A Decision Procedure for Bilinear Time Series Based on the Asymptotic Separation
Authors:
E. Goncalves a;
P. Jacob a;
N. Mendes-Lopes a
| Affiliation: | a Univ. Coimbra, Portugal and Univ. Montpellier II, France |
DOI:
10.1080/02331880008802699
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
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Abstract
This paper presents a non-classical decision procedure for a bilinear model with a general error process. This procedure allows us to decide, in a consistent way, between two hypotheses on the model. By establishing the asymptotic separation of the sequences of probability laws defined by each hypothesis, we obtain the consistence of this decision method. Some studies about the rate of convergence are presented and an exponential decay is obtained. A simulation study is done to illustrate the behaviour of the power and level functions in small and moderate samples when this procedure is used as a test.
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| Keywords: Time Series; asymptotic separation; bilinear models; test |
| AMS Classification: 62M10 |
| view references (15) |

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