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Abstract.
We study the estimation of parameters of one-dimensional diffusion processes that are discretely observed. We construct an estimator of the parameters based on the minimum Hellinger distance method. Under conditions which ensure the ergodicity and geometrically α-mixing of the Markov process, we establish the almost sure convergence and the asymptotic normality of the estimator.
Keywords: Hellinger distance estimation; diffusion processes; geometric ergodicity; α-mixing process; consistence; asymptotic normality
Received: 2012-06-12
Revised: 2013-09-06
Accepted: 2013-09-08
Published Online: 2013-11-02
Published in Print: 2013-12-01
© 2013 by Walter de Gruyter Berlin Boston