T-ridge

This repository provides the implementations of the methods described in Tuning-free ridge estimators for high-dimensional generalized linear models.

See also

An R package for the T-Ridge can be found here https://github.com/mohan-zhao/myTridge. Most of the functions are implemented in C++.

Simulations

We provide an example code in SimulationStudy.Rmd for a comparison of averaged relative prediction errors with 10-fold cross-validated ridge for three types of generalized linear models including Gaussian, Poisson, and Bernoulli cases. Developed for R 3.6.1.

Repository authors

• Shih-Ting Huang, Ph.D. student in Mathematical Statistics, Ruhr-University Bochum

• Fang Xie, post-doctoral researcher in Mathematical Statistics, Ruhr-University Bochum

• Johannes Lederer, Professor in Mathematical Statistics, Ruhr-University Bochum

Other folders

Additional functions : The source codes of some functions loaded in SimulationStudy.Rmd that are required in the simulation study.

SimulationProcess : The source codes loaded in SimulationStudy.Rmd for generating the simulation results.

RealData : Two data sets, mass-spec500peaks.csv, and riboflavin.csv for applying the t-ridge pipeline on real data and the R codes, RealData.R for the real data analysis.

Supported languages and platforms

All of the codes in this repository are written in R and supports all plarforms which are supported by R itself.

Dependencies

This repository depends on R libraries glmnet, MASS, htmlTable, and pander.

Licensing

The HDIM package is licensed under the MIT license. To view the MIT license please consult LICENSE.txt.

References

Tuning-free ridge estimators for high-dimensional generalized linear models

Cite as "S. Huang, F. Xie, and J. Lederer. Tuning-free ridge estimators for high-dimensional generalized linear models. arXiv:2002.11916".