Wed, 12 Feb 2020

Package FastCUB updated to version 0.0.2 with previous version 0.0.1 dated 2020-01-31

Title: Fast EM and Best-Subset Selection for CUB Models for Rating Data
Description: For ordinal rating data, consider the accelerated Expectation-Maximization algorithm to estimate and test models within the family of CUB models (where CUB stands for Combination of a discrete Uniform and a shifted Binomial distributions). The procedure is built upon Louis' identity for the observed information matrix. Best-subset variable selection for CUB regression models is then implemented on such basis. The methods here implemented are illustrated and discussed in the preprint available from Researchgate by Simone R. (2020) <https://tinyurl.com/vvk563e>.
Author: Rosaria Simone <rosaria.simone@unina.it>
Maintainer: Rosaria Simone <rosaria.simone@unina.it>

Diff between FastCUB versions 0.0.1 dated 2020-01-31 and 0.0.2 dated 2020-02-12

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Package Runuran updated to version 0.30 with previous version 0.28 dated 2020-02-04

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

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More information about Runuran at CRAN
Permanent link

Package periscope updated to version 0.4.8 with previous version 0.4.7 dated 2019-12-10

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>

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Package SDMTools (with last version 1.1-221.2) was removed from CRAN

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

2019-11-30 1.1-221.2
2019-04-18 1.1-221.1
2014-08-05 1.1-221
2014-04-02 1.1-20
2012-11-08 1.1-13
2012-05-16 1.1-12
2012-04-10 1.1-11
2012-01-23 1.1-9
2011-01-20 1.1-5
2010-05-04 1.1
2009-12-10 1.0

Permanent link
Package plotly updated to version 4.9.2 with previous version 4.9.1 dated 2019-11-07

Title: Create Interactive Web Graphics via 'plotly.js'
Description: Create interactive web graphics from 'ggplot2' graphs and/or a custom interface to the (MIT-licensed) JavaScript library 'plotly.js' inspired by the grammar of graphics.
Author: Carson Sievert [aut, cre] (<https://orcid.org/0000-0002-4958-2844>), Chris Parmer [aut], Toby Hocking [aut], Scott Chamberlain [aut], Karthik Ram [aut], Marianne Corvellec [aut] (<https://orcid.org/0000-0002-1994-3581>), Pedro Despouy [aut], Plotly Technologies Inc. [cph]
Maintainer: Carson Sievert <cpsievert1@gmail.com>

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Package warbleR updated to version 1.1.22 with previous version 1.1.21 dated 2020-02-04

Title: Streamline Bioacoustic Analysis
Description: Functions aiming to facilitate the analysis of the structure of animal acoustic signals in 'R'. Users can collect open-access avian recordings or enter their own data into a workflow that facilitates spectrographic visualization and measurement of acoustic parameters. 'warbleR' makes use of the basic sound analysis tools from the package 'seewave', and offers new tools for acoustic structure analysis. The main features of the package are the use of loops to apply tasks through acoustic signals referenced in a selection (annotation) table and the production of spectrograms in image files that allow to organize data and verify acoustic analyzes. The package offers functions to explore, organize and manipulate multiple sound files, explore and download 'Xeno-Canto' recordings, detect signals automatically, create spectrograms of complete recordings or individual signals, run different measures of acoustic signal structure, evaluate the performance of measurement methods, catalog signals, characterize different structural levels in acoustic signals, run statistical analysis of duet coordination and consolidate databases and annotation tables, among others.
Author: Marcelo Araya-Salas [aut, cre] (<https://orcid.org/0000-0003-3594-619X>), Grace Smith-Vidaurre [aut]
Maintainer: Marcelo Araya-Salas <marceloa27@gmail.com>

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Package ergmito updated to version 0.2-1 with previous version 0.2-0 dated 2020-02-01

Title: Exponential Random Graph Models for Small Networks
Description: Simulation and estimation of Exponential Random Graph Models (ERGMs) for small networks using exact statistics. As a difference from the 'ergm' package, 'ergmito' circumvents using Markov-Chain Maximum Likelihood Estimator (MC-MLE) and instead uses Maximum Likelihood Estimator (MLE) to fit ERGMs for small networks. As exhaustive enumeration is computationally feasible for small networks, this R package takes advantage of this and provides tools for calculating likelihood functions, and other relevant functions, directly, meaning that in many cases both estimation and simulation of ERGMs for small networks can be faster and more accurate than simulation-based algorithms.
Author: George Vega Yon [cre, aut] (<https://orcid.org/0000-0002-3171-0844>), Kayla de la Haye [ths] (<https://orcid.org/0000-0002-2536-7701>), Army Research Laboratory and the U.S. Army Research Office [fnd] (Grant Number W911NF-15-1-0577)
Maintainer: George Vega Yon <g.vegayon@gmail.com>

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Package xlsx updated to version 0.6.2 with previous version 0.6.1 dated 2018-06-11

Title: Read, Write, Format Excel 2007 and Excel 97/2000/XP/2003 Files
Description: Provide R functions to read/write/format Excel 2007 and Excel 97/2000/XP/2003 file formats.
Author: Adrian Dragulescu [aut], Cole Arendt [aut, cre]
Maintainer: Cole Arendt <cole.arendt@outlook.com>

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Package simsem updated to version 0.5-15 with previous version 0.5-14 dated 2018-06-03

Title: SIMulated Structural Equation Modeling
Description: Provides an easy framework for Monte Carlo simulation in structural equation modeling, which can be used for various purposes, such as such as model fit evaluation, power analysis, or missing data handling and planning.
Author: Sunthud Pornprasertmanit [aut], Patrick Miller [aut], Alexander Schoemann [aut], Terrence D. Jorgensen [aut, cre] (<https://orcid.org/0000-0001-5111-6773>), Corbin Quick [ctb]
Maintainer: Terrence D. Jorgensen <TJorgensen314@gmail.com>

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Package Rraven updated to version 1.0.9 with previous version 1.0.8 dated 2019-11-02

