.3525622>. The equilibrium estimation constitutes a special case of a system of simultaneous equations. The disequilibrium models, instead, replace the market clearing condition with a short side rule and allow for different specifications of price dynamics.
Language: en-US
URL: https://github.com/pi-kappa-devel/diseq/
BugReports: https://github.com/pi-kappa-devel/diseq/issues
Depends: R (>= 3.5.0)
Imports: bbmle (>= 1.0.20), dplyr (>= 0.7.6), magrittr (>= 1.5), MASS (>= 7.3-50), methods, rlang (>= 0.2.1), systemfit (>= 1.1), tibble (>= 1.4.2), tidyr (>= 1.0.2)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: ggplot2 (>= 3.0.0), knitr (>= 1.20), numDeriv (>= 2016.8.1.1), rmarkdown (>= 1.10), testthat (>= 2.0.0)
VignetteBuilder: knitr
Collate: 'equation_base.R' 'system_base.R' 'equation_basic.R' 'system_basic.R' 'derivatives_basic.R' 'equation_deterministic_adjustment.R' 'system_deterministic_adjustment.R' 'derivatives_deterministic_adjustment.R' 'equation_directional.R' 'system_directional.R' 'derivatives_directional.R' 'system_fiml.R' 'derivatives_fiml.R' 'equation_stochastic_adjustment.R' 'system_stochastic_adjustment.R' 'derivatives_stochastic_adjustment.R' 'diseq.R' 'model_logger.R' 'model_base.R' 'diseq_base.R' 'diseq_basic.R' 'diseq_deterministic_adjustment.R' 'diseq_directional.R' 'diseq_stochastic_adjustment.R' 'eq_base.R' 'eq_2sls.R' 'eq_fiml.R' 'model_simulation.R'
NeedsCompilation: no
Packaged: 2020-09-13 22:32:37 UTC; ntelispak
Author: Pantelis Karapanagiotis [aut, cre] (<https://orcid.org/0000-0001-9871-1908>)
Maintainer: Pantelis Karapanagiotis <pikappa.devel@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-21 16:50:11 UTC

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Package cplexAPI updated to version 1.4.0 with previous version 1.3.6 dated 2019-06-21

Title: R Interface to C API of IBM ILOG CPLEX
Description: This is the R Interface to the C API of IBM ILOG CPLEX. It necessarily depends on IBM ILOG CPLEX (>= 12.1).
Author: Mayo Roettger [cre], Gabriel Gelius-Dietrich [aut], C. Jonathan Fritzemeier [ctb]
Maintainer: Mayo Roettger <mayo.roettger@hhu.de>

Diff between cplexAPI versions 1.3.6 dated 2019-06-21 and 1.4.0 dated 2020-09-21

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New package colocalization with initial version 1.0.2
Package: colocalization
Type: Package
Title: Normalized Spatial Intensity Correlation
Version: 1.0.2
Author: Jiahui Xu, Xueyan Liu, Lin Li, Cheng Cheng, Hui Zhang
Maintainer: Hui Zhang <hzhang@northwestern.edu>
Depends: R (>= 2.10)
Description: Calculate the colocalization index, NSInC, in two different ways as described in the paper (Liu et al., 2019. Manuscript submitted for publication.) for multiple-species spatial data which contain the precise locations and membership of each spatial point. The two main functions are nsinc.d() and nsinc.z(). They provide the Pearson’s correlation coefficients of signal proportions in different memberships within a concerned proximity of every signal (or every base signal if single direction colocalization is considered) across all (base) signals using two different ways of normalization. The proximity sizes could be an individual value or a range of values, where the default ranges of values are different for the two functions.
License: GPL-3
Encoding: UTF-8
Suggests: testthat, rgl
Imports: utils, stats, ggplot2
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2020-09-13 22:00:43 UTC; lli3188
Repository: CRAN
Date/Publication: 2020-09-21 16:50:16 UTC

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Package boot.heterogeneity updated to version 0.1.1 with previous version 0.1.0 dated 2020-05-08

