Accuracy of normal approximation for the maximum likelihood estimator and Bayes estimators in the Ornstein-Uhlenbeck process using random normings

J. P. N. Bishwal

Statistics & Probability Letters, 2001, vol. 52, issue 4, 427-439

Abstract: Using different random normings, the paper shows that the distributions of the normalized maximum likelihood estimator and normalized regular Bayes estimators of the drift parameter in the Ornstein-Uhlenbeck process observed continuously over [0,T] converge to the standard normal distribution with an error rate O(T-1/2).

Keywords: Ito; stochastic; differential; equation; Ornstein-Uhlenbeck; process; Maximum; likelihood; estimator; Bayes; estimators; Rate; of; weak; convergence; Random; normings (search for similar items in EconPapers)
Date: 2001
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Citations: View citations in EconPapers (2)

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