Quasi-likelihood analysis of an ergodic diffusion plus noise

06/25/2018

∙

by   Shogo H. Nakakita, et al.

∙

0

∙

share

We consider adaptive maximum-likelihood-type estimators and adaptive Bayes-type ones for discretely observed ergodic diffusion processes with observation noise whose variance is constant. The quasi-likelihood functions for the diffusion and drift parameters are introduced and the polynomial-type large deviation inequalities for those quasi-likelihoods are shown to see the convergence of moments for those estimators.