Fri, 15 Dec 2017

Package cit updated to version 2.2 with previous version 2.1 dated 2016-11-15

Title: Causal Inference Test
Description: A likelihood-based hypothesis testing approach is implemented for assessing causal mediation. For example, it could be used to test for mediation of a known causal association between a DNA variant, the 'instrumental variable', and a clinical outcome or phenotype by gene expression or DNA methylation, the potential mediator. Another example would be testing mediation of the effect of a drug on a clinical outcome by the molecular target. The hypothesis test generates a p-value or permutation-based FDR value with confidence intervals to quantify uncertainty in the causal inference. The outcome can be represented by either a continuous or binary variable, the potential mediator is continuous, and the instrumental variable can be continuous or binary and is not limited to a single variable but may be a design matrix representing multiple variables.
Author: Joshua Millstein
Maintainer: Joshua Millstein <joshua.millstein@usc.edu>

Diff between cit versions 2.1 dated 2016-11-15 and 2.2 dated 2017-12-15

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Package lingtypology updated to version 1.0.10 with previous version 1.0.9 dated 2017-11-30

Title: Linguistic Typology and Mapping
Description: Provides R with the Glottolog database <http://glottolog.org> and some more abilities for purposes of linguistic mapping. The Glottolog database contains the catalogue of languages of the world. This package helps researchers to make a linguistic maps, using philosophy of the Cross-Linguistic Linked Data project <http://clld.org/>, which allows for while at the same time facilitating uniform access to the data across publications. A tutorial for this package is available on GitHub pages <https://ropensci.github.io/lingtypology/> and package vignette. Maps created by this package can be used both for the investigation and linguistic teaching. In addition, package provides an ability to download data from typological databases such as WALS, AUTOTYP and others.
Author: George Moroz
Maintainer: George Moroz <agricolamz@gmail.com>

Diff between lingtypology versions 1.0.9 dated 2017-11-30 and 1.0.10 dated 2017-12-15

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New package xmrr with initial version 1.0.0
Package: xmrr
Type: Package
Title: Generate XMR Control Chart Data from Time-Series Data
Description: XMRs combine X-Bar control charts and Moving Range control charts. These functions also will recalculate the reference lines when significant change has occured.
Version: 1.0.0
Date: 2017-12-15
Authors@R: person("Alex", "Zanidean", email = "AZanidean@mhc.ab.ca", role = c("aut","cre"))
Maintainer: Alex Zanidean <AZanidean@mhc.ab.ca>
LazyData: TRUE
License: GPL-3 | file LICENSE
Imports: dplyr, tidyr, ggplot2
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2017-12-15 15:40:06 UTC; AZanidean
Author: Alex Zanidean [aut, cre]
Repository: CRAN
Date/Publication: 2017-12-15 18:03:32 UTC

More information about xmrr at CRAN
Permanent link

Package VeryLargeIntegers updated to version 0.1.5 with previous version 0.1.4 dated 2017-09-27

Title: Store and Manage Arbitrarily Large Integers
Description: Multi-precission library that allows to store and manage arbitrarily big integers without loss of precision. It includes a large list of tools to work with them, like: - Arithmetic and logic operators - Modular-arithmetic operators - Computer Number Theory utilities - Probabilistic primality tests - Factorization algorithms - Random generators of diferent types of integers.
Author: Javier Leiva Cuadrado
Maintainer: Javier Leiva Cuadrado <jleivacuadrado@gmail.com>

Diff between VeryLargeIntegers versions 0.1.4 dated 2017-09-27 and 0.1.5 dated 2017-12-15

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Package ipumsr updated to version 0.1.1 with previous version 0.1.0 dated 2017-11-13

Title: Read 'IPUMS' Extract Files
Description: An easy way to import census, survey and geographic data provided by 'IPUMS' into R plus tools to help use the associated metadata to make analysis easier. 'IPUMS' data describing 1.4 billion individuals drawn from over 750 censuses and surveys is available free of charge from our website <https://ipums.org>.
Author: Greg Freedman Ellis [aut, cre], Derek Burk [ctb], Joe Grover [ctb], Minnesota Population Center [cph]
Maintainer: Greg Freedman Ellis <gfellis@umn.edu>

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Package astsa updated to version 1.8 with previous version 1.7 dated 2016-12-22

Title: Applied Statistical Time Series Analysis
Description: Included are data sets and scripts to accompany Time Series Analysis and Its Applications: With R Examples (4th ed), by R.H. Shumway and D.S. Stoffer. Springer Texts in Statistics, 2017. <DOI:10.1007/978-3-319-52452-8>.
Author: David Stoffer
Maintainer: David Stoffer <stoffer@pitt.edu>

Diff between astsa versions 1.7 dated 2016-12-22 and 1.8 dated 2017-12-15

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Package ade4 updated to version 1.7-10 with previous version 1.7-8 dated 2017-08-09

Title: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences
Description: Tools for multivariate data analysis. Several methods are provided for the analysis (i.e., ordination) of one-table (e.g., principal component analysis, correspondence analysis), two-table (e.g., coinertia analysis, redundancy analysis), three-table (e.g., RLQ analysis) and K-table (e.g., STATIS, multiple coinertia analysis). The philosophy of the package is described in Dray and Dufour (2007) <doi:10.18637/jss.v022.i04>.
Author: Stéphane Dray <stephane.dray@univ-lyon1.fr>, Anne-Béatrice Dufour <anne-beatrice.dufour@univ-lyon1.fr>, and Jean Thioulouse <jean.thioulouse@univ-lyon1.fr>, with contributions from Thibaut Jombart, Sandrine Pavoine, Jean R. Lobry, Sébastien Ollier, Daniel Borcard, Pierre Legendre and Aurélie Siberchicot. Based on earlier work by Daniel Chessel.
Maintainer: Aurélie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>

