Knopov P.S., Kasitskaya E.J.
Consistency and properties of large deviations of empirical estimates in stochastic optimization problems for homogeneous random fields under nonhomogeneous and homogeneous observations

The paper considers a stochastic programming problem with the empirical function constructed from nonhomogeneous observations of a homogeneous random field. The field satisfying the strong mixing condition is investigated in the problem. The conditions whereby the empirical estimate is consistent are given, and large deviations of the estimate for homogeneous observations are estimated. © 2021, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords: large deviations, nonhomogeneous observations, random field homogeneous in a strict sense, stochastic programming problem, strong mixing condition, Computer science, Cybernetics, Empirical estimate, Empirical functions, Large deviations, Non-homogeneous, Random fields, Stochastic optimization problems, Strong mixing conditions, Stochastic programming

Cite:
Knopov P.S., Kasitskaya E.J. (2021). Consistency and properties of large deviations of empirical estimates in stochastic optimization problems for homogeneous random fields under nonhomogeneous and homogeneous observations. Cybernetics and Systems Analysis, 57 (1), 21–34. doi: https://doi.org/10.1007/s10559-021-00326-0 http://jnas.nbuv.gov.ua/article/UJRN-0001199854 [In Russian].