Thu, 19 Oct 2017

Package spTimer updated to version 3.0-1 with previous version 3.0-0 dated 2017-10-15

Title: Spatio-Temporal Bayesian Modelling
Description: Fits, spatially predicts and temporally forecasts large amounts of space-time data using [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian Auto-Regressive (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based AR Models for spatio-temporal big-n problems. Bakar and Sahu (2015) <doi:10.18637/jss.v063.i15>.
Author: K. Shuvo Bakar & Sujit K. Sahu
Maintainer: Shuvo Bakar <shuvo.bakar@gmail.com>

Diff between spTimer versions 3.0-0 dated 2017-10-15 and 3.0-1 dated 2017-10-19

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New package multimode with initial version 1.0
Encoding: UTF-8
Package: multimode
Type: Package
Title: Mode Testing and Exploring
Version: 1.0
Date: 2017-10-17
Author: Jose Ameijeiras-Alonso [aut,cre], Rosa M. Crujeiras [aut], Alberto Rodríguez-Casal [aut], The R Core Team 1996-2012 [ctb,cph] (C function 'BinDist2' obtained from package 'stats'), The R Foundation 2005 [ctb,cph] (C function 'BinDist2' obtained from package 'stats')
Maintainer: Jose Ameijeiras-Alonso <jose.ameijeiras@usc.es>
Description: Different examples and methods for testing (including different proposals described in Ameijeiras-Alonso et al., 2016 <arXiv:1609.05188>) and exploring (including the mode tree, mode forest and SiZer) the number of modes using nonparametric techniques.
Depends: R (>= 2.0.1)
License: GPL-3
NeedsCompilation: yes
LazyData: TRUE
Imports: diptest, ks, rootSolve
Suggests: nor1mix
Packaged: 2017-10-18 18:28:57 UTC; Usuario
Repository: CRAN
Date/Publication: 2017-10-19 13:50:45 UTC

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Package mafs updated to version 0.0.3 with previous version 0.0.2 dated 2017-01-25

Title: Multiple Automatic Forecast Selection
Description: Fits several forecast models available from the forecast package and selects the best one according to an error metric. Its main function is select_forecast().
Author: Sillas Gonzaga [aut, cre]
Maintainer: Sillas Gonzaga <sillas.gonzaga@gmail.com>

Diff between mafs versions 0.0.2 dated 2017-01-25 and 0.0.3 dated 2017-10-19

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Package sjPlot updated to version 2.4.0 with previous version 2.3.3 dated 2017-08-23

Title: Data Visualization for Statistics in Social Science
Description: Collection of plotting and table output functions for data visualization. Results of various statistical analyses (that are commonly used in social sciences) can be visualized using this package, including simple and cross tabulated frequencies, histograms, box plots, (generalized) linear models, mixed effects models, principal component analysis and correlation matrices, cluster analyses, scatter plots, stacked scales, effects plots of regression models (including interaction terms) and much more. This package supports labelled data.
Author: Daniel Lüdecke [aut, cre], Carsten Schwemmer [ctb]
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package ChainLadder updated to version 0.2.5 with previous version 0.2.4 dated 2017-01-01

Title: Statistical Methods and Models for Claims Reserving in General Insurance
Description: Various statistical methods and models which are typically used for the estimation of outstanding claims reserves in general insurance, including those to estimate the claims development result as required under Solvency II.
Author: Markus Gesmann [aut, cre], Daniel Murphy [aut], Yanwei (Wayne) Zhang [aut], Alessandro Carrato [aut], Giuseppe Crupi [aut], Christophe Dutang [ctb], Arnaud Lacoume [ctb], Arthur Charpentier [ctb], Mario Wuthrich [aut], Fabio Concina [aut]
Maintainer: Markus Gesmann <markus.gesmann@googlemail.com>

Diff between ChainLadder versions 0.2.4 dated 2017-01-01 and 0.2.5 dated 2017-10-19

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Wed, 18 Oct 2017

Package SubTite updated to version 2.0.0 with previous version 1.1.1 dated 2017-08-24

Title: Subgroup Specific Optimal Dose Assignment
Description: Contains functions for choosing subgroup specific optimal doses in a phase I dose finding clinical trial allowing for subgroup combination and simulating a clinical trial under the subgroup specific time to event continual reassessment method.
Author: Andrew Chapple
Maintainer: Andrew Chapple <andrew.g.chapple@rice.edu>

Diff between SubTite versions 1.1.1 dated 2017-08-24 and 2.0.0 dated 2017-10-18

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Package SparseDC updated to version 0.1.14 with previous version 0.1.12 dated 2017-09-17

Title: Implementation of SparseDC Algorithm
Description: Implements the algorithm described in Barron, M., Zhang, S. and Li, J. "A sparse differential clustering algorithm for tracing cell type changes via single-cell RNA-sequencing data" (Unpublished). This algorithm clusters samples from two different populations, links the clusters across the conditions and identifies marker genes for these changes. The package was designed for scRNA-Seq data but is also applicable to many other data types, just replace cells with samples and genes with variables. The package also contains functions for estimating the parameters for SparseDC as outlined in the paper.
Author: Jun Li [aut, cre], Martin Barron [aut]
Maintainer: Jun Li <jun.li@nd.edu>

Diff between SparseDC versions 0.1.12 dated 2017-09-17 and 0.1.14 dated 2017-10-18

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Package onemap updated to version 2.1.1 with previous version 2.1.0 dated 2017-10-10

Title: Construction of Genetic Maps in Experimental Crosses: Full-Sib, RILs, F2 and Backcrosses
Description: Analysis of molecular marker data from model (backcrosses, F2 and recombinant inbred lines) and non-model systems (i. e. outcrossing species). For the later, it allows statistical analysis by simultaneously estimating linkage and linkage phases (genetic map construction) according to Wu et al. (2002) <doi:10.1006/tpbi.2002.1577>. All analysis are based on multipoint approaches using hidden Markov models.
Author: Gabriel Margarido [aut], Marcelo Mollinari [aut], Karl Broman [ctb], Rodrigo Amadeu [ctb], Cristiane Taniguti [ctb, cre], Augusto Garcia [aut, ctb]
Maintainer: Cristiane Taniguti <chtaniguti@usp.br>

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Package Haplin updated to version 6.2.1 with previous version 6.2.0 dated 2017-02-28

Title: Analyzing Case-Parent Triad and/or Case-Control Data with SNP Haplotypes
Description: Performs genetic association analyses of case-parent triad (trio) data with multiple markers. It can also incorporate complete or incomplete control triads, for instance independent control children. Estimation is based on haplotypes, for instance SNP haplotypes, even though phase is not known from the genetic data. 'Haplin' estimates relative risk (RR + conf.int.) and p-value associated with each haplotype. It uses maximum likelihood estimation to make optimal use of data from triads with missing genotypic data, for instance if some SNPs has not been typed for some individuals. 'Haplin' also allows estimation of effects of maternal haplotypes and parent-of-origin effects, particularly appropriate in perinatal epidemiology. 'Haplin' allows special models, like X-inactivation, to be fitted on the X-chromosome. A GxE analysis allows testing interactions between environment and all estimated genetic effects. The models were originally described in Gjessing, HK and Lie, RT (2006) <doi:10.1111/j.1529-8817.2005.00218.x>.
Author: Hakon K. Gjessing
Maintainer: Hakon K. Gjessing <hakon.gjessing@uib.no>

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 Haplin-6.2.1/Haplin/man/pedToHaplin.Rd          |  110 +++----
 Haplin-6.2.1/Haplin/man/plot.haplin.Rd          |   94 +++---
 Haplin-6.2.1/Haplin/man/plot.haplinTDT.Rd       |   90 +++---
 Haplin-6.2.1/Haplin/man/plot.haptable.Rd        |  116 ++++----
 Haplin-6.2.1/Haplin/man/prepPed.Rd              |  120 ++++----
 Haplin-6.2.1/Haplin/man/print.haplin.Rd         |   64 ++--
 Haplin-6.2.1/Haplin/man/print.summary.haplin.Rd |   88 +++---
 Haplin-6.2.1/Haplin/man/rbindFiles.Rd           |  122 ++++----
 Haplin-6.2.1/Haplin/man/snpPos.Rd               |    2 
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 Haplin-6.2.1/Haplin/man/snpSampleSize.Rd        |  138 ++++-----
 Haplin-6.2.1/Haplin/man/suest.Rd                |  142 +++++-----
 Haplin-6.2.1/Haplin/man/summary.haplin.Rd       |   80 ++---
 Haplin-6.2.1/Haplin/man/summary.haplinTDT.Rd    |   68 ++--
 Haplin-6.2.1/Haplin/man/toDataFrame.Rd          |   58 ++--
 37 files changed, 2239 insertions(+), 2241 deletions(-)

More information about Haplin at CRAN
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Package gpuR updated to version 2.0.0 with previous version 1.2.1 dated 2017-01-05

Title: GPU Functions for R Objects
Description: Provides GPU enabled functions for R objects in a simple and approachable manner. New gpu* and vcl* classes have been provided to wrap typical R objects (e.g. vector, matrix), in both host and device spaces, to mirror typical R syntax without the need to know OpenCL.
Author: Charles Determan Jr.
Maintainer: Charles Determan Jr. <cdetermanjr@gmail.com>

