UBR provides Bayesian regularization methods for high-dimensional linear regression. The methods implemented in this package leverage a novel data augmentation scheme based on the scale mixture of uniform (SMU) distribution that leads to a set of efficient Gibbs samplers with tractable full conditional posterior distributions and superior performance over existing methods.
Package details |
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Maintainer | Himel Mallick <himel.mallick@merck.com> |
License | MIT |
Version | 0.1 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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