Bilinear autoregressive vector models and their application to estimation of revenue series.

A. E. Usoro; C. O. Omekara

No Detail Found!

Bilinear autoregressive vector models and their application to estimation of revenue series.

Author(s)

A. E. Usoro Department of Statistics, Akwa Ibom State Polytechnic, Ikot Osurua, Ikot Ekpene, Akwa Ibom State, Nigeria

C. O. Omekara Michael Okpara University of Agriculture, Umudike, Abia State, Nigeria

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 modeling 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.

Publication Details

Page(s) 50-56

DOI DOI not available

Published Journal: Asian Journal of Mathematics & Statistics, Volume: 1, Issue: 1, Year: 2008

Request the full text from PASTIC

Citations

Downloads

Views