Diff between gpuR versions 1.2.1 dated 2017-01-05 and 2.0.0 dated 2017-10-18

 gpuR-1.2.1/gpuR/inst/include/gpuR/eigen_helpers.hpp                         |only
 gpuR-1.2.1/gpuR/inst/include/gpuR/eigen_templates.hpp                       |only
 gpuR-1.2.1/gpuR/inst/include/gpuR/vcl_vec_helpers.hpp                       |only
 gpuR-2.0.0/gpuR/DESCRIPTION                                                 |   13 
 gpuR-2.0.0/gpuR/INSTALL                                                     |   20 
 gpuR-2.0.0/gpuR/MD5                                                         |  690 
 gpuR-2.0.0/gpuR/NAMESPACE                                                   |  249 
 gpuR-2.0.0/gpuR/R/RcppExports.R                                             | 1988 
 gpuR-2.0.0/gpuR/R/asserts.R                                                 |   62 
 gpuR-2.0.0/gpuR/R/chol.R                                                    |  374 
 gpuR-2.0.0/gpuR/R/class-gpuMatrix.R                                         |  372 
 gpuR-2.0.0/gpuR/R/class-gpuVector.R                                         |  276 
 gpuR-2.0.0/gpuR/R/class-vclMatrix.R                                         |  315 
 gpuR-2.0.0/gpuR/R/class-vclVector.R                                         |  266 
 gpuR-2.0.0/gpuR/R/classes.R                                                 |   11 
 gpuR-2.0.0/gpuR/R/custom_opencl.R                                           |only
 gpuR-2.0.0/gpuR/R/eigen.R                                                   |  292 
 gpuR-2.0.0/gpuR/R/generics.R                                                |  246 
 gpuR-2.0.0/gpuR/R/gpuMatrix.R                                               |  730 
 gpuR-2.0.0/gpuR/R/gpuVector.R                                               |  378 
 gpuR-2.0.0/gpuR/R/hello-gpuR.R                                              |   74 
 gpuR-2.0.0/gpuR/R/inplace.R                                                 |only
 gpuR-2.0.0/gpuR/R/methods-gpuVector.R                                       |  753 
 gpuR-2.0.0/gpuR/R/methods-vclMatrix.R                                       | 2681 -
 gpuR-2.0.0/gpuR/R/methods-vclVector.R                                       | 1074 
 gpuR-2.0.0/gpuR/R/methods.R                                                 | 2446 
 gpuR-2.0.0/gpuR/R/norm.R                                                    |only
 gpuR-2.0.0/gpuR/R/pmax.R                                                    |only
 gpuR-2.0.0/gpuR/R/print.R                                                   |  104 
 gpuR-2.0.0/gpuR/R/qr.R                                                      |  398 
 gpuR-2.0.0/gpuR/R/sign.R                                                    |only
 gpuR-2.0.0/gpuR/R/solve.R                                                   |  428 
 gpuR-2.0.0/gpuR/R/svd.R                                                     |  172 
 gpuR-2.0.0/gpuR/R/test_utils.R                                              |  256 
 gpuR-2.0.0/gpuR/R/typeof.R                                                  |  132 
 gpuR-2.0.0/gpuR/R/utils.R                                                   |  497 
 gpuR-2.0.0/gpuR/R/vclMatrix.R                                               |  432 
 gpuR-2.0.0/gpuR/R/vclVector.R                                               |  499 
 gpuR-2.0.0/gpuR/R/wrappers-gpuVector.R                                      | 1677 
 gpuR-2.0.0/gpuR/R/wrappers-utils.R                                          |  616 
 gpuR-2.0.0/gpuR/R/wrappers-vclMatrix.R                                      | 3442 -
 gpuR-2.0.0/gpuR/R/wrappers-vclVector.R                                      | 1715 
 gpuR-2.0.0/gpuR/R/wrappers.R                                                | 2802 -
 gpuR-2.0.0/gpuR/R/zzz.R                                                     |   52 
 gpuR-2.0.0/gpuR/README.md                                                   |  136 
 gpuR-2.0.0/gpuR/build/vignette.rds                                          |binary
 gpuR-2.0.0/gpuR/cleanup.win                                                 |   10 
 gpuR-2.0.0/gpuR/configure                                                   |    3 
 gpuR-2.0.0/gpuR/inst/CITATION                                               |only
 gpuR-2.0.0/gpuR/inst/CL/basic_gemm.cl                                       |   38 
 gpuR-2.0.0/gpuR/inst/CL/dLogDeriv.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/dMatSign.cl                                         |only
 gpuR-2.0.0/gpuR/inst/CL/dMat_pmax.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/dMat_pmin.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/dPermute.cl                                         |only
 gpuR-2.0.0/gpuR/inst/CL/dScalarAXPY.cl                                      |only
 gpuR-2.0.0/gpuR/inst/CL/dScalarElemDiv.cl                                   |only
 gpuR-2.0.0/gpuR/inst/CL/dVecLogDeriv.cl                                     |only
 gpuR-2.0.0/gpuR/inst/CL/dVecSign.cl                                         |only
 gpuR-2.0.0/gpuR/inst/CL/dVec_pmax.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/dVec_pmin.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/dcholesky.cl                                        |  118 
 gpuR-2.0.0/gpuR/inst/CL/dset_row_order.cl                                   |   28 
 gpuR-2.0.0/gpuR/inst/CL/dset_row_order2.cl                                  |only
 gpuR-2.0.0/gpuR/inst/CL/fLogDeriv.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/fMatSign.cl                                         |only
 gpuR-2.0.0/gpuR/inst/CL/fMat_pmax.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/fMat_pmin.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/fScalarAXPY.cl                                      |only
 gpuR-2.0.0/gpuR/inst/CL/fScalarElemDiv.cl                                   |only
 gpuR-2.0.0/gpuR/inst/CL/fVecLogDeriv.cl                                     |only
 gpuR-2.0.0/gpuR/inst/CL/fVecSign.cl                                         |only
 gpuR-2.0.0/gpuR/inst/CL/fVec_pmax.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/fVec_pmin.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/fcholesky.cl                                        |  122 
 gpuR-2.0.0/gpuR/inst/CL/fset_row_order.cl                                   |   42 
 gpuR-2.0.0/gpuR/inst/CL/fset_row_order2.cl                                  |only
 gpuR-2.0.0/gpuR/inst/CL/iMatSign.cl                                         |only
 gpuR-2.0.0/gpuR/inst/CL/iMat_pmax.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/iMat_pmin.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/iScalarAXPY.cl                                      |only
 gpuR-2.0.0/gpuR/inst/CL/iScalarElemDiv.cl                                   |only
 gpuR-2.0.0/gpuR/inst/CL/iVecSign.cl                                         |only
 gpuR-2.0.0/gpuR/inst/CL/iVec_pmax.cl                                        |only
 gpuR-2.0.0/gpuR/inst/CL/iVec_pmin.cl                                        |only
 gpuR-2.0.0/gpuR/inst/NEWS.Rd                                                |  215 
 gpuR-2.0.0/gpuR/inst/doc/custom_ocl_gpuR.R                                  |only
 gpuR-2.0.0/gpuR/inst/doc/custom_ocl_gpuR.Rnw                                |only
 gpuR-2.0.0/gpuR/inst/doc/custom_ocl_gpuR.pdf                                |only
 gpuR-2.0.0/gpuR/inst/doc/gpuR.R                                             |   80 
 gpuR-2.0.0/gpuR/inst/doc/gpuR.Rnw                                           |  540 
 gpuR-2.0.0/gpuR/inst/doc/gpuR.pdf                                           |binary
 gpuR-2.0.0/gpuR/inst/include/CL/cl.h                                        | 2904 -
 gpuR-2.0.0/gpuR/inst/include/CL/cl.hpp                                      |25868 +++++-----
 gpuR-2.0.0/gpuR/inst/include/CL/cl_d3d10.h                                  |  262 
 gpuR-2.0.0/gpuR/inst/include/CL/cl_d3d11.h                                  |  262 
 gpuR-2.0.0/gpuR/inst/include/CL/cl_dx9_media_sharing.h                      |  264 
 gpuR-2.0.0/gpuR/inst/include/CL/cl_egl.h                                    |  272 
 gpuR-2.0.0/gpuR/inst/include/CL/cl_ext.h                                    |  782 
 gpuR-2.0.0/gpuR/inst/include/CL/cl_gl.h                                     |  334 
 gpuR-2.0.0/gpuR/inst/include/CL/cl_gl_ext.h                                 |  148 
 gpuR-2.0.0/gpuR/inst/include/CL/cl_platform.h                               | 2678 -
 gpuR-2.0.0/gpuR/inst/include/CL/opencl.h                                    |  118 
 gpuR-2.0.0/gpuR/inst/include/gpuR/dynEigenMat.hpp                           |  596 
 gpuR-2.0.0/gpuR/inst/include/gpuR/dynEigenVec.hpp                           |  284 
 gpuR-2.0.0/gpuR/inst/include/gpuR/dynVCLMat.hpp                             | 1101 
 gpuR-2.0.0/gpuR/inst/include/gpuR/dynVCLVec.hpp                             |  551 
 gpuR-2.0.0/gpuR/inst/include/gpuR/getVCLptr.hpp                             |   83 
 gpuR-2.0.0/gpuR/inst/include/gpuR/utils.hpp                                 |   82 
 gpuR-2.0.0/gpuR/inst/include/gpuR/windows_check.hpp                         |   30 
 gpuR-2.0.0/gpuR/inst/include/loader/icd.c                                   |  426 
 gpuR-2.0.0/gpuR/inst/include/loader/icd.h                                   |  378 
 gpuR-2.0.0/gpuR/inst/include/loader/icd_dispatch.c                          | 5300 +-
 gpuR-2.0.0/gpuR/inst/include/loader/icd_dispatch.h                          | 3032 -
 gpuR-2.0.0/gpuR/inst/include/loader/icd_linux.c                             |  376 
 gpuR-2.0.0/gpuR/inst/include/loader/icd_windows.c                           |  324 
 gpuR-2.0.0/gpuR/inst/src                                                    |only
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat.R                                 |    8 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_deepcopy.R               |  480 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuMatrixBlock_algebra.R | 1344 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuMatrix_algebra.R      | 1246 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuMatrix_classes.R      |  336 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuMatrix_cov.R          |   92 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuMatrix_dist.R         |   90 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuMatrix_eigen.R        |  226 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuMatrix_math.R         |  568 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuMatrix_row_col.R      |  482 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuMatrix_utils.R        |  328 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuVector_algebra.R      | 1108 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuVector_classes.R      |  204 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuVector_math.R         |  522 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_gpuVector_utils.R        |  226 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclMatrixBlock_algebra.R | 1348 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclMatrix_algebra.R      |  656 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclMatrix_classes.R      |  312 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclMatrix_cov.R          |   92 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclMatrix_dist.R         |   92 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclMatrix_eigen.R        |  226 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclMatrix_row_col.R      |  466 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclMatrtix_math.R        |  524 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclMatrtix_utils.R       |  310 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclVector_algebra.R      |  978 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclVector_classes.R      |  212 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclVector_math.R         |  522 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_cpu_vclVector_utils.R        |  240 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_deepcopy.R                   |  482 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuMatrixBlock_algebra.R     | 1360 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuMatrix_algebra.R          | 1234 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuMatrix_classes.R          |  438 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuMatrix_cov.R              |   84 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuMatrix_dist.R             |   82 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuMatrix_eigen.R            |  226 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuMatrix_math.R             |  524 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuMatrix_row_col.R          |  490 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuMatrix_utils.R            |  332 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuVector_algebra.R          | 1106 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuVector_classes.R          |  206 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuVector_math.R             |  522 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_gpuVector_utils.R            |  234 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_utils.R                      |   48 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclMatrixBlock_algebra.R     | 1360 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclMatrix_algebra.R          | 1212 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclMatrix_classes.R          |  310 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclMatrix_cov.R              |   84 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclMatrix_dist.R             |   82 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclMatrix_eigen.R            |  240 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclMatrix_math.R             |  536 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclMatrix_row_col.R          |  492 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclMatrix_utils.R            |  316 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclVector_algebra.R          |  996 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclVector_classes.R          |  212 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclVector_math.R             |  530 
 gpuR-2.0.0/gpuR/inst/testWithGPU/testthat/test_vclVector_utils.R            |  238 
 gpuR-2.0.0/gpuR/man/Arith-methods.Rd                                        |  173 
 gpuR-2.0.0/gpuR/man/Compare-methods.Rd                                      |   57 
 gpuR-2.0.0/gpuR/man/Math-methods.Rd                                         |   79 
 gpuR-2.0.0/gpuR/man/Summary-methods.Rd                                      |   69 
 gpuR-2.0.0/gpuR/man/as.gpuMatrix-methods.Rd                                 |   53 
 gpuR-2.0.0/gpuR/man/as.gpuVector-methods.Rd                                 |   61 
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 gpuR-2.0.0/gpuR/man/chol-methods.Rd                                         |   81 
 gpuR-2.0.0/gpuR/man/colnames-methods.Rd                                     |   79 
 gpuR-2.0.0/gpuR/man/cov-methods.Rd                                          |   97 
 gpuR-2.0.0/gpuR/man/currentContext.Rd                                       |   29 
 gpuR-2.0.0/gpuR/man/currentDevice.Rd                                        |   41 
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 gpuR-2.0.0/gpuR/man/detectCPUs.Rd                                           |   43 
 gpuR-2.0.0/gpuR/man/detectGPUs.Rd                                           |   43 
 gpuR-2.0.0/gpuR/man/detectPlatforms.Rd                                      |   35 
 gpuR-2.0.0/gpuR/man/deviceHasDouble.Rd                                      |   48 
 gpuR-2.0.0/gpuR/man/deviceInfo.Rd                                           |  117 
 gpuR-2.0.0/gpuR/man/deviceType.Rd                                           |   39 
 gpuR-2.0.0/gpuR/man/dgpuMatrix-class.Rd                                     |   50 
 gpuR-2.0.0/gpuR/man/dgpuVector-class.Rd                                     |   46 
 gpuR-2.0.0/gpuR/man/diag-methods.Rd                                         |   87 
 gpuR-2.0.0/gpuR/man/dim-methods.Rd                                          |   53 
 gpuR-2.0.0/gpuR/man/dist-vclMatrix.Rd                                       |  103 
 gpuR-2.0.0/gpuR/man/dvclMatrix-class.Rd                                     |   50 
 gpuR-2.0.0/gpuR/man/dvclVector-class.Rd                                     |   46 
 gpuR-2.0.0/gpuR/man/eigen-gpuMatrix.Rd                                      |  114 
 gpuR-2.0.0/gpuR/man/extract-methods.Rd                                      |  333 
 gpuR-2.0.0/gpuR/man/fgpuMatrix-class.Rd                                     |   50 
 gpuR-2.0.0/gpuR/man/fgpuVector-class.Rd                                     |   46 
 gpuR-2.0.0/gpuR/man/fvclMatrix-class.Rd                                     |   50 
 gpuR-2.0.0/gpuR/man/fvclVector-class.Rd                                     |   46 
 gpuR-2.0.0/gpuR/man/gpuMatrix-class.Rd                                      |   98 
 gpuR-2.0.0/gpuR/man/gpuMatrix-crossprod.Rd                                  |   85 
 gpuR-2.0.0/gpuR/man/gpuMatrix-methods.Rd                                    |  103 
 gpuR-2.0.0/gpuR/man/gpuMatrix.colSums.Rd                                    |   71 
 gpuR-2.0.0/gpuR/man/gpuR-block.Rd                                           |   95 
 gpuR-2.0.0/gpuR/man/gpuR-deepcopy.Rd                                        |   97 
 gpuR-2.0.0/gpuR/man/gpuR-package.Rd                                         |   85 
 gpuR-2.0.0/gpuR/man/gpuR-slice.Rd                                           |   85 
 gpuR-2.0.0/gpuR/man/gpuVector-class.Rd                                      |   70 
 gpuR-2.0.0/gpuR/man/gpuVector-methods.Rd                                    |   88 
 gpuR-2.0.0/gpuR/man/grapes-o-grapes-methods.Rd                              |   47 
 gpuR-2.0.0/gpuR/man/grapes-times-grapes-methods.Rd                          |   81 
 gpuR-2.0.0/gpuR/man/has_cpu_skip.Rd                                         |   25 
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 gpuR-2.0.0/gpuR/man/identity_matrix.Rd                                      |   59 
 gpuR-2.0.0/gpuR/man/igpuMatrix-class.Rd                                     |   50 
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 gpuR-2.0.0/gpuR/man/ivclMatrix-class.Rd                                     |   50 
 gpuR-2.0.0/gpuR/man/ivclVector-class.Rd                                     |   46 
 gpuR-2.0.0/gpuR/man/length-methods.Rd                                       |   67 
 gpuR-2.0.0/gpuR/man/listContexts.Rd                                         |   55 
 gpuR-2.0.0/gpuR/man/log-methods.Rd                                          |   75 
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 gpuR-2.0.0/gpuR/man/nrow-gpuR.Rd                                            |   63 
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Package FactoRizationMachines updated to version 0.35 with previous version 0.21 dated 2017-08-08