Title: Connecting R and 'Raven' Sound Analysis Software
Description: A tool to exchange data between R and 'Raven' sound analysis software (Cornell Lab of Ornithology). Functions work on data formats compatible with the R package 'warbleR'.
Author: Marcelo Araya-Salas [aut, cre] (<https://orcid.org/0000-0003-3594-619X>)
Maintainer: Marcelo Araya-Salas <marceloa27@gmail.com>

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Package ggnetwork updated to version 0.5.8 with previous version 0.5.1 dated 2016-03-24

Title: Geometries to Plot Networks with 'ggplot2'
Description: Geometries to plot network objects with 'ggplot2'.
Author: François Briatte [aut, cre] (<https://orcid.org/0000-0001-6494-9774>), Michał Bojanowski [ctb] (<https://orcid.org/0000-0001-7503-852X>), Mickaël Canouil [ctb] (<https://orcid.org/0000-0002-3396-4549>), Zachary Charlop-Powers [ctb] (<https://orcid.org/0000-0001-8816-4680>), Jacob C. Fisher [ctb] (<https://orcid.org/0000-0003-0299-0346>), Kipp Johnson [ctb] (<https://orcid.org/0000-0002-5102-741X>), Tyler Rinker [ctb]
Maintainer: François Briatte <f.briatte@gmail.com>

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Package weights updated to version 1.0.1 with previous version 1.0 dated 2018-10-16

Title: Weighting and Weighted Statistics
Description: Provides a variety of functions for producing simple weighted statistics, such as weighted Pearson's correlations, partial correlations, Chi-Squared statistics, histograms, and t-tests. Also now includes some software for quickly recoding survey data and plotting point estimates from interaction terms in regressions (and multiply imputed regressions). NOTE: Weighted partial correlation calculations pulled to address a bug.
Author: Josh Pasek [aut, cre], with some assistance from Alex Tahk and some code modified from R-core; Additional contributions by Gene Culter and Marcus Schwemmle.
Maintainer: Josh Pasek <josh@joshpasek.com>

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Package SubTite updated to version 3.0.1 with previous version 3.0.0 dated 2019-11-03

Title: Subgroup Specific Optimal Dose Assignment
Description: Chooses subgroup specific optimal doses in a phase I dose finding clinical trial allowing for subgroup combination and simulates clinical trials under the subgroup specific time to event continual reassessment method. Chapple, A.G., Thall, P.F. (2018) <doi:10.1002/pst.1891>.
Author: Andrew Chapple
Maintainer: Andrew Chapple <achapp@lsuhsc.edu>

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Package spaMM updated to version 3.1.2 with previous version 3.0.0 dated 2019-06-21

Title: Mixed-Effect Models, Particularly Spatial Models
Description: Inference based on mixed-effect models, including generalized linear mixed models with spatial correlations and models with non-Gaussian random effects (e.g., Beta). Both classical geostatistical models, and Markov random field models on irregular grids, can be fitted. Variation in residual variance (heteroscedasticity) can itself be represented by a generalized linear mixed model. Various approximations of likelihood or restricted likelihood are implemented, in particular h-likelihood (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) and Laplace approximation.
Author: François Rousset [aut, cre, cph] (<https://orcid.org/0000-0003-4670-0371>), Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut] (<https://orcid.org/0000-0003-0637-2959>), GSL authors [ctb] (src/gsl_bessel.*)
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

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Package smurf updated to version 1.0.4 with previous version 1.0.3 dated 2020-02-07

Title: Sparse Multi-Type Regularized Feature Modeling
Description: Implementation of the SMuRF algorithm of Devriendt et al. (2018) <arXiv:1810.03136> to fit generalized linear models (GLMs) with multiple types of predictors via regularized maximum likelihood.
Author: Tom Reynkens [aut, cre] (<https://orcid.org/0000-0002-5516-5107>), Sander Devriendt [aut], Katrien Antonio [aut]
Maintainer: Tom Reynkens <tomreynkens@hotmail.com>

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Package poppr updated to version 2.8.4 with previous version 2.8.3 dated 2019-06-18

Title: Genetic Analysis of Populations with Mixed Reproduction
Description: Population genetic analyses for hierarchical analysis of partially clonal populations built upon the architecture of the 'adegenet' package. Originally described in Kamvar, Tabima, and Grünwald (2014) <doi:10.7717/peerj.281> with version 2.0 described in Kamvar, Brooks, and Grünwald (2015) <doi:10.3389/fgene.2015.00208>.
Author: Zhian N. Kamvar [cre, aut] (<https://orcid.org/0000-0003-1458-7108>), Javier F. Tabima [aut] (<https://orcid.org/0000-0002-3603-2691>), Sydney E. Everhart [ctb, dtc] (<https://orcid.org/0000-0002-5773-1280>), Jonah C. Brooks [aut], Stacy A. Krueger-Hadfield [ctb] (<https://orcid.org/0000-0002-7324-7448>), Erik Sotka [ctb], Brian J. Knaus [ctb] (<https://orcid.org/0000-0003-1665-4343>), Patrick G. Meirmans [ctb] (<https://orcid.org/0000-0002-6395-8107>), Frédéric D. Chevalier [ctb] (<https://orcid.org/0000-0003-2611-8106>), Niklaus J. Grünwald [ths] (<https://orcid.org/0000-0003-1656-7602>)
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>

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Package hpiR updated to version 0.3.1 with previous version 0.3.0 dated 2020-01-11

Title: House Price Indexes
Description: Compute house price indexes and series using a variety of different methods and models common through the real estate literature. Evaluate index 'goodness' based on accuracy, volatility and revision statistics. Background on basic model construction for repeat sales models can be found at: Case and Quigley (1991) <https://ideas.repec.org/a/tpr/restat/v73y1991i1p50-58.html> and for hedonic pricing models at: Bourassa et al (2006) <doi:10.1016/j.jhe.2006.03.001>. The package author's working paper on the random forest approach to house price indexes can be found at: <http://www.github.com/andykrause/hpi_research>.
Author: Andy Krause [aut, cre]
Maintainer: Andy Krause <andyxkrause@gmail.com>

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Package DistributionOptimization updated to version 1.2.6 with previous version 1.2.4 dated 2019-11-25

