Multivariate linear time series models
- 1 September 1984
- journal article
- Published by Cambridge University Press (CUP) in Advances in Applied Probability
- Vol. 16 (3) , 492-561
- https://doi.org/10.2307/1427286
Abstract
This paper is in three parts. The first deals with the algebraic and topological structure of spaces of rational transfer function linear systems—ARMAX systems, as they have been called. This structure theory is dominated by the concept of a space of systems of order, or McMillan degree, n, because of the fact that this space, M(n), can be realised as a kind of high-dimensional algebraic surface of dimension n(2s + m) where s and m are the numbers of outputs and inputs. In principle, therefore, the fitting of a rational transfer model to data can be considered as the problem of determining n and then the appropriate element of M(n). However, the fact that M(n) appears to need a large number of coordinate neighbourhoods to cover it complicates the task. The problems associated with this program, as well as theory necessary for the analysis of algorithms to carry out aspects of the program, are also discussed in this first part of the paper, Sections 1 and 2.The second part, Sections 3 and 4, deals with algorithms to carry out the fitting of a model and exhibits these algorithms through simulations and the analysis of real data.The third part of the paper discusses the asymptotic properties of the algorithm. These properties depend on uniform rates of convergence being established for covariances up to some lag increasing indefinitely with the length of record, T. The necessary limit theorems and the analysis of the algorithms are given in Section 5. Many of these results are of interest independent of the algorithms being studied.Keywords
This publication has 36 references indexed in Scilit:
- Autocorrelation, Autoregression and Autoregressive ApproximationThe Annals of Statistics, 1982
- A One-Factor Multivariate Time Series Model of Metropolitan Wage RatesJournal of the American Statistical Association, 1981
- LATTICE METHODS IN SPECTRAL ESTIMATION**This work was supported in part by the Advanced Research Projects Agency and monitored by RADC/EEV under contract number F19628-78-C-0136.Published by Elsevier ,1981
- On canonical forms for linear constant systemsInternational Journal of Control, 1981
- Simultaneous estimation of poles and zeros in speech analysis and ITIF-iterative inverse filtering algorithmIEEE Transactions on Acoustics, Speech, and Signal Processing, 1979
- The efficient estimation of vector linear time series modelsBiometrika, 1976
- Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processesAnnals of the Institute of Statistical Mathematics, 1974
- Fitting autoregressive models for predictionAnnals of the Institute of Statistical Mathematics, 1969
- ALGEBRAIC STRUCTURE OF LINEAR DYNAMICAL SYSTEMS, I. THE MODULE OF ΣProceedings of the National Academy of Sciences, 1965
- A New Approach to Linear Filtering and Prediction ProblemsJournal of Basic Engineering, 1960