Sat, 13 Feb 2016

New package TransP with initial version 0.1
Package: TransP
Type: Package
Title: Implementation of Transportation Problem Algorithms
Version: 0.1
Date: 2016-02-11
Author: Somenath Sit
Maintainer: Somenath Sit <somenath.bhu.2010@gmail.com>
Description: Implementation of two transportation problem algorithms. 1. North West Corner Method 2. Minimum Cost Method or Least cost method. For more technical details about the algorithms please refer below URLs. <http://www.universalteacherpublications.com/univ/ebooks/or/Ch5/nw.htm>. <http://personal.maths.surrey.ac.uk/st/J.F/chapter7.pdf>.
License: GPL (>= 2)
LazyLoad: yes
RoxygenNote: 5.0.1
URL: https://github.com/Somenath24/TransP
NeedsCompilation: no
Packaged: 2016-02-13 05:28:10 UTC; Somenath
Repository: CRAN
Date/Publication: 2016-02-13 19:01:12

More information about TransP at CRAN
Permanent link

Package rstanarm updated to version 2.9.0-3 with previous version 2.9.0-1 dated 2016-01-09

Title: Bayesian Applied Regression Modeling via Stan
Description: Estimates pre-compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.
Author: Jonah Gabry [aut], Trustees of Columbia University [cph], R Core Deveopment Team [cph] (R/pp_data.R, R/stan_aov.R), Douglas Bates [cph] (R/pp_data.R), Martin Maechler [cph] (R/pp_data.R), Ben Bolker [cph] (R/pp_data.R), Steve Walker [cph] (R/pp_data.R), Brian Ripley [cph] (R/stan_aov.R, R/stan_polr.R), William Venables [cph] (R/stan_polr.R), Ben Goodrich [cre, aut]
Maintainer: Ben Goodrich <benjamin.goodrich@columbia.edu>

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Package RNetCDF updated to version 1.8-1 with previous version 1.7-3 dated 2015-05-11

Title: Interface to NetCDF Datasets
Description: An interface to the NetCDF file format designed by Unidata for efficient storage of array-oriented scientific data and descriptions. The R interface is closely based on the C API of the NetCDF library, and it includes calendar conversions from the Unidata UDUNITS library. The current implementation supports all operations on NetCDF datasets in classic and 64-bit offset file formats, and NetCDF4-classic format is supported for reading and modification of existing files.
Author: Pavel Michna, with contributions from Milton Woods
Maintainer: Milton Woods <mwoods@users.r-forge.r-project.org>

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Package rgeos updated to version 0.3-17 with previous version 0.3-15 dated 2015-11-04

Title: Interface to Geometry Engine - Open Source (GEOS)
Description: Interface to Geometry Engine - Open Source (GEOS) using the C API for topology operations on geometries. The GEOS library is external to the package, and, when installing the package from source, must be correctly installed first. Windows and Mac Intel OS X binaries are provided on CRAN.
Author: Roger Bivand [cre, aut], Colin Rundel [aut], Edzer Pebesma [ctb], Karl Ove Hufthammer [ctb]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

Diff between rgeos versions 0.3-15 dated 2015-11-04 and 0.3-17 dated 2016-02-13

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Package qrmtools updated to version 0.0-5 with previous version 0.0-4 dated 2016-01-15

Title: Tools for Quantitative Risk Management
Description: Functions and data sets for reproducing selected results from the book "Quantitative Risk Management: Concepts, Techniques and Tools". Furthermore, new developments and auxiliary functions for Quantitative Risk Management practice.
Author: Marius Hofert [aut, cre], Kurt Hornik [aut]
Maintainer: Marius Hofert <marius.hofert@uwaterloo.ca>

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Package pcadapt updated to version 2.2 with previous version 2.1.1 dated 2016-01-05

Title: Principal Component Analysis for Outlier Detection
Description: Methods to detect genetic markers involved in biological adaptation. 'pcadapt' provides statistical tools for outlier detection based on Principal Component Analysis.
Author: Keurcien Luu, Michael G.B. Blum
Maintainer: Keurcien Luu <keurcien.luu@imag.fr>

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Package maps updated to version 3.1.0 with previous version 3.0.2 dated 2016-01-04

Title: Draw Geographical Maps
Description: Display of maps. Projection code and larger maps are in separate packages ('mapproj' and 'mapdata').
Author: Original S code by Richard A. Becker and Allan R. Wilks. R version by Ray Brownrigg. Enhancements by Thomas P Minka and Alex Deckmyn.
Maintainer: Alex Deckmyn <alex.deckmyn@meteo.be>

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New package nproc with initial version 0.1
Package: nproc
Type: Package
Title: Neyman-Pearson Receiver Operator Curve
Version: 0.1
Date: 2016-02-11
Author: Yang Feng, Jessica Li and Xin Tong
Maintainer: Yang Feng <yang.feng@columbia.edu>
Imports: glmnet, e1071, randomForest, MASS, parallel, ada, stats, graphics
Description: Given a sample of class 0 and class 1 and a classification method, the package generates the corresponding Neyman-Pearson classifier with a pre-specified type-I error control and Neyman-Pearson Receiver Operator Curve.
License: GPL-2
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-02-13 03:37:51 UTC; yangfeng
Repository: CRAN
Date/Publication: 2016-02-13 19:01:18

More information about nproc at CRAN
Permanent link

Package mlr updated to version 2.8 with previous version 2.7 dated 2015-12-04

Title: Machine Learning in R
Description: Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized.
Author: Bernd Bischl [aut, cre], Michel Lang [aut], Jakob Richter [aut], Jakob Bossek [aut], Leonard Judt [aut], Tobias Kuehn [aut], Erich Studerus [aut], Lars Kotthoff [aut], Zachary Jones [ctb], Schiffner Julia [aut]
Maintainer: Bernd Bischl <bernd_bischl@gmx.net>

Diff between mlr versions 2.7 dated 2015-12-04 and 2.8 dated 2016-02-13

 mlr-2.7/mlr/R/benchmarkTest.R                                    |only
 mlr-2.7/mlr/R/checkColumnNames.R                                 |only
 mlr-2.7/mlr/R/checkDfTarget.R                                    |only
 mlr-2.7/mlr/R/generateCritDifferences.R                          |only
 mlr-2.7/mlr/R/generateROCRCurves.R                               |only
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 mlr-2.7/mlr/man/LearningCurveData.Rd                             |only
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 mlr-2.7/mlr/man/generateROCRCurvesData.Rd                        |only
 mlr-2.7/mlr/man/plotROCRCurves.Rd                                |only
 mlr-2.7/mlr/man/plotROCRCurvesGGVIS.Rd                           |only
 mlr-2.7/mlr/tests/run-learners.R                                 |only
 mlr-2.7/mlr/tests/testthat/test_base_BMRhypothesisTests.R        |only
 mlr-2.7/mlr/tests/testthat/test_regr_randomForest_se.R           |only
 mlr-2.8/mlr/DESCRIPTION                                          |   22 
 mlr-2.8/mlr/MD5                                                  |  660 +++++-----
 mlr-2.8/mlr/NAMESPACE                                            |   42 
 mlr-2.8/mlr/NEWS                                                 |   44 
 mlr-2.8/mlr/R/Aggregation.R                                      |   41 
 mlr-2.8/mlr/R/BaseEnsemble.R                                     |    7 
 mlr-2.8/mlr/R/BenchmarkResult_operators.R                        |   39 
 mlr-2.8/mlr/R/CostSensTask.R                                     |    4 
 mlr-2.8/mlr/R/CostSensWeightedPairsWrapper.R                     |    3 
 mlr-2.8/mlr/R/Filter.R                                           |   43 
 mlr-2.8/mlr/R/ImputeMethods.R                                    |    3 
 mlr-2.8/mlr/R/Learner_properties.R                               |   32 
 mlr-2.8/mlr/R/Measure.R                                          |   18 
 mlr-2.8/mlr/R/Measure_custom_resampled.R                         |   11 
 mlr-2.8/mlr/R/ModelMultiplexer.R                                 |   11 
 mlr-2.8/mlr/R/MulticlassWrapper.R                                |   14 
 mlr-2.8/mlr/R/OverBaggingWrapper.R                               |   34 
 mlr-2.8/mlr/R/OverUnderSampling.R                                |   34 
 mlr-2.8/mlr/R/OverUndersampleWrapper.R                           |   36 
 mlr-2.8/mlr/R/PreprocWrapperCaret.R                              |    2 
 mlr-2.8/mlr/R/RLearner.R                                         |   51 
 mlr-2.8/mlr/R/RLearner_classif_J48.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_JRip.R                            |    2 
 mlr-2.8/mlr/R/RLearner_classif_LiblineaRL2LogReg.R               |    7 
 mlr-2.8/mlr/R/RLearner_classif_LiblineaRL2SVC.R                  |    5 
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 mlr-2.8/mlr/R/RLearner_classif_PART.R                            |    2 
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 mlr-2.8/mlr/R/RLearner_classif_avNNet.R                          |    2 
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 mlr-2.8/mlr/R/RLearner_classif_cforest.R                         |   10 
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 mlr-2.8/mlr/R/RLearner_classif_dbnDNN.R                          |    2 
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 mlr-2.8/mlr/R/RLearner_classif_gbm.R                             |    5 
 mlr-2.8/mlr/R/RLearner_classif_geoDA.R                           |    3 
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 mlr-2.8/mlr/R/RLearner_classif_glmnet.R                          |    5 
 mlr-2.8/mlr/R/RLearner_classif_ksvm.R                            |    2 
 mlr-2.8/mlr/R/RLearner_classif_lda.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_linDA.R                           |    6 
 mlr-2.8/mlr/R/RLearner_classif_logreg.R                          |    2 
 mlr-2.8/mlr/R/RLearner_classif_lqa.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_mda.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_nnTrain.R                         |    2 
 mlr-2.8/mlr/R/RLearner_classif_nnet.R                            |    2 
 mlr-2.8/mlr/R/RLearner_classif_pamr.R                            |    2 
 mlr-2.8/mlr/R/RLearner_classif_plr.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_probit.R                          |    2 
 mlr-2.8/mlr/R/RLearner_classif_qda.R                             |    2 
 mlr-2.8/mlr/R/RLearner_classif_quaDA.R                           |    4 
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 mlr-2.8/mlr/R/RLearner_classif_svm.R                             |    3 
 mlr-2.8/mlr/R/RLearner_classif_xgboost.R                         |   11 
 mlr-2.8/mlr/R/RLearner_cluster_XMeans.R                          |    2 
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 mlr-2.8/mlr/R/RLearner_cluster_kmeans.R                          |    2 
 mlr-2.8/mlr/R/RLearner_regr_LiblineaRL2L1SVR.R                   |    2 
 mlr-2.8/mlr/R/RLearner_regr_LiblineaRL2L2SVR.R                   |    4 
 mlr-2.8/mlr/R/RLearner_regr_avNNet.R                             |    2 
 mlr-2.8/mlr/R/RLearner_regr_bartMachine.R                        |    2 
 mlr-2.8/mlr/R/RLearner_regr_blackBoost.R                         |    2 
 mlr-2.8/mlr/R/RLearner_regr_bst.R                                |    6 
 mlr-2.8/mlr/R/RLearner_regr_cforest.R                            |   10 
 mlr-2.8/mlr/R/RLearner_regr_ctree.R                              |    2 
 mlr-2.8/mlr/R/RLearner_regr_elmNN.R                              |    2 
 mlr-2.8/mlr/R/RLearner_regr_gbm.R                                |    4 
 mlr-2.8/mlr/R/RLearner_regr_glmboost.R                           |    2 
 mlr-2.8/mlr/R/RLearner_regr_glmnet.R                             |    5 
 mlr-2.8/mlr/R/RLearner_regr_km.R                                 |    2 
 mlr-2.8/mlr/R/RLearner_regr_ksvm.R                               |    2 
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 mlr-2.8/mlr/R/RLearner_regr_randomForest.R                       |  193 +-
 mlr-2.8/mlr/R/RLearner_regr_randomForestSRC.R                    |    6 
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 mlr-2.8/mlr/R/RLearner_regr_ranger.R                             |    2 
 mlr-2.8/mlr/R/RLearner_regr_rpart.R                              |    4 
 mlr-2.8/mlr/R/RLearner_regr_rsm.R                                |    2 
 mlr-2.8/mlr/R/RLearner_regr_rvm.R                                |    6 
 mlr-2.8/mlr/R/RLearner_regr_slim.R                               |    2 
 mlr-2.8/mlr/R/RLearner_regr_svm.R                                |    2 
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 mlr-2.8/mlr/R/RLearner_surv_cforest.R                            |   10 
 mlr-2.8/mlr/R/RLearner_surv_cvglmnet.R                           |    5 
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 mlr-2.8/mlr/R/RLearner_surv_ranger.R                             |    2 
 mlr-2.8/mlr/R/RLearner_surv_rpart.R                              |    4 
 mlr-2.8/mlr/R/ResampleDesc.R                                     |    8 
 mlr-2.8/mlr/R/ResampleInstances.R                                |    2 
 mlr-2.8/mlr/R/StackedLearner.R                                   |   62 
 mlr-2.8/mlr/R/Task.R                                             |   23 
 mlr-2.8/mlr/R/TaskDesc.R                                         |   22 
 mlr-2.8/mlr/R/Task_operators.R                                   |   19 
 mlr-2.8/mlr/R/WrappedModel.R                                     |    2 
 mlr-2.8/mlr/R/aggregations.R                                     |    2 
 mlr-2.8/mlr/R/benchmark.R                                        |    2 
 mlr-2.8/mlr/R/benchmarkResult_mergers.R                          |   12 
 mlr-2.8/mlr/R/capLargeValues.R                                   |   27 
 mlr-2.8/mlr/R/checkPrediction.R                                  |    2 
 mlr-2.8/mlr/R/checkTargetPreproc.R                               |only
 mlr-2.8/mlr/R/convertBMRToRankMatrix.R                           |   13 
 mlr-2.8/mlr/R/convertX.R                                         |    9 
 mlr-2.8/mlr/R/crossover.R                                        |    2 
 mlr-2.8/mlr/R/datasets.R                                         |   22 
 mlr-2.8/mlr/R/estimateResidualVariance.R                         |    9 
 mlr-2.8/mlr/R/evalOptimizationState.R                            |    9 
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 mlr-2.8/mlr/R/generateCalibration.R                              |   26 
 mlr-2.8/mlr/R/generateFilterValues.R                             |   29 
 mlr-2.8/mlr/R/generateLearningCurve.R                            |   30 
 mlr-2.8/mlr/R/generatePartialPrediction.R                        |  209 +--
 mlr-2.8/mlr/R/generateThreshVsPerf.R                             |  219 ++-
 mlr-2.8/mlr/R/getClassWeightParam.R                              |    5 
 mlr-2.8/mlr/R/helpers.R                                          |   15 
 mlr-2.8/mlr/R/listLearners.R                                     |   53 
 mlr-2.8/mlr/R/logFunOpt.R                                        |    2 
 mlr-2.8/mlr/R/makeLearner.R                                      |    5 
 mlr-2.8/mlr/R/measures.R                                         |   60 
 mlr-2.8/mlr/R/normalizeFeatures.R                                |    2 
 mlr-2.8/mlr/R/options.R                                          |    2 
 mlr-2.8/mlr/R/plotBMRBoxplots.R                                  |   10 
 mlr-2.8/mlr/R/plotBMRRanksAsBarChart.R                           |   20 
 mlr-2.8/mlr/R/plotBMRSummary.R                                   |   14 
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 mlr-2.8/mlr/R/resample.R                                         |    2 
 mlr-2.8/mlr/R/train.R                                            |    4 
 mlr-2.8/mlr/R/tuneIrace.R                                        |   17 
 mlr-2.8/mlr/R/tuneParams.R                                       |    7 
 mlr-2.8/mlr/R/utils_imbalancy.R                                  |   36 
 mlr-2.8/mlr/R/zzz.R                                              |   41 
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Fri, 12 Feb 2016

