Empirical Estimates in Stochastic Optimization and Identification
(Sprache: Englisch)
This book contains problems of stochastic 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...
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Klappentext zu „Empirical Estimates in Stochastic Optimization and Identification “
This book contains problems of stochastic 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 stochastic optimization and estimations, postgraduate students, and graduate students studying such topics
Inhaltsverzeichnis zu „Empirical Estimates in Stochastic Optimization and Identification “
Preface. 1. Introduction. 2. Parametric Empirical Methods. 3. Parametric Regression Models. 4. Periodogram Estimates for Random Processes and Fields. 5. Nonparametric Identification Problems. References.
Bibliographische Angaben
- Autoren: Evgeniya J. Kasitskaya , Pavel S. Knopov
- 2002, 264 Seiten, Maße: 16 x 24,1 cm, Gebunden, Englisch
- Verlag: Springer US
- ISBN-10: 1402007078
- ISBN-13: 9781402007071
- Erscheinungsdatum: 30.06.2002
Sprache:
Englisch
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