Asymptotic theory of conditional inference for stochastic processes
type: Item
instance of: scholarly article
title: Asymptotic theory of conditional inference for stochastic processes
zbMATH Open document ID: 0611.62105
DOI: 10.1016/0304-4149(86)90116-X
author: Paul D. Feigin
published in: Stochastic Processes and their Applications
publication date: 1986-01-01T00:00:00Z
review text: This paper develops an approach to conditional inference for nonergodic stochastic process models by considering asymptotic properties. The context for most of the analysis is that of \textit{L. Le Cam}'s local asymptotic theory [Proc. 6th Berkeley Sympos. Math. Statist. Probab., Univ. Calif. 1970, 1, 245-261 (1972; Zbl 0271.62004)], in particular, the locally asymptotically mixed normal (LAMN) situation. An attempt has been made to evaluate local asymptotic properties of global procedures.
Mathematics Subject Classification ID: 62M07
Mathematics Subject Classification ID: 62C99
zbMATH DE Number: 3988543
zbMATH Keywords: decision theoretic conditionality
zbMATH Keywords: approximate ancillarity
zbMATH Keywords: local ancillarity
zbMATH Keywords: asymptotic conditional risk
zbMATH Keywords: conditional inference
zbMATH Keywords: nonergodic stochastic process
zbMATH Keywords: local asymptotic theory
zbMATH Keywords: locally asymptotically mixed normal
zbMATH Keywords: LAMN
MaRDI profile type: Publication
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Wikidata QID: Q126654393
description: scientific article; zbMATH DE number 3988543