Author:

Keywords:

optimum design of experiments, q-optimality, adjustment algorithm, exchange algorithm, run order, time trend, Science & Technology, Technology, Physical Sciences, Computer Science, Interdisciplinary Applications, Statistics & Probability, Computer Science, Mathematics, Q-optimality, 0104 Statistics, 0802 Computation Theory and Mathematics, 1403 Econometrics, 3802 Econometrics, 4905 Statistics

Abstract:

Using a systematic run order can be the proper way to conduct an experiment when a temporal trend is present, The construction of run orders that are optimally balanced for time trend effects is based on maximization of the information on the parameters of interest whereas the parameters of the postulated time trend are treated as nuisance parameters, An adjustment algorithm to improve the efficiency of the run orders obtained from a search over a predefined set of candidate points is presented. This is done by repeatedly moving the design points or the time points of the candidate list a small amount along their axes as long as an improvement in the efficiency is obtained. It is illustrated that the adjustment algorithm involves substantial increases in the efficiency of the run orders, The use of the adjustment algorithm in addition to a search over a coarse grid of candidate points is especially recommended in situations where the computation time has to be kept within reasonable limits. (C) 2002 Elsevier Science B.V. All rights reserved.