Valid Edgeworth expansions of M-Estimators in regression models with weakly dependent residuals

Masanobu Taniguchi*, Madan L. Puri

*この研究の対応する著者

研究成果: Chapter

抄録

Consider a linear regression model y t = x t β+u t where the u t 's are weakly dependent random variables, the x t ,'s are known design nonrandom variables, and β is an unknown parameter. We define an M-estimator β n of β corresponding to a smooth score function. Then, the second-order Edgeworth expansion for β n is derived. Here we do not assume the normality of (u t ), and (u t ) includes the usual ARMA processes. Second, we give the second-order Edgeworth expansion for a transformation T(β n ) of β n . Then, a sufficient condition for T to extinguish the second-order terms is given. The results are applicable to many statistical problems.

本文言語English
ホスト出版物のタイトルProbability Theory and Extreme Value Theory
出版社De Gruyter Mouton
ページ517-532
ページ数16
2
ISBN(電子版)9783110917826
ISBN(印刷版)9789067643856
出版ステータスPublished - 2011 7 11
外部発表はい

ASJC Scopus subject areas

  • 数学 (全般)

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