Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-03T11:33:31.528Z Has data issue: false hasContentIssue false
  • English
  • Français

Applications of multivariate techniques in the study of multivariable stochastic systems

Published online by Cambridge University Press:  01 July 2016

M. B. Priestley
M. B. Priestley*
Affiliation:
University of Manchester Institute of Science and Technology
Get access Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
I. Invited Review and Research Papers
Information
Advances in Applied Probability , Volume 9 , Issue 2 , June 1977 , pp. 202 - 205
Copyright
Copyright © Applied Probability Trust 1977 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Akaike, H. (1974a) Markovian representation of stochastic processes and its applications to the analysis of autoregressive moving-average processes. Ann. Inst. Statist. Math. 26, 363–387.Google Scholar
Priestley, M. B. (1976) Applications of multivariate techniques in the study of multivariate stochastic systems. Department of Mathematics, UMIST, Technical Report No. 75, May 1976.Google Scholar
Priestley, M. B., Subba Rao, T. and Tong, H. (1973) Identification of the structure of multivariable stochastic systems. In Multivariate Analysis III, ed. Krishnaiah, P. R., Academic Press, New York, 351–368.Google Scholar
Priestley, M. B. and Subba Rao, T. (1975) The estimation of factor scores and Kalman filtering for discrete parameter stationary processes. Int. J. Control 21, 971–975.CrossRefGoogle Scholar
Subba Rao, T. (1975) An innovations approach to the reduction of the dimensions in a multivariable stochastic system. Int. J. Control 21, 673–680.CrossRefGoogle Scholar
Subba Rao, T. and Tong, H. (1974) Identification of the covariance structure of state space models. Bull. Inst. Math. Appl. 10, 201–203.Google Scholar