Title: Machine Learning with Higher-Order Factorization Machines
Description: Implementation of different machine learning approaches: Support Vector Machine with a linear kernel, second-order Factorization Machine, higher-order Factorization Machine, and adaptive-order Factorization Machine.
Author: Julian Knoll
Maintainer: Julian Knoll <julian.knoll@th-nuernberg.de>

Diff between FactoRizationMachines versions 0.21 dated 2017-08-08 and 0.35 dated 2017-10-18

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More information about FactoRizationMachines at CRAN
Permanent link

Package purrr updated to version 0.2.4 with previous version 0.2.3 dated 2017-08-02

Title: Functional Programming Tools
Description: A complete and consistent functional programming toolkit for R.
Author: Lionel Henry [aut, cre], Hadley Wickham [aut], RStudio [cph, fnd]
Maintainer: Lionel Henry <lionel@rstudio.com>

Diff between purrr versions 0.2.3 dated 2017-08-02 and 0.2.4 dated 2017-10-18

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More information about purrr at CRAN
Permanent link

Package jomo updated to version 2.5-1 with previous version 2.4-1 dated 2017-06-06

Title: Multilevel Joint Modelling Multiple Imputation
Description: Similarly to Schafer's package 'pan', 'jomo' is a package for multilevel joint modelling multiple imputation. Novel aspects of 'jomo' are the possibility of handling binary and categorical data through latent normal variables, the option to use cluster-specific covariance matrices and to impute compatibly with the substantive model.
Author: Matteo Quartagno, James Carpenter
Maintainer: Matteo Quartagno <matteo.quartagno@lshtm.ac.uk>

Diff between jomo versions 2.4-1 dated 2017-06-06 and 2.5-1 dated 2017-10-18

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Package irlba updated to version 2.3.1 with previous version 2.2.1 dated 2017-05-17

Title: Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense and Sparse Matrices
Description: Fast and memory efficient methods for truncated singular value decomposition and principal components analysis of large sparse and dense matrices.
Author: Jim Baglama [aut, cph], Lothar Reichel [aut, cph], B. W. Lewis [aut, cre, cph]
Maintainer: B. W. Lewis <blewis@illposed.net>

Diff between irlba versions 2.2.1 dated 2017-05-17 and 2.3.1 dated 2017-10-18

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More information about irlba at CRAN
Permanent link

Package htm2txt updated to version 2.1.0 with previous version 2.0.0 dated 2017-10-14

Title: Convert Html into Text
Description: Convert a html document to simple plain texts by removing all html tags. This package utilizes regular expressions to strip off html tags. It also offers gettxt() and browse() function, which enables you to get or browse texts at a certain web page.
Author: Sangchul Park [aut, cre]
Maintainer: Sangchul Park <mail@sangchul.com>

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New package ewoc with initial version 0.1.0
Package: ewoc
Type: Package
Title: Escalation with Overdose Control
Version: 0.1.0
Author: Marcio A. Diniz <marcio.diniz@cshs.org>
Maintainer: Marcio A. Diniz <marcio.diniz@cshs.org>
Description: An implementation of a variety of escalation with overdose control designs introduced by Babb, Rogatko and Zacks (1998) <doi:10.1002/(SICI)1097-0258(19980530)17:10%3C1103::AID-SIM793%3E3.0.CO;2-9>. It calculates the next dose as a clinical trial proceeds as well as performs simulations to obtain operating characteristics.
License: GPL (>= 2)
LazyData: TRUE
URL: https://github.com/dnzmarcio/ewoc/
BugReports: https://github.com/dnzmarcio/ewoc/issues
Imports: Formula(>= 1.2-1), rjags(>= 4-6), coda(>= 0.18-1), ggplot2(>= 2.2.0), graphics(>= 3.3.1), stats(>= 3.3.1)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-10-18 16:40:59 UTC; DinizMA
Repository: CRAN
Date/Publication: 2017-10-18 18:10:55 UTC

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Package ciTools updated to version 0.2.1 with previous version 0.2.0 dated 2017-10-10

Title: Confidence or Prediction Intervals, Quantiles, and Probabilities for Statistical Models
Description: Functions to append confidence intervals, prediction intervals, and other quantities of interest to data frames. All appended quantities are for the response variable, after conditioning on the model and covariates. This package has a data frame first syntax that allows for easy piping. Currently supported models include (log-) linear, (log-) linear mixed, and generalized linear models.
Author: John Haman [cre, aut], Matthew Avery [aut], Institute for Defense Analyses [cph]
Maintainer: John Haman <mail@johnhaman.org>

Diff between ciTools versions 0.2.0 dated 2017-10-10 and 0.2.1 dated 2017-10-18

 DESCRIPTION          |    6 +++---
 MD5                  |   12 ++++++------
 R/add_ci_lm.R        |    6 ++----
 R/add_ci_lognormal.R |    6 ++----
 R/add_pi_glm.R       |    9 +++++++--
 R/add_probs_glm.R    |   33 ++++++++++++++++++++-------------
 R/add_quantile_glm.R |    4 ++++
 7 files changed, 44 insertions(+), 32 deletions(-)

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New package adjclust with initial version 0.5.2
Package: adjclust
Maintainer: Pierre Neuvial <pierre.neuvial@math.univ-toulouse.fr>
Authors@R: c(person("Christophe", "Ambroise", role="aut"), person("Shubham", "Chaturvedi", role="aut"), person("Alia", "Dehman", role="aut"), person("Michel", "Koskas", role="aut"), person("Pierre", "Neuvial", role=c("aut", "cre"), email="pierre.neuvial@math.univ-toulouse.fr"), person("Guillem", "Rigaill", role="aut"), person("Nathalie", "Villa-Vialaneix", role="aut"))
Date: 2017-10-16
Version: 0.5.2
License: GPL-3
Title: Adjacency-Constrained Clustering of a Block-Diagonal Similarity Matrix
Description: Implements a constrained version of hierarchical agglomerative clustering, in which each observation is associated to a position, and only adjacent clusters can be merged. Typical application fields in bioinformatics include Genome-Wide Association Studies or Hi-C data analysis, where the similarity between items is a decreasing function of their genomic distance. Taking advantage of this feature, the implemented algorithm is time and memory efficient. This algorithm is described in Chapter 4 of Alia Dehman (2015) <https://hal.archives-ouvertes.fr/tel-01288568v1>.
Depends: R(>= 2.10.0)
Imports: Matrix, matrixStats, snpStats, methods, utils, HiTC,
Suggests: BiocStyle, knitr, testthat, rmarkdown, rioja
VignetteBuilder: knitr
URL: https://github.com/pneuvial/adjclust
BugReports: https://github.com/pneuvial/adjclust/issues
RoxygenNote: 6.0.1.9000
NeedsCompilation: yes
Packaged: 2017-10-17 12:08:09 UTC; pneuvial
Author: Christophe Ambroise [aut], Shubham Chaturvedi [aut], Alia Dehman [aut], Michel Koskas [aut], Pierre Neuvial [aut, cre], Guillem Rigaill [aut], Nathalie Villa-Vialaneix [aut]
Repository: CRAN
Date/Publication: 2017-10-18 18:17:39 UTC

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New package swa with initial version 0.8.1
Package: swa
Title: Subsampling Winner Algorithm for Classification
Version: 0.8.1
Authors@R: c(person("Xingye", "Qiao", email = "qiao@math.binghamton.edu", role = c("aut", "cre")),person("Jiayang", "Sun", email = "jsun@case.edu", role = c("aut")),person("Yiying", "Fan", email = "Y.FAN67@csuohio.edu", role = c("aut")))
Description: This algorithm conducts variable selection in the classification setting. It repeatedly subsamples variables and runs linear discriminant analysis (LDA) on the subsampled variables. Variables are scored based on the AUC and the t-statistics. Variables then enter a competition and the semi-finalist variables will be evaluated in a final round of LDA classification. The algorithm then outputs a list of variable selected. Qiao, Sun and Fan (2017) <http://people.math.binghamton.edu/qiao/swa.html>.
Depends: R (>= 3.3.1), ROCR, reshape, ggplot2
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2017-10-18 13:52:10 UTC; Xingye_Dell_5480
Author: Xingye Qiao [aut, cre], Jiayang Sun [aut], Yiying Fan [aut]
Maintainer: Xingye Qiao <qiao@math.binghamton.edu>
Repository: CRAN
Date/Publication: 2017-10-18 17:10:37 UTC

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New package RonFHIR with initial version 0.1.0
Package: RonFHIR
Type: Package
Title: Read and Search Interface to the 'HL7 FHIR' REST API
Version: 0.1.0
Authors@R: c(person("Sander", "Laverman", role = c("aut", "cre"), email = "s.laverman@furore.com"), person("Furore Health Informatics B.V.", role = c("aut", "cph")))
Description: R on FHIR is an easy to use wrapper around the 'HL7 FHIR' REST API (STU 3). It provides tools to easily read and search resources on a FHIR server and brings the results into the R environment. R on FHIR is based on the FhirClient of the official 'HL7 FHIR .NET API', also made by Furore Health Informatics.
License: BSD 3-clause License + file LICENSE
Imports: R6, httr, jsonlite
Suggests: testthat
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.0)
NeedsCompilation: no
RoxygenNote: 6.0.1
Packaged: 2017-10-18 13:41:22 UTC; Sander
Author: Sander Laverman [aut, cre], Furore Health Informatics B.V. [aut, cph]
Maintainer: Sander Laverman <s.laverman@furore.com>
Repository: CRAN
Date/Publication: 2017-10-18 17:17:52 UTC

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New package rabi with initial version 0.1.0
Package: rabi
Type: Package
Title: Generate Codes to Uniquely and Robustly Identify Individuals for Animal Behavior Studies
Version: 0.1.0
Authors@R: c( person("Andrew", "Burchill", "Taylor", role=c("aut","cre"), email="andrew.burchill@asu.edu"), person("Theodore", "P.", "Pavlic", role="ctb"))
Description: Facilitates the design and generation of optimal color (or symbol) codes that can be used to mark and identify individual animals. These codes are made such that the IDs are robust to partial erasure: even if sections of the code are lost, the entire identity of the animal can be reconstructed. Thus, animal subjects are not confused and no ambiguity is introduced.
License: GPL-3
LazyData: TRUE
VignetteBuilder: knitr
RoxygenNote: 6.0.1
Depends: R (>= 3.2.5)
Imports: numbers, polynom, stringdist, stats, utils
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2017-10-18 17:48:11 UTC; Andrew Burchill
Author: Andrew Taylor Burchill [aut, cre], Theodore Pavlic P. [ctb]
Maintainer: Andrew Taylor Burchill <andrew.burchill@asu.edu>
Repository: CRAN
Date/Publication: 2017-10-18 17:58:21 UTC

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New package NormalizeMets with initial version 0.21
Package: NormalizeMets
Type: Package
Title: Analysis of Metabolomics Data
Version: 0.21
Date: 2017-10-10
Author: Alysha M De Livera, Gavriel Olshansky
Maintainer: Alysha M De Livera <alyshad@unimelb.edu.au>
Description: Metabolomics data are inevitably subject to a component of unwanted variation, due to factors such as batch effects, matrix effects, and confounding biological variation. This package is a collection of functions designed to implement, assess, and choose a suitable normalization method for a given metabolomics study (De Livera et al (2015) <doi:10.1021/ac502439y> ).
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 3.4.0)
Imports: RGtk2, impute, crmn, gplots, limma, plotly, statTarget, Biobase, DiffCorr, e1071, AUC, htmlwidgets, metabolomics, MetNorm, ggplot2, GGally, grid
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-10-18 13:17:24 UTC; alyshad
Repository: CRAN
Date/Publication: 2017-10-18 17:39:54 UTC

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Package simstudy updated to version 0.1.6 with previous version 0.1.5 dated 2017-10-03

Title: Simulation of Study Data
Description: Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR).
Author: Keith Goldfeld [aut, cre]
Maintainer: Keith Goldfeld <Keith.Goldfeld@nyumc.org>

