Tutorials for the randomGLM R package
Lin Song, P. Langfelder, S. Horvath
Human Genetics, Biostatistics, University of California, Los Angeles
shorvath (at) mednet (dot) ucla (dot) edu
This page provides a set of tutorials for the randomGLM package.
Before going through the tutorials, please make sure you have installed (the newest version of) the randomGLM package and all packages it depends on. Please refer to the main randomGLM page and the installation instructions for details.
We provide the following tutorials
- Mini Tutorial
- Tutorial for UCI machine learning benchmark data
- Tuning Tutorial for a binary trait
that shows how to choose parameters based on out-of-bag estimate of the predictive accuracy. It uses the srbct.rda data
- Tuning Tutorial for a quantitative trait
that shows how to choose parameters based on out-of-bag estimate of the predictive accuracy. It uses the mouse data mouse.rda
- Tutorial for quantitative gene traits from the brain cancer data set.
- Tutorial that illustrates how to interpret the RGLM predictor.
The tutorials on this page were last Jan 31, 2013. This changelog
provides a summary of the updates.