Wed, 15 Mar 2017

Package SIBER updated to version 2.1.2 with previous version 2.1.0 dated 2017-02-22

Title: Stable Isotope Bayesian Ellipses in R
Description: Fits bi-variate ellipses to stable isotope data using Bayesian inference with the aim being to describe and compare their isotopic niche.
Author: Andrew Jackson and Andrew Parnell
Maintainer: Andrew Jackson <a.jackson@tcd.ie>

Diff between SIBER versions 2.1.0 dated 2017-02-22 and 2.1.2 dated 2017-03-15

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Package SGPdata updated to version 16.0-0.0 with previous version 15.0-0.0 dated 2017-02-20

Title: Exemplar Data Sets for SGP Analyses
Description: Data sets utilized by the SGP Package as exemplars for users to conduct their own SGP analyses.
Author: Damian W. Betebenner [aut, cre], Adam Van Iwaarden [aut], Ben Domingue [aut]
Maintainer: Damian W. Betebenner <dbetebenner@nciea.org>

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Package qqman updated to version 0.1.4 with previous version 0.1.2 dated 2014-09-25

Title: Q-Q and Manhattan Plots for GWAS Data
Description: Create Q-Q and manhattan plots for GWAS data from PLINK results.
Author: Stephen Turner <vustephen@gmail.com>
Maintainer: Stephen Turner <vustephen@gmail.com>

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Package MDMR updated to version 0.5.0 with previous version 0.4.3 dated 2016-09-19

Title: Multivariate Distance Matrix Regression
Description: Allows a user to conduct multivariate distance matrix regression using analytic p-values and compute measures of effect size.
Author: Daniel B. McArtor (dmcartor@nd.edu) [aut, cre]
Maintainer: Daniel B. McArtor <dmcartor@nd.edu>

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Package ipft updated to version 0.3.1 with previous version 0.2.8 dated 2017-03-02

Title: Indoor Positioning Fingerprinting Toolset
Description: Algorithms and utility functions for indoor positioning using fingerprinting techniques. These functions are designed for manipulation of RSSI (Received Signal Strength Intensity) data sets, estimation of positions,comparison of the performance of different models, and graphical visualization of data. Machine learning algorithms and methods such as k-nearest neighbors or probabilistic fingerprinting are implemented in this package to perform analysis and estimations over RSSI data sets.
Author: Emilio Sansano
Maintainer: Emilio Sansano <esansano@uji.es>

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Package biosignalEMG updated to version 2.0.1 with previous version 2.0.0 dated 2015-08-05

Title: Tools for Electromyogram Signals (EMG) Analysis
Description: Data processing tools to compute the rectified, integrated and the averaged EMG. Routines for automatic detection of activation phases. A routine to compute and plot the ensemble average of the EMG. An EMG signal simulator for general purposes.
Author: J.A. Guerrero, J.E. Macias-Diaz
Maintainer: Antonio Guerrero <jaguerrero@correo.uaa.mx>

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Package sparsebn updated to version 0.0.4 with previous version 0.0.3 dated 2017-03-12

Title: Learning Sparse Bayesian Networks from High-Dimensional Data
Description: Fast methods for learning sparse Bayesian networks from high-dimensional data using sparse regularization, as described in as described in Aragam, Gu, and Zhou (2017) <https://arxiv.org/abs/1703.04025>. Designed to handle mixed experimental and observational data with thousands of variables with either continuous or discrete observations.
Author: Bryon Aragam [aut, cre]
Maintainer: Bryon Aragam <sparsebn@gmail.com>

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Package simmer.plot updated to version 0.1.9 with previous version 0.1.8 dated 2017-02-10

Title: Plotting Methods for 'simmer'
Description: A set of plotting methods for 'simmer' trajectories and simulations.
Author: Iñaki Ucar [aut, cph, cre], Bart Smeets [aut, cph]
Maintainer: Iñaki Ucar <i.ucar86@gmail.com>

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Package rlas updated to version 1.1.1 with previous version 1.1.0 dated 2017-02-05