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Package tadaatoolbox updated to version 0.15.0 with previous version 0.14.0 dated 2017-11-05

Title: Helpers for Data Analysis and Presentation Focused on Undergrad Psychology
Description: Contains functions for the easy display of statistical tests as well as some convenience functions for data cleanup. It is meant to ease existing workflows with packages like 'sjPlot', 'dplyr', and 'ggplot2'. The primary components are the functions prefixed with 'tadaa_', which are built to work in an interactive environment, but also print tidy markdown tables powered by 'pixiedust' for the creation of 'RMarkdown' reports.
Author: Lukas Burk [aut, cre], Tobias Anton [aut], Daniel Lüdecke [ctb]
Maintainer: Lukas Burk <lukas@quantenbrot.de>

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Package plsVarSel updated to version 0.9.4 with previous version 0.9.3 dated 2017-11-22

Title: Variable Selection in Partial Least Squares
Description: Interfaces and methods for variable selection in Partial Least Squares. The methods include filter methods, wrapper methods and embedded methods. Both regression and classification is supported.
Author: Kristian Hovde Liland, Tahir Mehmood, Solve Sæbø
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>

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Package optiSel updated to version 2.0 with previous version 1.0.0 dated 2017-08-15

Title: Optimum Contribution Selection and Population Genetics
Description: A framework for the optimization of breeding programs via optimum contribution selection and mate allocation. An easy to use set of function for computation of optimum contributions of selection candidates, and of the population genetic parameters to be optimized. These parameters can be estimated using pedigree or genotype information, and include kinships, kinships at native haplotype segments, and breed composition of crossbred individuals. They are suitable for managing genetic diversity, removing introgressed genetic material, and accelerating genetic gain. Additionally, functions are provided for computing genetic contributions from ancestors, inbreeding coefficients, the native effective size, the native genome equivalent, pedigree completeness, and for preparing and plotting pedigrees.
Author: Robin Wellmann
Maintainer: Robin Wellmann <r.wellmann@uni-hohenheim.de>

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Package GMAC updated to version 3.0 with previous version 2.0 dated 2017-10-31

Title: Genomic Mediation Analysis with Adaptive Confounding Adjustment
Description: Performs genomic mediation analysis with adaptive confounding adjustment (GMAC) proposed by Yang et al. (2017) <doi:10.1101/078683>. It implements large scale mediation analysis and adaptively selects potential confounding variables to adjust for each mediation test from a pool of candidate confounders. The package is tailored for but not limited to genomic mediation analysis (e.g., cis-gene mediating trans-gene regulation pattern where an eQTL, its cis-linking gene transcript, and its trans-gene transcript play the roles as treatment, mediator and the outcome, respectively), restricting to scenarios with the presence of cis-association (i.e., treatment-mediator association) and random eQTL (i.e., treatment).
Author: Fan Yang, Jiebiao Wang and Lin Chen
Maintainer: Fan Yang <yfcarolyn@gmail.com>

Diff between GMAC versions 2.0 dated 2017-10-31 and 3.0 dated 2017-12-15

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Package gimme updated to version 0.3-2 with previous version 0.3-1 dated 2017-10-27

Title: Group Iterative Multiple Model Estimation
Description: Automated identification and estimation of group- and individual-level relations in time series data from within a structural equation modeling framework.
Author: Stephanie Lane [aut, cre, trl], Kathleen Gates [aut], Peter Molenaar [aut], Michael Hallquist [ctb], Hallie Pike [ctb], Zachary Fisher [ctb], Cara Arizmendi [ctb]
Maintainer: Stephanie Lane <slane@unc.edu>

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Package EMSC updated to version 0.9.0 with previous version 0.8.2 dated 2017-07-14

Title: Extended Multiplicative Signal Correction
Description: Background correction of spectral like data. Handles variations in scaling, polynomial baselines, interferents, constituents and replicate variation. Parameters for corrections are stored for further analysis, and spectra are corrected accordingly.
Author: Kristian Hovde Liland
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>

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New package afCEC with initial version 1.0.0
Package: afCEC
Type: Package
Title: Active Function Cross-Entropy Clustering
Version: 1.0.0
Date: 2017-12-11
Author: Krzysztof Byrski [aut, cre], Przemyslaw Spurek [ctb]
Maintainer: Krzysztof Byrski <krzysiek.byrski@uj.edu.pl>
Description: Active function cross-entropy clustering partitions the n-dimensional data into the clusters by finding the parameters of the mixed generalized multivariate normal distribution, that optimally approximates the scattering of the data in the n-dimensional space, whose density function is of the form: p_1*N(mi_1,^sigma_1,sigma_1,f_1)+...+p_k*N(mi_k,^sigma_k,sigma_k,f_k). The above-mentioned generalization is performed by introducing so called "f-adapted Gaussian densities" (i.e. the ordinary Gaussian densities adapted by the "active function"). Additionally, the active function cross-entropy clustering performs the automatic reduction of the unnecessary clusters. For more information please refer to P. Spurek, J. Tabor, K.Byrski, "Active function Cross-Entropy Clustering" (2017) <doi:10.1016/j.eswa.2016.12.011>.
URL: https://github.com/GeigenPrinzipal/afCEC
Encoding: UTF-8
NeedsCompilation: yes
License: GPL (>= 2)
Depends: R (>= 2.10), graphics, rgl
LinkingTo: Rcpp, RcppArmadillo
Packaged: 2017-12-15 15:00:09 UTC; Byrski Krzysztof
Repository: CRAN
Date/Publication: 2017-12-15 17:57:56 UTC

