Thu, 24 Oct 2019

Package sclr updated to version 0.2.0 with previous version 0.1.0 dated 2019-09-04

Title: Scaled Logistic Regression
Description: Maximum likelihood estimation of the scaled logit model parameters proposed in Dunning (2006) <doi:10.1002/sim.2282>.
Author: Arseniy Khvorov [aut, cre]
Maintainer: Arseniy Khvorov <khvorov45@gmail.com>

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Package ViSiElse updated to version 1.2.2 with previous version 1.2.1 dated 2018-10-31

Title: A Visual Tool for Behavior Analysis over Time
Description: A graphical R package designed to visualize behavioral observations over time. Based on raw time data extracted from video recorded sessions of experimental observations, ViSiElse grants a global overview of a process by combining the visualization of multiple actions timestamps for all participants in a single graph. Individuals and/or group behavior can easily be assessed. Supplementary features allow users to further inspect their data by adding summary statistics (mean, standard deviation, quantile or statistical test) and/or time constraints to assess the accuracy of the realized actions.
Author: Nastasia Fouret [aut, cph], Mederic Descoins [aut, cph], Elodie Garnier [aut, cre, cph], CEPOI - EA 7388 [cph]
Maintainer: Elodie Garnier <e.garnier30@gmail.com>

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Package rebird updated to version 1.1.0 with previous version 1.0.0 dated 2018-09-27

Title: R Client for the eBird Database of Bird Observations
Description: A programmatic client for the eBird database, including functions for searching for bird observations by geographic location (latitude, longitude), eBird hotspots, location identifiers, by notable sightings, by region, and by taxonomic name.
Author: Rafael Maia [aut], Scott Chamberlain [aut] (<https://orcid.org/0000-0003-1444-9135>), Andy Teucher [aut], Guy Babineau [ctb], Sebastian Pardo [aut, cre] (<https://orcid.org/0000-0002-4147-5796>)
Maintainer: Sebastian Pardo <sebpardo@gmail.com>

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Package mgcv updated to version 1.8-30 with previous version 1.8-29 dated 2019-09-20

Title: Mixed GAM Computation Vehicle with Automatic Smoothness Estimation
Description: Generalized additive (mixed) models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by (Restricted) Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference. See Wood (2017) <doi:10.1201/9781315370279> for an overview. Includes a gam() function, a wide variety of smoothers, 'JAGS' support and distributions beyond the exponential family.
Author: Simon Wood <simon.wood@r-project.org>
Maintainer: Simon Wood <simon.wood@r-project.org>

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Package effectFusion updated to version 1.1.2 with previous version 1.1.1 dated 2019-01-19

Title: Bayesian Effect Fusion for Categorical Predictors
Description: Variable selection and Bayesian effect fusion for categorical predictors in linear and logistic regression models. Effect fusion aims at the question which categories have a similar effect on the response and therefore can be fused to obtain a sparser representation of the model. Effect fusion and variable selection can be obtained either with a prior that has an interpretation as spike and slab prior on the level effect differences or with a sparse finite mixture prior on the level effects. The regression coefficients are estimated with a flat uninformative prior after model selection or by taking model averages. Posterior inference is accomplished by an MCMC sampling scheme which makes use of a data augmentation strategy (Polson, Scott & Windle (2013)) based on latent Polya-Gamma random variables in the case of logistic regression. The code for data augmentation is taken from Polson et al. (2013), who own the copyright.
Author: Daniela Pauger [aut], Magdalena Leitner [aut, cre], Helga Wagner [aut] (<https://orcid.org/0000-0002-7003-9512>), Gertraud Malsiner-Walli [aut] (<https://orcid.org/0000-0002-1213-4749>), Nicholas G. Polson [ctb], James G. Scott [ctb], Jesse Windle [ctb], Bettina Grün [ctb] (<https://orcid.org/0000-0001-7265-4773>)
Maintainer: Magdalena Leitner <effectfusion.jku@gmail.com>

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Package DALEX updated to version 0.4.9 with previous version 0.4.7 dated 2019-08-25

Title: Descriptive mAchine Learning EXplanations
Description: Machine Learning (ML) models are widely used and have various applications in classification or regression. Models created with boosting, bagging, stacking or similar techniques are often used due to their high performance, but such black-box models usually lack of interpretability. DALEX package contains various explainers that help to understand the link between input variables and model output. The single_variable() explainer extracts conditional response of a model as a function of a single selected variable. It is a wrapper over packages 'pdp' (Greenwell 2017) <doi:10.32614/RJ-2017-016>, 'ALEPlot' (Apley 2018) <arXiv:1612.08468> and 'factorMerger' (Sitko and Biecek 2017) <arXiv:1709.04412>. The single_prediction() explainer attributes parts of a model prediction to particular variables used in the model. It is a wrapper over 'breakDown' package (Staniak and Biecek 2018) <doi:10.32614/RJ-2018-072>. The variable_dropout() explainer calculates variable importance scores based on variable shuffling (Fisher at al. 2018) <arXiv:1801.01489>. All these explainers can be plotted with generic plot() function and compared across different models. 'DALEX' is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.
Author: Przemyslaw Biecek [aut, cre] (<https://orcid.org/0000-0001-8423-1823>), Szymon Maksymiuk [ctb]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>

