A characterization of symmetric isofactorial models

Abstract

The paper examines symmetric isofactorial models. A necessary and sufficient condition for a bivariate stationary random function to be isofactorial is given. Using this characterization, a procedure for checking whether an isofactorial model is appropriate is outlined. If data indicates that an isofactorial model is adequate, the procedure also provides a method for identifying the factors of the model. The paper concentrates on the case where Z(x) takes values 0, 1, 2,..., N and the general case is discussed briefly.