Maximum Likelihood Estimation for Short Time Series with Replicated Observations: A Simulation Study

by Shelton Peiris,R.Mellor and P.Ainkaran.

Abstract: Analysis of a large number of independent replications from short, first order autoregressive type time series is considered. Maximum likelihood estimation (mle) procedure is discussed in both approximate and exact forms. A simulation study is carried out. It is shown that both the approximate and exact mle methods provide unbiased and very efficient (in the minimum mean square sense) estimates for the parameters.

Key Words: Time series, Correlation, Estimation, Bias, Repeated measurements, Efficient, Maximum likelihood, Minimum mean square

Authors:
Shelton Peiries, shelton@maths.usyd.edu.au
R. Mellor, r.mellor@uws.edu.au
>P. Ainkaran, karan@maths.usyd.edu.au

Editor: Hatemi-J, Abdulnasser,Abdulnasser.Hatemi-J@ish.his.se

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