Properties of empirical estimates in stochastic optimization and identification problems

DOI10.1007/BF02031709zbMath0835.90057OpenAlexW2024628283MaRDI QIDQ1896455

Pavel S. Knopov, Evgeniya J. Kasitskaya

Publication date: 28 April 1996

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02031709

zbMATH Keywords

stochastic optimizationstrong consistencyseparable Banach spacenonlinear and nonparametric regression

Mathematics Subject Classification ID

Stochastic programming (90C15) Identification in stochastic control theory (93E12) Programming in abstract spaces (90C48)

Related Items

Optimization and identification of stochastic systems ⋮ Some scientific results of Yu. M. Ermoliev and his school in modern stochastic optimization theory ⋮ Analysis of empirical estimates obtained for Gibbs distribution parameters by the maximum likelihood method ⋮ Some approaches to financial risk assessment ⋮ Method of empirical means in stochastic programming problems ⋮ Consistency and properties of large deviations of empirical estimates in stochastic optimization problems for homogeneous random fields under nonhomogeneous and homogeneous observations ⋮ Asymptotic properties of some classes of \(M\)-estimates

Cites Work

• Unnamed Item
• Asymptotic behavior of statistical estimators and of optimal solutions of stochastic optimization problems
• Asymptotic analysis of stochastic programs
• On the Convergence in Distribution of Measurable Multifunctions (Random Sets) Normal Integrands, Stochastic Processes and Stochastic Infima