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Properties of empirical estimates in stochastic optimization and identification problems

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Abstract

This paper deals with a stochastic optimization problem when its decision parameter belongs to a separable Banach space. Conditions under which strong consistency of the parameter empirical estimates holds, are established. Leastl 1-norm estimates for two models (nonlinear and nonparametric regression) are investigated as special cases of such empirical estimates.

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Authors and Affiliations

  1. Institute of Cybernetics, Ukranian Academy of Sciences, Kiev, Ukraine

    P. S. Knopov & E. J. Kasitskaya

Authors
  1. P. S. Knopov
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  2. E. J. Kasitskaya
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Knopov, P.S., Kasitskaya, E.J. Properties of empirical estimates in stochastic optimization and identification problems. Ann Oper Res 56, 225–239 (1995). https://doi.org/10.1007/BF02031709

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  • DOI: https://doi.org/10.1007/BF02031709

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