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The Simulation, Fitting, and Testing of a Stochastic Cellular Proliferation Model

David G. Hoel and Toby J. Mitchell
Biometrics
Vol. 27, No. 1 (Mar., 1971), pp. 191-199
DOI: 10.2307/2528937
Stable URL: http://www.jstor.org/stable/2528937
Page Count: 9
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The Simulation, Fitting, and Testing of a Stochastic Cellular Proliferation Model
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Abstract

A stochastic model for the growth of a cell population is proposed, and is studied by means of simulations on a digital computer. In order to fit this model to experimental data, repeated computer simulations are performed and the `distance' between the data and the simulated trials is studied. By viewing the expectation of this `distance' as a response surface over the parameter space of the model, standard response surface methods may be used to optimize the fit. This technique is used to fit several competing models to some data of Kubitscheck [1962] on the growth of colonies of E. coli cells. Monte Carlo procedures for testing the `goodness of fit' of these models are proposed and carried out. Although these methods are unrefined, they permit the experimenter to consider his data in the light of stochastic models for which mathematical results are not available.

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