Chao Wang - Colloquium Speaker

Postdoctorate Researcher, Department of Statistics and Actuarial Science, University of Iowa
Date: 
Thursday, January 28, 2016 - 12:00am
Colloquium Title: 
Quasi-Likelihood Estimation of a Censored Autoregressive Model with Eogenous Variables
Location: 
Reception at 3:00 p.m. in 241 SH / Talk at 3:30 in 61 SH

Maximum likelihood estimation of a censored autoregres-sive model with exogenous variables (CARX) requires computing the conditional likelihood of blocks of data of variable dimensions. As the random block dimension gen-erally increases with the censoring rate, maximum likelihood estimation becomes quickly numerically intractable with increasing censoring. We introduce a new estimation approach using the complete-incomplete data framework with the complete data comprising the observations were there no censoring. We introduce a system of unbiased estimating equations motivated by the complete-data score vector, for estimating a CARX model. The proposed quasi-likelihood method reduces to maximum likelihood estimation when there is no censoring, and it is computa-tionally efficient. We derive the consistency and asymptotic normality of the quasi-likelihood estimator, under mild regularity conditions. We illustrate the efficacy of the proposed method by simulations and a real application on phosphorus concentration in river water. An accompanying R package will also introduced.

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