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Package sgmcmc updated to version 0.2.5 with previous version 0.2.4 dated 2019-05-01

Title: Stochastic Gradient Markov Chain Monte Carlo
Description: Provides functions that performs popular stochastic gradient Markov chain Monte Carlo (SGMCMC) methods on user specified models. The required gradients are automatically calculated using 'TensorFlow' <https://www.tensorflow.org/>, an efficient library for numerical computation. This means only the log likelihood and log prior functions need to be specified. The methods implemented include stochastic gradient Langevin dynamics (SGLD), stochastic gradient Hamiltonian Monte Carlo (SGHMC), stochastic gradient Nose-Hoover thermostat (SGNHT) and their respective control variate versions for increased efficiency. References: M. Welling, Y. W. Teh (2011) <http://www.icml-2011.org/papers/398_icmlpaper.pdf>; T. Chen, E. B. Fox, C. E. Guestrin (2014) <arXiv:1402.4102>; N. Ding, Y. Fang, R. Babbush, C. Chen, R. D. Skeel, H. Neven (2014) <https://papers.nips.cc/paper/5592-bayesian-sampling-using-stochastic-gradient-thermostats>; J. Baker, P. Fearnhead, E. B. Fox, C. Nemeth (2017) <arXiv:1706.05439>. For more details see <doi:10.18637/jss.v091.i03>.
Author: Jack Baker [aut, cre, cph], Christopher Nemeth [aut, cph], Paul Fearnhead [aut, cph], Emily B. Fox [aut, cph], STOR-i [cph]
Maintainer: Jack Baker <jackbaker92@mail.com>

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Package robin updated to version 0.99.1 with previous version 0.99.0 dated 2019-10-20

Title: ROBustness in Network
Description: Many community detection algorithms have been developed in network analysis. However, their applications leave unaddressed the statistical validation of the results, for this reason we developed ROBIN (ROBustness In Network), a useful method for the validation of community detection. It has a double aim, it studies the robustness of a single community detection algorithm and compares two community detection algorithms to understand which provides the best partition. Reference in Annamaria Carissimo, Luisa Cutillo, Italia De Feis (2018) <doi:10.1016/j.csda.2017.10.006>.
Author: Valeria Policastro [aut, cre], Dario Righelli [aut], Luisa Cutillo [aut], Italia De Feis [aut], Annamaria Carissimo [aut]
Maintainer: Valeria Policastro <valeria.policastro@gmail.com>

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New package SCOR with initial version 1.1.0
Package: SCOR
Type: Package
Title: Spherically Constrained Optimization Routine
Version: 1.1.0
Authors@R: c( person("Debsurya","De", ,"debsurya001@gmail.com", role =c("cre","aut")), person("Priyam","Das", ,"pdas@ncsu.edu" , role = "aut") )
Depends: R (>= 3.5.0)
Imports: doParallel, foreach, iterators, parallel
Collate: 'imports.R' 'biomarker.R' 'SHUM.R' 'EHUM.R' 'ULBA.R' 'SCOR.R' 'SCOR-package.R' 'optimized_HUM.R' 'youden_points.R' 'YoudenBoxPlot.R'
Maintainer: Debsurya De <debsurya001@gmail.com>
Description: A non-convex optimization package that optimizes any function under the criterion, combination of variables are on the surface of a unit sphere, as described in the paper : Das et al. (2019) <arXiv:1909.04024> .
License: GPL-3
URL: https://github.com/synx21/SCOR
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.99.9001
NeedsCompilation: no
Packaged: 2019-10-21 10:50:54 UTC; Debsurya
Author: Debsurya De [cre, aut], Priyam Das [aut]
Repository: CRAN
Date/Publication: 2019-10-24 17:20:02 UTC

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Package HGNChelper updated to version 0.8.1 with previous version 0.7.1 dated 2019-03-05

Title: Identify and Correct Invalid HGNC Human Gene Symbols and MGI Mouse Gene Symbols
Description: Contains functions for identifying and correcting HGNC human gene symbols and MGI mouse gene symbols which have been converted to date format by Excel, withdrawn, or aliased. Also contains functions for reversibly converting between HGNC symbols and valid R names.
Author: Levi Waldron and Markus Riester
Maintainer: Levi Waldron <lwaldron.research@gmail.com>

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New package CMShiny with initial version 0.1.0
Package: CMShiny
Type: Package
Title: Interactive Document for Working with Confusion Matrix
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive document on the topic of confusion matrix analysis using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at <https://predanalyticssessions1.shinyapps.io/ConfusionMatrixShiny/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,rmarkdown,shinyMatrix,Matrix,epitools,caret,e1071
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-21 10:23:30 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-10-24 17:20:05 UTC

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Package tokenbrowser updated to version 0.1.1 with previous version 0.1.0 dated 2019-05-17

Title: Create Full Text Browsers from Annotated Token Lists
Description: Create browsers for reading full texts from a token list format. Information obtained from text analyses (e.g., topic modeling, word scaling) can be used to annotate the texts.
Author: Kasper Welbers and Wouter van Atteveldt
Maintainer: Kasper Welbers <kasperwelbers@gmail.com>

