This paper presents a new approach for time series prediction using local dynamic modeling. The proposed method is composed of three blocks: a Time Delay Line that transforms the o...
Abstract— We present a novel framework that applies a metalearning approach to clustering algorithms. Given a dataset, our meta-learning approach provides a ranking for the candi...
Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data...
We propose an efficient forward regression algorithm based on greedy optimization of marginal likelihood. It can be understood as a forward selection procedure which adds a new bas...
A general approach for developing distribution free tests for general linear models based on simplicial depth is applied to multiple regression. The tests are based on the asympto...