Empirical Estimates in Stochastic Optimization and Identification / Edition 1

by Pavel S. Knopov, Evgeniya J. Kasitskaya

Overview

This book contains problems of shastic optimization and identification. Results concerning uniform law of large numbers, convergence of approximate estimates of extreme points, as well as empirical estimates of functionals with probability 1 and in probability are presented.

Audience: Specialists in shastic optimization and estimations, postgraduate students, and graduate students studying such topics

Product Details

ISBN-13:	9781402007071
Publisher:	Springer US
Publication date:	06/30/2002
Series:	Applied Optimization , #71
Edition description:	2002
Pages:	250
Product dimensions:	6.14(w) x 9.21(h) x 0.36(d)

Table of Contents

1 Introduction.- 2 Parametric Empirical Methods.- 3 Parametric Regression Models.- 4 Periodogram Estimates for Random Processes and Fields.- 5 Nonparametric Identification Problems.- References.