File Exchange

image thumbnail

Robust Lasso Regression with Student-t Residuals

version 1.0.0.0 (24.8 KB) by Statovic

Statovic (view profile)

Estimate robust lasso regression models with Student-t residuals

3 Downloads

Updated 21 May 2017

View License

This code implements the estimation of robust regression models using the lasso procedure. Robustness is handled by modelling the residuals as arising from a Student-t distribution with an appropriate degrees-of-freedom. The optimization is performed using the expectation-maximization algorithm.
Primary features of the code:
* Automatically produce a complete lasso regularization path for a given degrees-of-freedom
* Select amount of regularization, and the degrees-of-freedom using cross-validation or information criteria

To cite this toolbox:
Schmidt, D.F. and Makalic, E.
Robust Lasso Regression with Student-t Residuals
Lecture Notes in Artificial Intelligence, to appear, 2017

Comments and Ratings (0)

MATLAB Release Compatibility
Created with R2016a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Discover Live Editor

Create scripts with code, output, and formatted text in a single executable document.


Learn About Live Editor