Package yhatr updated to version 0.13.10 with previous version 0.13.9 dated 2016-02-11

Title: R Binder for the Yhat API
Description: Deploy, maintain, and invoke models via the Yhat REST API.
Author: Greg Lamp <greg@yhathq.com>, Brandon Hopkins <dev@yhathq.com>
Maintainer: Greg Lamp <greg@yhathq.com>

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New package tadaatoolbox with initial version 0.8.0
Package: tadaatoolbox
Type: Package
Date: 2016-02-12
Title: Helpers for Data Analysis and Presentation Focused on Undergrad Psychology
Version: 0.8.0
Authors@R: c(person('Lukas', 'Burk', email = 'lukas@quantenbrot.de', role = c('aut', 'cre')), person('Tobias', 'Anton', email = 'unsichtbarer@quantenbrot.de', role = c('aut')))
Description: Contains functions for the easy display of statistical tests as well as some convenience functions for recoding or 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 'pixiedist' for the creation of 'RMarkdown' reports.
License: MIT + file LICENSE
LazyData: TRUE
Encoding: UTF-8
Depends: R (>= 3.1.0)
Suggests: testthat
Imports: stats, broom, dplyr, pwr, pixiedust, car, ggplot2, lazyeval, sjmisc, haven, ryouready, vcd
RoxygenNote: 5.0.1
URL: https://github.com/tadaadata/tadaatoolbox
BugReports: https://github.com/tadaadata/tadaatoolbox/issues
NeedsCompilation: no
Packaged: 2016-02-12 23:50:25 UTC; Lukas
Author: Lukas Burk [aut, cre], Tobias Anton [aut]
Maintainer: Lukas Burk <lukas@quantenbrot.de>
Repository: CRAN
Date/Publication: 2016-02-13 01:01:49

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Package quantreg updated to version 5.21 with previous version 5.19 dated 2015-08-31

Title: Quantile Regression
Description: Estimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also included.
Author: Roger Koenker [cre, aut], Stephen Portnoy [ctb] (Contributions to Censored QR code), Pin Tian Ng [ctb] (Contributions to Sparse QR code), Achim Zeileis [ctb] (Contributions to dynrq code essentially identical to his dynlm code), Philip Grosjean [ctb] (Contributions to nlrq code), Brian D Ripley [trl, ctb] (Initial (2001) R port from S (to my everlasting shame -- how could I have been so slow to adopt R!) and for numerous other suggestions and useful advice)
Maintainer: Roger Koenker <rkoenker@illinois.edu>

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Package purrr updated to version 0.2.1 with previous version 0.2.0 dated 2016-01-04

Title: Functional Programming Tools
Description: Make your pure functions purr with the 'purrr' package. This package completes R's functional programming tools with missing features present in other programming languages.
Author: Hadley Wickham [aut, cre], Lionel Henry [ctb], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package provenance updated to version 1.3 with previous version 1.2 dated 2016-01-21

Title: Statistical Toolbox for Sedimentary Provenance Analysis
Description: Bundles a number of established statistical methods to facilitate the visual interpretation of large datasets in sedimentary geology. Includes functionality for adaptive kernel density estimation, multidimensional scaling, generalised procrustes analysis and individual differences scaling using a variety of dissimilarity measures. Univariate provenance proxies, such as single-grain ages or (isotopic) compositions are compared with the Kolmogorov- Smirnov dissimilarity and Sircombe-Hazelton L2-norm. Categorical provenance proxies, such as mineralogical, petrographic or chemical compositions are compared with the Aitchison and Bray-Curtis distances. Also included are tools to plot compositional data on ternary diagrams, to calculate the sample size required for specified levels of statistical precision, and to assess the effects of hydraulic sorting on detrital compositions. Includes an intuitive query-based user interface for users who are not proficient in R.
Author: Pieter Vermeesch [aut, cre]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

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Package munsell updated to version 0.4.3 with previous version 0.4.2 dated 2013-07-11

Title: Utilities for Using Munsell Colours
Description: Provides easy access to, and manipulation of, the Munsell colours. Provides a mapping between Munsell's original notation (e.g. "5R 5/10") and hexadecimal strings suitable for use directly in R graphics. Also provides utilities to explore slices through the Munsell colour tree, to transform Munsell colours and display colour palettes.
Author: Charlotte Wickham <cwickham@gmail.com>
Maintainer: Charlotte Wickham <cwickham@gmail.com>

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Package multimark updated to version 1.3.2 with previous version 1.3.1 dated 2015-10-21

Title: Capture-Mark-Recapture Analysis using Multiple Non-Invasive Marks
Description: Capture-mark-recapture analysis with multiple non-invasive marks. The models implemented in 'multimark' combine encounter history data arising from two different non-invasive ``marks'', such as images of left-sided and right-sided pelage patterns of bilaterally asymmetrical species, to estimate abundance and related demographic parameters while accounting for imperfect detection. Bayesian models are specified using simple formulae and fitted using Markov chain Monte Carlo. Addressing deficiencies in currently available software, 'multimark' also provides a user-friendly interface for performing Bayesian multimodel inference using capture-recapture data consisting of a single conventional mark or multiple non-invasive marks.
Author: Brett T. McClintock [aut, cre], Acho Arnold [ctb, cph] (C original matrix library, https://github.com/najela/matrix.h), Barry Brown [ctb] (Fortran original ranlib library), James Lovato [ctb] (Fortran original ranlib library), John Burkardt [ctb] (C original ranlib library, http://people.sc.fsu.edu/~jburkardt/c_src/ranlib), Cleve Moler [ctb] (C original linpack library, http://www.kkant.net/geist/ranlib/)
Maintainer: Brett T. McClintock <brett.mcclintock@noaa.gov>

Diff between multimark versions 1.3.1 dated 2015-10-21 and 1.3.2 dated 2016-02-12

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Package MSG updated to version 0.3 with previous version 0.2.2 dated 2012-08-19

Title: Data and Functions for the Book Modern Statistical Graphics
Description: A companion to the Chinese book ``Modern Statistical Graphics''.
Author: Yihui Xie
Maintainer: Yihui Xie <xie@yihui.name>

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Package monogeneaGM updated to version 1.1 with previous version 1.0 dated 2015-07-16

Title: Geometric Morphometric Analysis of Monogenean Anchors
Description: Geometric morphometric and evolutionary biology analyses of anchor shape from four-anchored monogeneans.
Author: Tsung Fei Khang
Maintainer: Tsung Fei Khang <tfkhang@um.edu.my>

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Package ggswissmaps updated to version 0.0.8 with previous version 0.0.6 dated 2015-12-21

Title: Offers Various Swiss Maps as ggplot2 Objects
Description: Offers various swiss maps as ggplot2 objects and gives the possibility to add layers of data on the maps. Data are publicly available from the swiss federal statistical office.
Author: Sandro Petrillo Burri [aut, cre], Eric Stephani [aut], Lisa Bottinelli [ctb]
Maintainer: Sandro Petrillo Burri <gibo.gaf@gmail.com>

