The question of minimizing the bias due to the survey sampling error when estimating the autocorrelation function of aggregated AR(1) processes is studied.

Using a microbased superpopulation approach some aspects of optimal prediction of aggregated AR(1) processes are studied.

Analysts using data from official statistical authorities often neglect the fact that data frequently is collected using sample surveys. We study the impact of sampling error on the estimation of the autocorrelation function for a population total under a microbased superpopulation time series...

In Cassel and Lundquist (1990) the existence of sampling bias in estimating autocorrelation functions was discussed under a superpopulation model. One restriction of that model was that the time series model should not exhibit trend. In this paper we relax that restriction. The bias of a...