Diff between simstudy versions 0.1.5 dated 2017-10-03 and 0.1.6 dated 2017-10-18

 DESCRIPTION            |   10 +-
 MD5                    |   25 ++++---
 NAMESPACE              |    3 
 NEWS.md                |    5 +
 R/genSpline.R          |only
 R/genSurv.R            |    6 +
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 17 files changed, 489 insertions(+), 98 deletions(-)

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Package HHG updated to version 2.2 with previous version 2.1 dated 2017-08-13

Title: Heller-Heller-Gorfine Tests of Independence and Equality of Distributions
Description: Heller-Heller-Gorfine ('HHG') tests are a set of powerful statistical tests of multivariate k-sample homogeneity and independence. For the univariate case, the package also offers implementations of the 'MinP DDP' and 'MinP ADP' tests, which are consistent against all continuous alternatives but are distribution-free, and are thus much faster to apply.
Author: Barak Brill & Shachar Kaufman, based in part on an earlier implementation by Ruth Heller and Yair Heller.
Maintainer: Barak Brill <barakbri@mail.tau.ac.il>

Diff between HHG versions 2.1 dated 2017-08-13 and 2.2 dated 2017-10-18

 HHG-2.1/HHG/src/hhg_init.c                     |only
 HHG-2.2/HHG/DESCRIPTION                        |   12 ++-
 HHG-2.2/HHG/MD5                                |   26 +++---
 HHG-2.2/HHG/NAMESPACE                          |    3 
 HHG-2.2/HHG/R/HHG.R                            |    4 -
 HHG-2.2/HHG/R/HHGRCPP_API.r                    |only
 HHG-2.2/HHG/R/HHG_univariate.R                 |   98 +++++++++++++++++++++----
 HHG-2.2/HHG/R/RcppExports.R                    |only
 HHG-2.2/HHG/README.md                          |only
 HHG-2.2/HHG/man/hhg.univariate.ind.pvalue.Rd   |    2 
 HHG-2.2/HHG/man/hhg.univariate.ind.stat.Rd     |    2 
 HHG-2.2/HHG/man/hhg.univariate.ks.nulltable.Rd |    2 
 HHG-2.2/HHG/man/hhg.univariate.ks.pvalue.Rd    |    2 
 HHG-2.2/HHG/man/hhg.univariate.ks.stat.Rd      |    2 
 HHG-2.2/HHG/src/RcppExports.cpp                |only
 HHG-2.2/HHG/src/StatsComputer.cpp              |    1 
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 17 files changed, 118 insertions(+), 36 deletions(-)

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New package BayesRS with initial version 0.1.2
Package: BayesRS
Type: Package
Title: Bayes Factors for Hierarchical Linear Models with Continuous Predictors
Version: 0.1.2
Authors@R: c(person(given="Mirko", family="Thalmann", role=c("aut", "cre"), email="mirkothalmann@hotmail.com"), person(given="Marcel", family="Niklaus", role="aut"), person(given="Klaus", family="Oberauer", role="ths"),person(given="John", family="Kruschke", role="ctb"))
Depends: R (>= 3.0.0)
Imports: rjags, ggplot2, metRology, grid, reshape, methods, coda
Suggests: R.rsp
VignetteBuilder: R.rsp
Description: Runs hierarchical linear Bayesian models. Samples from the posterior distributions of model parameters in JAGS (Just Another Gibbs Sampler; Plummer, 2003, <http://mcmc-jags.sourceforge.net/>). Computes Bayes factors for group parameters of interest with the Savage-Dickey density ratio (Wetzels, Raaijmakers, Jakab, Wagenmakers, 2009, <doi:10.3758/PBR.16.4.752>).
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-10-17 15:49:20 UTC; henrik
Author: Mirko Thalmann [aut, cre], Marcel Niklaus [aut], Klaus Oberauer [ths], John Kruschke [ctb]
Maintainer: Mirko Thalmann <mirkothalmann@hotmail.com>
Repository: CRAN
Date/Publication: 2017-10-18 15:08:50 UTC

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New package NNMIS with initial version 1.0.0
Package: NNMIS
Type: Package
Title: Nearest Neighbor Based Multiple Imputation for Survival Data with Missing Covariates
Version: 1.0.0
Date: 2017-10-17
Author: Di Ran, Chiu-Hsieh Hsu, Mandi Yu
Maintainer: Paul Hsu <pablo1639@gmail.com>
Description: Imputation for both missing covariates and censored observations (optional) for survival data with missing covariates by the nearest neighbor based multiple imputation algorithm as described in Hsu et al. (2006) <doi:10.1002/sim.2452>, Long et al. (2012) <doi:10.5705/ss.2010.069>, Hsu et al. (2014) <doi:10.1080/10543406.2014.888444>, and Hsu and Yu (2017) <arXiv:1710.04721>. Note that the current version can only impute for a situation with one missing covariate.
License: LGPL (>= 2)
Depends: R (>= 2.14.0)
Imports: stats, graphics, parallel, survival
LazyData: TRUE
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-10-17 14:58:44 UTC; diran
Repository: CRAN
Date/Publication: 2017-10-18 13:08:54 UTC

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New package LAGOSNE with initial version 1.0.0
Package: LAGOSNE
Title: Interface to the Lake Multi-Scaled Geospatial and Temporal Database
Version: 1.0.0
Authors@R: c( person("Joseph", "Stachelek", email = "stachel2@msu.edu", role = c("aut", "cre"), comment = c(ORCID = c("0000-0002-5924-2464"))), person("Samantha","Oliver", role = c("aut"), comment = c(ORCID = c("0000-0001-5668-1165"))), person("Farzan","Masrour", role = c("aut")) )
URL: https://github.com/cont-limno/LAGOSNE
BugReports: https://github.com/cont-limno/LAGOSNE/issues
Description: Client for programmatic access to the Lake Multi-scaled Geospatial and Temporal database <https://lagoslakes.org>, with functions for accessing lake water quality and ecological context data for the US.
Depends: R (>= 3.3.1)
Imports: dplyr (>= 0.7.0), rappdirs (>= 0.3.1), lazyeval (>= 0.2), purrr (>= 0.2.2.2), magrittr (>= 1.5), sf, curl (>= 2.7.0), stringr (>= 1.2.0)
Suggests: testthat, knitr, rmarkdown, devtools, prettydoc, R.rsp
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
VignetteBuilder: R.rsp, knitr
NeedsCompilation: no
Packaged: 2017-10-17 13:28:23 UTC; jose
Author: Joseph Stachelek [aut, cre] (0000-0002-5924-2464), Samantha Oliver [aut] (0000-0001-5668-1165), Farzan Masrour [aut]
Maintainer: Joseph Stachelek <stachel2@msu.edu>
Repository: CRAN
Date/Publication: 2017-10-18 13:27:10 UTC

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Package HSAR updated to version 0.4.2 with previous version 0.4.0 dated 2016-05-24

Title: Hierarchical Spatial Autoregressive Model
Description: A Hierarchical Spatial Autoregressive Model (HSAR), based on a Bayesian Markov Chain Monte Carlo (MCMC) algorithm ( Dong and Harris (2014) <doi:10.1111/gean.12049> ). The creation of this package was supported by the Economic and Social Research Council (ESRC) through the Applied Quantitative Methods Network: Phase II, grant number ES/K006460/1.
Author: Guanpeng Dong, Richard Harris, Angelos Mimis
Maintainer: Angelos Mimis <mimis@panteion.gr>

Diff between HSAR versions 0.4.0 dated 2016-05-24 and 0.4.2 dated 2017-10-18

 DESCRIPTION         |   12 +++++-----
 MD5                 |   26 +++++++++++------------
 NAMESPACE           |   18 ++++++++--------
 R/RcppExports.R     |   10 ++++-----
 R/hsar.R            |   15 ++++++++-----
 R/sar.R             |    5 ++--
 build/vignette.rds  |binary
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 inst/doc/hsar.R     |    2 -
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 src/RcppExports.cpp |   55 +++++++++++++++++++++++++++++++-------------------
 src/diagnostics.cpp |    2 -
 14 files changed, 120 insertions(+), 98 deletions(-)

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New package GreedySBTM with initial version 1.0
Package: GreedySBTM
Type: Package
Title: Greedy Stochastic Block Transition Models
Version: 1.0
Date: 2017-10-10
Authors@R: person(given = "Riccardo", family = "Rastelli", role = c("aut", "cre"), email = "riccardo.rastelli@wu.ac.at")
Description: Performs clustering on the nodes of an undirected binary dynamic network, by maximising the exact integrated complete likelihood. The greedy algorithm used is described in Rastelli, R. (2017) "Exact integrated completed likelihood maximisation in a stochastic block transition model for dynamic networks" <arXiv:1710.03551>.
License: GPL-3
Imports: Rcpp (>= 0.12.10)
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2017-10-18 08:29:58 UTC; rrastelli
Author: Riccardo Rastelli [aut, cre]
Maintainer: Riccardo Rastelli <riccardo.rastelli@wu.ac.at>
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2017-10-18 13:52:06 UTC

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Package satellite updated to version 1.0.1 with previous version 1.0.0 dated 2017-08-03

Title: Handling and Manipulating Remote Sensing Data
Description: Herein, we provide a broad variety of functions which are useful for handling, manipulating, and visualizing satellite-based remote sensing data. These operations range from mere data import and layer handling (eg subsetting), over Raster* typical data wrangling (eg crop, extend), to more sophisticated (pre-)processing tasks typically applied to satellite imagery (eg atmospheric and topographic correction). This functionality is complemented by a full access to the satellite layers' metadata at any stage and the documentation of performed actions in a separate log file. Currently available sensors include Landsat 4-5 (TM), 7 (ETM+), and 8 (OLI/TIRS Combined), and additional compatibility is ensured for the Landsat Global Land Survey data set. Moreover, support for Terra and Aqua-MODIS as well as PROBA-V is expected to arrive shortly.
Author: Thomas Nauss, Hanna Meyer, Tim Appelhans, Florian Detsch
Maintainer: Florian Detsch <fdetsch@web.de>

Diff between satellite versions 1.0.0 dated 2017-08-03 and 1.0.1 dated 2017-10-18

 DESCRIPTION                                                         |   27 
 LICENSE                                                             | 1350 +++++-----
 MD5                                                                 |  171 -
 NAMESPACE                                                           |  218 -
 NEWS                                                                |   83 
 NEWS.md                                                             |   83 
 R/AAAsatelliteClasses.R                                             |  132 
 R/RcppExports.R                                                     |   30 
 R/alignGeometry.R                                                   |  216 -
 R/brick.R                                                           |    2 
 R/calcAtmosCorr.R                                                   |    2 
 R/calcDODN.R                                                        |    4 
 R/calcEarthSunDist.R                                                |  138 -
 R/calcPathRadDOS.R                                                  |    2 
 R/calcTOAIrradModel.R                                               |    2 
 R/calcTOAIrradTable.R                                               |  256 -
 R/calcTopoCorr.R                                                    |    2 
 R/compFilePathLandsat.R                                             |   17 
 R/compMetaLandsat.R                                                 |   43 
 R/convRef2RadLinear.R                                               |   58 
 R/crop.R                                                            |    2 
 R/demTools.R                                                        |    2 
 R/extend.R                                                          |  152 -
 R/plot.R                                                            |  168 -
 R/print.R                                                           |   32 
 R/satInfo.R                                                         |    2 
 R/satellite-package.R                                               |    2 
 R/satellite.R                                                       |  238 -
 R/show.R                                                            |   12 
 R/stack.R                                                           |    2 
 R/subset.R                                                          |   11 
 README.md                                                           |   70 
 build/vignette.rds                                                  |binary
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 inst/doc/satellite.R                                                |only
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 inst/extdata/LC08_L1TP_195025_20130707_20170503_01_T1_MTL.txt       |  450 +--
 inst/extdata/LE07_L1TP_195025_20010730_20170204_01_T1_MTL.txt       |  480 +--
 inst/testdata/LC8/LC81950252013188LGN00_MTL.txt                     |  412 +--
 inst/testdata/LE7/LE71950252001211EDC00_MTL.txt                     |  376 +-
 inst/testdata/LT05/LT05_L1TP_167055_20000309_20161214_01_T1_MTL.txt |  388 +-
 man/Satellite-class.Rd                                              |   18 
 man/SatelliteInfo-class.Rd                                          |   46 
 man/SatelliteLayers-class.Rd                                        |   30 
 man/SatelliteLog-class.Rd                                           |   30 
 man/SatelliteMetaData-class.Rd                                      |   30 
 man/alignGeometry.Rd                                                |  118 
 man/brick.Rd                                                        |   60 
 man/calcAtmosCorr.Rd                                                |  304 +-
 man/calcDODN.Rd                                                     |  104 
 man/calcEarthSunDist.Rd                                             |  114 
 man/calcPathRadDOS.Rd                                               |  308 +-
 man/calcTOAIrradModel.Rd                                            |  184 -
 man/calcTOAIrradRadRef.Rd                                           |  148 -
 man/calcTOAIrradTable.Rd                                            |  150 -
 man/calcTopoCorr.Rd                                                 |  144 -
 man/compFilePathLandsat.Rd                                          |   88 
 man/compMetaLandsat.Rd                                              |  116 
 man/convRad2BT.Rd                                                   |   96 
 man/convRad2Ref.Rd                                                  |  134 
 man/convRef2RadLinear.Rd                                            |   68 
 man/convSC2Rad.Rd                                                   |  132 
 man/convSC2Ref.Rd                                                   |  144 -
 man/crop.Rd                                                         |  116 
 man/demTools.Rd                                                     |  100 
 man/extend.Rd                                                       |  100 
 man/l7.Rd                                                           |   44 
 man/l8.Rd                                                           |   46 
 man/lutInfo.Rd                                                      |  228 -
 man/maskInvarFeatures.Rd                                            |  152 -
 man/names.Rd                                                        |   66 
 man/plot.Rd                                                         |   88 
 man/satInfo.Rd                                                      |  752 ++---
 man/satellite-package.Rd                                            |   52 
 man/satellite.Rd                                                    |  126 
 man/stack.Rd                                                        |   60 
 man/subset.Rd                                                       |   89 
 tests/testthat/test-calcAtmosCorr.R                                 |   25 
 tests/testthat/test-calcEarthSunDist.R                              |   36 
 tests/testthat/test-calcTOAIrradTable.R                             |   84 
 tests/testthat/test-compMetaLandsat.R                               |  243 -
 tests/testthat/test-extend.R                                        |   64 
 vignettes/landsat-calibration.Rmd                                   |    5 
 vignettes/satellite.Rmd                                             |   38 
 88 files changed, 5544 insertions(+), 5458 deletions(-)