Title: Distribution Optimization
Description: Fits Gaussian Mixtures by applying evolution. As fitness function a mixture of the chi square test for distributions and a novel measure for approximating the common area under curves between multiple Gaussians is used. The package presents an alternative to the commonly used Likelihood Maximization as is used in Expectation Maximization. The algorithm and applications of this package are published under: Lerch, F., Ultsch, A., Lotsch, J. (2020) <doi:10.1038/s41598-020-57432-w>. The evolution is based on the 'GA' package: Scrucca, L. (2013) <doi:10.18637/jss.v053.i04> while the Gaussian Mixture Logic stems from 'AdaptGauss': Ultsch, A, et al. (2015) <doi:10.3390/ijms161025897>.
Author: Florian Lerch, Jorn Lotsch, Alfred Ultsch
Maintainer: Florian Lerch <lerch@mathematik.uni-marburg.de>

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Package DarkDiv updated to version 0.2.0 with previous version 0.1.0 dated 2019-04-27

Title: Estimating Dark Diversity and Site-Specific Species Pools
Description: Estimation of dark diversity and site-specific species pools using species co-occurrences. It includes implementations of probabilistic dark diversity based on the Hypergeometric distribution, as well as estimations based on the Beals index, which can be transformed to binary predictions using different thresholds, or transformed into a favorability index. All methods include the possibility of using a calibration dataset that is used to estimate the indication matrix between pairs of species, or to estimate dark diversity directly on a single dataset. See De Caceres and Legendre (2008) <doi:10.1007/s00442-008-1017-y>, Lewis et al. (2016) <doi:10.1111/2041-210X.12443>, Partel et al. (2011) <doi:10.1016/j.tree.2010.12.004>, Real et al. (2017) <doi:10.1093/sysbio/syw072> for further information.
Author: Carlos P. Carmona
Maintainer: Carlos P. Carmona <perezcarmonacarlos@gmail.com>

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Package AGread updated to version 1.1.0 with previous version 1.0.0 dated 2019-09-18

Title: Read Data Files from ActiGraph Monitors
Description: Standardize the process of bringing various modes of output files into R. Additionally, processes are provided to read and minimally pre- process raw data from primary accelerometer and inertial measurement unit files, as well as binary .gt3x files. ActiGraph monitors are used to estimate physical activity outcomes via body-worn sensors that measure (e.g.) acceleration or rotational velocity.
Author: Paul R. Hibbing [aut, cre], Vincent T. van Hees [ctb], Samuel R. LaMunion [ctb], John Muschelli [ctb], Daniel Judge [ctb], Judge Maygarden [ctb], ActiGraph LLC [cph]
Maintainer: Paul R. Hibbing <paulhibbing@gmail.com>

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Package RgoogleMaps updated to version 1.4.5.3 with previous version 1.4.5.2 dated 2020-01-26

Title: Overlays on Static Maps
Description: Serves two purposes: (i) Provide a comfortable R interface to query the Google server for static maps, and (ii) Use the map as a background image to overlay plots within R. This requires proper coordinate scaling.
Author: Markus Loecher
Maintainer: Markus Loecher <markus.loecher@gmail.com>

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Package digest updated to version 0.6.24 with previous version 0.6.23 dated 2019-11-23

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

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Package DDPNA updated to version 0.2.3 with previous version 0.2.1 dated 2019-06-15

Title: Disease-Related Differential Proteins and Co-Expression Network Analysis
Description: Functions designed to connect disease-related differential proteins and co-expression network. It provides the basic statics analysis included t test, ANOVA analysis. The network construction is not offered by the package, you can used 'WGCNA' package which you can learn in Peter et al. (2008) <doi:10.1186/1471-2105-9-559>. It also provides module analysis included PCA analysis, two enrichment analysis, Planner maximally filtered graph extraction and hub analysis.
Author: Kefu Liu [aut, cre]
Maintainer: Kefu Liu <liukefu19@163.com>

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Package dataPreparation updated to version 0.4.3 with previous version 0.4.2 dated 2019-11-14

Title: Automated Data Preparation
Description: Do most of the painful data preparation for a data science project with a minimum amount of code; Take advantages of data.table efficiency and use some algorithmic trick in order to perform data preparation in a time and RAM efficient way.
Author: Emmanuel-Lin Toulemonde [aut, cre]
Maintainer: Emmanuel-Lin Toulemonde <el.toulemonde@protonmail.com>

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Package callr updated to version 3.4.2 with previous version 3.4.1 dated 2020-01-24

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 worldmet updated to version 0.8.8 with previous version 0.8.7 dated 2019-04-17

Title: Import Surface Meteorological Data from NOAA Integrated Surface Database (ISD)
Description: Functions to import data from more than 30,000 surface meteorological sites around the world managed by the National Oceanic and Atmospheric Administration (NOAA) Integrated Surface Database (ISD, see <https://www.ncdc.noaa.gov/isd>).
Author: David Carslaw [aut, cre]
Maintainer: David Carslaw <david.carslaw@york.ac.uk>

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Package DRR updated to version 0.0.4 with previous version 0.0.3 dated 2018-01-06

Title: Dimensionality Reduction via Regression
Description: An Implementation of Dimensionality Reduction via Regression using Kernel Ridge Regression.
Author: Guido Kraemer [aut, cre]
Maintainer: Guido Kraemer <gkraemer@bgc-jena.mpg.de>

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Package coRanking updated to version 0.2.1 with previous version 0.1.4 dated 2018-10-01

Title: Co-Ranking Matrix
Description: Calculates the co-ranking matrix to assess the quality of a dimensionality reduction.
Author: Guido Kraemer
Maintainer: Guido Kraemer <gkraemer@bgc-jena.mpg.de>

Diff between coRanking versions 0.1.4 dated 2018-10-01 and 0.2.1 dated 2020-02-12

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Package Umatrix updated to version 3.3 with previous version 3.1 dated 2017-12-18