Title: Read and Write 'las' and 'laz' Binary File Formats Used for Remote Sensing Data
Description: Read and write 'las' and 'laz' binary file formats. The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. The LAS specifications are approved by the American Society for Photogrammetry and Remote Sensing. The LAZ file format is an open and lossless compression scheme for binary LAS format versions 1.0 to 1.3.
Author: Jean-Romain Roussel [aut, cre, cph], Martin Isenburg [cph] (Is the author of the LASlib and LASzip libraries), David Auty [ctb] (Reviewed the documentation), Pierrick Marie [ctb] (Helped to compile LASlib code in R), Florian De Boissieu [ctb] (Enable support of .lax file)
Maintainer: Jean-Romain Roussel <jean-romain.roussel.1@ulaval.ca>

Diff between rlas versions 1.1.0 dated 2017-02-05 and 1.1.1 dated 2017-03-15

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Package potts updated to version 0.5-6 with previous version 0.5-4 dated 2015-07-05

Title: Markov Chain Monte Carlo for Potts Models
Description: It does Markov chain Monte Carlo (MCMC) simulation of Potts models (Potts, 1952, <http://doi.org/10.1017/S0305004100027419>), which are the multi-color generalization of Ising models (so, as as special case, also simulates Ising models). It uses the Swendsen-Wang algorithm (Swendsen and Wang, 1987, <http://doi.org/10.1103/PhysRevLett.58.86>) so MCMC is fast. It does maximum composite likelihood estimation of parameters (Besag, 1975, <http://doi.org/10.2307/2987782>, Lindsay, 1988, <http://doi.org/10.1090/conm/080>).
Author: Charles J. Geyer <charlie@stat.umn.edu> and Leif Johnson <leif@stat.umn.edu>
Maintainer: Charles J. Geyer <charlie@stat.umn.edu>

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Package oceanmap updated to version 0.0.4 with previous version 0.0.3 dated 2017-03-08

Title: A Plotting Toolbox for 2D Oceanographic Data
Description: Plotting toolbox for 2D oceanographic data (satellite data, sst, chla, ocean fronts & bathymetry). Recognized classes and formats include ncdf4, Raster, '.nc' and '.gz' files.
Author: Robert K. Bauer
Maintainer: Robert K. Bauer <robert.bauer@ird.fr>

Diff between oceanmap versions 0.0.3 dated 2017-03-08 and 0.0.4 dated 2017-03-15

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 oceanmap-0.0.4/oceanmap/ChangeLog                                                                     |    4 
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 oceanmap-0.0.4/oceanmap/man/cmap.Rd                                                                   |   11 
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Package AdaptGauss updated to version 1.3.3 with previous version 1.2.4 dated 2016-06-30

Title: Gaussian Mixture Models (GMM)
Description: Multimodal distributions can be modelled as a mixture of components. The model is derived using the Pareto Density Estimation (PDE) for an estimation of the pdf. PDE has been designed in particular to identify groups/classes in a dataset. Precise limits for the classes can be calculated using the theorem of Bayes. Verification of the model is possible by QQ plot, Chi-squared test and Kolmogorov-Smirnov test. The package is based on the publication of Ultsch, A., Thrun, M.C., Hansen-Goos, O., Lotsch, J. (2015) <DOI:10.3390/ijms161025897>.
Author: Michael Thrun, Onno Hansen-Goos, Rabea Griese, Catharina Lippmann, Florian Lerch, Jorn Lotsch, Alfred Ultsch
Maintainer: Florian Lerch <lerch@mathematik.uni-marburg.de>

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Package RWeka updated to version 0.4-32 with previous version 0.4-31 dated 2017-01-23

Title: R/Weka Interface
Description: An R interface to Weka (Version 3.9.1). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package 'RWeka' contains the interface code, the Weka jar is in a separate package 'RWekajars'. For more information on Weka see <http://www.cs.waikato.ac.nz/ml/weka/>.
Author: Kurt Hornik [aut, cre], Christian Buchta [ctb], Torsten Hothorn [ctb], Alexandros Karatzoglou [ctb], David Meyer [ctb], Achim Zeileis [ctb]
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

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Package pltesim updated to version 0.1.2 with previous version 0.1.1 dated 2017-02-23

