Package: MVR
Type: Package
Title: Mean-Variance Regularization
Version: 1.33.0
Date: 2018-09-10
Authors@R: c(person("Jean-Eudes", "Dazard",
                    role = c("aut", "cre"),
                    email = "jean-eudes.dazard@case.edu"),
              person("Hua", "Xu",
                     role = "ctb",
                     email = "huaxu77@gmail.com"),
              person("Alberto", "Santana",
                     role = "ctb",
	                email = "ahs4@case.edu"))
Author: Jean-Eudes Dazard [aut, cre],
  Hua Xu [ctb],
  Alberto Santana [ctb]
Maintainer: Jean-Eudes Dazard <jean-eudes.dazard@case.edu>
Description: 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.
Depends: R (>= 3.0.2), statmod
Imports: parallel, methods
NeedsCompilation: yes
URL: https://github.com/jedazard/MVR
Repository: CRAN
License: GPL (>= 3) | file LICENSE
LazyLoad: yes
LazyData: yes
Packaged: 2018-09-10 16:45:39 UTC; Admin
Date/Publication: 2018-09-10 18:20:03 UTC
Built: R 4.4.3; x86_64-w64-mingw32; 2025-10-21 12:25:22 UTC; windows
Archs: x64
