MVR: Mean-Variance Regularization

This 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). Among those 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-statistics (F-statistics to follow), (iii) Generation of diverse diagnostic plots, (iv) Computationally efficient implementation using C/C++ interfacing and an option for parallel computing to enjoy a faster and easier experience in the R environment.

Version: 1.31.0
Depends: R (≥ 3.0.2), parallel, statmod
Imports: graphics, grDevices, methods, stats
Published: 2016-10-26
Author: Jean-Eudes Dazard [aut, cre], Hua Xu [ctb], Alberto Santana [ctb]
Maintainer: Jean-Eudes Dazard <jean-eudes.dazard at case.edu>
License: GPL (≥ 3) | file LICENSE
URL: https://github.com/jedazard/MVR
NeedsCompilation: yes
Citation: MVR citation info
Materials: NEWS
CRAN checks: MVR results

Downloads:

Reference manual: MVR.pdf
Package source: MVR_1.31.0.tar.gz
Windows binaries: r-devel: MVR_1.31.0.zip, r-release: MVR_1.31.0.zip, r-oldrel: MVR_1.31.0.zip
OS X Mavericks binaries: r-release: MVR_1.31.0.tgz, r-oldrel: MVR_1.31.0.tgz
Old sources: MVR archive

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