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More information about tokenbrowser at CRAN
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New package phyr with initial version 1.0.0
Package: phyr
Type: Package
Title: Model Based Phylogenetic Analysis
Version: 1.0.0
Authors@R: c( person("Anthony", "Ives", , "arives@wisc.edu", role = c("aut")), person("Russell", "Dinnage", , "r.dinnage@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0003-0846-2819")), person(c("Lucas", "A."), "Nell", , "lucas@lucasnell.com", role = c("aut"), comment = c(ORCID = "0000-0003-3209-0517")), person("Matthew", "Helmus", , "mrhelmus@temple.edu", role = c("aut")), person("Daijiang", "Li", , "daijianglee@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0925-3421")))
Description: A collection of functions to do model-based phylogenetic analysis. It includes functions to calculate community phylogenetic diversity, to estimate correlations among functional traits while accounting for phylogenetic relationships, and to fit phylogenetic generalized linear mixed models. The Bayesian phylogenetic generalized linear mixed models are fitted with the 'INLA' package (<http://www.r-inla.org>).
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1)
Imports: stats, ape, Rcpp, Matrix, methods, graphics, dplyr, lme4, nloptr, gridExtra, mvtnorm, latticeExtra
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, pez, tidyr, knitr, rmarkdown, covr, picante, rbenchmark, INLA, MCMCglmm, logistf, phylolm
VignetteBuilder: knitr
URL: https://github.com/daijiang/phyr/
BugReports: https://github.com/daijiang/phyr/issues
Additional_repositories: https://inla.r-inla-download.org/R/stable/
NeedsCompilation: yes
Packaged: 2019-10-20 15:29:40 UTC; dli
Author: Anthony Ives [aut], Russell Dinnage [aut] (<https://orcid.org/0000-0003-0846-2819>), Lucas A. Nell [aut] (<https://orcid.org/0000-0003-3209-0517>), Matthew Helmus [aut], Daijiang Li [aut, cre] (<https://orcid.org/0000-0002-0925-3421>)
Maintainer: Daijiang Li <daijianglee@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-24 16:10:06 UTC

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New package fishualize with initial version 0.1.0
Package: fishualize
Type: Package
Title: Color Palettes Based on Fish Species
Version: 0.1.0
Authors@R: c( person("Nina", "Schiettekatte", email = "nina.schiettekatte@gmail.com", role = c("cre", "aut")), person("Simon", "Brandl", role = "aut"), person("Jordan", "Casey", role = "aut"))
Maintainer: Nina Schiettekatte <nina.schiettekatte@gmail.com>
Description: Implementation of color palettes based on fish species.
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Suggests: hexbin (>= 1.27.0), testthat, knitr, rmarkdown, rfishbase, rnaturalearth, pkgdown
URL: https://github.com/nschiett/fishualize
BugReports: https://github.com/nschiett/fishualize/issues
Imports: ggplot2 (>= 1.0.1), gridExtra, grid, png
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-20 22:44:47 UTC; nschiettekatte
Author: Nina Schiettekatte [cre, aut], Simon Brandl [aut], Jordan Casey [aut]
Repository: CRAN
Date/Publication: 2019-10-24 16:20:02 UTC

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Package emmeans updated to version 1.4.2 with previous version 1.4.1 dated 2019-09-12

Title: Estimated Marginal Means, aka Least-Squares Means
Description: Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Author: Russell Lenth [aut, cre, cph], Henrik Singmann [ctb], Jonathon Love [ctb], Paul Buerkner [ctb], Maxime Herve [ctb]
Maintainer: Russell Lenth <russell-lenth@uiowa.edu>

Diff between emmeans versions 1.4.1 dated 2019-09-12 and 1.4.2 dated 2019-10-24

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New package downscaledl with initial version 1.0
Package: downscaledl
Type: Package
Title: Downscale of RS Images using Deep Learning
Version: 1.0
Date: 2019-10-11
Author: Lianfa Li
Maintainer: Lianfa Li <lspatial@gmail.com>
Description: Downscaling the coarse-resolution remote sensing images into fined-resolution images is important for preprocessing. This package provides the functions for this with high accuracy. Currently, the resautonet is used as the deep learning algorithm for downscaling. This work was done based on this paper, Lianfa Li (2019) <doi:10.3390/rs11111378>.
Depends: R (>= 3.1)
Imports: Rcpp (>= 1.0.0),rstack,dplyr,magrittr,keras,raster,parallel,tensorflow,sp,rgdal
LinkingTo: Rcpp, RcppArmadillo
SystemRequirements: C++11
License: GPL
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
RoxygenNote: 6.1.1
Packaged: 2019-10-20 20:25:15 UTC; lminer
Repository: CRAN
Date/Publication: 2019-10-24 16:20:10 UTC

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Package capm updated to version 0.14.0 with previous version 0.13.10 dated 2019-04-19