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New package rroad with initial version 0.0.4
Package: rroad
Type: Package
Title: Road Condition Analysis
Version: 0.0.4
Date: 2017-10-12
Authors@R: c( person("Viliam", "Simko", email = "viliam.simko@gmail.com", role = c("cre", "aut")), person("Kevin", "Laubis", email = "laubis@fzi.de", role = "aut"))
Description: Computation of the International Roughness Index (IRI) given a longitudinal road profile. The IRI can be calculated for a single road segment or for a sequence of segments with a fixed length (e. g. 100m). For the latter, an overlap of the segments can be selected. The IRI and likewise the algorithms for its determination are defined in Sayers, Michael W; Gillespie, Thomas D; Queiroz, Cesar A.V. 1986. The International Road Roughness Experiment (IRRE) : establishing correlation and a calibration standard for measurements. World Bank technical paper; no. WTP 45. Washington, DC : The World Bank. (ISBN 0-8213-0589-1) available from <http://documents.worldbank.org/curated/en/326081468740204115>.
License: MIT + file LICENSE
URL: http://github.com/vsimko/rroad
BugReports: http://github.com/vsimko/rroad/issues
LazyData: yes
Suggests: testthat, knitr, rmarkdown, zoo, biwavelet, dplyr
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-10-18 08:44:15 UTC; vlx
Author: Viliam Simko [cre, aut], Kevin Laubis [aut]
Maintainer: Viliam Simko <viliam.simko@gmail.com>
Repository: CRAN
Date/Publication: 2017-10-18 12:28:49 UTC

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Package mathpix updated to version 0.2.0 with previous version 0.1.0 dated 2017-09-27

Title: Support for the 'Mathpix' API (Image to 'LaTeX')
Description: Given an image of a formula (typeset or handwritten) this package provides calls to the 'Mathpix' service to produce the 'LaTeX' code which should generate that image, and pastes it into a (e.g. an 'rmarkdown') document. See <https://docs.mathpix.com/> for full details. 'Mathpix' is an external service and use of the API is subject to their terms and conditions.
Author: Jonathan Carroll [aut, cre] (0000-0002-1404-5264)
Maintainer: Jonathan Carroll <rpkg@jcarroll.com.au>

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Package FlowRegEnvCost updated to version 0.1.1 with previous version 0.1.0 dated 2017-10-09

Title: The Environmental Costs of Flow Regulation
Description: An application to calculate the daily environmental costs of river flow regulation by dams based on García de Jalon et al. 2017 <doi:10.1007/s11269-017-1663-0>.
Author: Silvestre Garcia de Jalon; Javier Martinez-Lopez; Marta Gonzalez del Tanago; Carlos Alonso; Diego Garcia de Jalon
Maintainer: Javier Martinez-Lopez <javi.martinez.lopez@gmail.com>

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Package SimInf updated to version 5.1.0 with previous version 5.0.0 dated 2017-06-13

Title: A Framework for Data-Driven Stochastic Disease Spread Simulations
Description: Livestock movements are important for the spread of many infectious diseases between herds. The package provides an efficient and flexible framework for stochastic disease spread modelling that integrates within-herd disease dynamics as continuous-time Markov chains and livestock movements between herds as scheduled events. The core simulation solver is implemented in C and uses 'OpenMP' (if available) to divide work over multiple processors. The package contains template models and can be extended with user defined models.
Author: Stefan Widgren (National Veterinary Institute, Sweden and Uppsala University, Sweden), Pavol Bauer (Uppsala University, Sweden), Stefan Engblom (Uppsala University, Sweden)
Maintainer: Stefan Widgren <stefan.widgren@gmail.com>

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Package ctsem updated to version 2.5.0 with previous version 2.4.0 dated 2017-05-17

Title: Continuous Time Structural Equation Modelling
Description: A multivariate continuous (and discrete) time dynamic modelling package for panel and time series data, using linear stochastic differential equations. Contains a faster frequentist set of functions using OpenMx for single subject and mixed-effects (random intercepts only) structural equation models, or a hierarchical Bayesian implementation using Stan that allows for random effects over all model parameters. Allows for modelling of multiple noisy measurements of multiple stochastic processes, time varying input / event covariates, and time invariant covariates used to predict the parameters.
Author: Charles Driver [aut, cre, cph], Manuel Voelkle [aut, cph], Han Oud [aut, cph]
Maintainer: Charles Driver <driver@mpib-berlin.mpg.de>

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Package areaplot updated to version 1.2-0 with previous version 1.1-0 dated 2017-10-10

Title: Plot Stacked Areas and Confidence Bands as Filled Polygons
Description: Plot stacked areas and confidence bands as filled polygons, or add polygons to existing plots. A variety of input formats are supported, including vectors, matrices, data frames, formulas, etc.
Author: Arni Magnusson [aut, cre]
Maintainer: Arni Magnusson <arni.magnusson@ices.dk>

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Package JMbayes updated to version 0.8-69 with previous version 0.8-68 dated 2017-10-02

Title: Joint Modeling of Longitudinal and Time-to-Event Data under a Bayesian Approach
Description: Shared parameter models for the joint modeling of longitudinal and time-to-event data using MCMC; Dimitris Rizopoulos (2016) <doi:10.18637/jss.v072.i07>.
Author: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>
Maintainer: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>

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Package geoRglm updated to version 0.9-11 with previous version 0.9-8 dated 2015-04-27

Title: A Package for Generalised Linear Spatial Models
Description: Functions for inference in generalised linear spatial models. The posterior and predictive inference is based on Markov chain Monte Carlo methods. Package geoRglm is an extension to the package geoR, which must be installed first.
Author: Ole F. Christensen [aut, cre], Paulo J. Ribeiro Jr [aut]
Maintainer: Ole F. Christensen <OleF.Christensen@mbg.au.dk>

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Package gcerisk updated to version 17.10.17 with previous version 17.8.7 dated 2017-08-08

Title: Generalized Competing Event Model
Description: Generalized competing event model based on Cox PH model and Fine-Gray model. This function is designed to develop optimized risk-stratification methods for competing risks data, such as described in: 1. Carmona R, Gulaya S, Murphy JD, Rose BS, Wu J, Noticewala S,McHale MT, Yashar CM, Vaida F, and Mell LK (2014) <DOI:10.1016/j.ijrobp.2014.03.047>. 2. Carmona R, Zakeri K, Green G, Hwang L, Gulaya S, Xu B, Verma R, Williamson CW, Triplett DP, Rose BS, Shen H, Vaida F, Murphy JD, and Mell LK (2016) <DOI:10.1200/JCO.2015.65.0739>. 3. Lunn, Mary, and Don McNeil (1995) <DOI:10.2307/2532940>.
Author: Hanjie Shen <has072@ucsd.edu>, Ruben Carmona <ruben.carmona13@gmail.com>, Loren Mell <lmell@ucsd.edu>
Maintainer: Hanjie Shen <shenhanjie0418@gmail.com>

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Tue, 17 Oct 2017

Package tempR updated to version 0.9.9.12 with previous version 0.9.9.10 dated 2017-03-08

Title: Temporal Sensory Data Analysis
Description: Analysis and visualization of data from temporal sensory methods, including for temporal check-all-that-apply (TCATA) and temporal dominance of sensations (TDS).
Author: J. C. Castura [aut, cre]
Maintainer: J. C. Castura <jcastura@compusense.com>

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Package rarhsmm updated to version 1.0.5 with previous version 1.0.4 dated 2017-05-07

Title: Regularized Autoregressive Hidden Semi Markov Model
Description: Fit Gaussian hidden Markov (or semi-Markov) models with / without autoregressive coefficients and with / without regularization. The fitting algorithm for the hidden Markov model is illustrated by Rabiner (1989) <doi:10.1109/5.18626>. The shrinkage estimation on the covariance matrices is based on the method by Ledoit et al. (2004) <doi:10.1016/S0047-259X(03)00096-4>. The shrinkage estimation on the autoregressive coefficients uses the elastic net shrinkage detailed in Zou et al. (2005) <doi:10.1111/j.1467-9868.2005.00503.x>.
Author: Zekun (Jack) Xu, Ye Liu
Maintainer: Zekun Xu <zekunxu@gmail.com>

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Package MRS updated to version 1.2.2 with previous version 1.2.1 dated 2016-07-21

Title: Multi-Resolution Scanning for Cross-Sample Differences
Description: An implementation of the MRS algorithm for comparison across distributions. The model is based on a nonparametric process taking the form of a Markov model that transitions between a "null" and an "alternative" state on a multi-resolution partition tree of the sample space. MRS effectively detects and characterizes a variety of underlying differences. These differences can be visualized using several plotting functions.
Author: Jacopo Soriano and Li Ma
Maintainer: Jacopo Soriano <jsoriano.stat@gmail.com>

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Package LZeroSpikeInference updated to version 1.0.3 with previous version 1.0.1 dated 2017-05-18

Title: Exact Spike Train Inference via L0 Optimization
Description: An implementation of algorithms described in Jewell and Witten (2017) <arXiv:1703.08644>.
Author: Sean Jewell [aut, cre]
Maintainer: Sean Jewell <swjewell@uw.edu>

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Package gamRR updated to version 0.2.0 with previous version 0.1.0 dated 2017-05-13

Title: Calculate the RR for the GAM
Description: To calculate the relative risk (RR) for the generalized additive model.
Author: Zhicheng Du, Yuantao Hao
Maintainer: Zhicheng Du<dgdzc@hotmail.com>

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Package drake updated to version 4.3.0 with previous version 4.2.0 dated 2017-09-29

Title: Data Frames in R for Make
Description: A solution for reproducible code and high-performance computing.
Author: William Michael Landau [aut, cre], Alex Axthelm [ctb], Jasper Clarkberg [ctb], Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@lilly.com>

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Package divo updated to version 1.0.0 with previous version 0.1.2 dated 2016-01-07

Title: Tools for Analysis of Diversity and Similarity in Biological Systems
Description: A set of tools for empirical analysis of diversity (a number and frequency of different types in population) and similarity (a number and frequency of shared types in two populations) in biological or ecological systems.
Author: Christoph Sadee, Maciej Pietrzak, Michal Seweryn, Grzegorz Rempala
Maintainer: Maciej Pietrzak <pietrzak.20@osu.edu>

Diff between divo versions 0.1.2 dated 2016-01-07 and 1.0.0 dated 2017-10-17

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Package knockoff updated to version 0.3.0 with previous version 0.2.1 dated 2015-04-15

Title: The Knockoff Filter for Controlled Variable Selection
Description: The knockoff filter is a general procedure for controlling the false discovery rate (FDR) when performing variable selection. For more information, see the website below and the accompanying paper: Candes et al., "Panning for Gold: Model-free Knockoffs for High-dimensional Controlled Variable Selection", 2016, <arXiv:1610.02351>.
Author: Rina Foygel Barber [ctb] (Development of the original fixed-design Knockoffs), Emmanuel Candes [ctb] (Development of Model-Free Knockoffs and original fixed-design Knockoffs), Lucas Janson [ctb] (Development of Model-Free Knockoffs), Evan Patterson [aut] (Original R package for the original fixed-design Knockoffs), Matteo Sesia [aut, cre] (R package for Model-Free Knockoffs)
Maintainer: Matteo Sesia <msesia@stanford.edu>