Title: Simulate Probabilistic Long-Term Effects in Models with Temporal Dependence
Description: Calculates and depicts probabilistic long-term effects in binary models with temporal dependence variables. The package performs two tasks. First, it calculates the change in the probability of the event occurring given a change in a theoretical variable. Second, it calculates the rolling difference in the future probability of the event for two scenarios: one where the event occurred at a given time and one where the event does not occur. The package is consistent with the recent movement to depict meaningful and easy-to-interpret quantities of interest with the requisite measures of uncertainty. It is the first to make it easy for researchers to interpret short- and long-term effects of explanatory variables in binary autoregressive models, which can have important implications for the correct interpretation of these models.
Author: Christopher Gandrud [aut, cre], Laron K. Williams [aut]
Maintainer: Christopher Gandrud <christopher.gandrud@gmail.com>

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Package Tmisc updated to version 0.1.13 with previous version 0.1.12 dated 2017-01-22

Title: Turner Miscellaneous
Description: Miscellaneous utility functions for data manipulation, data tidying, and working with gene expression data.
Author: Stephen Turner <vustephen@gmail.com>
Maintainer: Stephen Turner <vustephen@gmail.com>

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Package PopGenome updated to version 2.2.2 with previous version 2.2.0 dated 2017-02-11

Title: An Efficient Swiss Army Knife for Population Genomic Analyses
Description: Provides efficient tools for population genomics data analysis, able to process individual loci, large sets of loci, or whole genomes. PopGenome not only implements a wide range of population genetics statistics, but also facilitates the easy implementation of new algorithms by other researchers. PopGenome is optimized for speed via the seamless integration of C code.
Author: Bastian Pfeifer [aut, cre], Ulrich Wittelsbuerger [ctb], Heng Li [ctb], Bob Handsaker [ctb]
Maintainer: Bastian Pfeifer <Bastian.Pfeifer@uni-duesseldorf.de>

Diff between PopGenome versions 2.2.0 dated 2017-02-11 and 2.2.2 dated 2017-03-15

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New package hNMF with initial version 0.2
Package: hNMF
Title: Hierarchical Non-Negative Matrix Factorization
Version: 0.2
Author: Nicolas Sauwen
Maintainer: Nicolas Sauwen <nicolas.sauwen@openanalytics.eu>
Description: Hierarchical non-negative matrix factorization for tumor segmentation based on multi-parametric MRI data.
Depends: R (>= 3.3.2)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: NMF, oro.nifti, tcltk, nnls, R.matlab, spatialfil, rasterImage, stats, graphics, grDevices
RoxygenNote: 6.0.0
Suggests: testthat
NeedsCompilation: no
Packaged: 2017-03-15 08:50:19 UTC; nsauwen
Repository: CRAN
Date/Publication: 2017-03-15 14:36:51

More information about hNMF at CRAN
Permanent link

Package dynaTree updated to version 1.2-10 with previous version 1.2-9 dated 2016-06-06

Title: Dynamic Trees for Learning and Design
Description: Inference by sequential Monte Carlo for dynamic tree regression and classification models with hooks provided for sequential design and optimization, fully online learning with drift, variable selection, and sensitivity analysis of inputs. Illustrative examples from the original dynamic trees paper are facilitated by demos in the package; see demo(package="dynaTree").
Author: Robert B. Gramacy <rbgramacy@chicagobooth.edu>, Matt A. Taddy <taddy@chicagobooth.edu> and Christoforos Anagnostopoulos <christoforos.anagnostopoulos06@imperial.ac.uk>
Maintainer: Robert B. Gramacy <rbg@vt.edu>

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New package confinterpret with initial version 0.1.0
Package: confinterpret
Type: Package
Title: Descriptive Interpretations of Confidence Intervals
Version: 0.1.0
Authors@R: person("Jim", "Vine", email = "code@jimvine.co.uk", role = c("aut", "cre"))
Description: Produces descriptive interpretations of confidence intervals. Includes (extensible) support for various test types, specified as sets of interpretations dependent on where the lower and upper confidence limits sit.
License: AGPL-3
URL: https://github.com/jimvine/confinterpret
BugReports: https://github.com/jimvine/confinterpret/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: graphics, grDevices, testthat
NeedsCompilation: no
Packaged: 2017-03-15 11:08:24 UTC; jimvi
Author: Jim Vine [aut, cre]
Maintainer: Jim Vine <code@jimvine.co.uk>
Repository: CRAN
Date/Publication: 2017-03-15 14:36:50