Diff between ggswissmaps versions 0.0.6 dated 2015-12-21 and 0.0.8 dated 2016-02-12

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Permanent link

Package EnsemblePCReg updated to version 1.0.0 with previous version 0.6 dated 2014-11-27

Title: Extensible Package for Principal-Component-Regression-Based Integration of Base Learners
Description: Extends the base classes and methods of EnsembleBase package for Principal-Components-Regression-based (PCR) integration of base learners. Default implementation uses cross-validation error to choose the optimal number of PC components for the final predictor. The package takes advantage of the file method provided in EnsembleBase package for writing estimation objects to disk in order to circumvent RAM bottleneck. Special save and load methods are provided to allow estimation objects to be saved to permanent files on disk, and to be loaded again into temporary files in a later R session. Users and developers can extend the package by extending the generic methods and classes provided in EnsembleBase package as well as this package.
Author: Mansour T.A. Sharabiani, Alireza S. Mahani
Maintainer: Alireza S. Mahani <alireza.mahani@sentrana.com>

Diff between EnsemblePCReg versions 0.6 dated 2014-11-27 and 1.0.0 dated 2016-02-12

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More information about EnsemblePCReg at CRAN
Permanent link

Package data.tree updated to version 0.3.0 with previous version 0.2.4 dated 2015-10-24

Title: General Purpose Hierarchical Data Structure
Description: Create tree structures from hierarchical data, and traverse the tree in various orders. Aggregate, cumulate, print, plot, convert to and from data.frame and more. Useful for decision trees, machine learning, finance, conversion from and to JSON, and many other applications.
Author: Christoph Glur
Maintainer: Christoph Glur <christoph.glur@ipub.com>

Diff between data.tree versions 0.2.4 dated 2015-10-24 and 0.3.0 dated 2016-02-12

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Package archivist updated to version 2.0 with previous version 1.8 dated 2015-11-27

Title: Tools for Storing, Restoring and Searching for R Objects
Description: Data exploration and modelling is a process in which a lot of data artifacts are produced. Artifacts like: subsets, data aggregates, plots, statistical models, different versions of data sets and different versions of results. The more projects we work with the more artifacts are produced and the harder it is to manage these artifacts. Archivist helps to store and manage artifacts created in R. Archivist allows you to store selected artifacts as a binary files together with their metadata and relations. Archivist allows to share artifacts with others, either through shared folder or github. Archivist allows to look for already created artifacts by using it's class, name, date of the creation or other properties. Makes it easy to restore such artifacts. Archivist allows to check if new artifact is the exact copy that was produced some time ago. That might be useful either for testing or caching.
Author: Przemyslaw Biecek [aut, cre], Marcin Kosinski [aut], Witold Chodor [ctb]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>

Diff between archivist versions 1.8 dated 2015-11-27 and 2.0 dated 2016-02-12

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New package BonEV with initial version 1.0
Package: BonEV
Type: Package
Title: An Improved Multiple Testing Procedure for Controlling False Discovery Rates
Version: 1.0
Date: 2016-02-10
Author: Dongmei Li
Maintainer: Dongmei Li <dongmei_li@urmc.rochester.edu>
Depends: R (>= 3.2.0), qvalue
Description: An improved multiple testing procedure for controlling false discovery rates which is developed based on the Bonferroni procedure with integrated estimates from the Benjamini-Hochberg procedure and the Storey's q-value procedure. It controls false discovery rates through controlling the expected number of false discoveries.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2016-02-12 15:57:59 UTC; dli3
Repository: CRAN
Date/Publication: 2016-02-13 00:59:51

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New package wrswoR.benchmark with initial version 0.1-1
Encoding: UTF-8
Package: wrswoR.benchmark
Type: Package
Title: Benchmark and Correctness Data for Weighted Random Sampling Without Replacement
Version: 0.1-1
Authors@R: person("Kirill", "Müller", role = c("aut", "cre"), email = "krlmlr+r@mailbox.org")
Description: Includes performance measurements and results of repeated experiment runs (for correctness checks) for code in the 'wrswoR' package.
License: GPL-3
URL: http://krlmlr.github.io/wrswoR.benchmark
URLNote: https://github.com/krlmlr/wrswoR.benchmark
BugReports: https://github.com/krlmlr/wrswoR.benchmark/issues
Depends: R (>= 3.0.2)
Imports: lazyeval, curl
Suggests: knitr, rmarkdown, ggplot2, dplyr, tidyr
LazyData: true
RoxygenNote: 5.0.1
Collate: 'aaa-rextdata.R' 'timings.R' 'break_even.R' 'p_values_7.R' 'p_values_agg.R'
NeedsCompilation: no
Packaged: 2016-02-12 13:03:38 UTC; muelleki
Author: Kirill Müller [aut, cre]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>
Repository: CRAN
Date/Publication: 2016-02-12 14:41:11

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New package WaverR with initial version 1.0
Package: WaverR
Type: Package
Title: Data Estimation using Weighted Averages of Multiple Regressions
Version: 1.0
Date: 2015-09-22
Author: Olivia Cheronet, John A. Finarelli
Maintainer: Olivia Cheronet <cheronetolivia@gmail.com>
Description: For multivariate datasets, this function enables the estimation of missing data using the Weighted AVERage of all possible Regressions using the data available.
License: GPL-2
Depends: MASS (>= 7.3-33), kimisc (>= 0.2-1)
NeedsCompilation: no
Packaged: 2016-02-12 10:14:25 UTC; cheronetolivia
Repository: CRAN
Date/Publication: 2016-02-12 14:41:07

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Package TSdist updated to version 3.2 with previous version 3.1 dated 2015-07-14

Title: Distance Measures for Time Series Data
Description: A set of commonly used distance measures and some additional functions which, although initially not designed for this purpose, can be used to measure the dissimilarity between time series. These measures can be used to perform clustering, classification or other data mining tasks which require the definition of a distance measure between time series.
Author: Usue Mori, Alexander Mendiburu, J.A. Lozano
Maintainer: Usue Mori <usue.mori@ehu.es>

Diff between TSdist versions 3.1 dated 2015-07-14 and 3.2 dated 2016-02-12

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Package Directional updated to version 1.7.5 with previous version 1.7 dated 2016-01-27

Title: Directional Statistics
Description: A collection of R functions for directional data analysis.
Author: Michail Tsagris, Giorgos Athineou
Maintainer: Michail Tsagris <mtsagris@yahoo.gr>

Diff between Directional versions 1.7 dated 2016-01-27 and 1.7.5 dated 2016-02-12

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More information about Directional at CRAN
Permanent link

Package cartography updated to version 1.2 with previous version 1.1 dated 2015-11-18

Title: Thematic Cartography
Description: Create and integrate maps in your R workflow. This package allows various cartographic representations such as proportional symbols, chroropleth, typology, flows, discontinuities. In addition it also proposes some additional useful features as cartographic palettes, layout (scale, north arrow, title...), labels, legends, access to cartographic API to ease the graphic presentation of maps.
Author: Timothée Giraud [cre, aut], Nicolas Lambert [aut]
Maintainer: Timothée Giraud <timothee.giraud@ums-riate.fr>

Diff between cartography versions 1.1 dated 2015-11-18 and 1.2 dated 2016-02-12

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More information about cartography at CRAN
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Package simsalapar updated to version 1.0-9 with previous version 1.0-8 dated 2016-01-02

Title: Tools for Simulation Studies in Parallel
Description: Tools for setting up ("design"), conducting, and evaluating large-scale simulation studies with graphics and tables, including parallel computations.
Author: Marius Hofert and Martin Maechler <maechler@stat.math.ethz.ch>
Maintainer: Marius Hofert <marius.hofert@uwaterloo.ca>

Diff between simsalapar versions 1.0-8 dated 2016-01-02 and 1.0-9 dated 2016-02-12

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More information about simsalapar at CRAN
Permanent link

Package sdcTable updated to version 0.20.3 with previous version 0.20.1 dated 2015-12-11

Title: Methods for Statistical Disclosure Control in Tabular Data
Description: Methods for statistical disclosure control in tabular data such as primary and secondary cell suppression are covered in this package.
Author: Bernhard Meindl
Maintainer: Bernhard Meindl <bernhard.meindl@statistik.gv.at>

Diff between sdcTable versions 0.20.1 dated 2015-12-11 and 0.20.3 dated 2016-02-12

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More information about sdcTable at CRAN
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New package ECctmc with initial version 0.1.0
Package: ECctmc
Type: Package
Title: Simulation from Endpoint-Conditioned Continuous Time Markov Chains
Version: 0.1.0
Date: 2016-02-01
Authors@R: person("Jon", "Fintzi", email = "fintzij@uw.edu", role = c("aut", "cre"))
URL: https://github.com/fintzij/ECctmc
BugReports: https://github.com/fintzij/ECctmc/issues
Description: Draw sample paths for endpoint-conditioned continuous time Markov chains via modified rejection sampling or uniformization.
License: GPL-3
LazyData: TRUE
Imports: Rcpp (>= 0.12.3)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 5.0.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2016-02-12 08:59:13 UTC; Jonathan
Author: Jon Fintzi [aut, cre]
Maintainer: Jon Fintzi <fintzij@uw.edu>
Repository: CRAN
Date/Publication: 2016-02-12 10:59:12

More information about ECctmc at CRAN
Permanent link

Package DepthProc updated to version 1.0.7 with previous version 1.0.3 dated 2014-11-11

Title: Statistical Depth Functions for Multivariate Analysis
Description: Data depth concept offers a variety of powerful and user friendly tools for robust exploration and inference for multivariate data. The offered techniques may be successfully used in cases of lack of our knowledge on parametric models generating data due to their nonparametric nature. The package consist of among others implementations of several data depth techniques involving multivariate quantile-quantile plots, multivariate scatter estimators, multivariate Wilcoxon tests and robust regressions.
Author: Daniel Kosiorowski, Mateusz Bocian, Anna Wegrzynkiewicz and Zygmunt Zawadzki from Cracow University of Economics.
Maintainer: Zygmunt Zawadzki <zawadzkizygmunt@gmail.com>

Diff between DepthProc versions 1.0.3 dated 2014-11-11 and 1.0.7 dated 2016-02-12

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Package ACSNMineR updated to version 0.16.01.29 with previous version 0.15.11 dated 2015-11-24

Title: Gene Enrichment Analysis from ACSN Maps or GMT Files
Description: Compute and represent gene set enrichment or depletion from your data based on pre-saved maps from the Atlas of Cancer Signalling Networks (ACSN) or user imported maps. User imported maps must be complying with the GMT format as defined by the Broad Institute, that is to say that the file should be tab-separated, that the first column should contain the module name, the second column can contain comments that will be overwritten with the number of genes in the module, and subsequent columns must contain the list of genes (HUGO symbols; tab-separated) inside the module. The gene set enrichment can be run with hypergeometric test or Fisher exact test, and can use multiple corrections. Visualization of data can be done either by barplots or heatmaps.
Author: Paul Deveau [aut, cre], Eric Bonnet [aut]
Maintainer: Paul Deveau <paul.deveau@curie.fr>

Diff between ACSNMineR versions 0.15.11 dated 2015-11-24 and 0.16.01.29 dated 2016-02-12

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Package weights updated to version 0.85 with previous version 0.80 dated 2014-03-04

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). Future versions of the package will be more closely integrated with "anesrake" and additional weighting tools and will provide the option to find weighting benchmarks and weight data using a variety of methodologies. NOTE: Weighted partial correlation calculations temporarily pulled to address a bug.
Author: Josh Pasek, 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>

