The Estimation of Stationary Stochastic Regression Parameters Reexamined

This article reexamines the problem of estimation in repeated regression experiments wherein the regression parameters vary according to a stationary stochastic process with known covariance structure. Best linear unbiased estimators, more efficient than those recently proposed by Burnett and Guthrie, are derived.