Title: A Bootstrap-Based Heterogeneity Test for Meta-Analysis
Description: Implements a bootstrap-based heterogeneity test for standardized mean differences (d), Fisher-transformed Pearson's correlations (r), and natural-logarithm-transformed odds ratio (or) in meta-analysis studies. Depending on the presence of moderators, this Monte Carlo based test can be implemented in the random- or mixed-effects model. This package uses rma() function from the R package 'metafor' to obtain parameter estimates and likelihoods, so installation of R package 'metafor' is required. This approach refers to the studies of Anscombe (1956) <doi:10.2307/2332926>, Haldane (1940) <doi:10.2307/2332614>, Hedges (1981) <doi:10.3102/10769986006002107>, Hedges & Olkin (1985, ISBN:978-0123363800), Silagy, Lancaster, Stead, Mant, & Fowler (2004) <doi:10.1002/14651858.CD000146.pub2>, Viechtbauer (2010) <doi:10.18637/jss.v036.i03>, and Zuckerman (1994, ISBN:978-0521432009).
Author: Ge Jiang [aut, cre], Han Du [aut], Zijun Ke [ctb]
Maintainer: Ge Jiang <gejiang2@illinois.edu>

Diff between boot.heterogeneity versions 0.1.0 dated 2020-05-08 and 0.1.1 dated 2020-09-21

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Package bahc updated to version 0.3.0 with previous version 0.2.0 dated 2020-05-15

Title: Filter Covariance and Correlation Matrices with Bootstrapped-Averaged Hierarchical Ansatz
Description: A method to filter correlation and covariance matrices by averaging bootstrapped filtered hierarchical clustering and boosting. See Ch. Bongiorno and D. Challet, Covariance matrix filtering with bootstrapped hierarchies (2020) <arXiv:2003.05807> and Ch. Bongiorno and D. Challet, Reactive Global Minimum Variance Portfolios with k-BAHC covariance cleaning (2020) <arXiv:2005.08703>.
Author: Christian Bongiorno and Damien Challet
Maintainer: Damien Challet <damien.challet@gmail.com>

Diff between bahc versions 0.2.0 dated 2020-05-15 and 0.3.0 dated 2020-09-21

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Package tsapp updated to version 1.0.1 with previous version 1.0.0 dated 2020-03-20

Title: Time Series, Analysis and Application
Description: Accompanies the book Rainer Schlittgen and Cristina Sattarhoff (2020) <https://www.degruyter.com/view/title/575978> "Angewandte Zeitreihenanalyse mit R, 4. Auflage" . The package contains the time series and functions used therein. It was developed over many years teaching courses about time series analysis.
Author: Rainer Schlittgen
Maintainer: Rainer Schlittgen <R.Schlittgen@t-online.de>

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Package nvmix updated to version 0.0-5 with previous version 0.0-4 dated 2020-06-12

Title: Multivariate Normal Variance Mixtures
Description: Functions for working with (grouped) multivariate normal variance mixture distributions (evaluation of distribution functions and densities, random number generation and parameter estimation), including Student's t distribution for non-integer degrees-of-freedom as well as the grouped t distribution and copula with multiple degrees-of-freedom parameters. See Hintz, Hofert, Lemieux (2019) <arXiv:1911.03017> for more details.
Author: Marius Hofert [aut, cre], Erik Hintz [aut], Christiane Lemieux [aut]
Maintainer: Marius Hofert <marius.hofert@uwaterloo.ca>

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Package FLSSS updated to version 8.6.6 with previous version 8.5.6 dated 2019-10-28