Title: Visualization of Structures in High-Dimensional Data
Description: By gaining the property of emergence through self-organization, the enhancement of SOMs(self organizing maps) is called Emergent SOM (ESOM). The result of the projection by ESOM is a grid of neurons which can be visualised as a three dimensional landscape in form of the Umatrix. Further details can be found in the referenced publications (see url). This package offers tools for calculating and visualising the ESOM as well as Umatrix, Pmatrix and UStarMatrix. All the functionality is also available through graphical user interfaces implemented in 'shiny'.
Author: Florian Lerch[aut,cre], Michael Thrun[aut], Felix Pape[ctb], Raphael Paebst[ctb], Alfred Ultsch[aut]
Maintainer: Florian Lerch <lerch@mathematik.uni-marburg.de>

Diff between Umatrix versions 3.1 dated 2017-12-18 and 3.3 dated 2020-02-12

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More information about Umatrix at CRAN
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Package rgl updated to version 0.100.47 with previous version 0.100.30 dated 2019-08-19

Title: 3D Visualization Using OpenGL
Description: Provides medium to high level functions for 3D interactive graphics, including functions modelled on base graphics (plot3d(), etc.) as well as functions for constructing representations of geometric objects (cube3d(), etc.). Output may be on screen using OpenGL, or to various standard 3D file formats including WebGL, PLY, OBJ, STL as well as 2D image formats, including PNG, Postscript, SVG, PGF.
Author: Daniel Adler <dadler@uni-goettingen.de>, Duncan Murdoch <murdoch@stats.uwo.ca>, and others (see README)
Maintainer: Duncan Murdoch <murdoch@stats.uwo.ca>

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Package ps updated to version 1.3.1 with previous version 1.3.0 dated 2018-12-21

Title: List, Query, Manipulate System Processes
Description: List, query and manipulate all system processes, on 'Windows', 'Linux' and 'macOS'.
Author: Jay Loden [aut], Dave Daeschler [aut], Giampaolo Rodola' [aut], Gábor Csárdi [aut, cre], RStudio [cph]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between ps versions 1.3.0 dated 2018-12-21 and 1.3.1 dated 2020-02-12

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Package NMF updated to version 0.22.0 with previous version 0.21.0 dated 2018-03-06

Title: Algorithms and Framework for Nonnegative Matrix Factorization (NMF)
Description: Provides a framework to perform Non-negative Matrix Factorization (NMF). The package implements a set of already published algorithms and seeding methods, and provides a framework to test, develop and plug new/custom algorithms. Most of the built-in algorithms have been optimized in C++, and the main interface function provides an easy way of performing parallel computations on multicore machines.
Author: Renaud Gaujoux, Cathal Seoighe
Maintainer: Nicolas Sauwen <nicolas.sauwen@openanalytics.eu>

Diff between NMF versions 0.21.0 dated 2018-03-06 and 0.22.0 dated 2020-02-12

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More information about NMF at CRAN
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Package merDeriv updated to version 0.1-8 with previous version 0.1-7 dated 2019-07-10

Title: Case-Wise and Cluster-Wise Derivatives for Mixed Effects Models
Description: Compute case-wise and cluster-wise derivative for mixed effects models with respect to fixed effects parameter, random effect (co)variances, and residual variance. This material is partially based on work supported by the National Science Foundation under Grant Number 1460719.
Author: Ting Wang [aut, cre], Edgar Merkle [aut] (<https://orcid.org/0000-0001-7158-0653>), Yves Rosseel [ctb]
Maintainer: Ting Wang <twb8d@mail.missouri.edu>

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Package lotri updated to version 0.2.1 with previous version 0.1.1 dated 2019-05-14

Title: A Simple Way to Specify Symmetric, Block Diagonal Matrices
Description: Provides a simple mechanism to specify a symmetric block diagonal matrices (often used for covariance matrices). This is based on the domain specific language implemented in 'nlmixr' but expanded to create matrices in R generally instead of specifying parts of matrices to estimate.
Author: Matthew L. Fidler [aut, cre] (<https://orcid.org/0000-0001-8538-6691>)
Maintainer: Matthew L. Fidler <matthew.fidler@gmail.com>

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Permanent link

Package EmbedSOM updated to version 2.1.1 with previous version 1.9 dated 2019-08-19

Title: Fast Embedding Guided by Self-Organizing Map
Description: Provides a smooth mapping of multidimensional points into low-dimensional space defined by a self-organizing map. Designed to work with 'FlowSOM' and flow-cytometry use-cases. See Kratochvil et al. (2019) <doi:10.1101/496869>.
Author: Mirek Kratochvil [aut, cre], Sofie Van Gassen [cph], Britt Callebaut [cph], Yvan Saeys [cph], Ron Wehrens [cph]
Maintainer: Mirek Kratochvil <exa.exa@gmail.com>

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Package openblender updated to version 0.3.6 with previous version 0.3.5 dated 2020-01-29

Title: Request <https://openblender.io> API Services
Description: Interface to make HTTP requests to 'OpenBlender' API services. Go to <https://openblender.io> for more information.
Author: Open Blender Inc. [cph], Daniel V. Pinacho [aut, cre]
Maintainer: Daniel V. Pinacho <danielvpinacho@gmail.com>

Diff between openblender versions 0.3.5 dated 2020-01-29 and 0.3.6 dated 2020-02-12

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Package manymodelr updated to version 0.2.4 with previous version 0.2.3 dated 2020-02-05

Title: Build and Tune Several Models
Description: Frequently one needs a convenient way to build and tune several models in one go.The goal is to provide a number of convenience functions useful in machine learning applications. It provides the ability to build, tune and obtain predictions of several models in one function. The models are built using 'caret' functions with easier to read syntax. Kuhn(2014) <arXiv:1405.6974>. Kuhn(2008) <doi10.18637/jss.v028.i05>. Chambers,J.M.(1992) <doi:10.1007/978-3-642-50096-1_48>. Wilkinson,G.N. and Rogers, C. E. (1973) <doi:10.2307/2346786>.
Author: Nelson Gonzabato [aut, cre]
Maintainer: Nelson Gonzabato <gonzabato@hotmail.com>

