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On designing experiments for a dynamic response modeled by regression splines
Author(s) -
Pan Rong,
Saleh Moein
Publication year - 2019
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.2490
Subject(s) - computer science , mathematical optimization , design of experiments , function (biology) , spline (mechanical) , variable (mathematics) , mathematics , statistics , engineering , mathematical analysis , structural engineering , evolutionary biology , biology
Dynamic response systems are often found in science, engineering, and medical applications, but the discussion on experimental design for such a system is relatively rare in literature. For an experimenter, designing such experiments requires making decisions on (1) when or where to take response measurements along the dynamic variable and (2) how to choose the combination of experimental factors and their levels. The first consideration is unique for such experiments, especially when the measurement cost is high. In this paper, we present a design approach through the mixed‐effect linear model, which is based on a hierarchical B‐spline function for the dynamic response. We develop several theorems that can assist in finding a statistically efficient sampling plan and propose an algorithm for searching the D‐optimal design of a dynamic response system.