Title: Mining Rigs for Specialized Subset Sum, Multi-Subset Sum, Multidimensional Subset Sum, Multidimensional Knapsack, Generalized Assignment Problems
Description: Specialized solvers for combinatorial optimization problems in the Subset Sum family. These solvers differ from the mainstream in the options of (i) restricting subset size, (ii) bounding subset elements, (iii) mining real-value sets with predefined subset sum errors, and (iv) finding one or more subsets in limited time. A novel algorithm for mining the one-dimensional Subset Sum induced algorithms for the multi-Subset Sum and the multidimensional Subset Sum. The multi-threaded framework for the latter offers exact algorithms to the multidimensional Knapsack and the Generalized Assignment problems. Historical updates include (a) renewed implementation of the multi-Subset Sum, multidimensional Knapsack and Generalized Assignment solvers; (b) availability of bounding solution space in the multidimensional Subset Sum; (c) fundamental data structure and architectural changes for enhanced cache locality and better chance of SIMD vectorization; (d) an option of mapping real-domain problems to the integer domain with user-controlled precision loss, and those integers are further zipped non-uniformly in 64-bit buffers. Arithmetic on compressed integers is done by bit-manipulation and the design has virtually zero speed lag relative to normal integer arithmetic. Reduction in dimensionality from the compression may yield substantial acceleration; (e) distributed computing infrastructure for multidimensional subset sum. Compilation with g++ '-Ofast' is recommended. See package vignette (<arXiv:1612.04484v3>) for details. Functions prefixed with 'aux' (auxiliary) are or will be implementations of existing foundational or cutting-edge algorithms for solving optimization problems of interest.
Author: Charlie Wusuo Liu
Maintainer: Charlie Wusuo Liu <liuwusuo@gmail.com>

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Package AGHmatrix updated to version 2.0.0 with previous version 1.0.2 dated 2019-07-30

Title: Relationship Matrices for Diploid and Autopolyploid Species
Description: Computation of A (pedigree), G (genomic-base), and H (A corrected by G) relationship matrices for diploid and autopolyploid species. Several methods are implemented considering additive and non-additive models.
Author: Rodrigo Amadeu [aut, cre], Catherine Cellon [ctb], Leticia Lara [ctb], Marcio Resende [ctb], Ivone Oliveira [ctb], Luis Ferrao [ctb], Patricio Munoz [ctb], Augusto Garcia [ctb]
Maintainer: Rodrigo Amadeu <rramadeu@ufl.edu>

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Package ProcMod updated to version 1.0.6 with previous version 1.0.3 dated 2019-11-25

Title: Informative Procrustean Matrix Correlation
Description: Estimates corrected Procrustean correlation between matrices for removing overfitting effect. Coissac Eric and Gonindard-Melodelima Christelle (2019) <bioarXiv:10.1101/842070>.
Author: Eric Coissac, Christelle Gonindard-Melodelima
Maintainer: Eric Coissac <eric.coissac@metabarcoding.org>

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Package rmdcev (with last version 1.2.2) was removed from CRAN

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

2020-09-18 1.2.2

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Package ImportExport updated to version 1.3 with previous version 1.1 dated 2015-09-19

Title: Import and Export Data
Description: Import and export data from the most common statistical formats by using R functions that guarantee the least loss of the data information, giving special attention to the date variables and the labelled ones.
Author: Roger Pros, Isaac Subirana, Joan Vila.
Maintainer: Isaac Subirana <isubirana@imim.es>

Diff between ImportExport versions 1.1 dated 2015-09-19 and 1.3 dated 2020-09-21

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 ImportExport-1.3/ImportExport/R/access_import.R                           |    2 
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Package HSAUR2 updated to version 1.1-18 with previous version 1.1-17 dated 2017-08-20

Title: A Handbook of Statistical Analyses Using R (2nd Edition)
Description: Functions, data sets, analyses and examples from the second edition of the book ''A Handbook of Statistical Analyses Using R'' (Brian S. Everitt and Torsten Hothorn, Chapman & Hall/CRC, 2008). The first chapter of the book, which is entitled ''An Introduction to R'', is completely included in this package, for all other chapters, a vignette containing all data analyses is available. In addition, the package contains Sweave code for producing slides for selected chapters (see HSAUR2/inst/slides).
Author: Brian S. Everitt and Torsten Hothorn
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between HSAUR2 versions 1.1-17 dated 2017-08-20 and 1.1-18 dated 2020-09-21