Diff between weights versions 0.80 dated 2014-03-04 and 0.85 dated 2016-02-12

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Package TeachingDemos updated to version 2.10 with previous version 2.9 dated 2013-08-29

Title: Demonstrations for Teaching and Learning
Description: Demonstration functions that can be used in a classroom to demonstrate statistical concepts, or on your own to better understand the concepts or the programming.
Author: Greg Snow
Maintainer: Greg Snow <538280@gmail.com>

Diff between TeachingDemos versions 2.9 dated 2013-08-29 and 2.10 dated 2016-02-12

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Package loo updated to version 0.1.5 with previous version 0.1.4 dated 2015-12-10

Title: Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models
Description: Efficient approximate leave-one-out cross-validation (LOO) using Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct of the calculations, we also obtain approximate standard errors for estimated predictive errors, and for the comparison of predictive errors between models. We also compute the widely applicable information criterion (WAIC).
Author: Aki Vehtari [aut], Andrew Gelman [aut], Jonah Gabry [cre, aut], Juho Piironen [ctb], Ben Goodrich [ctb]
Maintainer: Jonah Gabry <jsg2201@columbia.edu>

Diff between loo versions 0.1.4 dated 2015-12-10 and 0.1.5 dated 2016-02-12

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New package noncompliance with initial version 0.1.1
Package: noncompliance
Type: Package
Title: Causal Inference in the Presence of Treatment Noncompliance Under the Binary Instrumental Variable Model
Version: 0.1.1
Date: 2016-02-11
Authors@R: c( person("Wen Wei", "Loh", email = "wloh@uw.edu", role = c("aut", "cre")), person("Thomas", "Richardson", role = "aut"))
Description: A finite-population significance test of the 'sharp' causal null hypothesis that treatment exposure X has no effect on final outcome Y, within the principal stratum of Compliers. A generalized likelihood ratio test statistic is used, and the resulting p-value is exact. Currently, it is assumed that there are only Compliers and Never Takers in the population.
Imports: data.table (>= 1.9.4), Rcpp (>= 0.12.1)
License: GPL (>= 3)
LazyData: TRUE
LinkingTo: Rcpp
RoxygenNote: 5.0.1
Suggests: testthat
URL: https://www.stat.washington.edu/~wloh/
NeedsCompilation: yes
Packaged: 2016-02-12 01:10:49 UTC; wloh
Author: Wen Wei Loh [aut, cre], Thomas Richardson [aut]
Maintainer: Wen Wei Loh <wloh@uw.edu>
Repository: CRAN
Date/Publication: 2016-02-12 07:41:04

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Package lme4 updated to version 1.1-11 with previous version 1.1-10 dated 2015-10-06

Title: Linear Mixed-Effects Models using 'Eigen' and S4
Description: Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".
Author: Douglas Bates [aut], Martin Maechler [aut], Ben Bolker [aut, cre], Steven Walker [aut], Rune Haubo Bojesen Christensen [ctb], Henrik Singmann [ctb], Bin Dai [ctb], Gabor Grothendieck [ctb], Peter Green [ctb]
Maintainer: Ben Bolker <bbolker+lme4@gmail.com>

Diff between lme4 versions 1.1-10 dated 2015-10-06 and 1.1-11 dated 2016-02-12

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Package FCMapper updated to version 1.1 with previous version 1.0 dated 2015-02-05

Title: Fuzzy Cognitive Mapping
Description: Provides several functions to create and manipulate fuzzy cognitive maps. It is based on 'FCMapper' for Excel, distributed at <http:// www.fcmappers.net/joomla/>, developed by Michael Bachhofer and Martin Wildenberg. Maps are inputted as adjacency matrices. Attributes of the maps and the equilibrium values of the concepts (including with user-defined constrained values) can be calculated. The maps can be graphed with a function that calls 'igraph'. Multiple maps with shared concepts can be aggregated.
Author: Shaun Turney and Michael Bachhofer
Maintainer: Shaun Turney <shaun.turney@mail.mcgill.ca>

Diff between FCMapper versions 1.0 dated 2015-02-05 and 1.1 dated 2016-02-12

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Thu, 11 Feb 2016

Package yhatr updated to version 0.13.9 with previous version 0.13.7 dated 2015-07-29

Title: R Binder for the Yhat API
Description: Deploy, maintain, and invoke models via the Yhat REST API.
Author: Greg Lamp <greg@yhathq.com>, Brandon Hopkins <dev@yhathq.com>
Maintainer: Greg Lamp <greg@yhathq.com>

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Package rstan updated to version 2.9.0-3 with previous version 2.9.0 dated 2016-01-05

Title: R Interface to Stan
Description: User-facing R functions are provided by this package to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via variational approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.
Author: Jiqiang Guo [aut], Daniel Lee [ctb], Krzysztof Sakrejda [ctb], Jonah Gabry [aut], Ben Goodrich [cre, aut], Joel de Guzman [cph] (Boost), Eric Niebler [cph] (Boost), Thomas Heller [cph] (Boost), John Fletcher [cph] (Boost)
Maintainer: Ben Goodrich <benjamin.goodrich@columbia.edu>

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Package oce updated to version 0.9-18 with previous version 0.9-17 dated 2015-05-22

Title: Analysis of Oceanographic Data
Description: Supports the analysis of Oceanographic data, including 'ADCP' measurements, measurements made with 'argo' floats, 'CTD' measurements, sectional data, sea-level time series, coastline and topographic data, etc. Provides specialized functions for calculating seawater properties such as potential temperature in either the 'UNESCO' or 'TEOS-10' equation of state. Produces graphical displays that conform to the conventions of the Oceanographic literature.
Author: Dan Kelley [aut, cre], Clark Richards [aut], Chantelle Layton [ctb, cph] (curl() coauthor), British Geological Survey [ctb, cph] (magnetic-field fortran subroutine)
Maintainer: Dan Kelley <Dan.Kelley@Dal.Ca>

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Package omics updated to version 0.1-4 with previous version 0.1-3 dated 2016-01-27

Title: '--omics' Data Analysis Toolbox
Description: A collection of functions to analyse '--omics' datasets such as DNA methylation and gene expression profiles.
Author: Gianluca Campanella [aut, cre]
Maintainer: Gianluca Campanella <gianluca@campanella.org>

Diff between omics versions 0.1-3 dated 2016-01-27 and 0.1-4 dated 2016-02-11

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Package geoknife updated to version 1.2.0 with previous version 1.1.3 dated 2016-01-20

Title: Web-Processing of Large Gridded Datasets
Description: Processes gridded datasets found on the U.S. Geological Survey Geo Data Portal web application or elsewhere, using a web-enabled workflow that eliminates the need to download and store large datasets that are reliably hosted on the Internet. The package provides access to several data subset and summarization algorithms that are available on remote web processing servers.
Author: Jordan Read [aut, cre], Jordan Walker [aut], Alison Appling [aut], David Blodgett [aut], Emily Read [aut], Luke Winslow [aut]
Maintainer: Jordan Read <jread@usgs.gov>

Diff between geoknife versions 1.1.3 dated 2016-01-20 and 1.2.0 dated 2016-02-11

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Permanent link

New package trackeR with initial version 0.0.1
Package: trackeR
Version: 0.0.1
Date: 2016-02-11
Title: Infrastructure for Running and Cycling Data from GPS-Enabled Tracking Devices
Authors@R: c(person(given = "Hannah", family = "Frick", role = c("aut", "cre"), email = "h.frick@ucl.ac.uk"), person(given = "Ioannis", family = "Kosmidis", role = "aut", email = "i.kosmidis@ucl.ac.uk"))
Description: The aim of this package is to provide infrastructure for handling running and cycling data from GPS-enabled tracking devices. After extraction and appropriate manipulation of the training or competition attributes, the data are placed into session-based and unit-aware data objects of class trackeRdata (S3 class). The information in the resultant data objects can then be visualised, summarised, and analysed through corresponding flexible and extensible methods.
Depends: R (>= 2.10.0), zoo
Imports: ggplot2
Suggests: plyr, XML, RSQLite, parallel, ggmap, scam, raster, testthat, fda
License: GPL-2 | GPL-3
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-02-11 21:04:07 UTC; frick
Author: Hannah Frick [aut, cre], Ioannis Kosmidis [aut]
Maintainer: Hannah Frick <h.frick@ucl.ac.uk>
Repository: CRAN
Date/Publication: 2016-02-12 00:49:43

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Package ssizeRNA updated to version 1.2.4 with previous version 1.1.2 dated 2015-05-12

Title: Sample Size Calculation for RNA-Seq Experimental Design
Description: We propose a procedure for sample size calculation while controlling false discovery rate for RNA-seq experimental design. Our procedure depends on the Voom method proposed for RNA-seq data analysis by Law et al. (2014) <DOI: 10.1186/gb-2014-15-2-r29> and the sample size calculation method proposed for microarray experiments by Liu and Hwang (2007) <DOI: 10.1093/bioinformatics/btl664>. We develop a set of functions that calculates appropriate sample sizes for two-sample t-test for RNA-seq experiments with fixed or varied set of parameters. The outputs also contain a plot of power versus sample size, a table of power at different sample sizes, and a table of critical test values at different sample sizes. To install this package, please use 'source("http://bioconductor.org/biocLite.R"); biocLite("ssizeRNA")'.
Author: Ran Bi [aut, cre], Peng Liu [aut], Tim Triche [ctb]
Maintainer: Ran Bi <biran@iastate.edu>

Diff between ssizeRNA versions 1.1.2 dated 2015-05-12 and 1.2.4 dated 2016-02-11

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New package SSDM with initial version 0.1.0
Package: SSDM
Type: Package
Title: Stacked Species Distribution Modelling
Version: 0.1.0
Date: 2016-02-12
Author: Sylvain Schmitt, Robin Pouteau, Dimitri Justeau, Philippe Birnbaum
Maintainer: Sylvain Schmitt <sylvain.schmitt@agroparistech.fr>
Description: Allows to map species richness and endemism based on stacked species distribution models (SSDM). Individuals SDMs can be created using a single or multiple algorithms (ensemble SDMs). For each species, an SDM can yield a habitat suitability map, a binary map, a between-algorithm variance map, and can assess variable importance, algorithm accuracy, and between- algorithm correlation. Methods to stack individual SDMs include summing individual probabilities and thresholding then summing. Thresholding can be based on a specific evaluation metric or by drawing repeatedly from a Bernoulli distribution. The SSDM package also provides a user-friendly interface.
License: GPL (>= 3) | file LICENSE
LazyData: TRUE
Imports: sp (>= 1.2.0), raster (>= 2.4.20), methods (>= 3.2.2), SDMTools (>= 1.1.221), mgcv (>= 1.8.7), earth (>= 4.4.3), rpart (>= 4.1.10), gbm (>= 2.1.1), randomForest (>= 4.6.10), dismo (>= 1.0.12), nnet (>= 7.3.10), e1071 (>= 1.6.7), shiny (>= 0.12.2), shinydashboard (>= 0.5.1), gplots (>= 0.1.0), spThin (>= 0.1.0)
Suggests: shinyFiles (>= 0.6.0)
Depends: R (>= 3.2.2)
Collate: 'Algorithm.SDM.R' 'Ensemble.SDM.R' 'Env.R' 'Occurrences.R' 'SSDM.R' 'Stacked.SDM.R' 'checkargs.R' 'ensemble.R' 'modelling.R' 'ensemble_modelling.R' 'gui.R' 'load_model.R' 'load_occ.R' 'load_var.R' 'plot.model.R' 'save.model.R' 'stack_modelling.R' 'stacking.R' 'update.stack.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2016-02-11 21:56:31 UTC; amap
Repository: CRAN
Date/Publication: 2016-02-12 00:55:58