Title: Companion Animal Population Management
Description: Quantitative analysis to support companion animal population management. Some functions assist survey sampling tasks (calculate sample size for simple and complex designs, select sampling units and estimate population parameters) while others assist the modelling of population dynamics. For demographic characterizations and population management evaluations see: "Baquero, et al." (2018), <doi:10.1016/j.prevetmed.2018.07.006>. For modelling of population dynamics see: "Baquero et al." (2016), <doi:10.1016/j.prevetmed.2015.11.009>. For sampling methods see: "Levy PS & Lemeshow S" (2013), "ISBN-10: 0470040076"; "Lumley" (2010), "ISBN: 978-0-470-28430-8".
Author: Oswaldo Santos Baquero [aut, cre], Marcos Amaku [ctb], Fernando Ferreira [ctb]
Maintainer: Oswaldo Santos Baquero <baquero@usp.br>

Diff between capm versions 0.13.10 dated 2019-04-19 and 0.14.0 dated 2019-10-24

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New package corx with initial version 1.0.2
Package: corx
Type: Package
Title: Create and Format Correlation Matrices
Version: 1.0.2
Date: 2019-10-21
Authors@R: person(given = "James", family = "Conigrave", role = c("aut", "cre"), email = "james.conigrave@gmail.com", comment = c(ORCID = "0000-0002-8816-6229"))
Description: Create correlation (or partial correlation) matrices. Correlation matrices are formatted with significance stars based on user preferences. Matrices of coefficients, p-values, and number of pairwise observations are returned. Send resultant formatted matrices to the clipboard to be pasted into excel and other programs. A plot method allows users to visualize correlation matrices created with 'corx'.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: ppcor, crayon, ggcorrplot, glue, psych, clipr, tidyselect, moments
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-10-21 03:15:29 UTC; jcon4884
Author: James Conigrave [aut, cre] (<https://orcid.org/0000-0002-8816-6229>)
Maintainer: James Conigrave <james.conigrave@gmail.com>
Repository: CRAN
Date/Publication: 2019-10-24 16:50:02 UTC

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New package STGS with initial version 0.1.0
Package: STGS
Type: Package
Title: Genomic Selection using Single Trait
Version: 0.1.0
Author: Neeraj Budhlakoti, D C Mishra, Anil Rai, K K Chaturvedi
Maintainer: Neeraj Budhlakoti <neeraj35669@gmail.com>
Description: Genomic Selection (GS) is a latest development in animal and plant breeding where whole genome markers information is used to predict genetic merit of an individuals in a practical breeding programme. GS is one of the promising tool for improving genetic gain in animal and plants in today’s scenario. This package is basically developed for genomic predictions by estimating marker effects. These marker effects further used for calculation of genotypic merit of individual i.e. genome estimated breeding values (GEBVs). Genomic selection may be based on single trait or multi traits information. This package performs genomic selection only for single traits hence named as STGS i.e. single trait genomic selection. STGS is a comprehensive package which gives single step solution for genomic selection based on most commonly used statistical methods.
License: GPL-3
Depends: R (>= 3.6)
Imports: glmnet, brnn, kernlab, randomForest, rrBLUP
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-18 01:47:13 UTC; Neeraj
Repository: CRAN
Date/Publication: 2019-10-24 16:00:05 UTC

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Package EstimationTools updated to version 1.2.1 with previous version 1.2.0 dated 2019-06-11

Title: Maximum Likelihood Estimation for Probability Functions from Data Sets
Description: A routine for parameter estimation for any probability density or mass function implemented in R via maximum likelihood (ML) given a data set. This routine is a wrapper function specifically developed for ML estimation. There are included optimization procedures such as 'nlminb' and 'optim' from base package, and 'DEoptim' Mullen (2011) <doi: 10.18637/jss.v040.i06>. Standard errors are estimated with 'numDeriv' Gilbert (2011) <http://CRAN.R-project.org/package=numDeriv> or the option 'Hessian = TRUE' of 'optim' function.
Author: Jaime Mosquera [aut, cre] (<https://orcid.org/0000-0002-1684-4756>), Freddy Hernandez [aut] (<https://orcid.org/0000-0001-7459-3329>)
Maintainer: Jaime Mosquera <jmosquerag@unal.edu.co>

Diff between EstimationTools versions 1.2.0 dated 2019-06-11 and 1.2.1 dated 2019-10-24

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Package cgmanalysis updated to version 2.5 with previous version 2.4 dated 2019-05-22

Title: Clean and Analyze Continuous Glucose Monitor Data
Description: This code provides several different functions for cleaning and analyzing continuous glucose monitor data. Currently it works with 'Dexcom' (<https://www.dexcom.com>), 'iPro 2' (<http://professional.medtronicdiabetes.com/ipro2-professional-cgm>), Diasend (<https://diasend.com//us>), Libre (<https://www.freestylelibre.us/>) or Carelink (<https://www.medtronicdiabetes.com/products/carelink-personal-diabetes-software>) data. The cleandata() function takes a directory of CGM data files and prepares them for analysis. cgmvariables() iterates through a directory of cleaned CGM data files and produces a single spreadsheet with data for each file in either rows or columns. The column format of this spreadsheet is compatible with REDCap data upload ("--1" is added to each subject ID automatically for double data entry). cgmreport() also iterates through a directory of cleaned data, and produces PDFs of individual and aggregate AGP plots. Please visit <https://github.com/childhealthbiostatscore/R-Packages/> to download the new-user guide.
Author: Tim Vigers [aut, cre]
Maintainer: Tim Vigers <tim.b.vigers@gmail.com>

