Minimum density power divergence estimator for diffusion processes

Sangyeol Lee () and Junmo Song

Annals of the Institute of Statistical Mathematics, 2013, vol. 65, issue 2, 213-236

Abstract: In this paper, we consider the robust estimation for a certain class of diffusion processes including the Ornstein–Uhlenbeck process based on discrete observations. As a robust estimator, we consider the minimum density power divergence estimator (MDPDE) proposed by Basu et al. (Biometrika 85:549–559, 1998 ). It is shown that the MDPDE is consistent and asymptotically normal. A simulation study demonstrates the strong robustness of the MDPDE. Copyright The Institute of Statistical Mathematics, Tokyo 2013

Keywords: Diffusion processes; The Ornstein–Uhlenbeck process; Minimum density power divergence estimator; Discretely observed sample; Robustness (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s10463-012-0366-9

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