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Local asymptotic mixed normality property for nonsynchronously observed diffusion processes

Authors
  • Ogihara, Teppei
Type
Published Article
Publication Date
Sep 18, 2015
Submission Date
Oct 20, 2013
Identifiers
DOI: 10.3150/14-BEJ634
Source
arXiv
License
Yellow
External links

Abstract

We prove the local asymptotic mixed normality (LAMN) property for a family of probability measures defined by parametrized diffusion processes with nonsynchronous observations. We assume that observation times of processes are independent of processes and we will study asymptotics when the maximum length of observation intervals goes to zero in probability. We also prove that the quasi-maximum likelihood estimator and the Bayes-type estimator proposed in Ogihara and Yoshida (Stochastic Process. Appl. 124 (2014) 2954-3008) are asymptotically efficient.

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