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Package fbar updated to version 0.3.3 with previous version 0.1.23 dated 2017-01-14

Title: An Extensible Approach to Flux Balance Analysis
Description: A simple package for Flux Balance Analysis and related metabolic modeling techniques. Functions are provided for: parsing models in tabular format, converting parsed metabolic models to input formats for common linear programming solvers, and evaluating and applying gene-protein-reaction mappings. In addition, there are wrappers to parse a model, select a solver, find the metabolic fluxes, and return the results applied to the original model. Compared to other packages in this field, this package puts a much heavier focus on providing reusable components that can be used in the design of new implementation of new techniques, in particular those that involve large parameter sweeps.
Author: Max Conway [aut, cre]
Maintainer: Max Conway <conway.max1@gmail.com>

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Package EasyMx updated to version 0.2 with previous version 0.1-3 dated 2017-05-02

Title: Easy Model-Builder Functions for 'OpenMx'
Description: Utilities for building certain kinds of common matrices and models in the extended structural equation modeling package, 'OpenMx'.
Author: Michael D. Hunter [aut, cre], Joshua N. Pritikin [ctb]
Maintainer: Michael D. Hunter <mhunter.ou@gmail.com>

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Package vennplot updated to version 1.0 with previous version 0.9.02 dated 2017-04-21

Title: Venn Diagrams in 2D and 3D
Description: Calculate and plot Venn diagrams in 2D and 3D.
Author: Zehao Xu [aut, cre], R. Wayne Oldford [aut], Martin Lysy [ctb]
Maintainer: Zehao Xu <z267xu@uwaterloo.ca>

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Package vcrpart updated to version 1.0-1 with previous version 1.0-0 dated 2017-08-22

Title: Tree-Based Varying Coefficient Regression for Generalized Linear and Ordinal Mixed Models
Description: Recursive partitioning for varying coefficient generalized linear models and ordinal linear mixed models. Special features are coefficient-wise partitioning, non-varying coefficients and partitioning of time-varying variables in longitudinal regression.
Author: Reto Buergin [aut, cre, cph], Gilbert Ritschard [ctb, ths]
Maintainer: Reto Buergin <rbuergin@gmx.ch>

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Package randomForestSRC updated to version 2.5.1 with previous version 2.5.0 dated 2017-08-07

Title: Random Forests for Survival, Regression, and Classification (RF-SRC)
Description: A unified treatment of Breiman's random forests for survival, regression and classification problems based on Ishwaran and Kogalur's random survival forests (RSF) package. Now extended to include multivariate and unsupervised forests. Also includes quantile regression forests for univariate and multivariate training/testing settings. The package runs in both serial and parallel (OpenMP) modes.
Author: Hemant Ishwaran <hemant.ishwaran@gmail.com>, Udaya B. Kogalur <ubk@kogalur.com>
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>

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Package NAM updated to version 1.5.4 with previous version 1.5.3 dated 2017-08-15

Title: Nested Association Mapping
Description: Designed for association studies in nested association mapping (NAM) panels, experimental and random panels. It includes tools for genome-wide associations of multiple populations, marker quality control, population genetics analysis, genome-wide prediction, solving mixed models and finding variance components through likelihood and Bayesian methods.
Author: Alencar Xavier, William Muir, Katy Rainey, Shizhong Xu.
Maintainer: Alencar Xavier <alenxav@gmail.com>

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Package mregions updated to version 0.1.6 with previous version 0.1.4 dated 2016-12-07

Title: Marine Regions Data from 'Marineregions.org'
Description: Tools to get marine regions data from <http://www.marineregions.org/>. Includes tools to get region metadata, as well as data in 'GeoJSON' format, as well as Shape files. Use cases include using data downstream to visualize 'geospatial' data by marine region, mapping variation among different regions, and more.
Author: Scott Chamberlain [aut, cre], Francois Michonneau [ctb], Pieter Provoost [ctb], Michael Sumner [ctb]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package httpcache updated to version 1.1.0 with previous version 1.0.2 dated 2017-08-28

Title: Query Cache for HTTP Clients
Description: In order to improve performance for HTTP API clients, 'httpcache' provides simple tools for caching and invalidating cache. It includes the HTTP verb functions GET, PUT, PATCH, POST, and DELETE, which are drop-in replacements for those in the 'httr' package. These functions are cache-aware and provide default settings for cache invalidation suitable for RESTful APIs; the package also enables custom cache-management strategies. Finally, 'httpcache' includes a basic logging framework to facilitate the measurement of HTTP request time and cache performance.
Author: Neal Richardson [aut, cre]
Maintainer: Neal Richardson <neal.p.richardson@gmail.com>

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Package ggimage updated to version 0.0.6 with previous version 0.0.4 dated 2017-03-29

Title: Use Image in 'ggplot2'
Description: Supports image files and graphic objects to be visualized in 'ggplot2' graphic system.
Author: Guangchuang Yu [aut, cre] (0000-0002-6485-8781)
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package geoops updated to version 0.1.2 with previous version 0.1.0 dated 2017-10-14

Title: 'GeoJSON' Topology Calculations and Operations
Description: Tools for doing calculations and manipulations on 'GeoJSON', a 'geospatial' data interchange format (<https://tools.ietf.org/html/rfc7946>). 'GeoJSON' is also valid 'JSON'.
Author: Scott Chamberlain [aut, cre], Niels Lohmann [cph]
Maintainer: Scott Chamberlain <myrmecocystus+r@gmail.com>

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Package snht updated to version 1.0.5 with previous version 1.0.4 dated 2016-04-03

Title: Standard Normal Homogeneity Test
Description: Implementation of robust and non-robust Standard Normal Homogeneity Test (SNHT) for changepoint detection. This test statistic is equal sided, as proposed in "Homogenization of Radiosonde Temperature Time Series Using Innovation Statistics" by Haimberger, L., 2007. However, the statistic contains an estimate of sigma^2 in the denominator instead of sigma, which seems to be a more appropriate value (based on the paper "Homogenization of Swedish temperature data. Part I: Homogeneity test for linear trends." by Alexandersson, H., and A. Moberg, 1997).
Author: Josh Browning [aut, cre], Carina Schneider [aut]
Maintainer: Josh Browning <rockclimber112358@gmail.com>

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Package tidycensus updated to version 0.3 with previous version 0.2 dated 2017-08-09

Title: Load US Census Boundary and Attribute Data as 'tidyverse' and 'sf'-Ready Data Frames
Description: An integrated R interface to the decennial US Census and American Community Survey APIs and the US Census Bureau's geographic boundary files. Allows R users to return Census and ACS data as tidyverse-ready data frames, and optionally returns a list-column with feature geometry for many geographies.
Author: Kyle Walker [aut, cre], Kris Eberwein [ctb]
Maintainer: Kyle Walker <kyle.walker@tcu.edu>

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Package ivmodel updated to version 1.7.1 with previous version 1.7 dated 2017-08-18

Title: Statistical Inference and Sensitivity Analysis for Instrumental Variables Model
Description: Contains functions for carrying out instrumental variable estimation of causal effects, including power analysis, sensitivity analysis, and diagnostics.
Author: Yang Jiang, Hyunseung Kang, Dylan Small, and Qingyuan Zhao
Maintainer: Hyunseung Kang <hyunseung@stat.wisc.edu>

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Package OpenML updated to version 1.7 with previous version 1.6 dated 2017-08-14

Title: Open Machine Learning and Open Data Platform
Description: We provide an R interface to 'OpenML.org' which is an online machine learning platform where researchers can access open data, download and upload data sets, share their machine learning tasks and experiments and organize them online to work and collaborate with other researchers. The R interface allows to query for data sets with specific properties, and allows the downloading and uploading of data sets, tasks, flows and runs. See <https://www.openml.org/guide/api> for more information.
Author: Giuseppe Casalicchio <giuseppe.casalicchio@stat.uni-muenchen.de>, Bernd Bischl <bernd_bischl@gmx.net>, Dominik Kirchhoff <dom.kirchhoff@gmail.com>, Michel Lang <michellang@gmail.com>, Benjamin Hofner <benjamin.hofner@fau.de>, Jakob Bossek <j.bossek@gmail.com>, Pascal Kerschke <kerschke@uni-muenster.de>, Joaquin Vanschoren <joaquin.vanschoren@gmail.com>
Maintainer: Giuseppe Casalicchio <giuseppe.casalicchio@stat.uni-muenchen.de>

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Package mvord updated to version 0.1.0 with previous version 0.0.1 dated 2017-09-07

Title: Multivariate Ordinal Regression Models
Description: A flexible framework for fitting multivariate ordinal regression models with composite likelihood methods.
Author: Rainer Hirk [aut, cre], Kurt Hornik [aut], Laura Vana [aut], Alan Genz [ctb] (Fortran Code)
Maintainer: Rainer Hirk <rhirk@wu.ac.at>

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Package dbstats updated to version 1.0.5 with previous version 1.0.4 dated 2014-12-10

Title: Distance-Based Statistics
Description: Prediction methods where explanatory information is coded as a matrix of distances between individuals. Distances can either be directly input as a distances matrix, a squared distances matrix, an inner-products matrix or computed from observed predictors.
Author: Boj, Eva <evaboj@ub.edu>, Caballe, Adria <adria.caballe@upc.edu>, Delicado, Pedro <pedro.delicado@upc.edu> and Fortiana, Josep <fortiana@ub.edu>.
Maintainer: Josep Fortiana <fortiana@ub.edu>

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Package devRate updated to version 0.1.4 with previous version 0.1.3 dated 2017-08-07

Title: Quantify the Relationship Between Development Rate and Temperature in Ectotherms
Description: A set of functions to quantify the relationship between development rate and temperature. The package comprises a set of models and estimated parameters borrowed from a literature review in ectotherms (mostly arthropods).
Author: Francois Rebaudo [aut, cre], Quentin Struelens [aut]
Maintainer: Francois Rebaudo <francois.rebaudo@ird.fr>

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Package RegularizedSCA updated to version 0.5.0 with previous version 0.4.2 dated 2017-06-25

Title: Regularized Simultaneous Component Based Data Integration
Description: It performs regularized simultaneous component based data integration for multiblock data.
Author: Zhengguo Gu [aut, cre], Katrijn Van Deun [aut]
Maintainer: Zhengguo Gu <z.gu@uvt.nl>

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New package WeightIt with initial version 0.1.0
Package: WeightIt
Type: Package
Title: Weighting for Covariate Balance in Observational Studies
Version: 0.1.0
Author: Noah Greifer [aut, cre]
Maintainer: Noah Greifer <noah@unc.edu>
Description: Generates weights to form equivalent groups in observational studies by easing and extending the functionality of the R packages 'twang' (Ridgeway et al., 2017) <https://CRAN.R-project.org/package=twang> for generalized boosted modeling, 'CBPS' (Fong, Ratkovic, & Imai, 2017) <https://CRAN.R-project.org/package=CBPS> for covariate balancing propensity score weighting, 'ebal' (Hainbueller, 2014) <https://CRAN.R-project.org/package=ebal> for entropy balancing, and 'ATE' (Haris & Chan, 2015) <https://CRAN.R-project.org/package=ATE> for empirical balancing calibration weighting. Also allows for assessment of weights and checking of covariate balance by interfacing directly with 'cobalt' (Greifer, 2017) <https://CRAN.R-project.org/package=cobalt>.
Depends: R (>= 3.4.0)
Imports: cobalt (>= 3.0.0)
Suggests: twang (>= 1.5), CBPS (>= 0.14), ebal (>= 0.1-6), ATE (>= 0.2.0), mlogit (>= 0.2-4), MNP (>= 3.1-0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Date: 2017-10-16
NeedsCompilation: no
Packaged: 2017-10-17 02:32:08 UTC; NoahGreifer
Repository: CRAN
Date/Publication: 2017-10-17 11:06:27 UTC

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Package clustMixType updated to version 0.1-29 with previous version 0.1-28 dated 2017-09-04

Title: k-Prototypes Clustering for Mixed Variable-Type Data
Description: Functions to perform k-prototypes partitioning clustering for mixed variable-type data according to Z.Huang (1998): Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Variables, Data Mining and Knowledge Discovery 2, 283-304, <DOI:10.1023/A:1009769707641>.
Author: Gero Szepannek
Maintainer: Gero Szepannek <gero.szepannek@web.de>

Diff between clustMixType versions 0.1-28 dated 2017-09-04 and 0.1-29 dated 2017-10-17

