jedazard/MVR: Mean-Variance Regularization

Implements 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.

Getting started

Package details

AuthorJean-Eudes Dazard [aut, cre], Hua Xu [ctb], Alberto Santana [ctb]
MaintainerJean-Eudes Dazard <jean-eudes.dazard@case.edu>
LicenseGPL (>= 3) | file LICENSE
Version1.34.0
URL https://github.com/jedazard/MVR
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("jedazard/MVR")
jedazard/MVR documentation built on July 16, 2022, 10:55 p.m.