Discriminant Analysis for Regression Models with Stationary Long-Memory Disturbances

We shall consider the problems of classifying an observation from regression model with stationary long-memory or short-memory disturbances into one of two populations described by the mean functions of the model. We use the log-likelihood ratio as a discrimant statistic which is optimal in the sense of its minimizing the misclassification probabilities. Then we confirm the theoretical results by some simple polynomial regression models.