FIQ / Investigación

Grupo de Estadística / Statistics Group

This repository contains code to reproduce results in:

L. Forzani, R. Garcia Arancibia, P. Llop and D. Tomassi, “Supervised dimension reduction for ordinal predictors” (submitted).
The main code for the proposed method is written in MATLAB. Nevertheless, some comparisons with other methods require running scripts in R. Instructions on how to use the code and reproduce results reported in the manuscript are detailed in the README.pdf file located in the main folder.
Supervised dimension reduction for ordinal predictors [LINK CODE] [LINK ARXIV]

D. Tomassi, L. Forzani, E. Bura and R. Pfeiffer, "Sufficient dimension reduction for censored predictors". To appear in Biometrics.
The code for the proposed method is written in MATLAB. Usage instructions are detailed in the README.pdf file located in the main folder. Sufficient dimension reduction for censored predictors (code)

R. D. Cook, L. Forzani and D. Tomassi, “LDR: a package for likelihood-based sufficient dimension reduction”. Journal of Statistical Software, Vol. 39(3), 2011. 
The code for the proposed method is written in MATLAB. LDR package (code).