Two chi-square statistics for determining the orders p and q of an ARMA (p, q) process

The theta , lambda , and eta functions have been previously proposed for use in choosing the autoregressive and moving-average orders of an ARMA (q, p) process visually. Two chi-square statistics associated with these three functions are presented and used here to determine the orders of an ARMA process statistically. It is shown that the two statistics are asymptotically equivalent to the Quenouille-Walker's goodness-of-fit test statistic, which is a Lagrange multiplier test statistic. Some numerical examples are presented to illustrate the usefulness of the two chi-square statistics as well as the three functions in ARMA modeling.<
>