Package: lspls
Type: Package
Title: LS-PLS Models
Version: 0.2-1
Date: 2011-10-20
Author: Bjørn-Helge Mevik
Maintainer: Bjørn-Helge Mevik <bhx6@mevik.net>
Encoding: latin1
Depends: pls (>= 2.2.0)
Description: Implements the LS-PLS (least squares - partial least
squares) method described in for instance Jørgensen, K.,
Segtnan, V. H., Thyholt, K., Næs, T. (2004) A Comparison of
Methods for Analysing Regression Models with Both Spectral and
Designed Variables. Journal of Chemometrics, 18(10), 451--464.
License: GPL-2
URL: http://mevik.net/work/software/lspls.html
Packaged: 2011-10-20 18:42:49 UTC; bhm
Repository: CRAN
Date/Publication: 2011-10-20 20:26:07
Package: monomvn
Type: Package
Title: Estimation for Multivariate Normal and Student-t Data with
Monotone Missingness
Version: 1.9-6
Date: 2016-02-10
Author: Robert B. Gramacy <rbgramacy@chicagobooth.edu>
Maintainer: Robert B. Gramacy <rbgramacy@chicagobooth.edu>
Description: Estimation of multivariate normal and student-t data of
arbitrary dimension where the pattern of missing data is monotone.
Through the use of parsimonious/shrinkage regressions
(plsr, pcr, lasso, ridge, etc.), where standard regressions fail,
the package can handle a nearly arbitrary amount of missing data.
The current version supports maximum likelihood inference and
a full Bayesian approach employing scale-mixtures for Gibbs sampling.
Monotone data augmentation extends this
Bayesian approach to arbitrary missingness patterns.
A fully functional standalone interface to the Bayesian lasso
(from Park & Casella), Normal-Gamma (from Griffin & Brown),
Horseshoe (from Carvalho, Polson, & Scott), and ridge regression
with model selection via Reversible Jump, and student-t errors
(from Geweke) is also provided.
Depends: R (>= 2.14.0), pls, lars, MASS
Imports: quadprog, mvtnorm
License: LGPL
URL: http://bobby.gramacy.com/r_packages/monomvn
NeedsCompilation: yes
Packaged: 2016-02-10 21:11:47 UTC; bobby
Repository: CRAN
Date/Publication: 2016-02-11 00:43:05
Package: LGEWIS
Type: Package
Title: Tests for Genetic Association/Gene-Environment Interaction in
Longitudinal Gene-Environment-Wide Interaction Studies
Version: 0.2
Date: 2015-10-07
Author: Zihuai He, Seunggeun Lee, Bhramar Mukherjee, Min Zhang
Maintainer: Zihuai He <zihuai@umich.edu>
Description: Functions for testing the genetic association/gene-environment interaction in longitudinal gene-environment-wide interaction studies. Generalized score type tests are used for set based analyses. Then GEE based score tests are applied to all single variants within the defined set.
License: GPL-3
Depends: CompQuadForm, SKAT, geeM, pls, splines
NeedsCompilation: no
Packaged: 2015-10-12 13:14:06 UTC; statzihuai
Repository: CRAN
Date/Publication: 2015-10-14 09:48:39
Package: dmm
Type: Package
Title: Dyadic Mixed Model for Pedigree Data
Version: 1.7-1
Date: 2016-04-12
Author: Neville Jackson
Maintainer: Neville Jackson <nanddjackson@bigpond.com>
Description: Dyadic mixed model analysis with multi-trait responses and
pedigree-based partitioning of individual variation into a range of
environmental and genetic variance components for individual and
maternal effects.
Depends: MASS, Matrix, nadiv, robustbase, pls
Imports: stats, graphics, grDevices
License: GPL-2 | GPL (>= 2) | GPL-3
NeedsCompilation: no
Packaged: 2016-04-12 04:57:43 UTC; nevj
Repository: CRAN
Date/Publication: 2016-04-12 08:12:28
Package: dbstats
Type: Package
Title: Distance-Based Statistics
Version: 1.0.4
Date: 2014-12-10
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>
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.
License: GPL-2
LazyLoad: no
Repository: CRAN
Depends: R (>= 2.10.0), cluster, pls
Suggests: proxy
Packaged: 2014-12-10 17:15:34 UTC; josep
NeedsCompilation: no
Date/Publication: 2014-12-10 21:13:55
Package: BioMark
Type: Package
Title: Find Biomarkers in Two-Class Discrimination Problems
Version: 0.4.5
Author: Ron Wehrens, Pietro Franceschi
Maintainer: Ron Wehrens <ron.wehrens@gmail.com>
Description: Variable selection methods are provided for several classification methods: the lasso/elastic net, PCLDA, PLSDA, and several t-tests. Two approaches for selecting cutoffs can be used, one based on the stability of model coefficients under perturbation, and the other on higher criticism.
License: GPL (>= 2)
Depends: pls, glmnet, MASS, st (>= 1.1.6)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2015-09-07 12:04:07 UTC; ron
Repository: CRAN
Date/Publication: 2015-09-07 18:17:37
providing 
.