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Package RSocrata updated to version 1.7.0-14 with previous version 1.6.2-10 dated 2015-07-13

Title: Download or Upload 'Socrata' Data Sets
Description: Provides easier interaction with Socrata open data portals http://dev.socrata.com. Users can provide a 'Socrata' data set resource URL, or a 'Socrata' Open Data API (SoDA) web query, or a 'Socrata' "human-friendly" URL, returns an R data frame. Converts dates to 'POSIX' format and manages throttling by 'Socrata'. Users can upload data to Socrata portals directly from R.
Author: Hugh Devlin, Ph. D., Tom Schenk, Jr., and John Malc
Maintainer: "Tom Schenk Jr." <developers@cityofchicago.org>

Diff between RSocrata versions 1.6.2-10 dated 2015-07-13 and 1.7.0-14 dated 2016-02-11

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More information about RSocrata at CRAN
Permanent link

New package rdatacite with initial version 0.1.0
Package: rdatacite
Type: Package
Title: 'DataCite' Client for 'OAI-PMH' Methods and their Search 'API'
Description: Client for the web service methods provided by 'DataCite' (<https://www.datacite.org/>), including functions to interface with their 'OAI-PMH' 'metadata' service, and a 'RESTful' search 'API'. The 'API' is backed by 'SOLR', allowing expressive queries, including faceting, statistics on variables, and 'more-like-this' queries.
Version: 0.1.0
License: MIT + file LICENSE
Authors@R: c(person("Scott", "Chamberlain", role = c("aut", "cre"), email = "myrmecocystus@gmail.com"))
URL: https://github.com/ropensci/rdatacite
BugReports: https://github.com/ropensci/rdatacite/issues
Imports: oai (>= 0.2.0), solrium (>= 0.3.0)
Suggests: knitr, testthat
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-02-11 23:02:31 UTC; sacmac
Author: Scott Chamberlain [aut, cre]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>
Repository: CRAN
Date/Publication: 2016-02-12 00:49:48

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Package MCMC.OTU updated to version 1.0.10 with previous version 1.0.8 dated 2014-05-05

Title: Bayesian Analysis of Multivariate Counts Data in DNA Metabarcoding and Ecology
Description: Poisson-lognormal generalized linear mixed model analysis of multivariate counts data using MCMC, aiming to infer the changes in relative proportions of individual variables. The package was originally designed for sequence-based analysis of microbial communities ("metabarcoding", variables = operational taxonomic units, OTUs), but can be used for other types of multivariate counts, such as in ecological applications (variables = species). The results are summarized and plotted using 'ggplot2' functions. Includes functions to remove sample and variable outliers and reformat counts into normalized log-transformed values for correlation and principal component/coordinate analysis. Walkthrough and examples: http://www.bio.utexas.edu/research/matz_lab/matzlab/Methods_files/walkthroughExample_mcmcOTU_R.txt.
Author: Mikhail V. Matz
Maintainer: Mikhail V. Matz <matz@utexas.edu>

Diff between MCMC.OTU versions 1.0.8 dated 2014-05-05 and 1.0.10 dated 2016-02-11

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Package lmerTest updated to version 2.0-30 with previous version 2.0-29 dated 2015-07-16

Title: Tests in Linear Mixed Effects Models
Description: Different kinds of tests for linear mixed effects models as implemented in 'lme4' package are provided. The tests comprise types I - III F tests for fixed effects, LR tests for random effects. The package also provides the calculation of population means for fixed factors with confidence intervals and corresponding plots. Finally the backward elimination of non-significant effects is implemented.
Author: Alexandra Kuznetsova [aut, cre], Per Bruun Brockhoff [aut, ths], Rune Haubo Bojesen Christensen [aut]
Maintainer: Alexandra Kuznetsova <alku@dtu.dk>

Diff between lmerTest versions 2.0-29 dated 2015-07-16 and 2.0-30 dated 2016-02-11

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Package LCMCR updated to version 0.4.1 with previous version 0.4 dated 2016-02-08

Title: Bayesian Nonparametric Latent-Class Capture-Recapture
Description: Bayesian population size estimation using non parametric latent-class models.
Author: Daniel Manrique-Vallier
Maintainer: Daniel Manrique-Vallier <dmanriqu@indiana.edu>

Diff between LCMCR versions 0.4 dated 2016-02-08 and 0.4.1 dated 2016-02-11

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Package CAvariants updated to version 3.1 with previous version 3.0 dated 2015-09-11

Title: Correspondence Analysis Variants
Description: Provides six variants of two-way correspondence analysis (ca): simple ca, singly ordered ca, doubly ordered ca, non-symmetrical ca, singly ordered non symmetrical ca, and doubly ordered non symmetrical ca.
Author: Rosaria Lombardo and Eric J Beh
Maintainer: Rosaria Lombardo <rosaria.lombardo@unina2.it>

Diff between CAvariants versions 3.0 dated 2015-09-11 and 3.1 dated 2016-02-11

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New package customizedTraining with initial version 1.0
Package: customizedTraining
Type: Package
Title: Customized Training for Lasso and Elastic-Net Regularized Generalized Linear Models
Version: 1.0
Date: 2016-02-11
Author: Scott Powers, Trevor Hastie, Robert Tibshirani
Maintainer: Scott Powers <sspowers@stanford.edu>
Imports: FNN, glmnet
Description: Customized training is a simple technique for transductive learning, when the test covariates are known at the time of training. The method identifies a subset of the training set to serve as the training set for each of a few identified subsets in the training set. This package implements customized training for the glmnet() and cv.glmnet() functions.
License: GPL-2
NeedsCompilation: no
Packaged: 2016-02-11 23:19:58 UTC; sspowers
Repository: CRAN
Date/Publication: 2016-02-12 01:02:34

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Package ARTP2 updated to version 0.9.22 with previous version 0.9.21 dated 2016-02-11

Title: Pathway and Gene-Level Association Test
Description: Pathway and gene level association test using raw data or summary statistics.
Author: Han Zhang, Bill Wheeler, Kai Yu, Yifan Yang
Maintainer: Han Zhang <han.zhang2@nih.gov>

Diff between ARTP2 versions 0.9.21 dated 2016-02-11 and 0.9.22 dated 2016-02-11

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New package AMCP with initial version 0.0.1
Package: AMCP
Type: Package
Title: A Multiple Comparison Perspective
Version: 0.0.1
Date: 2016-02-10
Authors@R: c(person(given="Scott", family="Maxwell", role = "aut"), person(given="Harold", family="Delaney", role = "aut"), person("Ken", "Kelley", role = c("aut", "cre"), email = "kkelley@nd.edu"))
Maintainer: Ken Kelley <kkelley@nd.edu>
Description: Accompanies "Designing Experiments and analyzing data: A model comparison perspective"" (3rd ed.) Maxwell, Delaney, & Kelley (forthcoming). This package contains all of the data sets in the book. Information about the book is available here <http://www.DesigningExperiments.com>.
License: GPL (>= 3)
NeedsCompilation: no
Packaged: 2016-02-11 16:40:17 UTC; kkelley
Author: Scott Maxwell [aut], Harold Delaney [aut], Ken Kelley [aut, cre]
Repository: CRAN
Date/Publication: 2016-02-12 01:05:21

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Package timedelay updated to version 1.0.2 with previous version 1.0.1 dated 2016-01-05

Title: Time Delay Estimation for Stochastic Time Series of Gravitationally Lensed Quasars
Description: We provide a toolbox to estimate the time delay between the brightness time series of gravitationally lensed quasar images via Bayesian and profile likelihood approaches. The model is based on a state-space representation for irregularly observed time series data generated from a latent continuous-time Ornstein-Uhlenbeck process. Our Bayesian method adopts scientifically motivated hyper-prior distributions and a Metropolis-Hastings within Gibbs sampler, producing posterior samples of the model parameters that include the time delay. A profile likelihood of the time delay is a simple approximation to the marginal posterior distribution of the time delay. Both Bayesian and profile likelihood approaches complement each other, producing almost identical results; the Bayesian way is more principled but the profile likelihood is easier to implement.
Author: Hyungsuk Tak, Kaisey Mandel, David A. van Dyk, Vinay L. Kashyap, Xiao-Li Meng, and Aneta Siemiginowska
Maintainer: Hyungsuk Tak <hyungsuk.tak@gmail.com>

Diff between timedelay versions 1.0.1 dated 2016-01-05 and 1.0.2 dated 2016-02-11

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Package RPPanalyzer updated to version 1.4.3 with previous version 1.4.1 dated 2015-06-24

Title: Reads, Annotates, and Normalizes Reverse Phase Protein Array Data
Description: Reads in sample description and slide description files and annotates the expression values taken from GenePix results files (text file format used by many microarray scanner and software providers). After normalization data can be visualized as boxplot, heatmap or dotplot.
Author: Heiko Mannsperger with contributions of Stephan Gade
Maintainer: Astrid Wachter <astrid.wachter@med.uni-goettingen.de>

Diff between RPPanalyzer versions 1.4.1 dated 2015-06-24 and 1.4.3 dated 2016-02-11

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Package emdbook updated to version 1.3.9 with previous version 1.3.8 dated 2015-05-01

Title: Support Functions and Data for "Ecological Models and Data"
Description: Auxiliary functions and data sets for "Ecological Models and Data", a book presenting maximum likelihood estimation and related topics for ecologists (ISBN 978-0-691-12522-0).
Author: Ben Bolker
Maintainer: Ben Bolker <bolker@mcmaster.ca>

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Package BSSasymp updated to version 1.1-2 with previous version 1.1-1 dated 2015-08-17

Title: Asymptotic Covariance Matrices of Some BSS Mixing and Unmixing Matrix Estimates
Description: Functions to compute the asymptotic covariance matrices of mixing and unmixing matrix estimates of the following blind source separation (BSS) methods: symmetric and squared symmetric FastICA, regular and adaptive deflation-based FastICA, FOBI, JADE, AMUSE and deflation-based and symmetric SOBI. Also functions to estimate these covariances based on data are available.
Author: Jari Miettinen, Klaus Nordhausen, Hannu Oja, Sara Taskinen
Maintainer: Jari Miettinen <jari.p.miettinen@jyu.fi>

Diff between BSSasymp versions 1.1-1 dated 2015-08-17 and 1.1-2 dated 2016-02-11

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Package BGPhazard updated to version 1.2.3 with previous version 1.2.2 dated 2015-03-17

Title: Markov Beta and Gamma Processes for Modeling Hazard Rates
Description: Computes the hazard rate estimate as described by Nieto-Barajas and Walker (2002) and Nieto-Barajas (2003).
Author: L. E. Nieto-Barajas and J. A. Garcia Bueno
Maintainer: Jose Antonio Garcia Bueno <joseagbueno@gmail.com>

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Package bbmle updated to version 1.0.18 with previous version 1.0.17 dated 2014-05-27

Title: Tools for General Maximum Likelihood Estimation
Description: Methods and functions for fitting maximum likelihood models in R. This package modifies and extends the 'mle' classes in the 'stats4' package.
Author: Ben Bolker <bolker@mcmaster.ca>, R Development Core Team
Maintainer: Ben Bolker <bolker@mcmaster.ca>

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Package AICcmodavg updated to version 2.0-4 with previous version 2.0-3 dated 2015-01-16