Diff between manymodelr versions 0.2.3 dated 2020-02-05 and 0.2.4 dated 2020-02-12

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New package WaterML with initial version 1.9.0
Package: WaterML
Type: Package
Title: Fetch and Analyze Data from 'WaterML' and 'WaterOneFlow' Web Services
Version: 1.9.0
Authors@R: person("Jiri","Kadlec", email="jirikadlec2@gmail.com", role=c("aut", "cre"))
Description: Lets you connect to any of the 'Consortium of Universities for the Advancement of Hydrological Science, Inc.' ('CUAHSI') Water Data Center 'WaterOneFlow' web services and read any 'WaterML' time series data file. To see list of available web services, see <http://hiscentral.cuahsi.org>. All versions of 'WaterML' (1.0, 1.1 and 2.0) and both types of the web service protocol ('SOAP' and 'REST') are supported. The package has six data download functions: GetServices(): show all public web services from the HIS Central Catalog. HISCentral_GetSites() and HISCentral_GetSeriesCatalog(): search for sites or time series from the HIS Central catalog based on geographic bounding box, server, or keyword. GetVariables(): Show a data.frame with all variables on the server. GetSites(): Show a data.frame with all sites on the server. GetSiteInfo(): Show what variables, methods and quality control levels are available at the specific site. GetValues(): Given a site code, variable code, start time and end time, fetch a data.frame of all the observation time series data values. The GetValues() function can also parse 'WaterML' data from a custom URL or from a local file.
License: MIT + file LICENSE
Depends: R (>= 3.0)
Imports: stats, XML, httr
LazyData: true
URL: https://github.com/jirikadlec2/waterml
Suggests: knitr, qpdf
VignetteBuilder: knitr
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-02-12 01:00:03 UTC; Admin
Author: Jiri Kadlec [aut, cre]
Maintainer: Jiri Kadlec <jirikadlec2@gmail.com>
Repository: CRAN
Date/Publication: 2020-02-12 10:50:05 UTC

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Package Umoments updated to version 0.1.1 with previous version 0.1.0 dated 2019-04-01

Title: Unbiased Central Moment Estimates
Description: Calculates one-sample unbiased central moment estimates and two-sample pooled estimates up to 6th order, including estimates of powers and products of central moments. Provides the machinery for obtaining unbiased central moment estimators beyond 6th order by generating expressions for expectations of raw sample moments and their powers and products. Gerlovina and Hubbard (2019) <doi:10.1080/25742558.2019.1701917>.
Author: Inna Gerlovina [aut, cre], Alan Hubbard [aut]
Maintainer: Inna Gerlovina <innager@berkeley.edu>

Diff between Umoments versions 0.1.0 dated 2019-04-01 and 0.1.1 dated 2020-02-12

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Package raptr updated to version 0.1.5 with previous version 0.1.4 dated 2019-04-11

Title: Representative and Adequate Prioritization Toolkit in R
Description: Biodiversity is in crisis. The overarching aim of conservation is to preserve biodiversity patterns and processes. To this end, protected areas are established to buffer species and preserve biodiversity processes. But resources are limited and so protected areas must be cost-effective. This package contains tools to generate plans for protected areas (prioritizations), using spatially explicit targets for biodiversity patterns and processes. To obtain solutions in a feasible amount of time, this package uses the commercial 'Gurobi' software package (obtained from <http://www.gurobi.com/>). For more information on using this package, see Hanson et al. (2018) <doi:10.1111/2041-210X.12862>.
Author: Jeffrey O Hanson [aut, cre], Jonathan R Rhodes [aut], Hugh P Possingham [aut], Richard A Fuller [aut]
Maintainer: Jeffrey O Hanson <jeffrey.hanson@uqconnect.edu.au>

Diff between raptr versions 0.1.4 dated 2019-04-11 and 0.1.5 dated 2020-02-12

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New package RcppSimdJson with initial version 0.0.1
Package: RcppSimdJson
Type: Package
Title: 'Rcpp' Bindings for the 'simdjson' Header-Only Library for 'JSON' Parsing
Version: 0.0.1
Date: 2020-01-25
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>
Description: The 'JSON' format is ubiquitous for data interchange, and the 'simdjson' library written by Daniel Lemire (and many contributors) provides a high-performance parser for these files which by relying on parallel 'SIMD' instruction manages to parse these files as faster than disk speed. See the <arXiv:1902.08318> paper for more details about 'simdjson'. This package is at present only a very thin and incomplete wrapper and does not aim to replace the existing and excellent 'JSON' packages for R. But it does already validate orders of magnitude faster.
SystemRequirements: C++17
OS_type: unix
License: GPL (>= 2)
Imports: Rcpp
LinkingTo: Rcpp
Suggests: tinytest
RoxygenNote: 7.0.2
NeedsCompilation: yes
Packaged: 2020-01-25 23:02:02.1361 UTC; edd
Repository: CRAN
Date/Publication: 2020-02-12 10:10:02 UTC

