Local asymptotic mixed normality property for nonsynchronously observed diffusion processes
Statistics Theory
2015-09-21 v3 Statistics Theory
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.
Cite
@article{arxiv.1310.5304,
title = {Local asymptotic mixed normality property for nonsynchronously observed diffusion processes},
author = {Teppei Ogihara},
journal= {arXiv preprint arXiv:1310.5304},
year = {2015}
}
Comments
Published at http://dx.doi.org/10.3150/14-BEJ634 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)