WEAK-CONVERGENCE OF THE SEQUENTIAL EMPIRICAL PROCESSES OF RESIDUALS IN ARMA MODELS
成果类型：
Article
署名作者：
BAI, JS
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
DOI：
10.1214/aos/1176325771
发表日期：
1994
页码：
2051-2061
关键词：
摘要：
This paper studies the weak convergence of the sequential empirical process (K) over cap(n), of the estimated residuals in ARMA(p, q) models when the errors are independent and identically distributed. It is shown that, under some mild conditions, (K) over cap(n), converges weakly to a Kiefer process. The weak convergence is discussed for both finite and infinite variance time series models. An application to a change-point problem is considered.
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