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New package retroharmonize with initial version 0.1.13
Package: retroharmonize
Type: Package
Title: Ex Post Survey Data Harmonization
Version: 0.1.13
Authors@R: c(person(given = "Daniel", family = "Antal", role = c("aut", "cre"), email = "daniel.antal@ceemid.eu", comment = c(ORCID = "0000-0001-7513-6760")), person(given = "Marta", family = "Kolczynska", role = c("ctb"), email = "mkolczynska@gmail.com", comment = c(ORCID = "0000-0003-4981-0437")) )
Maintainer: Daniel Antal <daniel.antal@ceemid.eu>
Description: Assist in reproducible retrospective (ex-post) harmonization of data, particularly individual level survey data, by providing tools for organizing metadata, standardizing the coding of variables, and variable names and value labels, including missing values, and documenting the data transformations, with the help of comprehensive s3 classes.
License: GPL-3
Encoding: UTF-8
Language: en-US
URL: https://retroharmonize.dataobservatory.eu/
BugReports: https://github.com/antaldaniel/retroharmonize/issues
LazyData: true
Imports: vctrs, haven, dplyr (>= 1.0.0), magrittr, stats, tibble, labelled, methods, rlang, fs, assertthat, tidyselect, pillar, snakecase, purrr, tidyr, here
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
Suggests: knitr, rmarkdown, covr, testthat, png
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-11 21:54:27 UTC; Daniel Antal
Author: Daniel Antal [aut, cre] (<https://orcid.org/0000-0001-7513-6760>), Marta Kolczynska [ctb] (<https://orcid.org/0000-0003-4981-0437>)
Repository: CRAN
Date/Publication: 2020-09-21 09:10:02 UTC

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New package mobr with initial version 2.0.0
Package: mobr
Title: Measurement of Biodiversity
Version: 2.0.0
Authors@R: c(person("Daniel", "McGlinn", email = "danmcglinn@gmail.com", role = c("aut", "cre")), person("Xiao", "Xiao", email = "xiao@weecology.org", role = "aut"), person("Brian", "McGill", email = "brimcgill@gmail.com", role = "aut"), person("Felix", "May", email = "felix.may@idiv.de", role = "aut"), person("Thore", "Engel", email = "thore.engel@idiv.de", role = "aut"), person("Caroline", "Oliver", email = "olivercs@g.cofc.edu", role = "aut"), person("Shane", "Blowes", email = "shane.blowes@idiv.de", role = "aut"), person("Tiffany", "Knight", email = "tiffany.knight@idiv.de", role = 'aut'), person("Oliver", "Purschke", email = "oliverpurschke@web.de", role = 'aut'), person("Nicholas", "Gotelli", email = "Nicholas.Gotelli@uvm.edu", role = "aut"), person("Jon", "Chase", email = "jonathan.chase@idiv.de", role = "aut"))
Date: 2020-08-15
Description: Functions for calculating metrics for the measurement biodiversity and its changes across scales, treatments, and gradients. The methods implemented in this package are described in: Chase, J.M., et al. (2018) <doi:10.1111/ele.13151>, McGlinn, D.J., et al. (2019) <doi:10.1111/2041-210X.13102>, and McGlinn, D.J., et al. (2020) <doi:10.1101/851717>.
Depends: R (>= 3.5.0)
Imports: plotrix, scales, dplyr, purrr, tidyr, pbapply, ggplot2, egg, tibble, vctrs, rlang, geosphere
Suggests: knitr, rmarkdown, testthat
License: MIT + file LICENSE
LazyData: true
RoxygenNote: 7.1.1
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-09-12 16:55:33 UTC; mcglinndj
Author: Daniel McGlinn [aut, cre], Xiao Xiao [aut], Brian McGill [aut], Felix May [aut], Thore Engel [aut], Caroline Oliver [aut], Shane Blowes [aut], Tiffany Knight [aut], Oliver Purschke [aut], Nicholas Gotelli [aut], Jon Chase [aut]
Maintainer: Daniel McGlinn <danmcglinn@gmail.com>
Repository: CRAN
Date/Publication: 2020-09-21 09:30:03 UTC

