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Asian Journal of Mathematics & Statistics
  Year: 2008 | Volume: 1 | Issue: 1 | Page No.: 43-49
DOI: 10.3923/ajms.2008.43.49
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Detecting Non-linearity Using Squares of Time Series Data

C.O. Omekara

The aim of this study is to discuss the properties of squares of a pure diagonal bilinear (PDBL) time series model and how these properties can be used to distinguish between a linear (ARMA) model and a non-linear (bilinear) model. We showed that for the Pure diagonal bilinear process, the square of the series have the same covariance structure as an ARMA process. Simulated data was used to illustrate the results obtained in this study.
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  •    Central Limit Theorem for the Sum of a Random Number of Dependent Random Variables
How to cite this article:

C.O. Omekara , 2008. Detecting Non-linearity Using Squares of Time Series Data. Asian Journal of Mathematics & Statistics, 1: 43-49.

DOI: 10.3923/ajms.2008.43.49






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