Properties of empirical estimates in stochastic optimization and identification problems

Properties of empirical estimates in stochastic optimization and identification problems

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Article ID: iaor19952296
Country: Switzerland
Volume: 56
Issue: 1
Start Page Number: 225
End Page Number: 239
Publication Date: Jun 1995
Journal: Annals of Operations Research
Authors: ,
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. Least l1-norm estimates for two models (nonlinear and nonparametric regression) are investigated as special cases of such empirical estimates.

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