Package: MVR 1.34.0

Jean-Eudes Dazard

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.

Authors:Jean-Eudes Dazard [aut, cre], Hua Xu [ctb], Alberto Santana [ctb]

MVR_1.34.0.tar.gz
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MVR.pdf |MVR.html
MVR/json (API)
NEWS

# Install 'MVR' in R:
install.packages('MVR', repos = c('https://jedazard.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jedazard/mvr/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • Real - Real Proteomics Dataset
  • Synthetic - Multi-Groups Synthetic Dataset

On CRAN:

7 exports 1 stars 2.77 score 1 dependencies 13 mentions 12 scripts 218 downloads

Last updated 2 years agofrom:dd6ae1635e. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 08 2024
R-4.5-win-x86_64NOTESep 08 2024
R-4.5-linux-x86_64NOTESep 08 2024
R-4.4-win-x86_64NOTESep 08 2024
R-4.4-mac-x86_64NOTESep 08 2024
R-4.4-mac-aarch64NOTESep 08 2024
R-4.3-win-x86_64NOTESep 08 2024
R-4.3-mac-x86_64NOTESep 08 2024
R-4.3-mac-aarch64NOTESep 08 2024

Exports:cluster.diagnosticmvrMVR.newsmvrt.testnormalization.diagnosticstabilization.diagnostictarget.diagnostic

Dependencies:statmod