Estimating normal regression parameters on the basis of an extended measurement vector

Classical normal regression theory is applied to processing discrete measurements when the measurement vector includes not only sample values of the information process but also the values of the derivatives of various orders. Traditional cases are considered of recovering the normal-regression parameters in the polynomial class and in the class of parameter-linear functions.