A review of asymptotic theory of estimating functions

Jean  Jacod; Michael Sørensen

doi:10.1007/s11203-018-9178-8

A review of asymptotic theory of estimating functions

Jean Jacod, Michael Sørensen

Department of Mathematical Sciences

7 Citations (Scopus)

49 Downloads (Pure)

Abstract

Asymptotic statistical theory for estimating functions is reviewed in a generality
suitable for stochastic processes. Conditions concerning existence of a consistent estimator,
uniqueness, rate of convergence, and the asymptotic distribution are treated separately. Our
conditions are not minimal, but can be verified for many interesting stochastic processmodels.
Several examples illustrate the wide applicability of the theory and why the generality is
needed.

Original language	English
Journal	Statistical Inference for Stochastic Processes
Volume	21
Issue number	2
Pages (from-to)	415-434
ISSN	1387-0874
DOIs	https://doi.org/10.1007/s11203-018-9178-8
Publication status	Published - 1 Jul 2018

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A review of asymptotic theory of estimating functions

Abstract

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