๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Rates of convergence of approximate maximum likelihood estimators in the Ornstein-Uhlenbeck process

โœ Scribed by J.P.N. Bishwal; A. Bose


Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
828 KB
Volume
42
Category
Article
ISSN
0898-1221

No coin nor oath required. For personal study only.

โœฆ Synopsis


Berry-Esseen bounds, with random and nonrandom normings, and large deviation probability bounds for two approximate maximum likelihood estimators of the drift parameter in the

Ornstein-Uhlenbeck process are obtained when the process is observed at equally spaced dense time points. Also obtained are the rates at which these estimators converge to the maximum likelihood estimator based on continuous observation.


๐Ÿ“œ SIMILAR VOLUMES


Optimal designs for parameter estimation
โœ Maroussa Zagoraiou; Alessandro Baldi Antognini ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 152 KB ๐Ÿ‘ 2 views

## Abstract This paper deals with optimal designs for Gaussian random fields with constant trend and exponential correlation structure, widely known as the Ornsteinโ€“Uhlenbeck process. Assuming the maximum likelihood approach, we study the optimal design problem for the estimation of the trend ยต and

Non-convergence of the approximate maxim
โœ V. Panuska ๐Ÿ“‚ Article ๐Ÿ“… 1980 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 205 KB

The question of non-convergence of the approximate maximum likelihood identification algorithm is discussed. It is pointed out that although there are systems for which in theory the algorithm does not converge to any finite limit, the computer implementation always gives results which settle at con

Maximum Likelihood Estimation of the Mor
โœ B. N. Dimitrov; S. T. Rachev; Dr. Sci. A. Yu. Yakovlev ๐Ÿ“‚ Article ๐Ÿ“… 1985 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 465 KB ๐Ÿ‘ 2 views

Maximum likelihood estimator is obtained for the mortality rate function of a specific type appearing in survival data andysis. Strict consistency of this estimator is proved.

Comments on โ€˜non-convergence of the appr
โœ Lennart Ljung ๐Ÿ“‚ Article ๐Ÿ“… 1980 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 130 KB

The following three comments and claims are made: 1. The 'approximate maximum likelihood method ' [called RELS in (S6derstr6m et al., 1978)] may work well in applications even though it has been proven that it does not always converge. 2. It was incorrect in (\* Ljung et al., 1975) to call the 'si