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New package wayback with initial version 0.2.4
Package: wayback
Type: Package
Title: Rock Solid Package Installation for Legacy R Versions
Version: 0.2.4
Date: 2020-09-11
Authors@R: c( person( given = "Peter", family = "Meissner", email = "retep.meissner@gmail.com", role = c("aut", "cre") ), person( family = "virtual7", email = "info@virtual7.de", role = c("cph") ) )
Maintainer: Peter Meissner <retep.meissner@gmail.com>
Description: Make sure packages are available at runtime without any setup. Package installation, reproducibility and exchanging code can be frustrating especially if code is used on older R versions. Often it is hard to puzzle out which package versions are able to work together after some years have passed and packages evolved further and further. The 'wayback' package aims to make this process as painless and robust as possible by using 'MRAN's 'CRAN' snapshots to build local package libraries from way back.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: checkpoint
NeedsCompilation: no
Packaged: 2020-09-11 20:02:05 UTC; peter
Author: Peter Meissner [aut, cre], virtual7 [cph]
Repository: CRAN
Date/Publication: 2020-09-21 09:00:02 UTC

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New package splmm with initial version 1.0
Package: splmm
Type: Package
Title: Simultaneous Penalized Linear Mixed Effects Models
Version: 1.0
Date: 2020-08-12
Author: Luoying Yang, Tong Tong Wu
Maintainer: Luoying Yang <lyang19@u.rochester.edu>
Description: Contains functions that fit linear mixed-effects models for high-dimensional data (p>>n) with penalty for both the fixed effects and random effects for variable selection. The details of the algorithm can be found in Luoying Yang PhD thesis (available soon). The algorithm implementation is based on the R package 'lmmlasso'.
License: GPL-3
Imports: Rcpp (>= 1.0.1), emulator, miscTools, penalized, ggplot2, gridExtra, plot3D, MASS
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2020-09-11 15:10:22 UTC; lyang19
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2020-09-21 08:40:03 UTC

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New package SlidingWindows with initial version 0.1.4
Package: SlidingWindows
Type: Package
Title: Methods for Time Series Analysis
Description: A collection of functions to perform Detrended Fluctuation Analysis (DFA exponent), GUEDES et al. (2019) <doi:10.1016/j.physa.2019.04.132> , Detrended cross-correlation coefficient (RHODCCA), GUEDES & ZEBENDE (2019) <doi:10.1016/j.physa.2019.121286>, and Detrended Multiple cross-correlation coefficient (DMC), ZEBENDE & SILVA-FILHO (2018) <doi:10.1016/j.physa.2018.06.119>, both with sliding windows approach.
Version: 0.1.4
Date: 2020-09-11
Authors@R: c(person("Everaldo Freitas","Guedes", email = "efgestatistico@gmail.com", role = c("aut","cre"), comment = c(ORCID="0000-0002-2986-7367")), person("Ivan Costa da Cunha","Lima", email = "ivandacunhalima@gmail.com", role = c("aut"), comment = c(ORCID="0000-0002-4525-2346")), person("Gilney Figueira","Zebende", email = "gfzebende@hotmail", role = c("aut"), comment = c(ORCID="0000-0003-2420-9805")), person("Aloísio Machado","Silva-Filho", email = "aloisioestatistico@uefs.br", role = c("aut"), comment = c(ORCID="0000-0001-8250-1527")))
Maintainer: Everaldo Freitas Guedes <efgestatistico@gmail.com>
License: GPL-3
URL: https://github.com/efguedes/SlidingWindows
BugReports: https://github.com/efguedes/SlidingWindows
NeedsCompilation: no
Encoding: UTF-8
LazyData: true
Imports: stats, DCCA, PerformanceAnalytics, nonlinearTseries
Suggests: xts, zoo, quantmod
RoxygenNote: 7.1.1
Packaged: 2020-09-11 14:46:25 UTC; Everaldo Guedes
Author: Everaldo Freitas Guedes [aut, cre] (<https://orcid.org/0000-0002-2986-7367>), Ivan Costa da Cunha Lima [aut] (<https://orcid.org/0000-0002-4525-2346>), Gilney Figueira Zebende [aut] (<https://orcid.org/0000-0003-2420-9805>), Aloísio Machado Silva-Filho [aut] (<https://orcid.org/0000-0001-8250-1527>)
Repository: CRAN
Date/Publication: 2020-09-21 08:30:03 UTC

