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.
Package details |
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Author | Jean-Eudes Dazard [aut, cre], Hua Xu [ctb], Alberto Santana [ctb] |
Maintainer | Jean-Eudes Dazard <jean-eudes.dazard@case.edu> |
License | GPL (>= 3) | file LICENSE |
Version | 1.34.0 |
URL | https://github.com/jedazard/MVR |
Package repository | View on GitHub |
Installation |
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