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Minimum contrast estimation in diffusion processes

Published online by Cambridge University Press:  14 July 2016

Vĕra Lánska
Vĕra Lánska*
Affiliation:
Institute of Information Theory and Automation, Czechoslovak Academy of Sciences
*
∗Postal address: Institute of Information Theory and Automation, Czechoslovak Academy of Sciences, 18076 Prague 8, Pod vodárenskou vĕž í4, Czechoslovakia.
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Abstract

This paper is concerned with the asymptotic theory of estimates of an unknown parameter in continuous-time Markov processes, which are described by non-linear stochastic differential equations. The maximum likelihood estimate and the minimum contrast estimate are investigated. For these estimates strong consistency and asymptotic normality are proved. The unknown parameter is assumed to take its values either in an open or in a compact set of real numbers.

Keywords

CONTINUOUS-TIME STOCHASTIC PROCESSMAXIMUM LIKELIHOOD FUNCTIONMINIMUM CONTRAST FUNCTIONESTIMATEASYMPTOTIC BEHAVIOUR
Type
Research Papers
Information
Journal of Applied Probability , Volume 16 , Issue 1 , March 1979 , pp. 65 - 75
Copyright
Copyright © Applied Probability Trust 1979 

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References

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