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New package RZigZag with initial version 0.1.3
Package: RZigZag
Type: Package
Title: Zig-Zag Sampler
Version: 0.1.3
Date: 2017-10-17
Author: Joris Bierkens
Maintainer: Joris Bierkens <joris.bierkens@tudelft.nl>
Description: Implements the Zig-Zag algorithm with subsampling and control variates (ZZ-CV) of (Bierkens, Fearnhead, Roberts, 2016) <arXiv:1607.03188> as applied to Bayesian logistic regression, as well as basic Zig-Zag for a Gaussian target distribution.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.3)
LinkingTo: Rcpp, RcppEigen
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-10-17 08:30:42 UTC; joris
Repository: CRAN
Date/Publication: 2017-10-17 10:29:39 UTC

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New package crosswalkr with initial version 0.1.1
Package: crosswalkr
Title: Rename and Encode Data Frames Using External Crosswalk Files
Version: 0.1.1
Authors@R: person("Benjamin", "Skinner", email = "btskinner@virginia.edu", role = c("aut", "cre"))
Description: A pair of functions for renaming and encoding data frames using external crosswalk files. It is especially useful when constructing master data sets from multiple smaller data sets that do not name or encode variables consistently across files. Based on similar commands in 'Stata'.
URL: https://github.com/btskinner/crosswalkr
BugReports: https://github.com/btskinner/crosswalkr/issues
Depends: R (>= 3.3.0)
Imports: dplyr, haven, labelled, methods, readr, readxl, tibble
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-10-17 10:04:09 UTC; benski
Author: Benjamin Skinner [aut, cre]
Maintainer: Benjamin Skinner <btskinner@virginia.edu>
Repository: CRAN
Date/Publication: 2017-10-17 10:45:19 UTC

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Package scorecard updated to version 0.1.1 with previous version 0.1.0 dated 2017-09-16

Title: Credit Risk Scorecard
Description: Makes the development of credit risk scorecard easily and efficiently by providing functions such as information value, variable filter, optimal woe binning, scorecard scaling and performance evaluation etc. The references including: 1. Refaat, M. (2011, ISBN: 9781447511199). Credit Risk Scorecard: Development and Implementation Using SAS. 2. Siddiqi, N. (2006, ISBN: 9780471754510). Credit risk scorecards. Developing and Implementing Intelligent Credit Scoring.
Author: Shichen Xie
Maintainer: Shichen Xie <xie@shichen.name>

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Package red updated to version 1.3.0 with previous version 1.2.1 dated 2017-10-06

Title: IUCN Redlisting Tools
Description: Includes algorithms to facilitate the assessment of extinction risk of species according to the IUCN (International Union for Conservation of Nature, see <http://www.iucn.org> for more information) red list criteria.
Author: Pedro Cardoso
Maintainer: Pedro Cardoso <pedro.cardoso@helsinki.fi>

Diff between red versions 1.2.1 dated 2017-10-06 and 1.3.0 dated 2017-10-17

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New package data360r with initial version 1.0.1
Package: data360r
Type: Package
Title: Wrapper for TC/Govdata360 API
Version: 1.0.1
Author: Authors@R: c( person("Ma. Regina Paz", "Onglao", email = "monglao@ifc.org", role = ["cre", "aut"]), person("Trade and Competitiveness Global Practice", "World Bank Group", email = "tcdata360@worldbank.org", role = "cph"))
Maintainer: Ma. Regina Paz S. Onglao <monglao@ifc.org>
Description: Makes it easy to engage with the Application Program Interface (API) of the TCdata360 and Govdata360 platforms at <https://tcdata360.worldbank.org/> and <https://govdata360.worldbank.org/>, respectively. These APIs provide access to over 5000 trade, competitiveness, and governance indicator data, metadata, and related information from sources both inside and outside the World Bank Group. Package functions include easier download of data sets, metadata, and related information, as well as searching based on user-inputted query.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/mrpsonglao/data360r
Date: 2017-10-13
Imports: data.table, reshape2, jsonlite, utils, curl
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-10-16 18:56:11 UTC; mrpso
Repository: CRAN
Date/Publication: 2017-10-17 09:04:18 UTC

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Package reddPrec updated to version 0.4.0 with previous version 0.3 dated 2017-01-30

Title: Reconstruction of Daily Data - Precipitation
Description: Computes quality control for daily precipitation datasets, reconstructs the original series by estimating precipitation in missing values, creates new series in a specified pair of coordinates and creates grids.
Author: Roberto Serrano-Notivoli
Maintainer: Roberto Serrano-Notivoli <rs@unizar.es>

Diff between reddPrec versions 0.3 dated 2017-01-30 and 0.4.0 dated 2017-10-17

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Mon, 16 Oct 2017

Package vtreat updated to version 1.0.1 with previous version 1.0.0 dated 2017-10-04

Title: A Statistically Sound 'data.frame' Processor/Conditioner
Description: A 'data.frame' processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. 'vtreat' prepares variables so that data has fewer exceptional cases, making it easier to safely use models in production. Common problems 'vtreat' defends against: 'Inf', 'NA', too many categorical levels, rare categorical levels, and new categorical levels (levels seen during application, but not during training). 'vtreat::prepare' should be used as you would use 'model.matrix'.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between vtreat versions 1.0.0 dated 2017-10-04 and 1.0.1 dated 2017-10-16

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Package TSclust updated to version 1.2.4 with previous version 1.2.3 dated 2014-11-18

Title: Time Series Clustering Utilities
Description: A set of measures of dissimilarity between time series to perform time series clustering. Metrics based on raw data, on generating models and on the forecast behavior are implemented. Some additional utilities related to time series clustering are also provided, such as clustering algorithms and cluster evaluation metrics.
Author: Pablo Montero Manso, José Antonio Vilar
Maintainer: Pablo Montero <pmontm@gmail.com>

Diff between TSclust versions 1.2.3 dated 2014-11-18 and 1.2.4 dated 2017-10-16

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Package sjstats updated to version 0.12.0 with previous version 0.11.2 dated 2017-09-28

Title: Collection of Convenient Functions for Common Statistical Computations
Description: Collection of convenient functions for common statistical computations, which are not directly provided by R's base or stats packages. This package aims at providing, first, shortcuts for statistical measures, which otherwise could only be calculated with additional effort (like standard errors or root mean squared errors). Second, these shortcut functions are generic (if appropriate), and can be applied not only to vectors, but also to other objects as well (e.g., the Coefficient of Variation can be computed for vectors, linear models, or linear mixed models; the r2()-function returns the r-squared value for 'lm', 'glm', 'merMod' or 'lme' objects). The focus of most functions lies on summary statistics or fit measures for regression models, including generalized linear models and mixed effects models. However, some of the functions also deal with other statistical measures, like Cronbach's Alpha, Cramer's V, Phi etc.
Author: Daniel Lüdecke <d.luedecke@uke.de>
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package sicegar updated to version 0.2.2 with previous version 0.2 dated 2017-07-11

Title: Analysis of Single-Cell Viral Growth Curves
Description: Aims to quantify time intensity data by using sigmoidal and double sigmoidal curves. It fits straight lines, sigmoidal, and double sigmoidal curves on to time vs intensity data. Then all the fits are used to make decision on which model (sigmoidal, double sigmoidal, no signal or ambiguous) best describes the data. No signal means the intensity does not reach a high enough point or does not change at all over time. Sigmoidal means intensity starts from a small number than climbs to a maximum. Double sigmoidal means intensity starts from a small number, climbs to a maximum then starts to decay. After the decision between those four options, the algorithm gives the sigmoidal (or double sigmoidal) associated parameter values that quantifies the time intensity curve. The origin of the package name came from "SIngle CEll Growth Analysis in R".
Author: M. Umut Caglar [aut, cre], Claus O. Wilke [aut]
Maintainer: M. Umut Caglar <umut.caglar@gmail.com>

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Package geomedb updated to version 0.2 with previous version 0.1 dated 2017-05-03

Title: Fetch 'GeOMe-db' FIMS Data
Description: The Genomic Observatory Metadatabase (GeOMe Database) is an open access repository for geographic and ecological metadata associated with sequenced samples. This package is used to retrieve GeOMe data for analysis. See <http://www.geome-db.org> for more information regarding GeOMe.
Author: RJ Ewing
Maintainer: RJ Ewing<ewing.rj@gmail.com>

Diff between geomedb versions 0.1 dated 2017-05-03 and 0.2 dated 2017-10-16

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Package bayeslm updated to version 0.3.1 with previous version 0.3.0 dated 2017-09-26

Title: Efficient Sampling for Gaussian Linear Regression with Arbitrary Priors
Description: Efficient sampling for Gaussian linear regression with arbitrary priors.
Author: P. Richard Hahn, Jingyu He and Hedibert Lopes
Maintainer: Jingyu He <jingyu.he@chicagobooth.edu>

Diff between bayeslm versions 0.3.0 dated 2017-09-26 and 0.3.1 dated 2017-10-16

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Package tidyr updated to version 0.7.2 with previous version 0.7.1 dated 2017-09-01

Title: Easily Tidy Data with 'spread()' and 'gather()' Functions
Description: An evolution of 'reshape2'. It's designed specifically for data tidying (not general reshaping or aggregating) and works well with 'dplyr' data pipelines.
Author: Hadley Wickham [aut, cre], Lionel Henry [aut], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

Diff between tidyr versions 0.7.1 dated 2017-09-01 and 0.7.2 dated 2017-10-16

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Package future updated to version 1.6.2 with previous version 1.6.1 dated 2017-09-09

Title: Unified Parallel and Distributed Processing in R for Everyone
Description: The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multiprocess)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, on in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implements additional backends for processing futures via compute cluster schedulers etc. Because of its unified API, there is no need to modify code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

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Package Directional updated to version 2.9 with previous version 2.8 dated 2017-07-25

Title: Directional Statistics
Description: A collection of functions for directional data analysis. Hypothesis testing, discriminant and regression analysis, MLE of distributions and more are included. The standard textbook for such data is the "Directional Statistics" by Mardia, K. V. and Jupp, P. E. (2000).
Author: Michail Tsagris, Giorgos Athineou, Anamul Sajib
Maintainer: Michail Tsagris <mtsagris@yahoo.gr>

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Package Deriv updated to version 3.8.2 with previous version 3.8.1 dated 2017-06-14

Title: Symbolic Differentiation
Description: R-based solution for symbolic differentiation. It admits user-defined function as well as function substitution in arguments of functions to be differentiated. Some symbolic simplification is part of the work.
Author: Andrew Clausen [aut], Serguei Sokol [aut, cre]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

Diff between Deriv versions 3.8.1 dated 2017-06-14 and 3.8.2 dated 2017-10-16

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Package corrplot updated to version 0.84 with previous version 0.77 dated 2016-04-21

Title: Visualization of a Correlation Matrix
Description: A graphical display of a correlation matrix or general matrix. It also contains some algorithms to do matrix reordering. In addition, corrplot is good at details, including choosing color, text labels, color labels, layout, etc.
Author: Taiyun Wei [cre, aut], Viliam Simko [aut], Michael Levy [ctb], Yihui Xie [ctb], Yan Jin [ctb], Jeff Zemla [ctb]
Maintainer: Taiyun Wei <weitaiyun@gmail.com>

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Package BDgraph updated to version 2.41 with previous version 2.40 dated 2017-08-14

Title: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC
Description: Provides statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889> and Mohammadi et al. (2017) <doi:10.1111/rssc.12171>. To speed up the computations, the BDMCMC sampling algorithms are implemented in parallel using OpenMP in C++.
Author: Abdolreza Mohammadi and Ernst Wit
Maintainer: Abdolreza Mohammadi <a.mohammadi@rug.nl>

Diff between BDgraph versions 2.40 dated 2017-08-14 and 2.41 dated 2017-10-16

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Package sperrorest updated to version 2.1.1 with previous version 2.1.0 dated 2017-09-26

Title: Perform Spatial Error Estimation and Variable Importance in Parallel
Description: Implements spatial error estimation and permutation-based variable importance measures for predictive models using spatial cross-validation and spatial block bootstrap.
Author: Alexander Brenning [aut, cre], Patrick Schratz [aut], Tobias Herrmann [aut]
Maintainer: Alexander Brenning <alexander.brenning@uni-jena.de>

Diff between sperrorest versions 2.1.0 dated 2017-09-26 and 2.1.1 dated 2017-10-16

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Package neatmaps updated to version 1.0.6 with previous version 1.0.5 dated 2017-08-28

Title: Heatmaps for Multiple Network Data
Description: Simplify the exploratory data analysis process for multiple network data sets with the help of hierarchical clustering and heatmaps. Multiple network data consists of multiple disjoint networks that share common graph, node and edge variables. Contains the tools necessary to convert this raw data into a single dynamic report, summarizing the relationships of the graph, node and structural characteristics of the networks.
Author: Phil Boileau [aut, cre]
Maintainer: Phil Boileau <philippe.boileau@mail.concordia.ca>

