Package: lm.br
Type: Package
Title: Linear Model with Breakpoint
Version: 2.8
Date: 2016-01-28
Authors@R: c( person("Marc", "Adams", role= c("aut", "cre"), email= "lm.br.pkg@gmail.com"),
person("authors of R function 'lm'", role = "ctb", comment = "general interface"),
person("authors of 'lm.gls'", role = "ctb", comment = "interface and R code for covariate weights"),
person("U.S. NIST", role = "ctb", comment = "C++ code for TNT::Vector template") )
Copyright: 'lm.br' uses the design and some R-code of 'lm' copyright
(C) 2015 The R Foundation for Statistical Computing, and of
'lm.gls' copyright (C) 1994-2005 W. N. Venables and B. D.
Ripley.
Description: Exact significance tests for a changepoint in linear or multiple linear regression.
Confidence regions with exact coverage probabilities for the changepoint.
License: GPL (>= 2)
Depends: R (>= 3.0.1), Rcpp (>= 0.11.0)
Imports: stats, methods, graphics, datasets
LinkingTo: Rcpp
Packaged: 2016-01-29 03:57:55 UTC; rforge
Author: Marc Adams [aut, cre],
authors of R function 'lm' [ctb] (general interface),
authors of 'lm.gls' [ctb] (interface and R code for covariate weights),
U.S. NIST [ctb] (C++ code for TNT::Vector template)
Maintainer: Marc Adams <lm.br.pkg@gmail.com>
Repository: CRAN
Repository/R-Forge/Project: blmr
Repository/R-Forge/Revision: 56
Repository/R-Forge/DateTimeStamp: 2016-01-29 03:19:38
Date/Publication: 2016-01-29 22:42:36
NeedsCompilation: yes
Package: multicool
Type: Package
Title: Permutations of Multisets in Cool-Lex Order
Version: 0.1-9
Date: 2015-10-28
Author: James Curran, Aaron Williams, Jerome Kelleher, Dave Barber
Maintainer: James Curran <j.curran@auckland.ac.nz>
Description: A set of tools to permute multisets without loops or hash tables and to generate integer partitions. The permutation functions are based on C code from Aaron Williams. Cool-lex order is similar to colexicographical order. The algorithm is described in Williams, A. Loopless Generation of Multiset Permutations by Prefix Shifts. SODA 2009, Symposium on Discrete Algorithms, New York, United States. The permutation code is distributed without restrictions. The code for stable and efficient computation of multinomial coefficients comes from Dave Barber. The code can be download from http://home.comcast.net/~tamivox/dave/multinomial/index.html and is distributed without conditions. The package also generates the integer partitions of a positive, non-zero integer n. The C++ code for this is based on Python code from Jerome Kelleher which can be found here http://jeromekelleher.net/partitions.php. The C++ code and Python code are distributed without conditions.
License: GPL-2
Depends: methods, Rcpp (>= 0.11.2)
LinkingTo: Rcpp
RcppModules: Multicool
NeedsCompilation: yes
Packaged: 2015-10-28 08:46:16 UTC; jcur002
Repository: CRAN
Date/Publication: 2015-10-28 18:39:18
Package: mvcluster
Type: Package
Title: Multi-View Clustering
Version: 1.0
Date: 2016-04-01
Author: Jiangwen Sun, Jin Lu, Tingyang Xu, Joseph Muller, Jinbo Bi
Maintainer: Jiangwen Sun <javon@engr.uconn.edu>
Description: Implementation of multi-view bi-clustering algorithms. When a sample is characterized by two or more sets of input features, it creates multiple data matrices for the same set of examples, each corresponding to a view. For instance, individuals who are diagnosed with a disorder can be described by their clinical symptoms (one view) and their genomic markers (another view). Rows of a data matrix correspond to examples and columns correspond to features. A multi-view bi-clustering algorithm groups examples (rows) consistently across the views and simultaneously identifies the subset of features (columns) in each view that are associated with the row groups. This mvcluster package includes three such methods. (1) MVSVDL1: multi-view bi-clustering based on singular value decomposition where the left singular vectors are used to identify row clusters and the right singular vectors are used to identify features (columns) for each row cluster. Each singular vector is regularized by the L1 vector norm. (2) MVLRRL0: multi-view bi-clustering based on sparse low rank representation (i.e., matrix approximation) where the decomposed components are regularized by the so-called L0 vector norm (which is not really a vector norm). (3) MVLRRL1: multi-view bi-clustering based on sparse low rank representation (i.e., matrix approximation) where the decomposed components are regularized by the L1 vector norm.
