Constructing D-optimal designs from a list of candidate samples

Abstract The main characteristics of a Matlab program to select D-optimal subsets of calibration samples for multiple linear regression are described. The performance of Fedorov's exchange algorithm to select samples is compared with the Kennard-Stone algorithm and the random selection of samples into training and test sets.