Learn R Programming

MVR

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: MVR.news().

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.

============

Branches

  • The default branch (master) hosts the current development release (version 1.33.0).

===========

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:

CRAN downloads in the last month:

CRAN downloads in the last week:

================

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:

See CRAN checks: .

================

Installation

  • To install the stable version (1.33.0) of MVR from the CRAN repository,

simply download and install the current version (1.33.0) from the CRAN repository:

install.packages("MVR")
  • Alternatively, you can install the most up-to-date development version (>= 1.33.0) of MVR from the GitHub repository,

simply run the following using devtools:

install.packages("devtools")
library("devtools")
devtools::install_github("jedazard/MVR")

=========

Usage

  • To load the MVR library in an R session and start using it:
library("MVR")
  • Check the package news with the R command:
MVR.news()
  • Check on how to cite the package with the R command:
citation("MVR")

etc...

===================

Acknowledgments

Authors:

Maintainers:

Funding/Provision/Help:

  • 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

  • Dazard J-E. and J. S. Rao. Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data. Comput. Statist. Data Anal. (2012), 56(7):2317-2333. (The Official Journal of the International Association for Statistical Computing).

  • Dazard J-E., Hua Xu and J. S. Rao. R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization. In JSM Proceedings, Section for Statistical Programmers and Analysts. Miami Beach, FL, USA: American Statistical Association IMS - JSM, 3849-3863. JSM (2011).

  • Dazard J-E. and J. S. Rao. Regularized Variance Estimation and Variance Stabilization of High-Dimensional Data. In JSM Proceedings, Section for High-Dimensional Data Analysis and Variable Selection. Vancouver, BC, Canada: American Statistical Association IMS - JSM, 5295-5309. JSM (2010).

Copy Link

Version

Install

install.packages('MVR')

Monthly Downloads

242

Version

1.33.0

License

GPL (>= 3) | file LICENSE

Issues

Pull Requests

Stars

Forks

Last Published

September 10th, 2018

Functions in MVR (1.33.0)

cluster.diagnostic

Function for Plotting Summary Cluster Diagnostic Plots
stabilization.diagnostic

Function for Plotting Summary Variance Stabilization Diagnostic Plots
MVR.news

Function to Display the NEWS File
mvr

Function for Mean-Variance Regularization and Variance Stabilization
target.diagnostic

Function for Plotting Summary Target Moments Diagnostic Plots
mvrt.test

Function for Computing Mean-Variance Regularized T-test Statistic and Its Significance
normalization.diagnostic

Function for Plotting Summary Normalization Diagnostic Plots
Real

Real Proteomics Dataset
Synthetic

Multi-Groups Synthetic Dataset
MVR-package

Mean-Variance Regularization Package