License: GPL (>= 3)
Depends: Rcpp (>= 0.12.0)
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
URL: http://www.labhealthinfo.uconn.edu/multi-view-analytics/
Repository: CRAN
Date/Publication: 2016-04-03 16:31:05
Package: ngspatial
Version: 1.0-5
Date: 1-16-2015
Title: Fitting the centered autologistic and sparse spatial generalized
linear mixed models for areal data
Type: Package
Author: John Hughes <hughesj@umn.edu> and Xiaohui Cui <cuixx132@umn.edu>
Maintainer: John Hughes <hughesj@umn.edu>
Depends: Rcpp, utils, batchmeans
Suggests: parallel
Description: ngspatial provides tools for analyzing spatial data, especially
non-Gaussian areal data. The current version supports the sparse spatial
generalized linear mixed model of Hughes and Haran (2013) and the centered
autologistic model of Caragea and Kaiser (2009).
License: GPL (>= 2)
LinkingTo: Rcpp, RcppArmadillo
URL: http://www.biostat.umn.edu/~johnh
Repository: CRAN
RcppModules: moller, perfsampler
Packaged: 2015-01-16 14:48:25 UTC; jphughesjr
NeedsCompilation: yes
Date/Publication: 2015-01-16 18:12:08
Package: nonlinearTseries
Type: Package
Title: Nonlinear Time Series Analysis
Version: 0.2.3
Date: 2015-07-17
Maintainer: Constantino A. Garcia <constantinoantonio.garcia@usc.es>
Authors@R: c(person("Constantino A.", "Garcia",
email = "constantinoantonio.garcia@usc.es",
role = c("aut", "cre")),
person("Gunther", "Sawitzki",
role = "ctb"))
Description: Functions for nonlinear time series analysis. This package permits
the computation of the most-used nonlinear statistics/algorithms
including generalized correlation dimension, information dimension,
largest Lyapunov exponent, sample entropy and Recurrence
Quantification Analysis (RQA), among others. Basic routines
for surrogate data testing are also included. Part of this work
was based on the book "Nonlinear time series analysis" by
Holger Kantz and Thomas Schreiber (ISBN: 9780521529020).
License: GPL (>= 3)
Copyright: ANN library is copyright University of Maryland and Sunil
Arya and David Mount. R wrapper is based on the ANN library,
copyright Samuel Kemp 2005-9 and Gregory Jefferis 2009-2013.
See file COPYRIGHT for details
Depends: Matrix, rgl, tseries, TSA, Rcpp (>= 0.10.5), graphics, stats
LinkingTo: Rcpp
Suggests: plot3D, knitr,
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2015-07-25 11:31:31 UTC; gaussllego
Author: Constantino A. Garcia [aut, cre],
Gunther Sawitzki [ctb]
Repository: CRAN
Date/Publication: 2015-07-25 17:43:38
Package: matchingR
Type: Package
Title: Matching Algorithms in R and C++
Version: 1.2.1
Date: 2015-10-31
Author: Jan Tilly, Nick Janetos
Maintainer: Jan Tilly <jtilly@econ.upenn.edu>
Description: Computes matching algorithms quickly using Rcpp.
Implements the Gale-Shapley Algorithm to compute the stable
matching for two-sided markets, such as the stable marriage
problem and the college-admissions problem. Implements Irving's
Algorithm for the stable roommate problem. Implements the top
trading cycle algorithm for the indivisible goods trading problem.
License: GPL (>= 2)
URL: https://github.com/jtilly/matchingR/
BugReports: https://github.com/jtilly/matchingR/issues/
Depends: Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, knitr, microbenchmark
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2015-11-01 03:36:27 UTC; jtilly
Repository: CRAN
Date/Publication: 2015-11-01 17:54:54
providing 
.