Sample Partitioning Estimation for Ergodic Diffusions: Application to Ornstein-Uhlenbeck Diffusion

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Abstract

When a diffusion is ergodic its transition density converges to its invariant density, see Durrett (1998). This convergence enabled us to introduce a sample partitioning technique that gives in each sub-sample, maximum likelihood estimators. The averages of these being a natural choice as estimators. To compare our estimators with the optimal we obtained from martingale estimating functions, see Sorensen (1998), we used the Ornstein-Uhlenbeck process for which exact simulations can be carried out.
Original languageUnknown
Pages (from-to)117-122
JournalDiscussiones Mathematicae Probability and Statistics
Volume30 (1)
Issue numberNA
Publication statusPublished - 1 Jan 2010

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