Back to Departmental Colloquium: Spring 2012
Departmental Colloquium
Date: Thursday, Jan 12, 2012
Time: 4:15PM
Location: JWB 335
Hailin Sang
Indiana University, Bloomington
Title |
Autoregressive model selection with simultaneous sparse coefficient estimation |
Abstract |
In this talk we study a sparse coefficient estimation procedure for autoregressive (AR) models based on penalized conditional maximum likelihood. The penalized conditional maximum likelihood estimator (PCMLE) thus developed has the advantage of performing simultaneous coefficient estimation and model selection. Mild conditions are given on the penalty function and the innovation process, under which the PCMLE satisfies a strong consistency and oracle property, respectively. Two penalty functions, least absolute shrinkage and selection operator (LASSO) and smoothly clipped average deviation (SCAD), are considered as examples, and SCAD is shown to have better performances than LASSO. At the end, we provide a simulation study and an application of this method to a historical price data of the US Industrial Production Index for consumer goods, and the result is very promising. This is a joint work with Yan Sun. |
Computational Mathematics
Applied Mathematics