Maximum likelihood estimation for continuous-time stochastic processes

1 June 1976

journal article
research article
Published by Cambridge University Press (CUP) in Advances in Applied Probability

Vol. 8 (04) , 712-736
https://doi.org/10.1017/s0001867800042890

Abstract

This paper is mainly concerned with the asymptotic theory of maximum likelihood estimation for continuous-time stochastic processes. The role of martingale limit theory in this theory is developed. Some analogues of classical statistical concepts and quantities are also suggested. Various examples that illustrate parts of the theory are worked through, producing new results in some cases. The role of diffusion approximations in estimation is also explored.

Keywords

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