Showing papers on "STAR model published in 1968"

Distribution of residual autocorrelations in integrated autoregressive-moving average time series models.

Abstract: : It is shown that to a close approximation the residuals from any moving average or mixed autoregressive - moving average process will be the same as those from a suitably chosen autoregressive process. The adequacy of this approximation is confirmed by empirical calculation. It follows from this that one need not consider separately these two classes of processes.

Bayesian Autoregressive Time Series Analysis

Abstract: Two Bayesian autoregressive time series models for partially observable dynamic processes are presented. In the first model, a general inference procedure is developed for the situation in which k previous values of the time series plus a change error determine the next value. This general model is specialized to an example in which the observational and change errors follow a normal probability law; the results for k = 1 are given and discussed. The second general model adds the facility for simultaneously inferring an unknown and unchanging parameter of the time series. This model is specialized to the same normal example presented earlier, with the precision of the change error as the unknown process parameter.