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Package rbacon updated to version 2.3.1.1 with previous version 2.3.1 dated 2017-12-14

Title: Age-Depth Modelling using Bayesian Statistics
Description: Bacon is an approach to age-depth modelling that uses Bayesian statistics to reconstruct accumulation histories for deposits, through combining radiocarbon and other dates with prior information. See Blaauw & Christen (2011) <doi:10.1214/11-BA618>.
Author: Maarten Blaauw [aut, cre], J. Andres Christen [aut], Ted Belding [cph], James Theiler [cph], Brian Gough [cph], Charles Karney [cph]
Maintainer: Maarten Blaauw <maarten.blaauw@qub.ac.uk>

Diff between rbacon versions 2.3.1 dated 2017-12-14 and 2.3.1.1 dated 2017-12-15

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Package BClustLonG updated to version 0.1.2 with previous version 0.1.1 dated 2017-12-15

Title: A Dirichlet Process Mixture Model for Clustering Longitudinal Gene Expression Data
Description: Many clustering methods have been proposed, but most of them cannot work for longitudinal gene expression data. 'BClustLonG' is a package that allows us to perform clustering analysis for longitudinal gene expression data. It adopts a linear-mixed effects framework to model the trajectory of genes over time, while clustering is jointly conducted based on the regression coefficients obtained from all genes. To account for the correlations among genes and alleviate the high dimensionality challenges, factor analysis models are adopted for the regression coefficients. The Dirichlet process prior distribution is utilized for the means of the regression coefficients to induce clustering. This package allows users to specify which variables to use for clustering (intercepts or slopes or both) and whether a factor analysis model is desired. More details about this method can be found in Jiehuan Sun, et al. (2017) <doi:10.1002/sim.7374>.
Author: Jiehuan Sun [aut, cre], Jose D. Herazo-Maya[aut], Naftali Kaminski[aut], Hongyu Zhao [aut], and Joshua L. Warren [aut],
Maintainer: Jiehuan Sun <jiehuan.sun@gmail.com>

Diff between BClustLonG versions 0.1.1 dated 2017-12-15 and 0.1.2 dated 2017-12-15

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New package tidyhydat with initial version 0.3.1
Package: tidyhydat
Title: Extract and Tidy Canadian 'Hydrometric' Data
Version: 0.3.1
Authors@R: c(person("Sam", "Albers", email = "sam.albers@gov.bc.ca", role = c("aut", "cre")), person("David", "Hutchinson", email = "david.hutchinson@canada.ca", role = "ctb"), person("Province of British Columbia", role = "cph"), person("Luke", "Winslow", role = "rev", comment = "Reviewed for rOpenSci, see <https://github.com/ropensci/onboarding/issues/118>"), person("Laura", "DeCicco", role = "rev", comment = "Reviewed for rOpenSci, see <https://github.com/ropensci/onboarding/issues/118>") )
Description: Provides functions to extract historical and real-time national 'hydrometric' data from Water Survey of Canada data sources (<http://dd.weather.gc.ca/hydrometric/csv/> and <http://collaboration.cmc.ec.gc.ca/cmc/hydrometrics/www/>) and then applies tidy data principles.
Depends: R (>= 3.4.0)
License: Apache License (== 2.0) | file LICENSE
URL: https://github.com/ropensci/tidyhydat
BugReports: https://github.com/ropensci/tidyhydat/issues
Encoding: UTF-8
Imports: dplyr (>= 0.7.3), readr (>= 1.1.1), dbplyr (>= 1.1.0), lubridate (>= 1.6.0), tidyr (>= 0.7.1), DBI (>= 0.7), RSQLite (>= 2.0), tibble (>= 1.3.4), httr (>= 1.3.1), rappdirs (>= 0.3.1)
Suggests: ggplot2, knitr, rmarkdown, testthat
LazyData: true
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-12-15 04:03:16 UTC; boshek
Author: Sam Albers [aut, cre], David Hutchinson [ctb], Province of British Columbia [cph], Luke Winslow [rev] (Reviewed for rOpenSci, see <https://github.com/ropensci/onboarding/issues/118>), Laura DeCicco [rev] (Reviewed for rOpenSci, see <https://github.com/ropensci/onboarding/issues/118>)
Maintainer: Sam Albers <sam.albers@gov.bc.ca>
Repository: CRAN
Date/Publication: 2017-12-15 13:29:18 UTC