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Package subniche updated to version 0.9.3 with previous version 0.9.2 dated 2017-02-03

Title: Within Outlying Mean Indexes: Refining the OMI Analysis
Description: Complementary multivariate analysis to the Outlying Mean Index analysis to explore niche shift of a community and biological constraint within an Euclidean space, with graphical displays.
Author: Stephane Karasiewicz
Maintainer: Stephane Karasiewicz <stephane.karasiewicz@wanadoo.fr>

Diff between subniche versions 0.9.2 dated 2017-02-03 and 0.9.3 dated 2017-03-15

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Package mitml updated to version 0.3-5 with previous version 0.3-4 dated 2016-09-13

Title: Tools for Multiple Imputation in Multilevel Modeling
Description: Provides tools for multiple imputation of missing data in multilevel modeling. Includes a user-friendly interface to the packages 'pan' and 'jomo', and several functions for visualization, data management and the analysis of multiply imputed data sets.
Author: Simon Grund [aut,cre], Alexander Robitzsch [aut], Oliver Luedtke [aut]
Maintainer: Simon Grund <grund@ipn.uni-kiel.de>

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Package kohonen updated to version 3.0.0 with previous version 2.0.19 dated 2015-09-04

Title: Supervised and Unsupervised Self-Organising Maps
Description: Functions to train self-organising maps (SOMs). Also interrogation of the maps and prediction using trained maps are supported. The name of the package refers to Teuvo Kohonen, the inventor of the SOM.
Author: Ron Wehrens and Johannes Kruisselbrink
Maintainer: Ron Wehrens <ron.wehrens@gmail.com>

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Package bibliometrix updated to version 1.5 with previous version 1.4 dated 2017-01-24

Title: Bibliometric and Co-Citation Analysis Tool
Description: Tool for quantitative research in scientometrics and bibliometrics. It provides various routines for importing bibliographic data from SCOPUS (<http://scopus.com>) and Thomson Reuters' ISI Web of Knowledge (<http://www.webofknowledge.com/>) databases, performing bibliometric analysis and building data matrices for co-citation, coupling, scientific collaboration and co-word analysis.
Author: Massimo Aria [cre, aut], Corrado Cuccurullo [aut]
Maintainer: Massimo Aria <aria@unina.it>

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Package PGRdup updated to version 0.2.3.1 with previous version 0.2.3 dated 2017-02-01

Title: Discover Probable Duplicates in Plant Genetic Resources Collections
Description: Provides functions to aid the identification of probable/possible duplicates in Plant Genetic Resources (PGR) collections using 'passport databases' comprising of information records of each constituent sample. These include methods for cleaning the data, creation of a searchable Key Word in Context (KWIC) index of keywords associated with sample records and the identification of nearly identical records with similar information by fuzzy, phonetic and semantic matching of keywords.
Author: J. Aravind [aut, cre], J. Radhamani [aut], Kalyani Srinivasan [aut], B. Ananda Subhash [aut], R. K. Tyagi [aut]
Maintainer: J. Aravind <j.aravind@icar.gov.in>

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Package aster updated to version 0.9.1 with previous version 0.9 dated 2017-03-12

Title: Aster Models
Description: Aster models are exponential family regression models for life history analysis. They are like generalized linear models except that elements of the response vector can have different families (e. g., some Bernoulli, some Poisson, some zero-truncated Poisson, some normal) and can be dependent, the dependence indicated by a graphical structure. Discrete time survival analysis, zero-inflated Poisson regression, and generalized linear models that are exponential family (e. g., logistic regression and Poisson regression with log link) are special cases. Main use is for data in which there is survival over discrete time periods and there is additional data about what happens conditional on survival (e. g., number of offspring). Uses the exponential family canonical parameterization (aster transform of usual parameterization).
Author: Charles J. Geyer <charlie@stat.umn.edu>.
Maintainer: Charles J. Geyer <charlie@stat.umn.edu>

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Package pbkrtest updated to version 0.4-7 with previous version 0.4-6 dated 2016-01-27

