Investigating Distribution of the Model Parameters Estimates for the Population System Using Numerical Methods

The paper is aimed at determining the marginal distributions of the estimates of model parameters for a nonlinear dynamic model of the cell population dynamics. The cell population system evolves in the laboratory (in vitro) and comprises two types of cells.Basic estimates of model parameters are obtained on a single limited sample of experimental data. The value of the number of populations of each cell type is obtained from the experiment at equal intervals of time. This paper proposes a technique for determining the marginal distributions of the parameter estimates using numerical modeling.This technique includes the identification of parameters of nonlinear models and test of the obtained model adequacy with base parameter estimates, the identification of the initial data and finding the reference trajectory. The initial data for the trajectory are found using the least squares method, while minimizing the deviation from the experimental trajectory. Data sets on measured densities of the populations at specific points in time are generated using the reference trajectory and the normally distributed random numbers generator. The problem of obtaining estimates of system parameters is solved for each data set. Tests of hypotheses about the marginal distribution of each parameter are carried out based on the calculated set of estimated parameters. To prove hypothesis, the Kolmogorov test is used. The description of a numerical example is included. The obtained marginal distributions of the parameter estimates can be further used to evaluate the probabilities of different scenarios of the population system development.DOI: 10.7463/mathm.0415.0812686