Stochastical computation methods and experimental designing

Abstract

This paper contains a brief review of the most important results obtained by the staff of the department of statistical modeling. Results include mathematical justification of computer simulation of randomness, stochastic methods of solving equations, stochastic optimization, study of stochastic stability and parallelism of Monte-Carlo algorithms. In the area of experiment planning, special attention is paid to regression experiment under nonlinear parameterization. The list of references mainly includes monographs written by members of the department. The exceptions are some articles with results not included in them.