Diff between cgmanalysis versions 2.4 dated 2019-05-22 and 2.5 dated 2019-10-24

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Package slm updated to version 1.1.0 with previous version 1.0.0 dated 2019-07-23

Title: Stationary Linear Models
Description: Provides statistical procedures for linear regression in the general context where the errors are assumed to be correlated. Different ways to estimate the asymptotic covariance matrix of the least squares estimators are available. Starting from this estimation of the covariance matrix, the confidence intervals and the usual tests on the parameters are modified. The functions of this package are very similar to those of 'lm': it contains methods such as summary(), plot(), confint() and predict(). The 'slm' package is described in the paper by E. Caron, J. Dedecker and B. Michel (2019), "Linear regression with stationary errors: the R package slm", arXiv preprint <arXiv:1906.06583>.
Author: Emmanuel Caron, Jérôme Dedecker, Bertrand Michel
Maintainer: Emmanuel Caron <emmanuelcaron3@gmail.com>

Diff between slm versions 1.0.0 dated 2019-07-23 and 1.1.0 dated 2019-10-24

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Package jpeg updated to version 0.1-8.1 with previous version 0.1-8 dated 2014-01-23

Title: Read and write JPEG images
Description: This package provides an easy and simple way to read, write and display bitmap images stored in the JPEG format. It can read and write both files and in-memory raw vectors.
Author: Simon Urbanek <Simon.Urbanek@r-project.org>
Maintainer: Simon Urbanek <Simon.Urbanek@r-project.org>

Diff between jpeg versions 0.1-8 dated 2014-01-23 and 0.1-8.1 dated 2019-10-24

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Package iptmnetr updated to version 0.1.6 with previous version 0.1.5 dated 2018-09-27

Title: Interface to the 'iPTMnet' API
Description: Provides an R interface to the 'iPTMnet' database REST API, which can be used to retrieve Post Translational Modification (PTM) data in systems biology context. This package handles all the aspects of communicating with the API, which involve sending the request, checking the error codes and parsing the response in a format that is ready to integrate into existing workflows.
Author: Sachin Gavali
Maintainer: Sachin Gavali <saching@udel.edu>

Diff between iptmnetr versions 0.1.5 dated 2018-09-27 and 0.1.6 dated 2019-10-24

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Package detectRUNS updated to version 0.9.6 with previous version 0.9.5 dated 2018-02-06

Title: Detect Runs of Homozygosity and Runs of Heterozygosity in Diploid Genomes
Description: Detection of runs of homozygosity and of heterozygosity in diploid genomes using two methods: sliding windows (Purcell et al (2007) <doi:10.1086/519795>) and consecutive runs (Marras et al (2015) <doi:10.1111/age.12259>).
Author: Filippo Biscarini [aut, cre], Paolo Cozzi [aut], Giustino Gaspa [aut], Gabriele Marras [aut]
Maintainer: Filippo Biscarini <filippo.biscarini@gmail.com>

Diff between detectRUNS versions 0.9.5 dated 2018-02-06 and 0.9.6 dated 2019-10-24

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Package MSGARCH updated to version 2.31 with previous version 2.3 dated 2018-05-16

Title: Markov-Switching GARCH Models
Description: Fit (by Maximum Likelihood or MCMC/Bayesian), simulate, and forecast various Markov-Switching GARCH models as described in Ardia et al. (2019) <doi:10.18637/jss.v091.i04>.
Author: David Ardia [aut], Keven Bluteau [aut, cre], Kris Boudt [ctb], Leopoldo Catania [aut], Alexios Ghalanos [ctb], Brian Peterson [ctb], Denis-Alexandre Trottier [aut]
Maintainer: Keven Bluteau <Keven.Bluteau@unine.ch>

Diff between MSGARCH versions 2.3 dated 2018-05-16 and 2.31 dated 2019-10-24

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New package sankeywheel with initial version 0.1.0
Package: sankeywheel
Title: Create Dependency Wheels and Sankey Diagrams
Type: Package
Version: 0.1.0
Authors@R: c( person(given = "Zhenxing", family = "Cheng", role = c("aut", "cre"), email = "czxjnu@163.com"), person(given = "Qiongqiong", family = "Li", role = c("aut", "ctb"), email = "lqqflora@163.com"))
Description: By binding R functions and the 'Highcharts' <http://www.highcharts.com/> charting library, 'sankeywheel' package provides a simple way to draw dependency wheels and sankey diagrams.
License: MIT + file LICENSE
Date: 2019-10-19
Encoding: UTF-8
Depends: R (>= 3.0.0)
LazyData: true
Imports: htmlwidgets
Suggests: knitr, rmarkdown, shiny, colourpicker, manipulateWidget, DT
VignetteBuilder: knitr
URL: https://github.com/czxa/sankeywheel
BugReports: https://github.com/czxa/sankeywheel/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-20 11:09:07 UTC; czx
Author: Zhenxing Cheng [aut, cre], Qiongqiong Li [aut, ctb]
Maintainer: Zhenxing Cheng <czxjnu@163.com>
Repository: CRAN
Date/Publication: 2019-10-24 10:40:02 UTC

