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THE ESTIMATION AND PREDICTION OF SUBSET BILINEAR TIME SERIES MODELS WITH APPLICATIONS
Author(s) -
Gabr M. M.,
Rao T. Subba
Publication year - 1981
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.1981.tb00319.x
Subject(s) - autoregressive model , series (stratigraphy) , mathematics , bilinear interpolation , setar , independence (probability theory) , star model , nonlinear autoregressive exogenous model , time series , econometrics , linear model , estimation , autoregressive integrated moving average , statistics , paleontology , management , economics , biology
Abstract. In this paper we define subset bilinear time series models, and then describe an algorithm for the estimation of these models. It is also pointed out that for this class of non‐linear time series models, it is possible to obtain optimal several step predictors. The estimation technique of these models is illustrated with respect to three time series, and the optimal several steps ahead forecasts of these time series models are calculated. A comparison of these forecasts is made with the forecasts obtained by the best linear autoregressive and threshold autoregressive models. The residuals obtained from the models are tested for independence and Gaussianity using higher order moments.