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New package sim1000G with initial version 1.33
Package: sim1000G
Type: Package
Title: Genotype Simulations for Rare or Common Variants Using Haplotypes from 1000 Genomes
Version: 1.33
Date: 2017-12-13
Author: Apostolos Dimitromanolakis <apostolis@live.ca>, Jingxiong Xu <jingxiong.xu@mail.utoronto.ca>, Agnieszka Krol <krol@lunenfeld.ca>, Laurent Briollais <laurent@lunenfeld.ca>
Maintainer: Apostolos Dimitromanolakis <apostolis@live.ca>
Description: Generates realistic simulated genetic data in families or unrelated individuals.
License: GPL (>= 2)
Depends: R (>= 2.15.2), stats, hapsim, MASS, stringr
NeedsCompilation: no
VignetteBuilder: knitr, prettydoc
RoxygenNote: 5.0.1
Suggests: knitr, prettydoc, testthat, rmarkdown, gplots
Encoding: UTF-8
Repository: CRAN
Packaged: 2017-12-13 17:09:13 UTC; apo
Date/Publication: 2017-12-15 13:01:20 UTC

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New package PPforest with initial version 0.1.0
Package: PPforest
Type: Package
Version: 0.1.0
Title: Projection Pursuit Classification Forest
Author: Natalia da Silva, Eun-Kyung Lee, Di Cook
Maintainer: Natalia da Silva <natalia@iesta.edu.uy>
Description: Implements projection pursuit forest algorithm for supervised classification.
License: LGPL-2.1
URL: https://github.com/natydasilva/PPforest
LazyData: yes
Depends: R (>= 3.2.0)
Imports: Rcpp (>= 0.12.7), magrittr, plyr, dplyr, tidyr, doParallel
Suggests: knitr, gridExtra, GGally, ggplot2, RColorBrewer, roxygen2 (>= 3.0.0), PPtreeViz, rmarkdown
VignetteBuilder: knitr
LinkingTo: Rcpp,RcppArmadillo
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-12-14 21:05:48 UTC; natydasilva
Repository: CRAN
Date/Publication: 2017-12-15 13:04:41 UTC

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Package irtoys updated to version 0.2.1 with previous version 0.2.0 dated 2016-10-10

Title: A Collection of Functions Related to Item Response Theory (IRT)
Description: A collection of functions useful in learning and practicing IRT, which can be combined into larger programs. Provides basic CTT analysis, a simple common interface to the estimation of item parameters in IRT models for binary responses with three different programs (ICL, BILOG-MG, and ltm), ability estimation (MLE, BME, EAP, WLE, plausible values), item and person fit statistics, scaling methods (MM, MS, Stocking-Lord, and the complete Hebaera method), and a rich array of parametric and non-parametric (kernel) plots. Estimates and plots Haberman's interaction model when all items are dichotomously scored.
Author: Ivailo Partchev [aut, cre], Gunter Maris [aut], Tamaki Hattori [ctb]
Maintainer: Ivailo Partchev <partchev@gmail.com>

Diff between irtoys versions 0.2.0 dated 2016-10-10 and 0.2.1 dated 2017-12-15

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Package BisRNA updated to version 0.2.2 with previous version 0.2.1 dated 2017-04-12

Title: Analysis of RNA Cytosine-5 Methylation
Description: Bisulfite-treated RNA non-conversion in a set of samples is analysed as follows : each sample's non-conversion distribution is identified to a Poisson distribution. P-values adjusted for multiple testing are calculated in each sample. Combined non-conversion P-values and standard errors are calculated on the intersection of the set of samples. For further details, see C Legrand, F Tuorto, M Hartmann, R Liebers, D Jakob, M Helm and F Lyko (2017) <doi:10.1101/gr.210666.116>.
Author: C Legrand
Maintainer: Carine Legrand <c.legrand@dkfz.de>

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Package batchtools updated to version 0.9.8 with previous version 0.9.7 dated 2017-11-15

Title: Tools for Computation on Batch Systems
Description: As a successor of the packages 'BatchJobs' and 'BatchExperiments', this package provides a parallel implementation of the Map function for high performance computing systems managed by schedulers 'IBM Spectrum LSF' (<http://www-03.ibm.com/systems/spectrum-computing/products/lsf/>), 'OpenLava' (<http://www.openlava.org/>), 'Univa Grid Engine'/'Oracle Grid Engine' (<http://www.univa.com/>), 'Slurm' (<http://slurm.schedmd.com/>), 'TORQUE/PBS' (<http://www.adaptivecomputing.com/products/open-source/torque/>), or 'Docker Swarm' (<https://docs.docker.com/swarm/>). A multicore and socket mode allow the parallelization on a local machines, and multiple machines can be hooked up via SSH to create a makeshift cluster. Moreover, the package provides an abstraction mechanism to define large-scale computer experiments in a well-organized and reproducible way.
Author: Michel Lang [cre, aut] (0000-0001-9754-0393), Bernd Bischl [aut], Dirk Surmann [ctb]
Maintainer: Michel Lang <michellang@gmail.com>

Diff between batchtools versions 0.9.7 dated 2017-11-15 and 0.9.8 dated 2017-12-15

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Package woeBinning updated to version 0.1.5 with previous version 0.1.4 dated 2017-06-12

Title: Supervised Weight of Evidence Binning of Numeric Variables and Factors
Description: Implements an automated binning of numeric variables and factors with respect to a dichotomous target variable. Two approaches are provided: An implementation of fine and coarse classing that merges granular classes and levels step by step. And a tree-like approach that iteratively segments the initial bins via binary splits. Both procedures merge, respectively split, bins based on similar weight of evidence (WOE) values and stop via an information value (IV) based criteria. The package can be used with single variables or an entire data frame. It provides flexible tools for exploring different binning solutions and for deploying them to (new) data.
Author: Thilo Eichenberg
Maintainer: Thilo Eichenberg <te.r@gmx.net>

