Optimal experiment design for locally adaptive regression models

Abstract

The problem of reconstruction of dependencies using locally adaptive linear regression models is considered. The problem of a priori optimal design of experiments during identification of locally adaptive linear regression models is solved. In this case, the region of determining the active factors is divided into 2 or 3 fuzzy partitions. The problem of constructing D-optimal designs of experiment is formulated and solved