CONSTRUCTION OF BAYESIAN ESTIMATES OF PARAMETERS OF LINEAR MARKOV PROCESSES WITH OBSERVATION OF ONLY CERTAIN COMPONENTS.

Abstract

A system of equations is obtained for finding Bayesian estimates of the parameters of many-dimensional linear Markov processes when only certain of the components are observed. The eequations enable the authors simultaneously to carry out filtration of the unobservable components in the case of unknown process parameters. Estimation of the unknown parameters of the correlation function of Gaussian processes with rational spectral densities reduces to this problem.

Original language	English
Title of host publication	Eng Cybern
Pages	1142-1151
Number of pages	10
Volume	9
Edition	6
Publication status	Published - Nov 1971

ASJC Scopus subject areas

Engineering(all)

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title = "CONSTRUCTION OF BAYESIAN ESTIMATES OF PARAMETERS OF LINEAR MARKOV PROCESSES WITH OBSERVATION OF ONLY CERTAIN COMPONENTS.",

abstract = "A system of equations is obtained for finding Bayesian estimates of the parameters of many-dimensional linear Markov processes when only certain of the components are observed. The eequations enable the authors simultaneously to carry out filtration of the unobservable components in the case of unknown process parameters. Estimation of the unknown parameters of the correlation function of Gaussian processes with rational spectral densities reduces to this problem.",

author = "Konev, {V. V.} and Khazen, {E. M.}",

year = "1971",

month = nov,

language = "English",

volume = "9",

pages = "1142--1151",

booktitle = "Eng Cybern",

edition = "6",

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AU - Khazen, E. M.

PY - 1971/11

Y1 - 1971/11

N2 - A system of equations is obtained for finding Bayesian estimates of the parameters of many-dimensional linear Markov processes when only certain of the components are observed. The eequations enable the authors simultaneously to carry out filtration of the unobservable components in the case of unknown process parameters. Estimation of the unknown parameters of the correlation function of Gaussian processes with rational spectral densities reduces to this problem.

AB - A system of equations is obtained for finding Bayesian estimates of the parameters of many-dimensional linear Markov processes when only certain of the components are observed. The eequations enable the authors simultaneously to carry out filtration of the unobservable components in the case of unknown process parameters. Estimation of the unknown parameters of the correlation function of Gaussian processes with rational spectral densities reduces to this problem.

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