Parameter identification for hyperbolic stochastic systems

ShinIchi Aihara; Arunabha Bagchi

doi:10.1016/0022-247X(91)90321-P

Parameter identification for hyperbolic stochastic systems

ShinIchi Aihara, Arunabha Bagchi

Research output: Contribution to journal › Article › Academic › peer-review

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Abstract

Parameter identification is studied for hyperbolic stochastic systems. Explicit sufficient conditions ensuring consistency of the maximum likelihood estimate are given.

Original language	English
Pages (from-to)	485-499
Number of pages	15
Journal	Journal of mathematical analysis and applications
Volume	160
Issue number	2
DOIs	https://doi.org/10.1016/0022-247X(91)90321-P
Publication status	Published - 1991

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title = "Parameter identification for hyperbolic stochastic systems",

abstract = "Parameter identification is studied for hyperbolic stochastic systems. Explicit sufficient conditions ensuring consistency of the maximum likelihood estimate are given.",

author = "ShinIchi Aihara and Arunabha Bagchi",

year = "1991",

doi = "10.1016/0022-247X(91)90321-P",

language = "English",

volume = "160",

pages = "485--499",

journal = "Journal of mathematical analysis and applications",

issn = "0022-247X",

publisher = "Academic Press Inc.",

number = "2",

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T1 - Parameter identification for hyperbolic stochastic systems

AU - Aihara, ShinIchi

AU - Bagchi, Arunabha

PY - 1991

Y1 - 1991

N2 - Parameter identification is studied for hyperbolic stochastic systems. Explicit sufficient conditions ensuring consistency of the maximum likelihood estimate are given.

AB - Parameter identification is studied for hyperbolic stochastic systems. Explicit sufficient conditions ensuring consistency of the maximum likelihood estimate are given.

U2 - 10.1016/0022-247X(91)90321-P

DO - 10.1016/0022-247X(91)90321-P

M3 - Article

VL - 160

SP - 485

EP - 499

JO - Journal of mathematical analysis and applications

JF - Journal of mathematical analysis and applications

SN - 0022-247X

IS - 2

ER -

Parameter identification for hyperbolic stochastic systems

Abstract

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