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New package ScriptMapR with initial version 0.0.2
Package: ScriptMapR
Type: Package
Title: R Script Visualization in Cytoscape
Version: 0.0.2
Author: Raphael Bonnet [aut, cre], Marion Guernoté [ctb], Terry Gouin [ctb], Maxime Laurens [ctb], Thibault Meekel [ctb], Jean-François Peyron[aut,ths]
Maintainer: Raphaël Bonnet <raphael.bonnet@univ-cotedazur.fr>
Description: Displays the content of a R script into the 'Cytoscape' network-visualization app <https://cytoscape.org/>.
BugReports: https://github.com/peyronlab/ScriptMapR/issues
Imports: RCy3, formatR, dplyr, stringr, utils, grDevices
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-11 15:54:30 UTC; raphael
Repository: CRAN
Date/Publication: 2020-09-21 08:50:02 UTC

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New package Neighboot with initial version 1.0.0
Package: Neighboot
Title: Neighborhood Bootstrap Method for RDS
Version: 1.0.0
Date: 2020-09-09
Author: Mamadou Yauck [aut, cre], Erica E. M. Moodie [aut]
Maintainer: Mamadou Yauck <mamadou.yauck@mcgill.ca>
Description: A bootstrap method for Respondent-Driven Sampling (RDS) that relies on the underlying structure of the RDS network to estimate uncertainty.
License: GPL-3
LazyData: true
RoxygenNote: 7.1.1
Imports: magrittr, RDStreeboot, igraph, RDS, dplyr
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-09-11 14:41:36 UTC; Utilisateur
Repository: CRAN
Date/Publication: 2020-09-21 08:30:07 UTC

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New package lightgbm with initial version 3.0.0
Package: lightgbm
Type: Package
Title: Light Gradient Boosting Machine
Version: 3.0.0
Date: 2020-09-11
Authors@R: c( person("Guolin", "Ke", email = "guolin.ke@microsoft.com", role = c("aut", "cre")), person("Damien", "Soukhavong", email = "damien.soukhavong@skema.edu", role = c("aut")), person("Yachen", "Yan", role = c("ctb")), person("James", "Lamb", email="jaylamb20@gmail.com", role = c("aut")), person("Qi", "Meng", role = c("aut")), person("Thomas", "Finley", role = c("aut")), person("Taifeng", "Wang", role = c("aut")), person("Wei", "Chen", role = c("aut")), person("Weidong", "Ma", role = c("aut")), person("Qiwei", "Ye", role = c("aut")), person("Tie-Yan", "Liu", role = c("aut")), person("Microsoft Corporation", role = c("cph")), person("Dropbox, Inc.", role = c("cph")) )
Description: Tree based algorithms can be improved by introducing boosting frameworks. 'LightGBM' is one such framework, based on Ke, Guolin et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>. This package offers an R interface to work with it. It is designed to be distributed and efficient with the following advantages: 1. Faster training speed and higher efficiency. 2. Lower memory usage. 3. Better accuracy. 4. Parallel learning supported. 5. Capable of handling large-scale data. In recognition of these advantages, 'LightGBM' has been widely-used in many winning solutions of machine learning competitions. Comparison experiments on public datasets suggest that 'LightGBM' can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, 'LightGBM' can achieve a linear speed-up in training time by using multiple machines.
Encoding: UTF-8
License: MIT + file LICENSE
URL: https://github.com/Microsoft/LightGBM
BugReports: https://github.com/Microsoft/LightGBM/issues
NeedsCompilation: yes
Biarch: true
Suggests: testthat
Depends: R (>= 3.5), R6 (>= 2.0)
Imports: data.table (>= 1.9.6), graphics, jsonlite (>= 1.0), Matrix (>= 1.1-0), methods, utils
SystemRequirements: C++11
RoxygenNote: 7.1.1
Packaged: 2020-09-11 15:05:31 UTC; jlamb
Author: Guolin Ke [aut, cre], Damien Soukhavong [aut], Yachen Yan [ctb], James Lamb [aut], Qi Meng [aut], Thomas Finley [aut], Taifeng Wang [aut], Wei Chen [aut], Weidong Ma [aut], Qiwei Ye [aut], Tie-Yan Liu [aut], Microsoft Corporation [cph], Dropbox, Inc. [cph]
Maintainer: Guolin Ke <guolin.ke@microsoft.com>
Repository: CRAN
Date/Publication: 2020-09-21 08:40:06 UTC