Title: Parametric Bootstrap and Kenward Roger Based Methods for Mixed Model Comparison
Description: Test in mixed effects models. Attention is on mixed effects models as implemented in the 'lme4' package. This package implements a parametric bootstrap test and a Kenward Roger modification of F-tests for linear mixed effects models and a parametric bootstrap test for generalized linear mixed models.
Author: Ulrich Halekoh <uhalekoh@health.sdu.dk> Søren Højsgaard <sorenh@math.aau.dk>
Maintainer: Søren Højsgaard <sorenh@math.aau.dk>

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More information about pbkrtest at CRAN
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Package mlr updated to version 2.11 with previous version 2.10 dated 2017-02-07

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], Lars Kotthoff [aut], Julia Schiffner [aut], Jakob Richter [aut], Zachary Jones [aut], Giuseppe Casalicchio [aut], Mason Gallo [aut], Jakob Bossek [ctb], Erich Studerus [ctb], Leonard Judt [ctb], Tobias Kuehn [ctb], Pascal Kerschke [ctb], Florian Fendt [ctb], Philipp Probst [ctb], Xudong Sun [ctb], Janek Thomas [ctb], Bruno Vieira [ctb], Laura Beggel [ctb], Quay Au [ctb], Martin Binder [ctb], Florian Pfisterer [ctb], Stefan Coors [ctb]
Maintainer: Bernd Bischl <bernd_bischl@gmx.net>

Diff between mlr versions 2.10 dated 2017-02-07 and 2.11 dated 2017-03-15

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 mlr-2.11/mlr/NEWS.md                                              |   46 
 mlr-2.11/mlr/R/BaggingWrapper.R                                   |   34 
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 mlr-2.11/mlr/R/ClassifTask.R                                      |   13 
 mlr-2.11/mlr/R/ClusterTask.R                                      |    8 
 mlr-2.11/mlr/R/ConstantClassWrapper.R                             |    2 
 mlr-2.11/mlr/R/CostSensClassifWrapper.R                           |    2 
 mlr-2.11/mlr/R/CostSensRegrWrapper.R                              |   23 
 mlr-2.11/mlr/R/CostSensTask.R                                     |   12 
 mlr-2.11/mlr/R/CostSensWeightedPairsWrapper.R                     |    2 
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 mlr-2.11/mlr/R/FailureModel.R                                     |   10 
 mlr-2.11/mlr/R/FeatSelControl.R                                   |   16 
 mlr-2.11/mlr/R/FeatSelControlExhaustive.R                         |    2 
 mlr-2.11/mlr/R/FeatSelControlGA.R                                 |    2 
 mlr-2.11/mlr/R/FeatSelControlRandom.R                             |    2 
 mlr-2.11/mlr/R/FeatSelControlSequential.R                         |    2 
 mlr-2.11/mlr/R/Filter.R                                           |   32 
 mlr-2.11/mlr/R/FilterWrapper.R                                    |   14 
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 mlr-2.11/mlr/R/Impute.R                                           |   15 
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 mlr-2.11/mlr/R/ModelMultiplexer.R                                 |    3 
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 mlr-2.11/mlr/R/MultilabelTask.R                                   |   10 
 mlr-2.11/mlr/R/OptControl.R                                       |    4 
 mlr-2.11/mlr/R/OverBaggingWrapper.R                               |   15 
 mlr-2.11/mlr/R/Prediction.R                                       |   34 
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 mlr-2.11/mlr/R/RLearner.R                                         |    2 
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 mlr-2.11/mlr/R/RLearner_classif_cforest.R                         |    3 
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 mlr-2.11/mlr/R/RLearner_classif_glmnet.R                          |   17 
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 mlr-2.11/mlr/R/RLearner_classif_kknn.R                            |    2 
 mlr-2.11/mlr/R/RLearner_classif_logreg.R                          |   11 
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New package gee4 with initial version 0.1.0.0
Package: gee4
Type: Package
Title: Generalised Estimating Equations (GEE/WGEE) using 'Armadillo' and S4
Version: 0.1.0.0
Authors@R: c(person("Jianxin", "Pan", email = "Jianxin.Pan@manchester.ac.uk", role = c("aut")), person("Yi", "Pan", email = "ypan1988@gmail.com", role = c("aut", "cre")))
Maintainer: Yi Pan <ypan1988@gmail.com>
Description: Fit joint mean-covariance models for longitudinal data within the framework of (weighted) generalised estimating equations (GEE/WGEE). The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Armadillo' C++ library for numerical linear algebra and 'RcppArmadillo' glue.
License: GPL (>= 2)
LazyData: TRUE
SystemRequirements: C++11
Depends: R (>= 3.2.2)
Imports: Formula, methods, Rcpp (>= 0.12.4)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
NeedsCompilation: yes
Author: Jianxin Pan [aut], Yi Pan [aut, cre]
URL: https://github.com/ypan1988/gee4/
BugReports: https://github.com/ypan1988/gee4/issues/
Packaged: 2017-03-14 23:38:21 UTC; yipan
Repository: CRAN
Date/Publication: 2017-03-15 08:49:09

