**METHOD ****NON-GAUSSIAN ****DATA DEFINITION BY PROBABILISTIC MODELS**** ****BASED ON THE TRUNCATED NORMAL DISTRIBUTIONS**

*I.K. Vasilyeva*

The statistical model for the components of multidimensional random
variable based on the truncated
normal distributions and the technique of the model’s parameters estimation are
proposed. The results of the approximation a number of non-Gaussian
distributions by the truncated Gaussian probability distributions and their
mixtures are produced. Test of the model’s acceptability completed for to
describe the results of random variables simulation with uniform, exponential,
Rayleigh and arcsine probability distributions. It is shown that the proposed
model is adequate, thereby justified background for the development of a
sufficiently universal multidimensional statistical model in the form of
K-components mixture of N-dimensional truncated Gaussian distributions.

**Key words:** truncated normal distribution, distribution parameters, mixture
parameters, statistical estimation, criterion function, approximation.