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New package GHap with initial version 2.0.0
Package: GHap
Type: Package
Title: Genome-Wide Haplotyping
Version: 2.0.0
Date: 2020-08-12
Author: Yuri Tani Utsunomiya, Marco Milanesi, Mario Barbato
Maintainer: Yuri Tani Utsunomiya <ytutsunomiya@gmail.com>
Description: Haplotype calling from phased marker data. Given user-defined haplotype blocks (HapBlock), the package identifies the different haplotype alleles (HapAllele) present in the data and scores sample haplotype allele genotypes (HapGenotype) based on HapAllele dose (i.e. 0, 1 or 2 copies). The output is not only useful for analyses that can handle multi-allelic markers, but is also conveniently formatted for existing pipelines intended for bi-allelic markers. The package was first described in Bioinformatics by Utsunomiya et al. (2016, <doi:10.1093/bioinformatics/btw356>). Since the v2 release, the package provides functions for unsupervised and supervised detection of ancestry tracks. The methods implemented in these functions were described in an article published in Methods in Ecology and Evolution by Utsunomiya et al. (2020, <doi:10.1111/2041-210X.13467>).
License: GPL (>= 2)
Imports: parallel (>= 3.4.4), Matrix (>= 1.2-16), methods (>= 3.4.4), lme4 (>= 1.1-21), e1071 (>= 1.7-0.1), class (>= 7.3-15), data.table (>= 1.12.6)
VignetteBuilder: R.rsp
Suggests: R.rsp
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-09-11 18:05:25 UTC; yuri
Repository: CRAN
Date/Publication: 2020-09-21 08:50:08 UTC

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Package vcd updated to version 1.4-8 with previous version 1.4-7 dated 2020-04-02

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

Diff between vcd versions 1.4-7 dated 2020-04-02 and 1.4-8 dated 2020-09-21

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Package TestDesign updated to version 1.1.2 with previous version 1.0.2 dated 2020-02-05

Title: Optimal Test Design Approach to Fixed and Adaptive Test Construction
Description: Use the optimal test design approach by Birnbaum (1968, ISBN:9781593119348) and van der Linden (2018) <doi:10.1201/9781315117430> in constructing fixed and adaptive tests. Supports the following mixed-integer programming (MIP) solver packages: 'lpsymphony', 'Rsymphony', 'gurobi', 'lpSolve', and 'Rglpk'. The 'gurobi' package is not available from CRAN; see <https://www.gurobi.com/downloads/>. See vignette for installing 'Rsymphony' package on Mac systems.
Author: Seung W. Choi [aut, cre] (<https://orcid.org/0000-0003-4777-5420>), Sangdon Lim [aut] (<https://orcid.org/0000-0002-2988-014X>)
Maintainer: Seung W. Choi <schoi@austin.utexas.edu>

Diff between TestDesign versions 1.0.2 dated 2020-02-05 and 1.1.2 dated 2020-09-21