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Package pairwiseComparisons updated to version 0.1.2 with previous version 0.1.1 dated 2019-09-17

Title: Multiple Pairwise Comparison Tests
Description: Multiple pairwise comparison tests for one-way analysis of variance for both between-subjects and within-subjects designs. Currently, it supports only the most common types of statistical analyses and tests: parametric (Welch's and Student's t-test), nonparametric (Durbin-Conover test and Dwass-Steel-Crichtlow-Fligner test), robust (Yuen’s trimmed means test).
Author: Indrajeet Patil [cre, aut, ctb] (<https://orcid.org/0000-0003-1995-6531>)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

Diff between pairwiseComparisons versions 0.1.1 dated 2019-09-17 and 0.1.2 dated 2019-10-24

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More information about pairwiseComparisons at CRAN
Permanent link

New package dwdradar with initial version 0.2.0
Package: dwdradar
Title: Read Binary Radar Files from 'DWD' (German Weather Service)
Version: 0.2.0
Date: 2019-10-20
Authors@R: c( person("Berry", "Boessenkool", role=c("aut", "cre"), email="berry-b@gmx.de"), person("Henning", "Rust", role="ctb", email="henning.rust@met.fu-berlin.de"), person("Christoph", "Ritschel", role="ctb") )
Description: The 'DWD' provides gridded radar data for Germany in binary format. 'dwdradar' reads these files and enables a fast conversion into numerical format.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Suggests: testthat, raster, berryFunctions, R.utils
NeedsCompilation: yes
RoxygenNote: 6.1.1
Packaged: 2019-10-20 14:17:13 UTC; berry
Author: Berry Boessenkool [aut, cre], Henning Rust [ctb], Christoph Ritschel [ctb]
Maintainer: Berry Boessenkool <berry-b@gmx.de>
Repository: CRAN
Date/Publication: 2019-10-24 10:50:02 UTC

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Permanent link

New package stratamatch with initial version 0.1.0
Package: stratamatch
Type: Package
Date: 2019-10-10
Title: Stratification and Matching for Large Observational Data Sets
Version: 0.1.0
Authors@R: c( person("Rachael C.", "Aikens", email = "rockyaikens@gmail.com", role = c("aut", "cre")), person("Joseph", "Rigdon", role = c("aut")), person("Justin", "Lee", role = c("aut")), person("Michael", "Baiocchi", email = "baiocchi@stanford.edu", role = c("aut")), person("Jonathan", "Chen", email = "jonc101@stanford.edu", role = c("aut")) )
Maintainer: Rachael C. Aikens <rockyaikens@gmail.com>
BugReports: https://github.com/raikens1/stratamatch/issues
Description: A pilot matching design to automatically stratify and match large datasets. The manual_stratify() function allows users to manually stratify a dataset based on categorical variables of interest, while the auto_stratify() function does automatically by allocating a held-aside (pilot) data set, fitting a prognostic score (see Hansen (2008) <doi:10.1093/biomet/asn004>) on the pilot set, and stratifying the data set based on prognostic score quantiles. The strata_match() function then does optimal matching of the data set in parallel within strata.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: dplyr (>= 0.8.3), Hmisc (>= 4.2-0), magrittr (>= 1.5), rlang (>= 0.4.0), survival(>= 2.44.1.1)
Depends: R (>= 3.4.0),
Suggests: knitr, optmatch (>= 0.9-11), rmarkdown, testthat (>= 2.1.0)
URL: https://github.com/raikens1/stratamatch
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-18 20:31:17 UTC; rocky
Author: Rachael C. Aikens [aut, cre], Joseph Rigdon [aut], Justin Lee [aut], Michael Baiocchi [aut], Jonathan Chen [aut]
Repository: CRAN
Date/Publication: 2019-10-24 09:50:02 UTC

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Permanent link

New package SDAR with initial version 0.9-3
Package: SDAR
Title: Stratigraphic Data Analysis
Version: 0.9-3
Authors@R: c(person("John R.", "Ortiz", role = c("aut", "cre"), email = "jrortizt@unal.edu.co"), person("Carlos", "Jaramillo", role = "aut"), person("Carlos", "Moreno", role = "ctb"))
Maintainer: John R. Ortiz <jrortizt@unal.edu.co>
Depends: R (>= 3.0)
Description: A fast, consistent tool for plotting and facilitating the analysis of stratigraphic and sedimentological data. Taking advantage of the flexible plotting tools available in R, 'SDAR' uses stratigraphic and sedimentological data to produce detailed graphic logs for outcrop sections and borehole logs. These logs can include multiple features (e.g., bed thickness, lithology, samples, sedimentary structures, colors, fossil content, bioturbation index, electrical logs) (Johnson, 1992, <ISSN 0037-0738>).
License: GPL (>= 2)
URL: https://repository.si.edu/10088/35917
Imports: methods, grid, linbin, grImport2, readxl
Repository: CRAN
Author: John R. Ortiz [aut, cre], Carlos Jaramillo [aut], Carlos Moreno [ctb]
Note: The development of this package was supported by Carlos Jaramillo, Center for Tropical Paleoecology and Archaeology at Smithsonian Tropical Research Institute.
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-10-18 20:25:18 UTC; john
Date/Publication: 2019-10-24 09:40:02 UTC