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Package arulesCBA updated to version 1.1.0 with previous version 1.0.2 dated 2016-10-05

Title: Classification Based on Association Rules
Description: Provides a function to build an association rule-based classifier for data frames, and to classify incoming data frames using such a classifier.
Author: Ian Johnson [aut, cre, cph], Michael Hahsler [ctb]
Maintainer: Ian Johnson <ianjjohnson@icloud.com>

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Package AIG updated to version 0.1.3 with previous version 0.1.2 dated 2017-03-05

Title: Automatic Item Generator
Description: A collection of Automatic Item Generators used mainly for psychological research. This package can generate linear syllogistic reasoning, arithmetic and 2D/3D spatial reasoning items. It is recommended for research purpose only.
Author: Bao Sheng Loe (Aiden)
Maintainer: Bao Sheng Loe (Aiden) <bsl28@cam.ac.uk>

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Package RcppEigen updated to version 0.3.2.9.1 with previous version 0.3.2.9.0 dated 2016-08-20

Title: 'Rcpp' Integration for the 'Eigen' Templated Linear Algebra Library
Description: R and 'Eigen' integration using 'Rcpp'. 'Eigen' is a C++ template library for linear algebra: matrices, vectors, numerical solvers and related algorithms. It supports dense and sparse matrices on integer, floating point and complex numbers, decompositions of such matrices, and solutions of linear systems. Its performance on many algorithms is comparable with some of the best implementations based on 'Lapack' and level-3 'BLAS'. The 'RcppEigen' package includes the header files from the 'Eigen' C++ template library (currently version 3.2.9). Thus users do not need to install 'Eigen' itself in order to use 'RcppEigen'. Since version 3.1.1, 'Eigen' is licensed under the Mozilla Public License (version 2); earlier version were licensed under the GNU LGPL version 3 or later. 'RcppEigen' (the 'Rcpp' bindings/bridge to 'Eigen') is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'.
Author: Douglas Bates, Dirk Eddelbuettel, Romain Francois, and Yixuan Qiu; the authors of Eigen for the included version of Eigen
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package redist updated to version 1.3-1 with previous version 1.3 dated 2016-12-21

Title: Markov Chain Monte Carlo Methods for Redistricting Simulation
Description: Enables researchers to sample redistricting plans from a pre- specified target distribution using a Markov Chain Monte Carlo algorithm. The package allows for the implementation of various constraints in the redistricting process such as geographic compactness and population parity requirements. The algorithm also can be used in combination with efficient simulation methods such as simulated and parallel tempering algorithms. Tools for analysis such as inverse probability reweighting and plotting functionality are included. The package implements methods described in Fifield, Higgins, Imai and Tarr (2016) ``A New Automated Redistricting Simulator Using Markov Chain Monte Carlo,'' working paper available at <http://http://imai.princeton.edu/ research/files/redist.pdf>.
Author: Ben Fifield <bfifield@princeton.edu>, Alexander Tarr <atarr@princeton.edu>, Michael Higgins <mikehiggins@k-state.edu>, and Kosuke Imai <kimai@princeton.edu>
Maintainer: Ben Fifield <bfifield@princeton.edu>

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Package polyapost updated to version 1.4-3 with previous version 1.4-2 dated 2015-07-08