Title: Model Selection and Multimodel Inference Based on (Q)AIC(c)
Description: Functions to implement model selection and multimodel inference based on Akaike's information criterion (AIC) and the second-order AIC (AICc), as well as their quasi-likelihood counterparts (QAIC, QAICc) from various model object classes. The package implements classic model averaging for a given parameter of interest or predicted values, as well as a shrinkage version of model averaging parameter estimates or effect sizes. The package includes diagnostics and goodness-of-fit statistics for certain model types including those of 'unmarkedFit' classes estimating demographic parameters after accounting for imperfect detection probabilities. Some functions also allow the creation of model selection tables for Bayesian models of the 'bugs' and 'rjags' classes. Objects following model selection and multimodel inference can be formatted to LaTeX using 'xtable' methods included in the package.
Author: Marc J. Mazerolle <marc.mazerolle@sbf.ulaval.ca>.
Maintainer: Marc J. Mazerolle <marc.mazerolle@sbf.ulaval.ca>

Diff between AICcmodavg versions 2.0-3 dated 2015-01-16 and 2.0-4 dated 2016-02-11

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New package MDplot with initial version 0.2
Package: MDplot
Version: 0.2
Date: 2016-02-09
Authors@R: person( given = "Christian", family = "Margreitter", email = "christian.margreitter@gmail.com", role = c( "aut", "cre" ) )
Title: Visualizing Molecular Dynamics Analysis
Depends: R (>= 3.0.0), methods, MASS, RColorBrewer, gplots, gtools
Description: Provides automatization for plot generation succeeding common molecular dynamics analyses. This includes straightforward plots, such as RMSD (Root-Mean-Square-Deviation) and RMSF (Root-Mean-Square-Fluctuation) but also more sophisticated ones such as dihedral angle maps, hydrogen bonds, cluster bar plots and DSSP (Definition of Secondary Structure of Proteins) analysis.
License: GPL-3
LazyLoad: yes
Author: Christian Margreitter [aut, cre]
Maintainer: Christian Margreitter <christian.margreitter@gmail.com>
NeedsCompilation: no
Repository: CRAN
Packaged: 2016-02-11 13:08:27 UTC; margreitterc
Date/Publication: 2016-02-11 14:28:36

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Package svd updated to version 0.4 with previous version 0.3.3-2 dated 2014-03-07

Title: Interfaces to Various State-of-Art SVD and Eigensolvers
Description: R bindings to SVD and eigensolvers (PROPACK, nuTRLan).
Author: Anton Korobeynikov [aut, cre], Rasmus Munk Larsen [ctb, cph], Lawrence Berkeley National Laboratory [ctb, cph]
Maintainer: Anton Korobeynikov <anton@korobeynikov.info>

Diff between svd versions 0.3.3-2 dated 2014-03-07 and 0.4 dated 2016-02-11

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New package tweenr with initial version 0.1.2
Package: tweenr
Type: Package
Title: Interpolate Data for Smooth Animations
Version: 0.1.2
Date: 2016-02-11
Authors@R: c( person('Thomas Lin', 'Pedersen', , 'thomasp85@gmail.com', c('aut', 'cre')) )
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>
Description: In order to create smooth animation between states of data, tweening is necessary. This package provides a range of functions for creating tweened data that plugs right into functions such as gg_animate() from the 'gganimate' package. Furthermore it adds a number of vectorized interpolaters for common R data types such as numeric, date and colour.
URL: https://github.com/thomasp85/tweenr
BugReports: https://github.com/thomasp85/tweenr/issues
License: GPL (>= 2)
LazyData: TRUE
Imports: Rcpp (>= 0.12.3), grDevices
LinkingTo: Rcpp
Collate: 'RcppExports.R' 'aaa.R' 'tween_numeric.R' 'display_ease.R' 'interpolate.R' 'tween_colour.R' 'tween_datetime.R' 'tween_date.R' 'tween.R' 'tween_appear.R' 'tween_constant.R' 'tween_elements.R' 'tween_states.R' 'tweenr_package.R'
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-02-11 10:36:27 UTC; Thomas
Author: Thomas Lin Pedersen [aut, cre]
Repository: CRAN
Date/Publication: 2016-02-11 12:23:39

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Package starma updated to version 1.3 with previous version 1.2 dated 2015-11-12

Title: Modelling Space Time AutoRegressive Moving Average (STARMA) Processes
Description: Statistical functions to identify, estimate and diagnose a Space-Time AutoRegressive Moving Average (STARMA) model.
Author: Felix Cheysson
Maintainer: Felix Cheysson <felix@cheysson.fr>

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Package sjmisc updated to version 1.5 with previous version 1.4 dated 2016-01-13

Title: Data Transformation and Labelled Data Utility Functions
Description: Collection of miscellaneous utility functions (especially intended for people coming from other statistical software packages like 'SPSS', and/ or who are new to R), supporting following common tasks: 1) Reading and writing data between R and other statistical software packages like 'SPSS', 'SAS' or 'Stata' and working with labelled data; this includes easy ways to get and set label attributes, to convert labelled vectors into factors (and vice versa), or to deal with multiple declared missing values etc. 2) Data transformation tasks like recoding, dichotomizing or grouping variables, setting and replacing missing values. 3) Convenient functions to perform frequently used statistical tests, or to calculate various commonly used statistical coefficients.
Author: Daniel Lüdecke <d.luedecke@uke.de>
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package seasonal updated to version 1.2.1 with previous version 1.2.0 dated 2016-01-28

Title: R Interface to X-13-ARIMA-SEATS
Description: Easy-to-use interface to X-13-ARIMA-SEATS, the seasonal adjustment software by the US Census Bureau. It offers full access to almost all options and outputs of X-13, including X-11 and SEATS, automatic ARIMA model search, outlier detection and support for user defined holiday variables, such as Chinese New Year or Indian Diwali. It also includes a Shiny-based graphical user interface. Seasonal uses the X-13 binaries from the 'x13binary' package.
Author: Christoph Sax
Maintainer: Christoph Sax <christoph.sax@gmail.com>

Diff between seasonal versions 1.2.0 dated 2016-01-28 and 1.2.1 dated 2016-02-11

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Package npregfast updated to version 1.2.0 with previous version 1.0.1 dated 2015-11-16

Title: Nonparametric Estimation of Regression Models with Factor-by-Curve Interactions
Description: A method for obtain nonparametric estimates of regression models with or without factor-by-curve interactions using local polynomial kernel smoothers. Additionally, a parametric model (allometric model) can be estimated.
Author: Marta Sestelo [aut, cre], Nora M. Villanueva [aut], Javier Roca-Pardinas [aut]
Maintainer: Marta Sestelo <sestelo@uvigo.es>

Diff between npregfast versions 1.0.1 dated 2015-11-16 and 1.2.0 dated 2016-02-11

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Package kintone (with last version 0.1.1) was removed from CRAN

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

2014-03-22 0.1.1
2014-03-09 0.1

Permanent link
Package Taxonstand updated to version 1.8 with previous version 1.7 dated 2014-12-15

Title: Taxonomic Standardization of Plant Species Names
Description: Automated standardization of taxonomic names and removal of orthographic errors in plant species names using 'The Plant List' website (www.theplantlist.org).
Author: Luis Cayuela, Jari Oksanen
Maintainer: Luis Cayuela <luis.cayuela@urjc.es>

Diff between Taxonstand versions 1.7 dated 2014-12-15 and 1.8 dated 2016-02-11

 DESCRIPTION  |    8 ++++----
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Package VarfromPDB updated to version 2.0.5 with previous version 1.1.0 dated 2015-12-21

Title: Capture the Genes and Variants Related to a Genetic Disease from Public Databases
Description: Captures and compiles the genes and variants related to a disease, a phenotype or a clinical feature based on the public databases including HPO (Human Phenotype Ontology, http://human-phenotype-ontology.github.io/about.html), Orphanet (http://www.orpha.net/consor/cgi-bin/index.php), OMIM (Online Mendelian Inheritance in Man, http://www.omim.org), ClinVar (http://www.ncbi.nlm.nih.gov/clinvar), and Uniprot (Universal Protein Resource, http://www.uniprot.org) and Pubmed. HPO provides a standardized vocabulary of phenotypic abnormalities encountered in human disease. HPO currently contains approximately 11,000 terms and over 115,000 annotations to hereditary diseases. Orphanet is the reference portal for information on rare diseases and orphan drugs, whose aim is to help improve the diagnosis, care and treatment of patients with rare diseases. OMIM is a continuously updated catalog of human genes and genetic disorders and traits, with particular focus on the molecular relationship between genetic variation and phenotypic expression. ClinVar is a freely accessible, public archive of reports of the relationships among human variations and phenotypes, with supporting evidence. Uniprot focuses on amino acid altering variants imported from Ensembl Variation databases. For Homo sapiens, the variants including human polymorphisms and disease mutations in the Uniprot are manually curated from UniProtKB/Swiss-Prot.
Author: Zongfu Cao
Maintainer: Zongfu Cao <caozongfu@gmail.com>

Diff between VarfromPDB versions 1.1.0 dated 2015-12-21 and 2.0.5 dated 2016-02-11

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Package SpatPCA updated to version 1.1.1.0 with previous version 1.1.0.0 dated 2015-11-01

Title: Regularized Principal Component Analysis for Spatial Data
Description: Provide regularized principal component analysis incorporating smoothness, sparseness and orthogonality of eigenfunctions by using the alternating direction method of multipliers algorithm. The method can be applied to either regularly or irregularly spaced data.
Author: Wen-Ting Wang and Hsin-Cheng Huang
Maintainer: Wen-Ting Wang <egpivo@gmail.com>

Diff between SpatPCA versions 1.1.0.0 dated 2015-11-01 and 1.1.1.0 dated 2016-02-11

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New package spacom with initial version 1.0-5
Package: spacom
Type: Package
Title: Spatially Weighted Context Data for Multilevel Modelling
Version: 1.0-5
Date: 2016-02-10
Authors@R: c(person("Till", "Junge", role = c("aut", "cre"), email = "till.junge@altermail.ch"), person("Sandra", "Penic", role = "aut", email = "sandra.penic@unil.ch"), person("Mathieu", "Cossuta", role = "aut", email = "mcossutta@gmail.com"), person("Guy", "Elcheroth", role = "aut", email = "guy.elcheroth@unil.ch"), person("Stephanie", "Glaeser", role = "ctb", email = "stephanie.glaeser@unil.ch"), person("Davide", "Morselli", role = "ctb", email = "davide.morselli@unil.ch"))
Description: Provides tools to construct and exploit spatially weighted context data. Spatial weights are derived by a Kernel function from a user-defined matrix of distances between contextual units. Spatial weights can then be applied either to precise contextual measures or to aggregate estimates based on micro-level survey data, to compute spatially weighted context data. Available aggregation functions include indicators of central tendency, dispersion, or inter-group variability, and take into account survey design weights. The package further allows combining the resulting spatially weighted context data with individual-level predictor and outcome variables, for the purposes of multilevel modelling. An ad hoc stratified bootstrap resampling procedure generates robust point estimates for multilevel regression coefficients and model fit indicators, and computes confidence intervals adjusted for measurement dependency and measurement error of aggregate estimates. As an additional feature, residual and explained spatial dependency can be estimated for the tested models.
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 2.3.2)
Imports: methods, spdep, foreach, iterators, lme4, nlme, Matrix
Collate: all_classes.R common.R moran.R SpawML.R Descriptives.R ResExSpawML.R ResAggSpawML.R Weights.R ExplorSpawML.R
NeedsCompilation: no
Packaged: 2016-02-11 00:53:01 UTC; junge
Author: Till Junge [aut, cre], Sandra Penic [aut], Mathieu Cossuta [aut], Guy Elcheroth [aut], Stephanie Glaeser [ctb], Davide Morselli [ctb]
Maintainer: Till Junge <till.junge@altermail.ch>
Repository: CRAN
Date/Publication: 2016-02-11 08:27:52

