Fits low-rank matrix and tensor mean models using non-parametric unimodal priors on the components. For fitting a rank-1 matrix or tensor mean model, flashr will run a variational expectation-maximization (VEM) algorithm where the componenets and variances are assumed to be separable. For higher-ranks, a greedy algorithm is available where the VEM algorithm is iteratively run on the residuals of the previous iteration. A backfitting procedure is available for refined estimation.
Package details |
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Bioconductor views | FactorAnalysis GeneExpression RNASeq Shrinkage Software Visualisation |
Maintainer | Wei Wang <weiwang@galton.uchicago.edu> |
License | GPL-3 |
Version | 0.1.1 |
URL | https://github.com/kkdey/flashr |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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