Measure of predictability of a stationary two dimensionally indexed autoregressive moving-average models.

In this article, we consider a measure of predictability of a random field following a stationary two-dimensionally indexed autoregressive moving-average (2-D ARMA). The purpose of this article is two-fold. First, we give a characterization of equal predictability processes by providing necessary and sufficient conditions, which highlight the role of the coefficients of the moving average (MA) and the equivalent autoregressive (EAR) representations. Second, we implement a procedure allowing us to carry out a test of equal predictability. A simulation study is presented and an application to real data of wheat yield is reported. [ABSTRACT FROM AUTHOR]