Statistics Seminar（2016-14）

Topic:Estimation of Semi-Varying Coefficient Time Series Models With ARMA Errors

Speaker:Lei Huang, Southwest Jiaotong University

Time:Tuesday, 14 June, 14:00-15:00

Place:Room 219, Guanghua Building 1

Abstract:

Serial correlation in the residuals of time series models can cause bias in both model estimation and prediction. However, models with such serially correlated residuals are difficult to estimate, especially when the regression function is nonlinear. Existing estimation methods require strong assumption for the relation between the residuals and the regressors, which excludes the commonly used autoregressive models in time series analysis. By extending the Whittle likelihood estimation, this paper investigates in details a semi-parametric autoregressive model with ARMA sequence of residuals. Asymptotic normality of the estimators is established, and a model selection procedure is proposed. Numerical examples are employed to illustrate the performance of the proposed estimation method and the necessity of incorporating the serial correlation in the residuals.

Introduction:

Dr. Lei Huang received his Ph.D. in Statistics from National University of Singapore in 2015 and is currently an Assistant Professsor of Statistics at Southwest Jiaotong University. His research interest is statistical theory with a focus on nonlinear time series analysis.

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