Abstract
There are certain situations where one observes several short time series. For instance, in testing the effect of a drug on patients, a doctor may obtain 3 or 4 blood pressure measurements every three hours from several patients; thus we have several short time series to deal with. In this paper, we address the estimation of the correlation parameter of a first order autoregressive process from a short time series. The proposed estimators are compared using a simulation study. Parameter estimation based on the method of maximum likelihood when there is extra source of variation in the model seems to give better results.
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