Diff between woeBinning versions 0.1.4 dated 2017-06-12 and 0.1.5 dated 2017-12-15

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Package storr updated to version 1.1.3 with previous version 1.1.2 dated 2017-09-08

Title: Simple Key Value Stores
Description: Creates and manages simple key-value stores. These can use a variety of approaches for storing the data. This package implements the base methods and support for file system, in-memory and DBI-based database stores.
Author: Rich FitzJohn [aut, cre]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>

Diff between storr versions 1.1.2 dated 2017-09-08 and 1.1.3 dated 2017-12-15

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Package nonnest2 updated to version 0.5 with previous version 0.4-1 dated 2016-09-13

Title: Tests of Non-Nested Models
Description: Testing non-nested models via theory supplied by Vuong (1989) <DOI:10.2307/1912557>. Includes tests of model distinguishability and of model fit that can be applied to both nested and non-nested models. Also includes functionality to obtain confidence intervals associated with AIC and BIC. This material is partially based on work supported by the National Science Foundation under Grant Number SES-1061334.
Author: Edgar Merkle [aut, cre], Dongjun You [aut], Lennart Schneider [ctb], Seongho Bae [ctb]
Maintainer: Edgar Merkle <merklee@missouri.edu>

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Package evtree updated to version 1.0-6 with previous version 1.0-5 dated 2017-04-06

Title: Evolutionary Learning of Globally Optimal Trees
Description: Commonly used classification and regression tree methods like the CART algorithm are recursive partitioning methods that build the model in a forward stepwise search. Although this approach is known to be an efficient heuristic, the results of recursive tree methods are only locally optimal, as splits are chosen to maximize homogeneity at the next step only. An alternative way to search over the parameter space of trees is to use global optimization methods like evolutionary algorithms. The 'evtree' package implements an evolutionary algorithm for learning globally optimal classification and regression trees in R. CPU and memory-intensive tasks are fully computed in C++ while the 'partykit' package is leveraged to represent the resulting trees in R, providing unified infrastructure for summaries, visualizations, and predictions.
Author: Thomas Grubinger [aut, cre], Achim Zeileis [aut] (0000-0003-0918-3766), Karl-Peter Pfeiffer [aut]
Maintainer: Thomas Grubinger <Thomas.Grubinger@scch.at>

Diff between evtree versions 1.0-5 dated 2017-04-06 and 1.0-6 dated 2017-12-15

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Package ecp updated to version 3.1.0 with previous version 3.0.0 dated 2016-09-27

Title: Non-Parametric Multiple Change-Point Analysis of Multivariate Data
Description: Implements various procedures for finding multiple change-points. Two methods make use of dynamic programming and pruning, with no distributional assumptions other than the existence of certain absolute moments in one method. Hierarchical and exact search methods are included. All methods return the set of estimated change- points as well as other summary information.
Author: Nicholas A. James, Wenyu Zhang and David S. Matteson
Maintainer: Wenyu Zhang <wz258@cornell.edu>

Diff between ecp versions 3.0.0 dated 2016-09-27 and 3.1.0 dated 2017-12-15

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Package earth updated to version 4.6.0 with previous version 4.5.1 dated 2017-07-28

Title: Multivariate Adaptive Regression Splines
Description: Build regression models using the techniques in Friedman's papers "Fast MARS" and "Multivariate Adaptive Regression Splines". (The term "MARS" is trademarked and thus not used in the name of the package.)
Author: Stephen Milborrow. Derived from mda:mars by Trevor Hastie and Rob Tibshirani. Uses Alan Miller's Fortran utilities with Thomas Lumley's leaps wrapper.
Maintainer: Stephen Milborrow <milbo@sonic.net>

Diff between earth versions 4.5.1 dated 2017-07-28 and 4.6.0 dated 2017-12-15

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More information about earth at CRAN
Permanent link

Package brms updated to version 2.0.0 with previous version 1.10.2 dated 2017-10-20

Title: Bayesian Regression Models using Stan
Description: Fit Bayesian generalized (non-)linear multivariate multilevel models using Stan for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include non-linear and smooth terms, auto-correlation structures, censored data, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with posterior predictive checks and leave-one-out cross-validation.
Author: Paul-Christian Bürkner [aut, cre]
Maintainer: Paul-Christian Bürkner <paul.buerkner@gmail.com>

Diff between brms versions 1.10.2 dated 2017-10-20 and 2.0.0 dated 2017-12-15

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Package bioinactivation updated to version 1.2.1 with previous version 1.2.0 dated 2017-11-23

Title: Simulation of Dynamic Microbial Inactivation
Description: Prediction and adjustment to experimental data of microbial inactivation. Several models available in the literature are implemented.
Author: Alberto Garre [aut, cre], Pablo S. Fernandez [aut], Jose A. Egea [aut]
Maintainer: Alberto Garre <garre.alberto@gmail.com>

Diff between bioinactivation versions 1.2.0 dated 2017-11-23 and 1.2.1 dated 2017-12-15

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New package quantregRanger with initial version 1.0
Package: quantregRanger
Type: Package
Title: Quantile Regression Forests for 'ranger'
Description: This is the implementation of quantile regression forests for the fast random forest package 'ranger'.
Authors@R: person("Philipp", "Probst", email = "philipp_probst@gmx.de", role = c("aut", "cre"))
URL: https://github.com/PhilippPro/quantregRanger
BugReports: https://github.com/PhilippPro/quantregRanger/issues
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.0.2), stats
Imports: Rcpp (>= 0.12.2), ranger
LinkingTo: Rcpp
LazyData: yes
ByteCompile: yes
Version: 1.0
Date: 2017-12-15
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: yes
Packaged: 2017-12-15 10:13:39 UTC; philipp
Author: Philipp Probst [aut, cre]
Maintainer: Philipp Probst <philipp_probst@gmx.de>
Repository: CRAN
Date/Publication: 2017-12-15 11:43:17 UTC

