  The standard approach for studying the periodic ARMA model with coefficients
that vary over the seasons is to express it in a vector form. In this paper we
introduce an alternative method which views the periodic formulation as a time
varying univariate process and obviates the need for vector analysis. The
specification, interpretation, and solution of a periodic ARMA process enable
us to formulate a forecasting method which avoids recursion and allows us to
obtain analytic expressions of the optimal predictors. Our results on periodic
models are general, analogous to those for stationary specifications, and place
the former on the same computational basis as the latter.