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Package rlang updated to version 0.4.1 with previous version 0.4.0 dated 2019-06-25

Title: Functions for Base Types and Core R and 'Tidyverse' Features
Description: A toolbox for working with base types, core R features like the condition system, and core 'Tidyverse' features like tidy evaluation.
Author: Lionel Henry [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>

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Package DisImpact updated to version 0.0.5 with previous version 0.0.4 dated 2019-04-24

Title: Calculates Disproportionate Impact When Binary Success Data are Disaggregated by Subgroups
Description: Implements methods for calculating disproportionate impact: the percentage point gap, proportionality index, and the 80% index. California Community Colleges Chancellor's Office (2017). Percentage Point Gap Method. <https://www.cccco.edu/-/media/CCCCO-Website/About-Us/Divisions/Digital-Innovation-and-Infrastructure/Research/Files/PercentagePointGapMethod2017.ashx>. California Community Colleges Chancellor's Office (2014). Guidelines for Measuring Disproportionate Impact in Equity Plans. <https://www.cccco.edu/-/media/CCCCO-Website/About-Us/Divisions/Digital-Innovation-and-Infrastructure/Network-Operations/Accountability/Files/GUIDELINES-FOR-MEASURING-DISPROPORTIONATE-IMPACT-IN-EQUITY-PLANS.ashx>.
Author: Vinh Nguyen [aut, cre]
Maintainer: Vinh Nguyen <nguyenvq714@gmail.com>

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New package dmacs with initial version 0.1.0
Package: dmacs
Type: Package
Title: Measurement Nonequivalence Effect Size Calculator
Version: 0.1.0
Authors@R: c(person("David", family = "Dueber", role=c("aut", "cre"), email="david.dueber@uky.edu"), person("Hao", family = "Zhou", role=c("ctb")))
Maintainer: David Dueber <david.dueber@uky.edu>
Description: Computes measurement nonequivalence effect size indices described in Nye and Drasgow (2011) <doi:10.1037/a0022955>.
URL: https://github.com/ddueber/dmacs
BugReports: https://github.com/ddueber/dmacs/issues
License: CC0
Encoding: UTF-8
LazyData: true
Imports: lavaan, MplusAutomation
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-10-18 21:38:17 UTC; David
Author: David Dueber [aut, cre], Hao Zhou [ctb]
Repository: CRAN
Date/Publication: 2019-10-24 09:50:06 UTC

More information about dmacs at CRAN
Permanent link

Package statGraph updated to version 0.3.0 with previous version 0.2.0 dated 2019-01-10

Title: Statistical Methods for Graphs
Description: Contains statistical methods to analyze graphs, such as graph parameter estimation, model selection based on the GIC (Graph Information Criterion), statistical tests to discriminate two or more populations of graphs (ANOGVA - Analysis of Graph Variability), correlation between graphs, and clustering of graphs. References: Takahashi et al. (2012) <doi:10.1371/journal.pone.0049949>, Futija et al. (2017) <doi:10.3389/fnins.2017.00066>, Fujita et al. (2017) <doi:10.1016/j.csda.2016.11.016>, Tang et al. (2017) <doi:10.3150/15-BEJ789>, Tang et al. (2017) <doi:10.1080/10618600.2016.1193505>, Ghoshdastidar et al. (2017) <arXiv:1705.06168>, Ghoshdastidar et al. (2017) <arXiv:1707.00833>, Cerqueira et al. (2017) <doi:10.1109/TNSE.2017.2674026>, Fraiman and Fraiman (2018) <doi:10.1038/s41598-018-23152-5>, Fujita et al. (2019) <doi:10.1093/comnet/cnz028>.
Author: Suzana S. Santos [aut], Eduardo S. Lira [aut], Andre Fujita [aut, cre]
Maintainer: Andre Fujita <fujita@ime.usp.br>

Diff between statGraph versions 0.2.0 dated 2019-01-10 and 0.3.0 dated 2019-10-24

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Package hetGP updated to version 1.1.2 with previous version 1.1.1 dated 2019-01-10

Title: Heteroskedastic Gaussian Process Modeling and Design under Replication
Description: Performs Gaussian process regression with heteroskedastic noise following Binois, M., Gramacy, R., Ludkovski, M. (2016) <arXiv:1611.05902>. The input dependent noise is modeled as another Gaussian process. Replicated observations are encouraged as they yield computational savings. Sequential design procedures based on the integrated mean square prediction error and lookahead heuristics are provided, and notably fast update functions when adding new observations.
Author: Mickael Binois, Robert B. Gramacy
Maintainer: Mickael Binois <mickael.binois@inria.fr>

