Picture of virus under microscope

Research under the microscope...

The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs.

Strathprints serves world leading Open Access research by the University of Strathclyde, including research by the Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), where research centres such as the Industrial Biotechnology Innovation Centre (IBioIC), the Cancer Research UK Formulation Unit, SeaBioTech and the Centre for Biophotonics are based.

Explore SIPBS research

On tail behaviour of nonlinear autoregressive functional conditional heteroscedastic model with heavy-tailed innovations

Pan, J. and Wu, G. (2005) On tail behaviour of nonlinear autoregressive functional conditional heteroscedastic model with heavy-tailed innovations. Science in China Series A: Mathematics, 48 (9). pp. 1169-1181. ISSN 1006-9283

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

We study the tail probability of the stationary distribution of nonparametric nonlinear autoregressive functional conditional heteroscedastic (NARFCH) model with heavy-tailed innovations. Our result shows that the tail of the stationary marginal distribution of an NARFCH series is heavily dependent on its conditional variance. When the innovations are heavy-tailed, the tail of the stationary marginal distribution of the series will become heavier or thinner than that of its innovations. We give some specific formulas to show how the increment or decrement of tail heaviness depends on the assumption on the conditional variance function. Some examples are given.