Grahn, Thorsten
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Abstract
In this paper we develop a Conditional Least Squares (CLS) procedurefor estimating bilinear time series models. We apply this method to twogeneral types of bilinear models. A model of type I is a special superdiagonalbilinear model which includes the linear ARMA model as a submodel. A model oftype II is a standardized version of the popular bilinear BL(p,0,p,1) model(see e.g. Liu and Chen (1990), Sesay and Subba Rao (1991)). For both models weshow that the limiting distribution of the resulting CLS estimates is Gaussianand the law of the iterated logarithm holds.
| Document type: | Working paper |
|---|---|
| Place of Publication: | Heidelberg |
| Date Deposited: | 20 Jun 2016 09:10 |
| Date: | April 1993 |
| Number of Pages: | 47 |
| Faculties / Institutes: | The Faculty of Mathematics and Computer Science > Institut für Mathematik |
| DDC-classification: | 510 Mathematics |
| Uncontrolled Keywords: | Estimation; bilinear time series; central limit theorem; law of the iterated logarithm; conditional moments |
| Series: | Beiträge zur Statistik > Beiträge |
