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Author Favetto, Benjamin
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Noisy Observation ♦ Ergodic Diffusion ♦ Drift Parameter ♦ Diffusion Parameter ♦ Central Limit Theorem ♦ Local Mean ♦ Rate Optimality ♦ Specific Minimum Contrast Estimator ♦ Diffusion Process ♦ General Estimating Function ♦ Discrete Time Noisy Observation ♦ High Frequency ♦ Simple Condition ♦ Parametric Inference
Abstract In this article, general estimating functions for ergodic diffusions sam-pled at high frequency with noisy observations are presented. The the-ory is formulated in term of approximate martingale estimating func-tions based on local means of the observations, and simple conditions are given for rate optimality. The estimation of diffusion parameter is faster that the estimation of drift parameter, and the rate of conver-gence in the Central Limit Theorem is classical for the drift parameter but not classical for the diffusion parameter. The link with specific minimum contrast estimators is established, as an example. Key Words: estimating functions, diffusion process, parametric inference, discrete time noisy observations, central limit theorem
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Publisher Date 2010-01-01