Maximum likelihood estimation of order m for stationary stochastic processes

Biometrika ◽  
1983 ◽  
Vol 70 (2) ◽  
pp. 381-387 ◽  
Author(s):  
ADELCHI AZZALINI
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Stochastic Processes ◽  
Likelihood Estimation ◽  
Stationary Stochastic Processes

Maximum likelihood estimation for continuous-time stochastic processes

1976 ◽  
Vol 8 (4) ◽  
pp. 712-736 ◽  
Author(s):  
Paul David Feigin
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Stochastic Processes ◽  
Continuous Time ◽  
Asymptotic Theory ◽  
Likelihood Estimation ◽  
Diffusion Approximations ◽  
Limit Theory

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.

Maximum likelihood estimation for continuous-time stochastic processes

1976 ◽  
Vol 8 (04) ◽  
pp. 712-736 ◽  
Author(s):  
Paul David Feigin
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Stochastic Processes ◽  
Continuous Time ◽  
Asymptotic Theory ◽  
Likelihood Estimation ◽  
Diffusion Approximations ◽  
Limit Theory

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.

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