Autocorrelation, Autoregression and Autoregressive Approximation

Theorems are proved relating to the rate of almost sure convergence of autocovariances, and hence autocorrelations, to their true values. These rates are uniform in the lag up to some order $P(T)$, increasing with $T$. The key assumption is that the process is stationary and the best linear predictor is the best predictor. In particular for an ARMA process and $P(T) = O\{(\ln T)^a\}, a < \infty$, the rate is $O\{(\ln \ln T/T)^{1/2}\}$. These results are used to discuss autoregressions and the use of autoregressions to approximate the structure of a more general process by increasing the order of the autoregression with $T$.