kperrakis/sbr: Sparse and Scalable Bayesian Regression for Linear Models
Scalable Bayesian regression for normal linear models with multiple design matrices from different types of data sources. Also provides sparse solutions via posterior post-processing. Fast and tuning-free procedures that scale up to ultra-high dimensions.
Getting started
Browse package contents
Package details |
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| Maintainer | |
| License | GPL-2 |
| Version | 0.0.0.9000 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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