Package: MVR
Type: Package
Title: Mean-Variance Regularization
Description: MVR is a non-parametric method for joint adaptive
        mean-variance regularization and variance stabilization of
        high-dimensional data. It is suited for handling difficult
        problems posed by high-dimensional multivariate datasets (p >>
        n paradigm), such as in omics-type data, among which are that
        the variance is often a function of the mean, variable-specific
        estimators of variances are not reliable, and tests statistics
        have low powers due to a lack of degrees of freedom. Key
        features include (i) Normalization and/or variance
        stabilization of the data, (ii) Computation of
        mean-variance-regularized t- and F-statistics, (iii) Generation
        of diverse diagnostic plots, (iv) Computationally efficiency
        implementation, using C++ interfacing, and an option for
        parallel computing to enjoy a fast and easy experience in the R
        environment.
Version: 1.00.0
Date: 2011-07-26
Depends: R (>= 2.13.0), statmod, snow
Suggests: RColorBrewer
Enhances:
Author: Jean-Eudes Dazard, PhD. <jxd101@case.edu>, with contributions
        from Hua Xu, PhD. <hxx58@case.edu>, and Alberto H. Santana,
        MBA. <ahs4@case.edu>, and J. Sunil Rao, PhD.
        <JRao@med.miami.edu>.
Maintainer: Jean-Eudes Dazard, PhD. <jxd101@case.edu>
URL: http://proteomics.case.edu/jean_eudes_dazard.aspx
Repository: CRAN
License: GPL (>= 3)
LazyLoad: yes
Packaged: 2011-07-26 18:38:21 UTC; jxd101
Date/Publication: 2011-07-26 20:23:40