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New package netdiffuseR with initial version 1.21.0
Package: netdiffuseR
Title: Analysis of Diffusion and Contagion Processes on Networks
Version: 1.21.0
Date: 2020-02-10
Authors@R: c( person("George", "Vega Yon", email="g.vegayon@gmail.com", role=c("aut", "cre"), comment=c(ORCID = "0000-0002-3171-0844", what="Rewrite functions with Rcpp, plus new features") ), person("Thomas", "Valente", email="tvalente@usc.edu", role=c("aut", "cph"), comment=c(ORCID="0000-0002-8824-5816", what="R original code")), person("Stephanie", "Dyal", email="stepharp@usc.edu", role=c("ctb"), comment="Package's first version"), person("Timothy", "Hayes", email="timothybhayes@gmail.com", role=c("ctb"), comment="Package's first version") )
Description: Empirical statistical analysis, visualization and simulation of diffusion and contagion processes on networks. The package implements algorithms for calculating network diffusion statistics such as transmission rate, hazard rates, exposure models, network threshold levels, infectiousness (contagion), and susceptibility. The package is inspired by work published in Valente, et al., (2015) <DOI:10.1016/j.socscimed.2015.10.001>; Valente (1995) <ISBN: 9781881303213>, Myers (2000) <DOI:10.1086/303110>, Iyengar and others (2011) <DOI:10.1287/mksc.1100.0566>, Burt (1987) <DOI:10.1086/228667>; among others.
Depends: R (>= 3.1.1)
License: MIT + file LICENSE
LazyData: true
Imports: Rcpp (>= 0.12.1), sna, network, networkDynamic, Matrix, MASS, MatchIt, SparseM, methods, grDevices, graphics, stats, utils, boot, igraph, viridisLite
Suggests: covr, testthat, knitr, ape, RSiena, survival
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.0.2
Encoding: UTF-8
URL: https://github.com/USCCANA/netdiffuseR, https://USCCANA.github.io/netdiffuseR
BugReports: https://github.com/USCCANA/netdiffuseR/issues
Classification/MSC: 90C35, 90B18, 91D30
Collate: 'RcppExports.R' 'imports.r' 'graph_data.r' 'adjmat.r' 'bass.r' 'bootnet.r' 'data.r' 'diffnet-c.R' 'diffnet-class.r' 'diffnet-indexing.r' 'diffnet-methods.r' 'egonets.R' 'formula.r' 'igraph.r' 'infect_suscept.r' 'mentor.r' 'misc.r' 'moran.r' 'netmatch.r' 'network.r' 'options.R' 'package-doc.r' 'plot_diffnet2.r' 'rewire.r' 'random_graph.R' 'rdiffnet.r' 'read_write_foreign.r' 'select_egoalter.R' 'spatial.R' 'stats.R' 'struct_equiv.R' 'struct_test.R' 'survey_to_diffnet.R'
NeedsCompilation: yes
Packaged: 2020-02-12 06:54:49 UTC; george
Author: George Vega Yon [aut, cre] (<https://orcid.org/0000-0002-3171-0844>, Rewrite functions with Rcpp, plus new features), Thomas Valente [aut, cph] (<https://orcid.org/0000-0002-8824-5816>, R original code), Stephanie Dyal [ctb] (Package's first version), Timothy Hayes [ctb] (Package's first version)
Maintainer: George Vega Yon <g.vegayon@gmail.com>
Repository: CRAN
Date/Publication: 2020-02-12 10:40:02 UTC

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Package multipleNCC updated to version 1.2-2 with previous version 1.2-1 dated 2016-04-19

Title: Weighted Cox-Regression for Nested Case-Control Data
Description: Fit Cox proportional hazard models with a weighted partial likelihood. It handles one or multiple endpoints, additional matching and makes it possible to reuse controls for other endpoints.
Author: Nathalie C. Stoer, Sven Ove Samuelsen
Maintainer: Nathalie C. Stoer <nathalie.c.stoer@kreftregisteret.no>

Diff between multipleNCC versions 1.2-1 dated 2016-04-19 and 1.2-2 dated 2020-02-12

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New package GenomicTools with initial version 0.2.9.5
Package: GenomicTools
Type: Package
Title: Collection of Tools for Genomic Data Analysis
Version: 0.2.9.5
Date: 2020-02-07
Author: Daniel Fischer
Maintainer: Daniel Fischer <daniel.fischer@luke.fi>
Depends: R (>= 3.3), gMWT (>= 1.1), Rcpp (>= 0.9.13), data.table (>= 1.9.6), GenomicTools.fileHandler (>= 0.1.5.8)
Imports: circlize, stringr, snpStats
Suggests: knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
Description: A loose collection of tools for the analysis of expression and genotype data, currently with the main focus on (e)QTL and MDR analysis.
VignetteBuilder: knitr
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2020-02-12 09:26:24 UTC; ejo138
Repository: CRAN
Date/Publication: 2020-02-12 10:30:09 UTC

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New package fplot with initial version 0.2.1
Package: fplot
Type: Package
Title: Automatic Distribution Graphs Using Formulas
Version: 0.2.1
Authors@R: person("Laurent", "Berge", email = "laurent.berge@uni.lu", role = c("aut", "cre"))
Imports: stats, graphics, utils, Formula, Rcpp
Suggests: knitr, rmarkdown, fixest
LinkingTo: Rcpp
Depends: R(>= 3.5.0), data.table
Description: Easy way to plot regular/weighted/conditional distributions by using formulas. The core of the package concerns distribution plots which are automatic: the many options are tailored to the data at hand to offer the nicest and most meaningful graphs possible -- with no/minimum user input. Further provide functions to plot conditional trends and boxplots.
License: GPL-3
SystemRequirements: C++11
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2020-02-12 09:05:37 UTC; Laurent
Author: Laurent Berge [aut, cre]
Maintainer: Laurent Berge <laurent.berge@uni.lu>
Repository: CRAN
Date/Publication: 2020-02-12 10:40:09 UTC

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New package cheese with initial version 0.0.3
Package: cheese
Version: 0.0.3
Date: 2020-02-11
Title: Tools for Intuitive and Flexible Statistical Analysis Workflows
Authors@R: person(given = "Alex", family = "Zajichek", email = "alexzajichek@gmail.com", role = c("aut", "cre"))
Description: Contains flexible and intuitive functions to assist in carrying out tasks in a statistical analysis and to get from the raw data to presentation-ready results. A user-friendly interface is used in specialized functions that are aimed at common tasks such as building a univariate descriptive table for variables in a dataset. These high-level functions are built on a collection of low(er)-level functions that may be useful for aspects of a custom statistical analysis workflow or for general programming use.
URL: https://github.com/zajichek/cheese
License: MIT + file LICENSE
Depends: R (>= 3.4.0)
Imports: dplyr (>= 0.7.7), forcats (>= 0.3.0), kableExtra (>= 1.0.1), knitr (>= 1.20), magrittr (>= 1.5), methods (>= 3.4.1), purrr (>= 0.2.4), rlang (>= 0.3.0.1), stringr (>= 1.3.1), tibble (>= 1.4.2), tidyr (>= 0.8.1), tidyselect (>= 0.2.4)
Suggests: rmarkdown (>= 1.10), tidyverse (>= 1.2.1)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2020-02-11 23:03:20 UTC; alexzajichek
Author: Alex Zajichek [aut, cre]
Maintainer: Alex Zajichek <alexzajichek@gmail.com>
Repository: CRAN
Date/Publication: 2020-02-12 10:50:02 UTC