Title: Simulating from the Polya Posterior
Description: Simulate via Markov chain Monte Carlo (hit-and-run algorithm) a Dirichlet distribution conditioned to satisfy a finite set of linear equality and inequality constraints (hence to lie in a convex polytope that is a subset of the unit simplex).
Author: Glen Meeden <glen@stat.umn.edu> and Radu Lazar <lazar@stat.umn.edu> and Charles J. Geyer <charlie@stat.umn.edu>
Maintainer: Glen Meeden <glen@stat.umn.edu>

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Package GrpString updated to version 0.2.1 with previous version 0.1.1 dated 2017-02-10

Title: Patterns and Statistical Differences Between Two Groups of Strings
Description: Methods include converting series of event names to strings, discovering common patterns in a group of strings, discovering "unique" patterns when comparing two groups of strings as well as the number and starting position of each "unique" pattern in each string, finding the transition matrix and information, and statistically comparing the difference between two groups of strings.
Author: Hui (Tom) Tang, Norbert J. Pienta
Maintainer: Hui (Tom) Tang <htang2013@gmail.com>

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Package GPvam updated to version 3.0-4 with previous version 3.0-3 dated 2015-07-20

Title: Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling
Description: An EM algorithm, Karl et al. (2013) <doi:10.1016/j.csda.2012.10.004>, is used to estimate the generalized, variable, and complete persistence models, Mariano et al. (2010) <doi:10.3102/1076998609346967>. These are multiple-membership linear mixed models with teachers modeled as "G-side" effects and students modeled with either "G-side" or "R-side" effects.
Author: Andrew Karl, Yan Yang, and Sharon Lohr
Maintainer: Andrew Karl <akarl@asu.edu>

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Package GERGM updated to version 0.11.2 with previous version 0.10.0 dated 2016-08-07

Title: Estimation and Fit Diagnostics for Generalized Exponential Random Graph Models
Description: Estimation and diagnosis of the convergence of Generalized Exponential Random Graph Models via Gibbs sampling or Metropolis Hastings with exponential down weighting.
Author: Matthew J. Denny <mdenny@psu.edu>, James D. Wilson <jdwilson1212@gmail.com>, Skyler Cranmer <cranmer.12@osu.edu >, Bruce A. Desmarais <bdesmarais@psu.edu>, Shankar Bhamidi <bhamidi@email.unc.edu>
Maintainer: Matthew J. Denny <mdenny@psu.edu>

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Package fuzzyRankTests updated to version 0.3-10 with previous version 0.3-7 dated 2015-07-07

Title: Fuzzy Rank Tests and Confidence Intervals
Description: Does fuzzy tests and confidence intervals (following Geyer and Meeden, Statistical Science, 2005, <doi:10.1214/088342305000000340>) for sign test and Wilcoxon signed rank and rank sum tests.
Author: Charles J. Geyer <charlie@stat.umn.edu>
Maintainer: Charles J. Geyer <charlie@stat.umn.edu>

Diff between fuzzyRankTests versions 0.3-7 dated 2015-07-07 and 0.3-10 dated 2017-03-15

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Package fivethirtyeight updated to version 0.2.0 with previous version 0.1.0 dated 2017-01-08

Title: Data and Code Behind the Stories and Interactives at 'FiveThirtyEight'
Description: An R library that provides access to the code and data sets published by FiveThirtyEight <https://github.com/fivethirtyeight/data>. Note that while we received guidance from editors at 538, this package is not officially published by 538.
Author: Albert Y. Kim [cre], Chester Ismay [aut], Jennifer Chunn [aut], Andrew Flowers [ctb], Jonathan Bouchet [ctb], G. Elliott Morris [ctb], Adam Spannbauer [ctb]
Maintainer: Albert Y. Kim <albert.ys.kim@gmail.com>

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Package findpython updated to version 1.0.2 with previous version 1.0.1 dated 2014-04-03

Title: Python Tools to Find an Acceptable Python Binary
Description: Package designed to find an acceptable python binary.
Author: Trevor L Davis and Paul Gilbert.
Maintainer: Trevor L Davis <trevor.l.davis@gmail.com>

Diff between findpython versions 1.0.1 dated 2014-04-03 and 1.0.2 dated 2017-03-15

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