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New package serial with initial version 1.1
Package: serial
Type: Package
Title: The Serial Interface Package
Version: 1.1
Date: 2016-02-04
Author: Martin Seilmayer
Maintainer: Martin Seilmayer <m.seilmayer@hzdr.de>
Description: Provides functionality for the use of the internal hardware RS232/RS422/RS485 or any other virtual serial interfaces of the computer.
Depends: R (>= 2.15.0)
License: GPL-2
RoxygenNote: 5.0.1
Packaged: 2016-02-11 06:37:12 UTC; ms5760
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2016-02-11 08:52:54

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Package rcbalance updated to version 1.8.2 with previous version 1.8.0 dated 2015-12-14

Title: Large, Sparse Optimal Matching with Refined Covariate Balance
Description: Tools for large, sparse optimal matching of treated units and control units in observational studies. Provisions are made for refined covariate balance constraints, which include fine and near-fine balance as special cases. Matches are optimal in the sense that they are computed as solutions to network optimization problems rather than greedy algorithms.
Author: Samuel D. Pimentel
Maintainer: Samuel D. Pimentel <spi@wharton.upenn.edu>

Diff between rcbalance versions 1.8.0 dated 2015-12-14 and 1.8.2 dated 2016-02-11

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More information about rcbalance at CRAN
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Package MCMCpack updated to version 1.3-4 with previous version 1.3-3 dated 2013-05-01

Title: Markov Chain Monte Carlo (MCMC) Package
Description: Contains functions to perform Bayesian inference using posterior simulation for a number of statistical models. Most simulation is done in compiled C++ written in the Scythe Statistical Library Version 1.0.3. All models return coda mcmc objects that can then be summarized using the coda package. Some useful utility functions such as density functions, pseudo-random number generators for statistical distributions, a general purpose Metropolis sampling algorithm, and tools for visualization are provided.
Author: Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park
Maintainer: Jong Hee Park <jongheepark@snu.ac.kr>

Diff between MCMCpack versions 1.3-3 dated 2013-05-01 and 1.3-4 dated 2016-02-11

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Package EnsembleBase updated to version 1.0.1 with previous version 1.0.0 dated 2016-01-18

Title: Extensible Package for Parallel, Batch Training of Base Learners for Ensemble Modeling
Description: Extensible S4 classes and methods for batch training of regression and classification algorithms such as Random Forest, Gradient Boosting Machine, Neural Network, Support Vector Machines, K-Nearest Neighbors, Penalized Regression (L1/L2), and Bayesian Additive Regression Trees. These algorithms constitute a set of 'base learners', which can subsequently be combined together to form ensemble predictions. This package provides cross-validation wrappers to allow for downstream application of ensemble integration techniques, including best-error selection. All base learner estimation objects are retained, allowing for repeated prediction calls without the need for re-training. For large problems, an option is provided to save estimation objects to disk, along with prediction methods that utilize these objects. This allows users to train and predict with large ensembles of base learners without being constrained by system RAM.
Author: Alireza S. Mahani, Mansour T.A. Sharabiani
Maintainer: Alireza S. Mahani <alireza.mahani@sentrana.com>

Diff between EnsembleBase versions 1.0.0 dated 2016-01-18 and 1.0.1 dated 2016-02-11

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New package ARTP2 with initial version 0.9.21
Package: ARTP2
Type: Package
Title: Pathway and Gene-Level Association Test
Version: 0.9.21
Date: 2016-02-10
Author: Han Zhang, Bill Wheeler, Kai Yu, Yifan Yang
Maintainer: Han Zhang <han.zhang2@nih.gov>
Depends: R (>= 2.10), parallel, Formula, data.table, stats, utils
Description: Pathway and gene level association test using raw data or summary statistics.
License: GPL-2 | GPL-3
URL: https://github.com/zhangh12/ARTP2
NeedsCompilation: yes
Packaged: 2016-02-11 03:44:55 UTC; zhangh12
Repository: CRAN
Date/Publication: 2016-02-11 08:27:33

More information about ARTP2 at CRAN
Permanent link

Wed, 10 Feb 2016

Package VNM updated to version 4.1 with previous version 4.0 dated 2015-02-09

Title: Using V-algorithm and Newton-Raphson Method to Obtain Multiple-objective Optimal Design
Description: Using V-algorithm and Newton-Raphson method to obtain multiple-objective optimal design for estimating the shape of dose-response, the ED50 (the dose producing an effect midway between the expected responses at the extreme doses) and the MED (the minimum effective dose level) for the 2,3,4-parameter logistic models and for evaluating its efficiencies for the three objectives.
Author: Seung Won Hyun, Weng Kee Wong, and Yarong Yang
Maintainer: Yarong Yang <Yarong.Yang@ndsu.edu>

Diff between VNM versions 4.0 dated 2015-02-09 and 4.1 dated 2016-02-10

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New package titrationCurves with initial version 0.1.0
Package: titrationCurves
Type: Package
Title: Acid/Base, Complexation, Redox, and Precipitation Titration Curves
Version: 0.1.0
Date: 2016-02-09
Authors@R: person("David","Harvey", email = "harvey@depauw.edu", role = c("aut", "cre"))
Maintainer: David Harvey <harvey@depauw.edu>
Description: A collection of functions to plot acid/base titration curves (pH vs. volume of titrant), complexation titration curves (pMetal vs. volume of EDTA), redox titration curves (potential vs.volume of titrant), and precipitation titration curves (either pAnalyte or pTitrant vs. volume of titrant). Options include the titration of mixtures, the ability to overlay two or more titration curves, and the ability to show equivalence points.
License: GPL-2
LazyData: TRUE
RoxygenNote: 5.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2016-02-10 20:42:24 UTC; davidharvey
Author: David Harvey [aut, cre]
Repository: CRAN
Date/Publication: 2016-02-11 00:49:16

More information about titrationCurves at CRAN
Permanent link

Package pxweb updated to version 0.6.0 with previous version 0.5.57 dated 2015-07-14

Title: R Interface to the PX-Web/PC-Axis API
Description: Generic interface for the PX-Web/PC-Axis API. The PX-Web/PC-Axis API is used by organizations such as Statistics Sweden and Statistics Finland to disseminate data. The R package can interact with all PX-Web/PC-Axis APIs to fetch information about the data hierarchy, extract metadata and extract and parse statistics to R data.frame format. PX-Web is a solution to disseminate PC-Axis data files in dynamic tables on the web. Since 2013 PX-Web contains an API to disseminate PC-Axis files.
Author: Mans Magnusson, Leo Lahti, Love Hansson
Maintainer: Mans Magnusson <mons.magnusson@gmail.com>

Diff between pxweb versions 0.5.57 dated 2015-07-14 and 0.6.0 dated 2016-02-10

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More information about pxweb at CRAN
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Package monomvn updated to version 1.9-6 with previous version 1.9-5 dated 2014-05-21

Title: Estimation for Multivariate Normal and Student-t Data with Monotone Missingness
Description: Estimation of multivariate normal and student-t data of arbitrary dimension where the pattern of missing data is monotone. Through the use of parsimonious/shrinkage regressions (plsr, pcr, lasso, ridge, etc.), where standard regressions fail, the package can handle a nearly arbitrary amount of missing data. The current version supports maximum likelihood inference and a full Bayesian approach employing scale-mixtures for Gibbs sampling. Monotone data augmentation extends this Bayesian approach to arbitrary missingness patterns. A fully functional standalone interface to the Bayesian lasso (from Park & Casella), Normal-Gamma (from Griffin & Brown), Horseshoe (from Carvalho, Polson, & Scott), and ridge regression with model selection via Reversible Jump, and student-t errors (from Geweke) is also provided.
Author: Robert B. Gramacy <rbgramacy@chicagobooth.edu>
Maintainer: Robert B. Gramacy <rbgramacy@chicagobooth.edu>

Diff between monomvn versions 1.9-5 dated 2014-05-21 and 1.9-6 dated 2016-02-10

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 NAMESPACE               |    9 ++++-
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New package ionr with initial version 0.3.0
Package: ionr
Type: Package
Title: Test for Indifference of Indicator
Version: 0.3.0
Date: 2016-10-02
Author: Uku Vainik <ukuvainik@gmail.com>, Rene Mottus <rene.mottus@ed.ac.uk>
Maintainer: Uku Vainik <ukuvainik@gmail.com>
Depends: R (>= 3.0)
Imports: gplots, psych
Suggests: lavaan
Description: Provides item exclusion procedure, which is a formal method to test 'Indifference Of iNdicator' (ION). When a latent personality trait-outcome association is assumed, then the association strength should not depend on which subset of indicators (i.e. items) has been chosen to reflect the trait. Personality traits are often measured (reflected) by a sum-score of a certain set of indicators. Item exclusion procedure randomly excludes items from a sum-score and tests, whether the sum-score - outcome correlation changes. ION has been achieved, when any item can be excluded from the sum-score without the sum-score - outcome correlation substantially changing . For more details, see Vainik, Mottus et. al, (2015) "Are Trait-Outcome Associations Caused by Scales or Particular Items? Example Analysis of Personality Facets and BMI",European Journal of Personality DOI: <10.1002/per.2009> .
License: GPL (>= 2)
NeedsCompilation: no
LazyData: TRUE
RoxygenNote: 5.0.1
Encoding: UTF-8
URL: www.ut.ee/uku.vainik/ion/
Packaged: 2016-02-10 20:16:09 UTC; uku
Repository: CRAN
Date/Publication: 2016-02-11 00:47:11

More information about ionr at CRAN
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Package x13binary updated to version 0.1.1 with previous version 0.1.0 dated 2016-01-19

Title: Provide the 'x13ashtml' Seasonal Adjustment Binary
Description: The US Census provides a seasonal adjustment program now called 'X-13ARIMA-SEATS' building on both earlier Census programs called X-11 and X-12 as well as the SEATS program by the Bank of Spain. Census offers both source and binary versions -- which this package integrates for use by other R packages.
Author: Dirk Eddelbuettel and Christoph Sax
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between x13binary versions 0.1.0 dated 2016-01-19 and 0.1.1 dated 2016-02-10

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Package TRADER updated to version 1.2-1 with previous version 1.2-0 dated 2015-11-20

Title: Tree Ring Analysis of Disturbance Events in R
Description: Tree Ring Analysis of Disturbance Events in R (TRADER) package provides only one way for disturbance reconstruction from tree-ring data.
Author: Pavel Fibich <pavel.fibich@prf.jcu.cz>, Jan Altman <altman.jan@gmail.com>, Tuomas Aakala <tuomas.aakala@helsinki.fi>, Jiri Dolezal <jiriddolezal@gmail.com>
Maintainer: Pavel Fibich <pavel.fibich@prf.jcu.cz>

Diff between TRADER versions 1.2-0 dated 2015-11-20 and 1.2-1 dated 2016-02-10

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 4 files changed, 60 insertions(+), 21 deletions(-)

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Package psData updated to version 0.2 with previous version 0.1.2 dated 2014-02-23

Title: Download Regularly Maintained Political Science Data Sets
Description: This R package includes functions for gathering commonly used and regularly maintained data set in political science. It also includes functions for combining components from these data sets into variables that have been suggested in the literature, but are not regularly maintained.
Author: Christopher Gandrud
Maintainer: Christopher Gandrud <christopher.gandrud@gmail.com>

