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  • 标题:Estimation for Non-Gaussian Locally Stationary Processes with Empirical Likelihood Method
  • 本地全文:下载
  • 作者:Hiroaki Ogata
  • 期刊名称:Advances in Decision Sciences
  • 印刷版ISSN:2090-3359
  • 电子版ISSN:2090-3367
  • 出版年度:2012
  • 卷号:2012
  • DOI:10.1155/2012/704693
  • 出版社:Hindawi Publishing Corporation
  • 摘要:An application of the empirical likelihood method to non-Gaussian locally stationary processes is presented. Based on the central limit theorem for locally stationary processes, we give the asymptotic distributions of the maximum empirical likelihood estimator and the empirical likelihood ratio statistics, respectively. It is shown that the empirical likelihood method enables us to make inferences on various important indices in a time series analysis. Furthermore, we give a numerical study and investigate a finite sample property.
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