Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I
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Published By Springer Berlin Heidelberg

9783642007835, 9783642007842

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Limit theorems and diffusion approximations for density dependent Markov chains

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I ◽

10.1007/bfb0120765 ◽

1976 ◽

pp. 67-78 ◽

Cited By ~ 80

Author(s):

Thomas G. Kurtz

Keyword(s):

Markov Chains ◽

Limit Theorems ◽

Diffusion Approximations ◽

Density Dependent ◽

And Diffusion

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Identification and estimation of the error-in-variables model (EVM) in structural form

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I ◽

10.1007/bfb0120773 ◽

1976 ◽

pp. 191-210 ◽

Cited By ~ 4

Author(s):

R. K. Mehra

Keyword(s):

Structural Form ◽

Error In Variables

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Asymptotic stability and angular convergence of stochastic systems

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I ◽

10.1007/bfb0120767 ◽

1976 ◽

pp. 93-102

Author(s):

Mark A. Pinsky

Keyword(s):

Asymptotic Stability ◽

Stochastic Systems

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Entrance-exit distributions for Markov additive processes

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I ◽

10.1007/bfb0120761 ◽

1976 ◽

pp. 22-38 ◽

Cited By ~ 6

Author(s):

Erhan Çinlar

Keyword(s):

Additive Processes ◽

Exit Distributions ◽

Markov Additive Processes

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Parametrically stochastic linear differential equations

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I ◽

10.1007/bfb0120760 ◽

1976 ◽

pp. 8-21 ◽

Cited By ~ 23

Author(s):

Roger W. Brockett

Keyword(s):

Differential Equations ◽

Linear Differential Equations ◽

Linear Differential

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Value of information in zero-sum games

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I ◽

10.1007/bfb0120774 ◽

1976 ◽

pp. 211-226 ◽

Cited By ~ 2

Author(s):

Fang-Kuo Sun ◽

Yu-Chi Ho

Keyword(s):

Value Of Information ◽

Zero Sum Games ◽

Zero Sum

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Sequential decision and stochastic control

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I ◽

10.1007/bfb0120775 ◽

1976 ◽

pp. 227-243 ◽

Cited By ~ 2

Author(s):

Edison Tse

Keyword(s):

Stochastic Control ◽

Sequential Decision

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On integrals in multi-output discrete-time Kalman-Bucy filtering

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I ◽

10.1007/bfb0120771 ◽

1976 ◽

pp. 145-168 ◽

Cited By ~ 2

Author(s):

Anders Lindquist

Keyword(s):

Discrete Time

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Extension of Clark’s innovations equivalence theorem to the case of signal z . independent of noise, with ∫0t z s2ds<∞ a.s.

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I ◽

10.1007/bfb0120759 ◽

1976 ◽

pp. 2-7 ◽

Cited By ~ 10

Author(s):

V. E. Beneš

Keyword(s):

Equivalence Theorem

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The choice of a stochastic model for a noise system

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I ◽

10.1007/bfb0120766 ◽

1976 ◽

pp. 79-92 ◽

Cited By ~ 3

Author(s):

E. J. McShane

Keyword(s):

Stochastic Model

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Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, ILatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Limit theorems and diffusion approximations for density dependent Markov chains

Identification and estimation of the error-in-variables model (EVM) in structural form

Asymptotic stability and angular convergence of stochastic systems

Entrance-exit distributions for Markov additive processes

Parametrically stochastic linear differential equations

Value of information in zero-sum games

Sequential decision and stochastic control

On integrals in multi-output discrete-time Kalman-Bucy filtering

Extension of Clark’s innovations equivalence theorem to the case of signal z . independent of noise, with ∫0t z s2ds<∞ a.s.

The choice of a stochastic model for a noise system

Mathematical Programming Studies - Stochastic Systems: Modeling, Identification and Optimization, I
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