This paper presents an algorithm to estimate parameters of a mathematical model of a bipartite endocrine axis. Secretion of one of the involved hormones is stimulated by the concentration of another one, called release hormone, with the latter secreted in a pulsatile manner. The hormone mechanism in question appears often in animal and human endocrine systems, i.e. in the regulation of testosterone in the human male. The model has been introduced elsewhere and enables the application of the theory of pulse-modulated feedback control systems to analysis of pulsatile endocrine regulation. The state-of-the art methods for hormone secretion analysis could not be applied here due to different modeling approach. Based on the mathematical machinery of constrained nonlinear least squares minimization, a parameter estimation algorithm is proposed and shown to perform well on actual biological data yielding accurate fitting of luteinizing hormone concentration profiles. The performance of the algorithm is compared with that of state-of-the art techniques and appears to be good especially in case of undersampled data.
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