Diff between neatmaps versions 1.0.5 dated 2017-08-28 and 1.0.6 dated 2017-10-16

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New package fdadensity with initial version 0.1.0
Package: fdadensity
URL: https://github.com/functionaldata/tDENS
BugReports: https://github.com/functionaldata/tDENS/issues
Type: Package
Title: Functional Data Analysis for Density Functions by Transformation to a Hilbert Space
Version: 0.1.0
Date: 2017-10-16
Author: A. Petersen, P. Z. Hadjipantelis and H.G. Mueller
Maintainer: Alexander Petersen <petersen@pstat.ucsb.edu>
Description: An implementation of the methodology described in Petersen and Mueller (2016) <doi:10.1214/15-AOS1363> for the functional data analysis of samples of density functions. Densities are first transformed to their corresponding log quantile densities, followed by ordinary Functional Principal Components Analysis (FPCA). Transformation modes of variation yield improved interpretation of the variability in the data as compared to FPCA on the densities themselves. The standard fraction of variance explained (FVE) criterion commonly used for functional data is adapted to the transformation setting, also allowing for an alternative quantification of variability for density data through the Wasserstein metric of optimal transport.
Depends: R (>= 3.3.1)
License: BSD_3_clause + file LICENSE
LazyData: false
Imports: Rcpp (>= 0.11.5), fdapace (>= 0.3.0)
LinkingTo: Rcpp
NeedsCompilation: yes
Suggests: testthat
RoxygenNote: 6.0.1
Packaged: 2017-10-16 17:26:41 UTC; alexanderpetersen
Repository: CRAN
Date/Publication: 2017-10-16 18:13:00 UTC

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New package metacart with initial version 1.0-0
Package: metacart
Type: Package
Title: Meta-CART: A Flexible Approach to Identify Moderators in Meta-Analysis
Version: 1.0-0
Date: 2017-10-15
Author: Xinru Li [aut, cre], Elise Dusseldorp [aut, cph], Kaihua Liu [ctb] (supported with the plot function), Jacqueline Meulman [ctb]
Maintainer: Xinru Li <x.li@math.leidenuniv.nl>
License: GPL-2 | GPL-3
LazyData: TRUE
Description: Fits meta-CART by integrating classification and regression trees (CART) into meta-analysis. Meta-CART is a flexible approach to identify interaction effects between moderators in meta-analysis. The methods are described in Dusseldorp et al. (2014) <doi:10.1037/hea0000018> and Li et al. (2017) <doi:10.1111/bmsp.12088>.
Encoding: UTF-8
Depends: R (>= 3.0.2), rpart, stats, methods, rpart.plot, ggplot2,gridExtra
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-10-16 14:47:43 UTC; xinruli
Repository: CRAN
Date/Publication: 2017-10-16 17:41:45 UTC

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New package inaparc with initial version 0.1.0
Package: inaparc
Type: Package
Title: Initialization Algorithms for Partitioning Cluster Analysis
Version: 0.1.0
Date: 2017-10-15
Authors@R: c(person("Zeynel", "Cebeci", email = "zcebeci@cukurova.edu.tr", role = c("aut", "cre")), person("Cagatay","Cebeci", role = "aut", email = "cagataycebeci@gmail.com"))
Author: Zeynel Cebeci [aut, cre], Cagatay Cebeci [aut]
Maintainer: Zeynel Cebeci <zcebeci@cukurova.edu.tr>
Description: Partitioning clustering algorithms divide data sets into k subsets or partitions which are so-called clusters. They require some initialization procedures for starting to partition the data sets. Initialization of cluster prototypes is one of such kind of procedures for most of the partitioning algorithms. Cluster prototypes are the data elements, i.e. centroids or medoids, representing the clusters in a data set. In order to initialize cluster prototypes, the package 'inaparc' contains a set of the functions that are the implementations of several linear time-complexity and loglinear time-complexity methods in addition to some novel techniques. Initialization of fuzzy membership degrees matrices is another important task for starting the probabilistic and possibilistic partitioning algorithms. In order to initialize membership degrees matrices required by these algorithms, a number of functions based on some traditional and novel initialization techniques are also available in the package 'inaparc'.
Depends: R (>= 3.0.0)
License: GPL (>= 2)
LazyData: true
Imports: kpeaks, lhs, stats
NeedsCompilation: no
Packaged: 2017-10-14 20:30:08 UTC; user1
Repository: CRAN
Date/Publication: 2017-10-16 17:32:59 UTC

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Package gsynth updated to version 1.0.6 with previous version 1.0.5 dated 2017-10-12

Title: Generalized Synthetic Control Method
Description: Provides causal inference with interactive fixed-effect models. It imputes counterfactuals for each treated unit using control group information based on a linear interactive fixed effects model that incorporates unit-specific intercepts interacted with time-varying coefficients. This method generalizes the synthetic control method to the case of multiple treated units and variable treatment periods, and improves efficiency and interpretability. This version supports unbalanced panels. Reference: Yiqing Xu (2017) <doi:10.1017/pan.2016.2>.
Author: Yiqing Xu, Licheng Liu
Maintainer: Yiqing Xu <yiqingxu@ucsd.edu>

Diff between gsynth versions 1.0.5 dated 2017-10-12 and 1.0.6 dated 2017-10-16

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Package fishmethods updated to version 1.10-4 with previous version 1.10-3 dated 2017-07-13

Title: Fishery Science Methods and Models in R
Description: Fishery science methods and models from published literature and contributions from colleagues.
Author: Gary A. Nelson <gary.nelson@state.ma.us>
Maintainer: Gary A. Nelson <gary.nelson@state.ma.us>

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New package CovTools with initial version 0.1.0
Package: CovTools
Type: Package
Title: Statistical Tools for Covariance Analysis
Version: 0.1.0
Authors@R: c(person("Kyoungjae","Lee",role="aut",email="leekjstat@gmail.com"),person("Kisung", "You", role = c("aut", "cre"),email = "kyou@nd.edu"))
Description: Covariance is of universal prevalence across various disciplines within statistics. We provide a rich collection of geometric and inferential tools for convenient analysis of covariance structures, topics including distance measures, mean covariance estimator, covariance hypothesis test for one-sample and two-sample cases, and covariance estimation. For an introduction to covariance in multivariate statistical analysis, see Schervish (1987) <doi:10.1214/ss/1177013111>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 0.12.10), geigen, shapes, expm, mvtnorm, stats, Matrix
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-10-14 16:37:19 UTC; kisung
Author: Kyoungjae Lee [aut], Kisung You [aut, cre]
Maintainer: Kisung You <kyou@nd.edu>
Repository: CRAN
Date/Publication: 2017-10-16 17:46:59 UTC

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New package copulaData with initial version 0.0-1
Package: copulaData
Version: 0.0-1
Title: Data Sets for Copula Modeling
Author: Marius Hofert <marius.hofert@uwaterloo.ca>, Ivan Kojadinovic <ivan.kojadinovic@univ-pau.fr>, Martin Maechler <maechler@stat.math.ethz.ch>, and Jun Yan <jun.yan@uconn.edu>
Maintainer: Marius Hofert <marius.hofert@uwaterloo.ca>
Depends: R (>= 3.1.0)
Description: Data sets used for copula modeling in addition to those in the package 'copula'. These include a random subsample from the US National Education Longitudinal Study (NELS) of 1988 and nursing home data from Wisconsin.
License: GPL (>= 3) | file LICENCE
NeedsCompilation: no
Encoding: UTF-8
URL: http://copula.r-forge.r-project.org/
Packaged: 2017-10-16 15:00:35 UTC; mhofert
Repository: CRAN
Date/Publication: 2017-10-16 17:48:51 UTC

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Package uGMAR updated to version 1.0.2 with previous version 1.0.1 dated 2017-08-29

Title: Estimate Univariate Gaussian or Student's t Mixture Autoregressive Model
Description: Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR) and Student's t Mixture Autoregressive (StMAR) models, quantile residual tests, graphical diagnostics, forecast and simulate from GMAR and StMAR processes. Also general linear constraints and restricting autoregressive parameters to be the same for all regimes are supported. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) <doi:10.1111/jtsa.12108>, Leena Kalliovirta (2012) <doi:10.1111/j.1368-423X.2011.00364.x>.
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen@helsinki.fi>

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Package SelvarMix updated to version 1.2.1 with previous version 1.2 dated 2016-11-07

Title: Regularization for Variable Selection in Model-Based Clustering and Discriminant Analysis
Description: Performs a regularization approach to variable selection in the model-based clustering and classification frameworks. First, the variables are arranged in order with a lasso-like procedure. Second, the method of Maugis, Celeux, and Martin-Magniette (2009, 2011) <doi:10.1016/j.csda.2009.04.013>, <doi:10.1016/j.jmva.2011.05.004> is adapted to define the role of variables in the two frameworks.
Author: Mohammed Sedki, Gilles Celeux, Cathy Maugis-Rabusseau
Maintainer: Mohammed Sedki <mohammed.sedki@u-psud.fr>

Diff between SelvarMix versions 1.2 dated 2016-11-07 and 1.2.1 dated 2017-10-16

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Package mvdalab updated to version 1.4 with previous version 1.3 dated 2017-10-04

Title: Multivariate Data Analysis Laboratory
Description: An open-source implementation of latent variable methods and multivariate modeling tools. The focus is on exploratory analyses using dimensionality reduction methods including low dimensional embedding, classical multivariate statistical tools, and tools for enhanced interpretation of machine learning methods (i.e. intelligible models to provide important information for end-users). Target domains include extension to dedicated applications e.g. for manufacturing process modeling, spectroscopic analyses, and data mining.
Author: Nelson Lee Afanador, Thanh Tran, Lionel Blanchet, and Richard Baumgartner
Maintainer: Nelson Lee Afanador <nelson.afanador@mvdalab.com>

Diff between mvdalab versions 1.3 dated 2017-10-04 and 1.4 dated 2017-10-16

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New package ESTER with initial version 0.1.0
Package: ESTER
Title: Efficient Sequential Testing with Evidence Ratios
Version: 0.1.0
Date: 2017-10-15
Authors@R: person("Ladislas", "Nalborczyk", email = "ladislas.nalborczyk@gmail.com", role = c("aut", "cre"))
Description: An implementation of sequential testing that uses evidence ratios computed from the Akaike weights of a set of models. These weights are being computed using either the Akaike Information Criterion (AIC) or the Bayesian Information Criterion (BIC), and following Burnham & Anderson (2004) recommendations. Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference: Understanding AIC and BIC in model selection. Sociological Methods and Research, 33(2), 261-304. <doi:10.1177/0049124104268644>.
License: MIT + file LICENSE
LazyData: yes
RoxygenNote: 6.0.1
Depends: R (>= 3.3.0)
Imports: lme4, dplyr, magrittr, ggplot2, rlang
URL: https://github.com/lnalborczyk/ESTER
BugReports: https://github.com/lnalborczyk/ESTER/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-10-16 14:02:07 UTC; Ladislas
Author: Ladislas Nalborczyk [aut, cre]
Maintainer: Ladislas Nalborczyk <ladislas.nalborczyk@gmail.com>
Repository: CRAN
Date/Publication: 2017-10-16 14:22:05 UTC

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Package rmsfuns updated to version 0.0.0.2 with previous version 0.0.0.1 dated 2017-10-14

Title: Quickly View Data Frames in 'Excel', Build Folder Paths and Create Date Vectors
Description: Contains several useful navigation helper functions, including easily building folder paths, quick viewing dataframes in 'Excel', creating date vectors and changing the console prompt to reflect time.
Author: Nico Katzke [aut, cre]
Maintainer: Nico Katzke <nfkatzke@gmail.com>

Diff between rmsfuns versions 0.0.0.1 dated 2017-10-14 and 0.0.0.2 dated 2017-10-16

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Package timetools updated to version 1.12.3 with previous version 1.12.2 dated 2017-09-15

Title: Seasonal/Sequential (Instants/Durations, Even or not) Time Series
Description: Objects to manipulate sequential and seasonal time series. Sequential time series based on time instants and time durations are handled. Both can be regularly or unevenly spaced (overlapping durations are allowed). Only POSIX* format are used for dates and times. The following classes are provided : 'POSIXcti', 'POSIXctp', 'TimeIntervalDataFrame', 'TimeInstantDataFrame', 'SubtimeDataFrame' ; methods to switch from a class to another and to modify the time support of series (hourly time series to daily time series for instance) are also defined. Tools provided can be used for instance to handle environmental monitoring data (not always produced on a regular time base).
Author: Vladislav Navel
Maintainer: Vladislav Navel <vnavel@yahoo.fr>

Diff between timetools versions 1.12.2 dated 2017-09-15 and 1.12.3 dated 2017-10-16

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