Estimation of the mean of some stationary markov sequences
This paper deals with the estimation of the mean e of the stationary distribution of some Markov sequences. In particular, if one can identify the error variables from a given realization of the model, it is possible to obtain improved estimators based on the errors. A two stage procedure for determining the regression parameter without error and then estimating the mean is presented. The conditional least square and the best linear unbiased estimators of e are studied and compared with the traditional timeaverage. The asymptotic properties of these estimators are also established.