Partial least squares (PLS) is a dimensionality reduction technique used as an alternative to ordinary (OLS) in situations where the data colinear or high dimensional. Both PLS and OLS provide mean based estimates, which are extremely sensitive presence of outliers heavy tailed distributions. In contrast, quantile regression that computes robust estimates. this work, multivariate extended frame...

This article discusses an extension of censored quantile regression to a distributed setting. With the growing availability massive datasets, it is oftentimes arduous task analyze all data with limited computational facilities efficiently. Our proposed method, which attempts overcome this challenge, comprised two key steps, namely: (i) estimation both Kaplan-Meier estimator and model coefficien...