More information about quantregRanger at CRAN
Permanent link

Package adegraphics updated to version 1.0-9 with previous version 1.0-8 dated 2017-04-11

Title: An S4 Lattice-Based Package for the Representation of Multivariate Data
Description: Graphical functionalities for the representation of multivariate data. It is a complete re-implementation of the functions available in the 'ade4' package.
Author: Stéphane Dray <stephane.dray@univ-lyon1.fr> and Aurélie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>, with contributions from Jean Thioulouse. Based on earlier work by Alice Julien-Laferrière.
Maintainer: Aurélie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>

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Package idefix updated to version 0.2.2 with previous version 0.1.2 dated 2017-08-08

Title: Efficient Designs for Discrete Choice Experiments
Description: Generates efficient designs for discrete choice experiments based on the multinomial logit model, and individually adapted designs for the mixed multinomial logit model. The generated designs can be presented on screen and choice data can be gathered using a shiny application. Crabbe M, Akinc D and Vandebroek M (2014) <doi:10.1016/j.trb.2013.11.008>.
Author: Frits Traets [aut, cre]
Maintainer: Frits Traets <frits.traets@kuleuven.be>

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Package antaresViz updated to version 0.12.0 with previous version 0.11.2 dated 2017-12-05

Title: Antares Visualizations
Description: Visualize results generated by Antares, a powerful software developed by RTE to simulate and study electric power systems (more information about Antares here: <https://antares.rte-france.com>). This package provides functions that create interactive charts to help Antares users visually explore the results of their simulations.
Author: Jalal-Edine ZAWAM [aut, cre], Francois Guillem [aut], Benoit Thieurmel [aut], Titouan Robert [aut], Baptiste SEGUINOT [ctb], RTE [cph]
Maintainer: Jalal-Edine ZAWAM <jalal-edine.zawam@rte-france.com>

Diff between antaresViz versions 0.11.2 dated 2017-12-05 and 0.12.0 dated 2017-12-15

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New package PCDimension with initial version 1.1.7
Package: PCDimension
Version: 1.1.7
Date: 2017-12-14
Title: Finding the Number of Significant Principal Components
Author: Kevin R. Coombes, Min Wang
Maintainer: Kevin R. Coombes <krc@silicovore.com>
Description: Implements methods to automate the Auer-Gervini graphical Bayesian approach for determining the number of significant principal components. Automation uses clustering, change points, or simple statistical models to distinguish "long" from "short" steps in a graph showing the posterior number of components as a function of a prior parameter.
Depends: R (>= 3.1), ClassDiscovery
Imports: methods, stats, graphics, oompaBase, kernlab, changepoint, cpm
Suggests: MASS, nFactors
License: Apache License (== 2.0)
biocViews: Clustering
URL: http://oompa.r-forge.r-project.org/
NeedsCompilation: no
Packaged: 2017-12-14 20:32:50 UTC; coom05
Repository: CRAN
Date/Publication: 2017-12-15 09:23:12 UTC

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Package icesAdvice updated to version 1.4-0 with previous version 1.3-1 dated 2017-05-13

Title: Functions Related to ICES Advice
Description: Functions that are related to the ICES advisory process.
Author: Arni Magnusson [aut, cre], Anne Cooper [aut], Colin Millar [ctb]
Maintainer: Arni Magnusson <arni.magnusson@ices.dk>

Diff between icesAdvice versions 1.3-1 dated 2017-05-13 and 1.4-0 dated 2017-12-15

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New package hypercube with initial version 0.1.0
Package: hypercube
Type: Package
Title: Organizing Data in a Hypercube
Version: 0.1.0
Author: Michael Scholz
Maintainer: Michael Scholz <michael.scholz@uni-passau.de>
Description: Provides methods for organizing data in a hypercube (i.e. a multi-dimensional cube). Cubes are generated from molten data frames. Each cube can be manipulated with five operations: rotation (changeDimensionOrder()), dicing and slicing (add.selection(), remove.selection()), drilling down (add.aggregation()), and rolling up (remove.aggregation()).
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.3.0), stats
Imports: methods, stringr
LazyData: TRUE
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-12-15 08:17:24 UTC; micha
Repository: CRAN
Date/Publication: 2017-12-15 09:58:18 UTC

