Moment convergence of Z-estimators

Ilia Negri*, Yoichi Nishiyama

*この研究の対応する著者

研究成果: Article査読

1 被引用数 (Scopus)

抄録

The problem to establish the asymptotic distribution of statistical estimators as well as the moment convergence of such estimators has been recognized as an important issue in advanced theories of statistics. This problem has been deeply studied for M-estimators for a wide range of models by many authors. The purpose of this paper is to present an alternative and apparently simple theory to derive the moment convergence of Z-estimators. In the proposed approach the cases of parameters with different rate of convergence can be treated easily and smoothly and any large deviation type inequalities necessary for the same result for M-estimators do not appear in this approach. Applications to the model of i.i.d. observation, Cox’s regression model as well as some diffusion process are discussed.

本文言語English
ページ(範囲)387-397
ページ数11
ジャーナルStatistical Inference for Stochastic Processes
20
3
DOI
出版ステータスPublished - 2017 10月 1

ASJC Scopus subject areas

  • 統計学および確率

フィンガープリント

「Moment convergence of Z-estimators」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