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Package DODR (with last version 0.99.2) was removed from CRAN

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

2016-05-30 0.99.2

Permanent link
Package precautionary updated to version 0.1-4 with previous version 0.1-3 dated 2020-09-13

Title: Safety Diagnostics for Dose-Escalation Trial Designs
Description: Enhances various R packages that support the design and simulation of phase 1 dose-escalation trials, adding diagnostics to examine the safety characteristics of these designs in light of expected inter-individual variation in pharmacokinetics and pharmacodynamics. See Norris (2020), "Retrospective analysis of a fatal dose-finding trial" <arXiv:2004.12755>.
Author: David C. Norris [aut, cre, cph] (<https://orcid.org/0000-0001-9593-6343>)
Maintainer: David C. Norris <david@precisionmethods.guru>

Diff between precautionary versions 0.1-3 dated 2020-09-13 and 0.1-4 dated 2020-09-21

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Package pathfindR.data updated to version 1.1.0 with previous version 1.0.0 dated 2020-06-04

Title: Data Package for 'pathfindR'
Description: This is a data-only package, containing data needed to run the CRAN package 'pathfindR', a package for enrichment analysis utilizing active subnetworks. This package contains protein-protein interaction network data, data related to gene sets and example input/output data.
Author: Ege Ulgen [cre, cph] (<https://orcid.org/0000-0003-2090-3621>), Ozan Ozisik [aut] (<https://orcid.org/0000-0001-5980-8002>)
Maintainer: Ege Ulgen <egeulgen@gmail.com>

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Package nightmares updated to version 0.0.2 with previous version 0.0.1 dated 2020-09-09

Title: Common Analysis with Remote Sensing Data
Description: A collection of functions used in remote sensing analysis (e.g., conversion from digital numbers to radiance, reflectance, and temperature). It includes several algorithms to calculate the albedo: Liang (2000) <doi:10.1016/S0034-4257(00)00205-4>, Silva et al. (2016) <doi:10.32614/RJ-2016-051>, Tasumi et al. (2008) <doi:10.1061/(ASCE)1084-0699(2008)13:2(51)>, among others; and include functions to derive several spectral indices. Although the current version implements basic functions, it will be expandable to a more robust tool for water cycle modeling (e.g., to include surface runoff and evapotranspiration calculations) in the near future. This package is under development at the Institute about Natural Resources Research (INIRENA) from the Universidad Michoacana de San Nicolas de Hidalgo.
Author: Rafael Hernandez-Guzman [aut, cre] (<https://orcid.org/0000-0002-2711-9015>)
Maintainer: Rafael Hernandez-Guzman <rhernandez.g@gmail.com>

Diff between nightmares versions 0.0.1 dated 2020-09-09 and 0.0.2 dated 2020-09-21

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More information about nightmares at CRAN
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Package RUVIIIC (with last version 1.0.17) was removed from CRAN

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

2020-09-08 1.0.17
2020-09-04 1.0.16

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Package sdwd (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:

2020-09-03 1.0.4

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Package bnlearn updated to version 4.6.1 with previous version 4.6 dated 2020-09-15

Title: Bayesian Network Structure Learning, Parameter Learning and Inference
Description: Bayesian network structure learning, parameter learning and inference. This package implements constraint-based (PC, GS, IAMB, Inter-IAMB, Fast-IAMB, MMPC, Hiton-PC, HPC), pairwise (ARACNE and Chow-Liu), score-based (Hill-Climbing and Tabu Search) and hybrid (MMHC, RSMAX2, H2PC) structure learning algorithms for discrete, Gaussian and conditional Gaussian networks, along with many score functions and conditional independence tests. The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented. Some utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple and advanced plots) are included, as well as support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries, cross-validation, bootstrap and model averaging. Development snapshots with the latest bugfixes are available from <https://www.bnlearn.com/>.
Author: Marco Scutari [aut, cre], Robert Ness [ctb]
Maintainer: Marco Scutari <marco.scutari@gmail.com>

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