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Package JointAI updated to version 0.6.1 with previous version 0.6.0 dated 2019-08-31

Title: Joint Analysis and Imputation of Incomplete Data
Description: Provides joint analysis and imputation of (generalized) linear and cumulative logit regression models, (generalized) linear and cumulative logit mixed models and parametric (Weibull) as well as Cox proportional hazards survival models with incomplete (covariate) data in the Bayesian framework. The package performs some preprocessing of the data and creates a 'JAGS' model, which will then automatically be passed to 'JAGS' <http://mcmc-jags.sourceforge.net> with the help of the package 'rjags'. It also provides summary and plotting functions for the output and allows the user to export imputed values.
Author: Nicole S. Erler [aut, cre] (<https://orcid.org/0000-0002-9370-6832>)
Maintainer: Nicole S. Erler <n.erler@erasmusmc.nl>

Diff between JointAI versions 0.6.0 dated 2019-08-31 and 0.6.1 dated 2020-02-12

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Package wyz.code.testthat updated to version 1.1.16 with previous version 1.1.9 dated 2019-10-13

Title: Wizardry Code Offensive Programming Test Generation
Description: Allows to generate automatically 'testthat' code files from offensive programming test cases. Generated test files are complete and ready to run. Using 'wyz.code.testthat' you will earn a lot of time, reduce the number of errors in test case production, be able to test immediately generated files without any need to view or modify them, and enter a zero time latency between code implementation and industrial testing. As with 'testthat', you may complete provided test cases according to your needs to push testing further, but this need is nearly void when using 'wyz.code.offensiveProgramming'. Refer to chapter 9 of Offensive Programming Book, Fabien GELINEAU (2019, ISBN:979-10-699-4075-8), to learn about details and get value from this package.
Author: Fabien Gelineau <neonira@gmail.com>
Maintainer: Fabien Gelineau <neonira@gmail.com>

Diff between wyz.code.testthat versions 1.1.9 dated 2019-10-13 and 1.1.16 dated 2020-02-12

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Package sharpeRratio updated to version 1.3 with previous version 1.2 dated 2019-12-05

Title: Moment-Free Estimation of Sharpe Ratios
Description: An efficient moment-free estimator of the Sharpe ratio, or signal-to-noise ratio, for heavy-tailed data (see <arXiv:1505.01333>).
Author: Damien Challet
Maintainer: Damien Challet <damien.challet@gmail.com>

Diff between sharpeRratio versions 1.2 dated 2019-12-05 and 1.3 dated 2020-02-12

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Package miceRanger (with last version 1.3.0) was removed from CRAN

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

2020-01-29 1.3.0
2020-01-20 1.2.0
2020-01-19 1.1.0

Permanent link
Package wyz.code.metaTesting updated to version 1.1.11 with previous version 1.1.4 dated 2019-10-13

Title: Wizardry Code Meta Testing
Description: Test R any R function without having to provide parameter values. Values will be generated, based on semantic naming of parameters as introduced by package 'wyz.code.offensiveProgramming'. Generated tests can be saved and reused. Value generation logic can be completed with your own specific data types and generation schemes, to meet your requirements. Main benefits of 'wyz.code.metaTesting' is higher developer productivity, reduced time to production, and industrial inference testing. Refer to chapter 10 of Offensive Programming Book, Fabien GELINEAU (2019, ISBN:979-10-699-4075-8), to learn about details and get value from this package.
Author: Fabien Gelineau <neonira@gmail.com>
Maintainer: Fabien Gelineau <neonira@gmail.com>

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Package predictmeans updated to version 1.0.2 with previous version 1.0.1 dated 2018-08-23

Title: Calculate Predicted Means for Linear Models
Description: Providing functions to diagnose and make inferences from various linear models, such as those obtained from 'aov', 'lm', 'glm', 'gls', 'lme', and 'lmer'. Inferences include predicted means and standard errors, contrasts, multiple comparisons, permutation tests and graphs.
Author: Dongwen Luo, Siva Ganesh and John Koolaard
Maintainer: Dongwen Luo <dongwen.luo@agresearch.co.nz>

Diff between predictmeans versions 1.0.1 dated 2018-08-23 and 1.0.2 dated 2020-02-12

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Package FCSlib updated to version 1.1.0 with previous version 1.0.0 dated 2019-08-05

Title: A Collection of Fluorescence Fluctuation Spectroscopy Methods
Description: A set of tools for fluorescence fluctuation spectroscopy data analysis performance is provided in this package. It includes techniques such as single-point fluorescence correlation spectroscopy, autocorrelation and pair correlation functions, number & brightness (raster line scan) and a novel, recently developed method by Hinde and co-workers, pair correlation of molecular brightness (doi:10.1038/ncomms11047). A set of simulations and real experimental data is used for the examples of each function provided in this package. For an in-depth description of the basics behind each function here included and a detailed step-by-step guide on how to use them on your own data, please refer to the Supplementary Material file provided at (<https://github.com/RPintoC/FCSlib_Sup_Data>).
Author: Raul Pinto Camara, Adan Guerrero.
Maintainer: Raul Pinto Camara <vasto.lorde.rp@gmail.com>

