A likelihood approximation for locally stationary processes

• 成果类型: Article
• 署名作者: Dahlhaus, R
• 署名单位: Ruprecht Karls University Heidelberg
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1015957480
• 发表日期: 2000
• 页码: 1762-1794
• 关键词: time-series models; parameter-estimation

摘要

A new approximation to the Gaussian likelihood of a multivariate locally stationary process is introduced. It is based on an approximation of the inverse of the covariance matrix of such processes. The new quasi likelihood is a generalization of the classical Whittle likelihood for stationary processes. Several approximation results are proved for the likelihood function. For parametric models, asymptotic normality and efficiency of the resulting estimator are derived for Gaussian locally stationary processes.