Optimal prediction designs in finite discrete spectrum linear regression models

In the paper, we solve the n-point optimal prediction design problem for the simplest nontrivial finite discrete spectrum linear regression models with correlated observations. We show that for all the models in consideration, there exists an optimal prediction design supported on at most three distinct points, which can be computed using one-dimensional optimization. In some cases, an optimal prediction design can be found explicitly.