Package: mgpd
Type: Package
Title: mgpd: Functions for multivariate generalized Pareto distribution
(MGPD of Type II)
Version: 1.99
Date: 2012-03-15
Author: Pal Rakonczai
Maintainer: Pal Rakonczai <rakonczai.p@gmail.com>
Depends: R (>= 2.10.1), evd, numDeriv, corpcor, fields
Description: Extends distribution and density functions to parametric
multivariate generalized Pareto distributions (MGPD of Type
II), and provides fitting functions which calculate maximum
likelihood estimates for bivariate and trivariate models. (Help
is under progress)
License: GPL-3
Packaged: 2012-03-19 17:13:26 UTC; Irgumburgum
Repository: CRAN
Date/Publication: 2012-03-19 17:35:21
Package: leapp
Version: 1.2
Date: 2014-07-07
Title: latent effect adjustment after primary projection
Author: Yunting Sun <yunting.sun@gmail.com> , Nancy R.Zhang
<nzhang@stanford.edu>, Art B.Owen <owen@stanford.edu>
Maintainer: Yunting Sun <yunting.sun@gmail.com>
Description: These functions take a gene expression value matrix, a
primary covariate vector, an additional known covariates
matrix. A two stage analysis is applied to counter the effects
of latent variables on the rankings of hypotheses. The
estimation and adjustment of latent effects are proposed by
Sun, Zhang and Owen (2011). "leapp" is developed in the
context of microarray experiments, but may be used as a general
tool for high throughput data sets where dependence may be
involved.
Depends: R (>= 3.1.1), sva, MASS, corpcor
License: GPL (>= 2)
Packaged: 2014-07-13 18:34:14 UTC; ytsun
Repository: CRAN
Date/Publication: 2014-07-22 08:52:54
NeedsCompilation: no
Package: longitudinal
Version: 1.1.12
Date: 2015-07-08
Title: Analysis of Multiple Time Course Data
Author: Rainer Opgen-Rhein and Korbinian Strimmer.
Maintainer: Korbinian Strimmer <strimmerlab@gmail.com>
Depends: R (>= 3.0.2), corpcor (>= 1.6.8)
Suggests:
Imports: graphics, grDevices, stats
Description: Contains general data structures and
functions for longitudinal data with multiple variables,
repeated measurements, and irregularly spaced time points.
Also implements a shrinkage estimator of dynamical correlation
and dynamical covariance.
License: GPL (>= 3)
URL: http://strimmerlab.org/software/longitudinal/
Packaged: 2015-07-08 13:43:50 UTC; strimmer
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-07-08 16:28:32
Package: netgsa
Type: Package
Title: Network-Based Gene Set Analysis
Version: 3.0
Date: 2016-06-15
Author: Ali Shojaie and Jing Ma
Maintainer: Jing Ma <jinma@upenn.edu>
Description: Carry out Network-based Gene Set Analysis by incorporating external information about interactions among genes, as well as novel interactions learned from data.
Depends: corpcor, Matrix, glasso, glmnet, igraph
Suggests: MASS
License: GPL (>= 2)
LazyLoad: yes
URL: http://arxiv.org/abs/1411.7919
NeedsCompilation: no
Packaged: 2016-06-16 15:41:43 UTC; jingma
Repository: CRAN
Date/Publication: 2016-06-16 18:27:48
Package: MAVTgsa
Type: Package
Title: Three methods to identify differentially expressed gene sets,
ordinary least square test, Multivariate Analysis Of Variance
test with n contrasts and Random forest.
Version: 1.3
Date: 2014-05-27
Author: Chih-Yi Chien, Chen-An Tsai, Ching-Wei Chang, and James J. Chen
Maintainer: Chih-Yi Chien <92354503@nccu.edu.tw>
Depends: R (>= 2.13.2), corpcor, foreach, multcomp, randomForest, MASS
Description: This package is a gene set analysis function for one-sided test (OLS), two-sided test (multivariate analysis of variance).
If the experimental conditions are equal to 2, the p-value for Hotelling's t^2 test is calculated.
If the experimental conditions are great than 2, the p-value for Wilks' Lambda is determined and post-hoc test is reported too.
Three multiple comparison procedures, Dunnett, Tukey, and sequential pairwise comparison, are implemented.
The program computes the p-values and FDR (false discovery rate) q-values for all gene sets.
The p-values for individual genes in a significant gene set are also listed.
MAVTgsa generates two visualization output: a p-value plot of gene sets (GSA plot) and a GST-plot of the empirical distribution function of the ranked test statistics of a given gene set.
A Random Forests-based procedure is to identify gene sets that can accurately predict samples from different experimental conditions or are associated with the continuous phenotypes.
License: GPL-2
LazyData: Yes
Repository: CRAN
Packaged: 2014-06-30 03:41:28 UTC; pelly
NeedsCompilation: no
Date/Publication: 2014-07-02 13:48:35
Package: HPbayes
Type: Package
Title: Heligman Pollard mortality model parameter estimation using
Bayesian Melding with Incremental Mixture Importance Sampling
Depends: MASS, mvtnorm, corpcor, numDeriv, stats, boot
Version: 0.1
Date: 2011-01-19
Author: David J Sharrow
Maintainer: Dave Sharrow <dsharrow@u.washington.edu>
Description: This package provides all the functions necessary to
estimate the 8 parameters of the Heligman Pollard mortality
model using a Bayesian Melding procedure with IMIS as well as
to convert those parameters into age-specifc probabilities of
death and a corresponding life table
License: Unlimited
LazyLoad: yes
Packaged: 2012-10-29 08:57:08 UTC; ripley
Repository: CRAN
Date/Publication: 2012-10-29 08:57:08
providing 
.