Abstract
A stochastic model for the simulation of pulsatile hormone secretion is presented. By properly adjusting the model parameters it is possible to reproduce typical observed patterns of hormone time series. By means of simulated data, an evaluation of the rate of false-positive and false-negative errors produced by a computerized pulse detection algorithm is provided. Finally, the stochastic model is used to develop a smoothing technique based on Kalman filtering theory.
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