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New package collpcm with initial version 1.1
Package: collpcm
Version: 1.1
Type: Package
Title: Collapsed Latent Position Cluster Model for Social Networks
Date: 2019-10-16
Authors@R: c( person( "Jason", "Wyse", email = "wyseja@tcd.ie", role = c( "aut", "cre" ) ), person( "Caitriona", "Ryan", email = "Caitriona.Ryan@ul.ie", role = c( "aut" ) ), person( "Nial", "Friel", email="nial.friel@ucd.ie", role=c("ths") ) )
Description: Markov chain Monte Carlo based inference routines for collapsed latent position cluster models or social networks, which includes searches over the model space (number of clusters in the latent position cluster model). The label switching algorithm used is that of Nobile and Fearnside (2007) <doi:10.1007/s11222-006-9014-7> which relies on the algorithm of Carpaneto and Toth (1980) <doi:10.1145/355873.355883>.
Depends: R (>= 2.10), vegan, network, latentnet
License: GPL-3
NeedsCompilation: yes
Maintainer: Jason Wyse <wyseja@tcd.ie>
Packaged: 2019-10-23 09:37:56 UTC; jason
Author: Jason Wyse [aut, cre], Caitriona Ryan [aut], Nial Friel [ths]
Repository: CRAN
Date/Publication: 2019-10-24 08:30:11 UTC

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Package BayesSUR updated to version 1.0-1 with previous version 1.0-0 dated 2019-10-14

Title: Bayesian Seemingly Unrelated Regression
Description: Bayesian seemingly unrelated regression with general variable selection and dense/sparse covariance matrix. The sparse seemingly unrelated regression is described in Banterle et al. (2018) <doi:10.1101/467019>.
Author: Marco Banterle [aut], Zhi Zhao [aut, cre], Leonardo Bottolo [ctb], Sylvia Richardson [ctb], Alex Lewin [aut], Manuela Zucknick [ctb]
Maintainer: Zhi Zhao <zhi.zhao@medisin.uio.no>

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Package Rata updated to version 0.0.2 with previous version 0.0.1 dated 2019-08-27

Title: Automated Test Assembly
Description: Automated test assembly of linear and adaptive tests using the mixed-integer programming. The full documentation and tutorials are at <https://github.com/xluo11/Rata>.
Author: Xiao Luo [aut, cre]
Maintainer: Xiao Luo <xluo1986@gmail.com>

Diff between Rata versions 0.0.1 dated 2019-08-27 and 0.0.2 dated 2019-10-24

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Package R.devices updated to version 2.16.1 with previous version 2.16.0 dated 2018-07-21

Title: Unified Handling of Graphics Devices
Description: Functions for creating plots and image files in a unified way regardless of output format (EPS, PDF, PNG, SVG, TIFF, WMF, etc.). Default device options as well as scales and aspect ratios are controlled in a uniform way across all device types. Switching output format requires minimal changes in code. This package is ideal for large-scale batch processing, because it will never leave open graphics devices or incomplete image files behind, even on errors or user interrupts.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between R.devices versions 2.16.0 dated 2018-07-21 and 2.16.1 dated 2019-10-24

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Package rqdatatable updated to version 1.2.3 with previous version 1.2.2 dated 2019-09-13

Title: 'rquery' for 'data.table'
Description: Implements the 'rquery' piped Codd-style query algebra using 'data.table'. This allows for a high-speed in memory implementation of Codd-style data manipulation tools.
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between rqdatatable versions 1.2.2 dated 2019-09-13 and 1.2.3 dated 2019-10-24

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Package IndexConstruction updated to version 0.1-2 with previous version 0.1-1 dated 2019-03-29

Title: Index Construction for Time Series Data
Description: Derivation of indexes for benchmarking purposes. A methodology with flexible number of constituents is implemented. Also functions for market capitalization and volume weighted indexes with fixed number of constituents are available. The main function of the package, indexComp(), provides the derived index, suitable for analysis purposes. The functions indexUpdate(), indexMemberSelection() and indexMembersUpdate() are components of indexComp() and enable one to construct and continuously update an index, e.g. for display on a website. The methodology behind the functions provided gets introduced in Trimborn and Haerdle (2018) <doi:10.1016/j.jempfin.2018.08.004>.
Author: Simon Trimborn <simon.trimborn@nus.edu.sg>
Maintainer: Simon Trimborn <simon.trimborn@nus.edu.sg>

Diff between IndexConstruction versions 0.1-1 dated 2019-03-29 and 0.1-2 dated 2019-10-24

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Package CNVScope updated to version 2.8.1 with previous version 2.7.7 dated 2019-10-14

Title: A Versatile Toolkit for Copy Number Variation Relationship Data Analysis and Visualization
Description: Provides the ability to create interaction maps, discover CNV map domains (edges), gene annotate interactions, and create interactive visualizations of these CNV interaction maps.
Author: James Dalgeish, Yonghong Wang, Jack Zhu, Paul Meltzer
Maintainer: James Dalgleish <james.dalgleish@nih.gov>

Diff between CNVScope versions 2.7.7 dated 2019-10-14 and 2.8.1 dated 2019-10-24

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