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: 1.32.0
Depends: R (≥ 3.0.2), statmod
Imports: parallel, methods
Published: 2017-05-29
Author: Jean-Eudes Dazard [aut, cre], Hua Xu [ctb], Alberto Santana [ctb]
Maintainer: Jean-Eudes Dazard <jean-eudes.dazard at>
License: GPL (≥ 3) | file LICENSE
NeedsCompilation: yes
Citation: MVR citation info
Materials: README NEWS
CRAN checks: MVR results


Reference manual: MVR.pdf
Package source: MVR_1.32.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: MVR_1.32.0.tgz
OS X Mavericks binaries: r-oldrel: MVR_1.32.0.tgz
Old sources: MVR archive


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