Abstract:
This study was motivated by the need
to establish multivariate time series models for pure autoregressive vector
series which assume both linear and nonlinear components. General Bilinear
Autoregressive Vector (BARV) models were established. The three vector
series namely, a response vector (X1t) and predictor vectors
(X2t) and (X3t) used for the modelling called for
trivariate time series models as a special case of multivariate time series
models and estimates obtained from the models. The finding in this study
is the isolation of multivariate bilinear models for a pure autoregressive
process based on the distribution of autocorrelation and partial autocorrelation
functions of the series from mixed models. This has been achieved as the
models were used for the estimation of the vector series. These prove
reality of the BARV models established.
A.E. Usoro and C.O. Omekara, 2008. Bilinear Autoregressive Vector Models and Their Application to Estimation of Revenue Series. Asian Journal of Mathematics & Statistics, 1: 50-56.
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