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New package BClustLonG with initial version 0.1.1
Package: BClustLonG
Type: Package
Title: A Dirichlet Process Mixture Model for Clustering Longitudinal Gene Expression Data
Version: 0.1.1
Author: Jiehuan Sun [aut, cre], Jose D. Herazo-Maya[aut], Naftali Kaminski[aut], Hongyu Zhao [aut], and Joshua L. Warren [aut],
Maintainer: Jiehuan Sun <jiehuan.sun@gmail.com>
Description: Many clustering methods have been proposed, but most of them cannot work for longitudinal gene expression data. 'BClustLonG' is a package that allows us to perform clustering analysis for longitudinal gene expression data. It adopts a linear-mixed effects framework to model the trajectory of genes over time, while clustering is jointly conducted based on the regression coefficients obtained from all genes. To account for the correlations among genes and alleviate the high dimensionality challenges, factor analysis models are adopted for the regression coefficients. The Dirichlet process prior distribution is utilized for the means of the regression coefficients to induce clustering. This package allows users to specify which variables to use for clustering (intercepts or slopes or both) and whether a factor analysis model is desired. More details about this method can be found in Jiehuan Sun, et al. (2017) <doi:10.1002/sim.7374>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0), MASS (>= 7.3-47), lme4 (>= 1.1-13), mcclust (>= 1.0)
Imports: Rcpp (>= 0.12.7)
Suggests: knitr, lattice
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-12-14 19:23:01 UTC; JiehuanSun
Repository: CRAN
Date/Publication: 2017-12-15 09:12:49 UTC

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Package gpHist (with last version 0.1) was removed from CRAN

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

2017-11-24 0.1

Permanent link
Package alR (with last version 2.2.2) was removed from CRAN

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

2017-12-07 2.2.2

Permanent link
Package spMaps updated to version 0.2 with previous version 0.1 dated 2017-11-17

Title: Europe SpatialPolygonsDataFrame Builder
Description: Build custom Europe SpatialPolygonsDataFrame, if you don't know what is a SpatialPolygonsDataFrame see SpatialPolygons() in 'sp', by example for mapLayout() in 'antaresViz'. Antares is a powerful software developed by RTE to simulate and study electric power systems (more information about 'Antares' here: <https://antares.rte-france.com>).
Author: Jalal-Edine ZAWAM [aut, cre], Benoit Thieurmel [aut], RTE [cph]
Maintainer: Jalal-Edine ZAWAM <jalal-edine.zawam@rte-france.com>

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Package GSODR updated to version 1.1.2 with previous version 1.1.1 dated 2017-11-26

Title: Global Surface Summary of the Day (GSOD) Weather Data from R
Description: Provides automated downloading, parsing, cleaning, unit conversion and formatting of Global Surface Summary of the Day (GSOD) weather data from the from the USA National Centers for Environmental Information (NCEI) for use in R. Units are converted from from United States Customary System (USCS) units to International System of Units (SI). Stations may be individually checked for number of missing days defined by the user, where stations with too many missing observations are omitted. Only stations with valid reported latitude and longitude values are permitted in the final data. Additional useful elements, saturation vapour pressure (es), actual vapour pressure (ea) and relative humidity are calculated from the original data and included in the final data set. The resulting data include station identification information, state, country, latitude, longitude, elevation, weather observations and associated flags. Data may be automatically saved to disk. File output may be returned as a comma-separated values (CSV) or GeoPackage (GPKG) file. Additional data are included with this R package: a list of elevation values for stations between -60 and 60 degrees latitude derived from the Shuttle Radar Topography Measuring Mission (SRTM). For information on the GSOD data from NCEI, please see the GSOD readme.txt file available from, <http://www1.ncdc.noaa.gov/pub/data/gsod/readme.txt>.
Author: Adam Sparks [aut, cre] (0000-0002-0061-8359), Tomislav Hengl [aut] (0000-0002-9921-5129), Andrew Nelson [aut] (0000-0002-7249-3778), Hugh Parsonage [cph, ctb] (0000-0003-4055-0835), Bob Rudis [cph, ctb] (0000-0001-5670-2640)
Maintainer: Adam Sparks <adamhsparks@gmail.com>

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Package getCRUCLdata updated to version 0.2.1 with previous version 0.2.0 dated 2017-11-16

Title: Use and Explore CRU CL v. 2.0 Climatology Elements in R
Description: Provides functions that automate downloading and importing University of East Anglia Climate Research Unit (CRU) CL v. 2.0 climatology data into R, facilitates the calculation of minimum temperature and maximum temperature and formats the data into a tidy data frame as a tibble or a list of raster stack objects for use in an R session. CRU CL v. 2.0 data are a gridded climatology of 1961-1990 monthly means released in 2002 and cover all land areas (excluding Antarctica) at 10 arcminutes (0.1666667 degree) resolution. For more information see the description of the data provided by the University of East Anglia Climate Research Unit, <https://crudata.uea.ac.uk/cru/data/hrg/tmc/readme.txt>.
Author: Adam Sparks [aut, cre] (0000-0002-0061-8359)
Maintainer: Adam Sparks <adamhsparks@gmail.com>

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Package FedData updated to version 2.5.0 with previous version 2.4.7 dated 2017-11-20

Title: Functions to Automate Downloading Geospatial Data Available from Several Federated Data Sources
Description: Functions to automate downloading geospatial data available from several federated data sources (mainly sources maintained by the US Federal government). Currently, the package enables extraction from seven datasets: The National Elevation Dataset digital elevation models (1 and 1/3 arc-second; USGS); The National Hydrography Dataset (USGS); The Soil Survey Geographic (SSURGO) database from the National Cooperative Soil Survey (NCSS), which is led by the Natural Resources Conservation Service (NRCS) under the USDA; the Global Historical Climatology Network (GHCN), coordinated by National Climatic Data Center at NOAA; the Daymet gridded estimates of daily weather parameters for North America, version 3, available from the Oak Ridge National Laboratory's Distributed Active Archive Center (DAAC); the International Tree Ring Data Bank; and the National Land Cover Database (NLCD).
Author: R. Kyle Bocinsky [aut, cre], Dylan Beaudette [ctb], Scott Chamberlain [ctb]
Maintainer: R. Kyle Bocinsky <bocinsky@gmail.com>

