Local asymptotic mixed normality for discretely observed non-recurrent Ornstein-Uhlenbeck processes

Yasutaka Shimizu*

*この研究の対応する著者

研究成果査読

8 被引用数 (Scopus)

抄録

Consider non-recurrent Ornstein-Uhlenbeck processes with unknown drift and diffusion parameters. Our purpose is to estimate the parameters jointly from discrete observations with a certain asymptotics. We show that the likelihood ratio of the discrete samples has the uniform LAMN property, and that some kind of approximated MLE is asymptotically optimal in a sense of asymptotic maximum concentration probability. The estimator is also asymptotically efficient in ergodic cases.

本文言語English
ページ(範囲)193-211
ページ数19
ジャーナルAnnals of the Institute of Statistical Mathematics
64
1
DOI
出版ステータスPublished - 2012 2
外部発表はい

ASJC Scopus subject areas

  • 統計学および確率

フィンガープリント

「Local asymptotic mixed normality for discretely observed non-recurrent Ornstein-Uhlenbeck processes」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル