Mean-Variance Regularization: a non-parametric method for joint adaptive mean-variance regularization and variance stabilization of high-dimensional data

=============== ### Description

MVR (Mean-Variance Regularization) 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:

  1. Normalization and/or variance stabilization of the data

  2. Computation of mean-variance-regularized t-statistics (F-statistics to come)

  3. Generation of diverse diagnostic plots

  4. Computationally efficient implementation using C/C++ interfacing and an option for parallel computing to enjoy a fast and easy experience in the R environment

See also below the package news with the R command:

All the codes are in the R folder and a manual (MVR.pdf) details the end-user (and internal) functions. At this stage and for simplicity, there are only 2 end-user function, 4 end-user diagnostic and plotting functions and 2 end-user datasets (synthetic and real). See the “MVR-package” introduction section of the manual for more details and examples.

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=========== ### License

PRIMsrc is open source / free software, licensed under the GNU General Public License version 3 (GPLv3), sponsored by the Free Software Foundation. To view a copy of this license, visit GNU Free Documentation License.

============= ### Downloads

CRAN downloads since October 1, 2012, the month the RStudio CRAN mirror started publishing logs:

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================ ### Requirements

MVR (>= 1.33.0) requires R-3.0.2 (2013-09-25). It was built and tested under R version 3.5.1 (2018-07-02) and Travis CI.

Installation has been tested on Windows, Linux, OSX and Solaris platforms.

See Travis CI build result: Build Status

See CRAN checks: CRAN_Status_Badge.

================ ### Installation


========= ### Usage



=================== ### Acknowledgments

Authors: + Jean-Eudes Dazard, Ph.D. ( + Hua Xu, Ph.D. ( + Alberto Santana, MBA. (

Maintainers: + Jean-Eudes Dazard, Ph.D. (

+ This work made use of the High Performance Computing Resource in the Core Facility for Advanced Research Computing at Case Western Reserve University. + This project was partially funded by the National Institutes of Health NIH - National Cancer Institute (P30-CA043703).

============== ### References