Experiment Design: Identification and Validation of Simple and Complex Models of Endocrine-Metabolic Systems
Mathematical models in conjunction with dynamic input-output data are increasingly used in quantitative studies of endocrine-metabolic systems both in physiology and clinical medicine /1/.The purpose of modeling includes understanding, estimation of internal (non-measurable) parameters, diagnosis and control. Depending on the purpose of the study, models of different complexity are developed, and an essential role is played by identification and validation, respectively the determination of structure and parameter values and the assessment of whether or not the postulated model is adequate for its intended purpose.
KeywordsFisher Information Matrix Sampling Schedule Optimal Input Optimal Experiment Design Identifiability Analysis
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