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New package onemap with initial version 2.1.2
Package: onemap
Title: Construction of Genetic Maps in Experimental Crosses: Full-Sib, RILs, F2 and Backcrosses
Version: 2.1.2
Description: Analysis of molecular marker data from model (backcrosses, F2 and recombinant inbred lines) and non-model systems (i. e. outcrossing species). For the later, it allows statistical analysis by simultaneously estimating linkage and linkage phases (genetic map construction) according to Wu et al. (2002) <doi:10.1006/tpbi.2002.1577>. All analysis are based on multipoint approaches using hidden Markov models.
Date: 2019-08-22
Authors@R: c(person("Gabriel", "Margarido", role = "aut", email = "gramarga@usp.br"), person("Marcelo", "Mollinari", role = "aut", email = "mmollina@usp.br"), person("Karl", "Broman", role = "ctb", email = "kbroman@biostat.wisc.edu"), person("Rodrigo", "Amadeu", role = "ctb", email = "rodrigo.amadeu@usp.br"), person("Cristiane", "Taniguti", role=c("ctb", "cre"), email="chtaniguti@usp.br"), person("Augusto", "Garcia", role = c("aut", "ctb"), email = "augusto.garcia@usp.br"), person("Getulio", "Ferreira", role="ctb", email="getulio.caifer@usp.br"))
Author: Gabriel Margarido [aut], Marcelo Mollinari [aut], Karl Broman [ctb], Rodrigo Amadeu [ctb], Cristiane Taniguti [ctb, cre], Augusto Garcia [aut, ctb], Getulio Ferreira [ctb]
LinkingTo: Rcpp (>= 0.10.5)
Depends: R (>= 3.6.0)
Imports: ggplot2 (>= 2.2.1), plotly (>= 4.7.1), reshape2 (>= 1.4.1), Rcpp (>= 0.10.5), graphics, methods, stats, utils, grDevices, MDSMap
Suggests: qtl (>= 1.36-6), knitr (>= 1.10), rmarkdown, htmlwidgets, vcfR (>= 1.6.0),
VignetteBuilder: knitr
Encoding: UTF-8
License: GPL-3
URL: https://github.com/augusto-garcia/onemap
BugReports: https://github.com/augusto-garcia/onemap/wiki
Maintainer: Cristiane Taniguti <chtaniguti@usp.br>
Repository: CRAN
Packaged: 2019-09-18 12:17:26 UTC; cristiane
NeedsCompilation: yes
Date/Publication: 2019-09-19 13:20:02 UTC
RoxygenNote: 6.1.1
biocViews:

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Package MLeval updated to version 0.3 with previous version 0.2 dated 2019-11-29

Title: Machine Learning Model Evaluation
Description: Straightforward and detailed evaluation of machine learning models. 'MLeval' can produce receiver operating characteristic (ROC) curves, precision-recall (PR) curves, calibration curves, and PR gain curves. 'MLeval' accepts a data frame of class probabilities and ground truth labels, or, it can automatically interpret the Caret train function results from repeated cross validation, then select the best model and analyse the results. 'MLeval' produces a range of evaluation metrics with confidence intervals.
Author: Christopher R John
Maintainer: Christopher R John <chris.r.john86@gmail.com>

Diff between MLeval versions 0.2 dated 2019-11-29 and 0.3 dated 2020-02-12

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Package taxize updated to version 0.9.92 with previous version 0.9.91 dated 2019-11-15

Title: Taxonomic Information from Around the Web
Description: Interacts with a suite of web 'APIs' for taxonomic tasks, such as getting database specific taxonomic identifiers, verifying species names, getting taxonomic hierarchies, fetching downstream and upstream taxonomic names, getting taxonomic synonyms, converting scientific to common names and vice versa, and more.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Eduard Szoecs [aut], Zachary Foster [aut], Zebulun Arendsee [aut], Carl Boettiger [ctb], Karthik Ram [ctb], Ignasi Bartomeus [ctb], John Baumgartner [ctb], James O'Donnell [ctb], Jari Oksanen [ctb], Bastian Greshake Tzovaras [ctb], Philippe Marchand [ctb], Vinh Tran [ctb], Maëlle Salmon [ctb], Gaopeng Li [ctb], Matthias Grenié [ctb], rOpenSci [fnd] (https://ropensci.org/)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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More information about taxize at CRAN
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Package EBPRS updated to version 2.0.3 with previous version 2.0.1 dated 2020-01-16

Title: Derive Polygenic Risk Score Based on Emprical Bayes Theory
Description: EB-PRS is a novel method that leverages information for effect sizes across all the markers to improve the prediction accuracy. No parameter tuning is needed in the method, and no external information is needed. This R-package provides the calculation of polygenic risk scores from the given training summary statistics and testing data. We can use EB-PRS to extract main information, estimate Empirical Bayes parameters, derive polygenic risk scores for each individual in testing data, and evaluate the PRS according to AUC and predictive r2. See Song et al. (2020) <doi:10.1371/journal.pcbi.1007565> for a detailed presentation of the method.
Author: Shuang Song [aut, cre], Wei Jiang [aut], Lin Hou [aut] and Hongyu Zhao [aut]
Maintainer: Shuang Song <song-s19@mails.tsinghua.edu.cn>

Diff between EBPRS versions 2.0.1 dated 2020-01-16 and 2.0.3 dated 2020-02-12

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More information about EBPRS at CRAN
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Package bayestestR updated to version 0.5.2 with previous version 0.5.1 dated 2020-01-27

Title: Understand and Describe Bayesian Models and Posterior Distributions
Description: Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors).
Author: Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Michael D. Wilson [aut] (<https://orcid.org/0000-0003-4143-7308>), Paul-Christian Bürkner [rev], Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>), Quentin F. Gronau [ctb] (<https://orcid.org/0000-0001-5510-6943>)
Maintainer: Dominique Makowski <dom.makowski@gmail.com>

Diff between bayestestR versions 0.5.1 dated 2020-01-27 and 0.5.2 dated 2020-02-12

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Package AMORE updated to version 0.2-16 with previous version 0.2-15 dated 2014-04-14

Title: Artificial Neural Network Training and Simulating
Description: Commands for training a simulating an artificial neural network.
Author: Manuel Castejon Limas, Joaquin B. Ordieres Mere, Ana Gonzalez Marcos, Francisco Javier Martinez de Pison Ascacibar, Alpha V. Pernia Espinoza, Fernando Alba Elias, Jose Maria Perez Ramos
Maintainer: Manuel Castejón-Limas <manuel.castejon@gmail.com>

Diff between AMORE versions 0.2-15 dated 2014-04-14 and 0.2-16 dated 2020-02-12

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More information about AMORE at CRAN
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