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Package clustEff updated to version 0.1.2 with previous version 0.1.0 dated 2017-09-26

Title: Clusters of Effects Curves in Quantile Regression Models
Description: Clustering method to cluster both effects curves, through quantile regression coefficient modeling, and curves in functional data analysis. Sottile G. and Adelfio G. (2017) <https://iwsm2017.webhosting.rug.nl/IWSM_2017_V2.pdf>.
Author: Gianluca Sottile [aut, cre], Giada Adelfio [aut]
Maintainer: Gianluca Sottile <gianluca.sottile@unipa.it>

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Package bomrang updated to version 0.1.1 with previous version 0.1.0 dated 2017-12-04

Title: Australian Government Bureau of Meteorology Data from R
Description: Provides functions to interface with Australian Government Bureau of Meteorology (BoM) data, fetching data and returning a tidy data frame of précis forecasts, current weather data from stations, agriculture bulletin data, BoM 0900 or 1500 weather bulletins or a raster stack object of satellite imagery from GeoTIFF files. Data (c) Australian Government Bureau of Meteorology Creative Commons (CC) Attribution 3.0 licence or Public Access Licence (PAL) as appropriate. See <http://www.bom.gov.au/other/copyright.shtml> for further details.
Author: Adam Sparks [aut, cre] (0000-0002-0061-8359), Mark Padgham [aut] (0000-0003-2172-5265), Hugh Parsonage [aut] (0000-0003-4055-0835), Keith Pembleton [aut] (0000-0002-1896-4516)
Maintainer: Adam Sparks <adamhsparks@gmail.com>

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Package sensiPhy updated to version 0.8.0 with previous version 0.7.0 dated 2017-09-07

Title: Sensitivity Analysis for Comparative Methods
Description: An implementation of sensitivity analysis for phylogenetic comparative methods. The package is an umbrella of statistical and graphical methods that estimate and report different types of uncertainty in PCM: (i) Species Sampling uncertainty (sample size; influential species and clades). (ii) Phylogenetic uncertainty (different topologies and/or branch lengths). (iii) Data uncertainty (intraspecific variation and measurement error).
Author: Gustavo Paterno [cre, aut], Gijsbert Werner [aut], Caterina Penone [aut], Pablo Martinez [ctb]
Maintainer: Gustavo Paterno <paternogbc@gmail.com>

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 59 files changed, 1456 insertions(+), 62 deletions(-)

More information about sensiPhy at CRAN
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Package wallace updated to version 1.0.2 with previous version 1.0.1 dated 2017-11-29

Title: A Modular Platform for Reproducible Modeling of Species Niches and Distributions
Description: The 'shiny' application 'wallace' is a modular platform for reproducible modeling of species niches and distributions. 'wallace' guides users through a complete analysis, from the acquisition of species occurrence and environmental data to visualizing model predictions on an interactive map, thus bundling complex workflows into a single, streamlined interface.
Author: Jamie M. Kass [aut, cre], Bruno Vilela [aut], Matthew E. Aiello-Lammens [aut], Robert Muscarella [aut], Cory Merow [aut], Robert P. Anderson [aut]
Maintainer: Jamie M. Kass <jkass@gradcenter.cuny.edu>

Diff between wallace versions 1.0.1 dated 2017-11-29 and 1.0.2 dated 2017-12-15

 DESCRIPTION                            |    6 +++---
 MD5                                    |   24 ++++++++++++------------
 NEWS.md                                |    6 +++++-
 R/wallace-package.R                    |    4 ++--
 README.md                              |    2 +-
 inst/Rmd/text_intro.Rmd                |    4 ++--
 inst/Rmd/text_intro_tab.Rmd            |    2 +-
 inst/Rmd/userReport.Rmd                |    2 +-
 inst/shiny/modules/mod_c2_selectOccs.R |    8 ++++----
 inst/shiny/modules/mod_c6_maxent.R     |    6 ++++--
 inst/shiny/modules/mod_c7_respPlots.R  |   11 ++++++++---
 inst/shiny/server.R                    |    7 +------
 man/wallace-package.Rd                 |    7 +++----
 13 files changed, 47 insertions(+), 42 deletions(-)

More information about wallace at CRAN
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Package RcppAlgos updated to version 0.2.2 with previous version 0.2.1 dated 2017-11-29

Title: Tools for Combinatorics and Computational Mathematics
Description: Provides optimized functions implemented in C++ with 'Rcpp' for solving problems in combinatorics and computational mathematics. There is a combination function and a permutation function that are both flexible as well as efficient with respect to speed and memory. There are optional contraint arguments that when employed, generate all combinations/permutations of a vector meeting a specific criteria (E.g. finding all combinations such that the sum is less than a bound). The generalized permutation function is also capable of producing all permutations of multisets. Additionally, there are various sieving functions that quickly generate essential components for problems common in computational mathematics (E.g. number of comprime elements, divisors, prime factorizations, and complete factorizations for many numbers as well as primes in a range).
Author: Joseph Wood
Maintainer: Joseph Wood <jwood000@gmail.com>

Diff between RcppAlgos versions 0.2.1 dated 2017-11-29 and 0.2.2 dated 2017-12-15

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 MD5                            |   22 -
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 14 files changed, 779 insertions(+), 403 deletions(-)

More information about RcppAlgos at CRAN
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