Diff between psData versions 0.1.2 dated 2014-02-23 and 0.2 dated 2016-02-10

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More information about psData at CRAN
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Package pan updated to version 1.4 with previous version 1.3 dated 2015-02-10

Title: Multiple Imputation for Multivariate Panel or Clustered Data
Description: Multiple imputation for multivariate panel or clustered data.
Author: Original by Joseph L. Schafer
Maintainer: Jing hua Zhao <jinghua.zhao@mrc-epid.cam.ac.uk>

Diff between pan versions 1.3 dated 2015-02-10 and 1.4 dated 2016-02-10

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More information about pan at CRAN
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New package npmr with initial version 1.0
Package: npmr
Type: Package
Title: Nuclear Penalized Multinomial Regression
Version: 1.0
Date: 2016-02-09
Author: Scott Powers, Trevor Hastie, Robert Tibshirani
Maintainer: Scott Powers <sspowers@stanford.edu>
Description: Fit multinomial logistic regression with a penalty on the nuclear norm of the estimated regression coefficient matrix, using proximal gradient descent.
License: GPL-2
Packaged: 2016-02-10 11:28:12 UTC; sspowers
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2016-02-10 18:57:25

More information about npmr at CRAN
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New package mvnTest with initial version 1.1-0
Package: mvnTest
Version: 1.1-0
Authors@R: c(person("Natalya", "Pya", role = c("aut", "cre"), email = "nat.pya@gmail.com"), person("Vassilly", "Voinov", role = "aut", email = "voinovv@kimep.kz"), person("Rashid", "Makarov", role = "aut", email = "rashidm@kimep.kz"), person("Yevgeniy", "Voinov", role = "aut", email = "v.yevgeniy@yahoo.com"))
Author: Natalya Pya [aut, cre], Vassilly Voinov [aut], Rashid Makarov [aut], Yevgeniy Voinov [aut]
Maintainer: Natalya Pya <nat.pya@gmail.com>
Title: Goodness of Fit Tests for Multivariate Normality
Date: 2016-01-25
Description: Routines for assessing multivariate normality. Implements three Wald's type chi-squared tests; non-parametric Anderson-Darling and Cramer-von Mises tests; Doornik-Hansen test, Royston test and Henze-Zirkler test.
Depends: R (>= 2.15.0), mvtnorm
Imports: methods, stats, graphics, MASS
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2016-02-10 08:54:01 UTC; natalya
Repository: CRAN
Date/Publication: 2016-02-10 18:57:23

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Package gaston updated to version 1.4 with previous version 1.3.1 dated 2015-12-14

Title: Genetic Data Manipulation (Quality Control, GRM and LD Computations, PCA), Linear Mixed Models (AIREML Algorithm), Association Testing
Description: Manipulation of genetic data (SNPs), computation of Genetic Relationship Matrix, Linkage Disequilibrium, etc. Efficient algorithms for Linear Mixed Model (AIREML, diagonalization trick).
Author: Hervé Perdry & Claire Dandine-Roulland
Maintainer: Hervé Perdry <herve.perdry@u-psud.fr>

Diff between gaston versions 1.3.1 dated 2015-12-14 and 1.4 dated 2016-02-10

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New package GetTDData with initial version 1.0
Package: GetTDData
Title: Get Data for Brazilian Bonds (Tesouro Direto)
Version: 1.0
Authors@R: person("Marcelo", "Perlin", email = "marceloperlin@gmail.com", role = c("aut", "cre"))
Description: Downloads and aggregates data for Brazilian government issued bonds directly from the website of Tesouro Direto <http://www.tesouro.fazenda.gov.br/tesouro-direto-balanco-e-estatisticas>.
Depends: R (>= 3.2.3)
Imports: stringr,xlsx,utils,stats
License: GPL-2
LazyData: true
RoxygenNote: 5.0.1
Suggests: knitr, rmarkdown, testthat, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2016-02-10 10:34:54 UTC; Marcelo
Author: Marcelo Perlin [aut, cre]
Maintainer: Marcelo Perlin <marceloperlin@gmail.com>
Repository: CRAN
Date/Publication: 2016-02-10 18:57:02

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Package fractional updated to version 0.1.2 with previous version 0.1.1 dated 2016-02-08

Title: Vulgar Fractions in R
Description: The main function of this package allows numerical vector objects to be displayed with their values in vulgar fractional form. This is convenient if patterns can then be more easily detected. In some cases replacing the components of a numeric vector by a rational approximation can also be expected to remove some component of round-off error. The main functions form a re-implementation of the functions 'fractions' and 'rational' of the MASS package, but using a radically improved programming strategy.
Author: Bill Venables
Maintainer: Bill Venables <bill.venables@gmail.com>

Diff between fractional versions 0.1.1 dated 2016-02-08 and 0.1.2 dated 2016-02-10

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 vignettes/Vulgar_Fractions_in_R.Rmd |    2 +-
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New package exploreR with initial version 0.1
Package: exploreR
Type: Package
Title: Tools for Quickly Exploring Data
Version: 0.1
Date: 2016-02-10
Authors@R: person("Michael", "Coates", email = "azhain@gmail.com", role = c("aut", "cre"))
Description: Simplifies some complicated and labor intensive processes involved in exploring and explaining data. Allows you to quickly and efficiently visualize the interaction between variables and simplifies the process of discovering covariation in your data. Also includes some convenience features designed to remove as much redundant typing as possible.
Depends: R (>= 3.2.3)
License: GPL-3
LazyData: TRUE
RoxygenNote: 5.0.1
Imports: ggplot2, grDevices, stats
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2016-02-10 15:16:40 UTC; Michael
Author: Michael Coates [aut, cre]
Maintainer: Michael Coates <azhain@gmail.com>
Repository: CRAN
Date/Publication: 2016-02-10 18:57:17

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Package dendextend updated to version 1.1.8 with previous version 1.1.2 dated 2015-10-31

Title: Extending R's Dendrogram Functionality
Description: Offers a set of functions for extending dendrogram objects in R, letting you visualize and compare trees of hierarchical clusterings. You can (1) Adjust a tree's graphical parameters - the color, size, type, etc of its branches, nodes and labels. (2) Visually and statistically compare different dendrograms to one another.
Author: Tal Galili [aut, cre, cph] (http://www.r-statistics.com), Gavin Simpson [ctb], Gregory Jefferis [aut, ctb] (imported code from his dendroextras package), Marco Gallotta [ctb] (a.k.a: marcog), Johan Renaudie [ctb] (https://github.com/plannapus), The R Core Team [ctb] (Thanks for the Infastructure, and code in the examples), Kurt Hornik [ctb], Uwe Ligges [ctb], Andrej-Nikolai Spiess [ctb], Steve Horvath [ctb], Peter Langfelder [ctb], skullkey [ctb], Mark Van Der Loo [ctb] (https://github.com/markvanderloo d3dendrogram), Andrie de Vries [ctb] (ggdendro author), Zuguang Gu [ctb] (circlize author), Yoav Benjamini [ths]
Maintainer: Tal Galili <tal.galili@gmail.com>

Diff between dendextend versions 1.1.2 dated 2015-10-31 and 1.1.8 dated 2016-02-10

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 171 files changed, 9281 insertions(+), 8342 deletions(-)

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New package codingMatrices with initial version 0.1.1
Package: codingMatrices
Type: Package
Title: Alternative Coding Matrices for Factors in Linear Model Formulae
Version: 0.1.1
Author: Bill Venables
Maintainer: Bill Venables <Bill.Venables@gmail.com>
Description: A collection of coding functions as alternatives to the standard functions in the stats package, which have names starting with 'contr.'. Their main advantage is that they provide a consistent method for defining marginal effects in multi-way factorial models. In a simple one-way ANOVA model the intercept term is always the simple average of the class means.
Depends: stats
Imports: Matrix, methods, fractional
Suggests: MASS
License: GPL (>= 2)
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-02-10 12:41:08 UTC; Bill
Repository: CRAN
Date/Publication: 2016-02-10 18:57:08

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Package blockseg updated to version 0.2 with previous version 0.1 dated 2016-01-15

Title: Two Dimensional Change-Points Detection
Description: Segments a matrix in blocks with constant values.
Author: Julien Chiquet [aut, cre], Vincent Brault [aut]
Maintainer: Julien Chiquet <julien.chiquet@gmail.com>

Diff between blockseg versions 0.1 dated 2016-01-15 and 0.2 dated 2016-02-10

 DESCRIPTION               |    8 -
 MD5                       |   16 +-
 R/blockseg.R              |    2 
 R/stabsel-class.R         |  251 +++++++++++++++++++++-------------------------
 R/stabsel.R               |    2 
 man/blockSeg-proc.Rd      |    2 
 man/evolution.Rd          |    9 -
 man/plot.stab.blockSeg.Rd |   13 +-
 man/stab.blockSeg.Rd      |    4 
 9 files changed, 147 insertions(+), 160 deletions(-)

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Package tikzDevice updated to version 0.10-1 with previous version 0.10 dated 2016-02-06

Title: R Graphics Output in LaTeX Format
Description: Provides a graphics output device for R that records plots in a LaTeX-friendly format. The device transforms plotting commands issued by R functions into LaTeX code blocks. When included in a LaTeX document, these blocks are interpreted with the help of 'TikZ'---a graphics package for TeX and friends written by Till Tantau. Using the 'tikzDevice', the text of R plots can contain LaTeX commands such as mathematical formula. The device also allows arbitrary LaTeX code to be inserted into the output stream.
Author: Charlie Sharpsteen [aut], Cameron Bracken [aut], Kirill Müller [ctb, cre], Yihui Xie [ctb]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

Diff between tikzDevice versions 0.10 dated 2016-02-06 and 0.10-1 dated 2016-02-10

 DESCRIPTION                     |    8 +--
 MD5                             |   22 +++++-----
 NEWS.md                         |    6 ++
 inst/doc/tikzDevice.pdf         |binary
 src/tikzDevice.c                |    2 
 vignettes/figs/annotation.tex   |   86 +++++++++++++++++-----------------------
 vignettes/figs/latexEx.tex      |   80 ++++++++++++++++++-------------------
 vignettes/figs/pdf-example.pdf  |binary
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 vignettes/figs/titlePlot.tex    |    2 
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 12 files changed, 103 insertions(+), 109 deletions(-)

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New package solrium with initial version 0.3.0
Package: solrium
Title: General Purpose R Interface to 'Solr'
Description: Provides a set of functions for querying and parsing data from 'Solr' (<http://lucene.apache.org/solr>) 'endpoints' (local and remote), including search, 'faceting', 'highlighting', 'stats', and 'more like this'. In addition, some functionality is included for creating, deleting, and updating documents in a 'Solr' 'database'.
Version: 0.3.0
Authors@R: person("Scott", "Chamberlain", role = c("aut", "cre"), email = "myrmecocystus@gmail.com")
License: MIT + file LICENSE
URL: https://github.com/ropensci/solrium
BugReports: http://www.github.com/ropensci/solrium/issues
VignetteBuilder: knitr
Imports: stats, utils, methods, dplyr, plyr, httr (>= 1.0.0), XML, jsonlite
Suggests: testthat, knitr
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-02-09 20:28:53 UTC; sacmac
Author: Scott Chamberlain [aut, cre]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>
Repository: CRAN
Date/Publication: 2016-02-10 09:11:27

More information about solrium at CRAN
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