The stability test for symmetric alpha-stable distributions
Brcich, Ramon F., Iskander, D. Robert, & Zoubir, Abdelhak M. (2005) The stability test for symmetric alpha-stable distributions. IEEE Transactions on Signal Processing, 53(3), pp. 977-986.
Symmetric alpha-stable distributions are a popular statistical model for heavy-tailed phenomena encountered in communications, radar, biomedicine, and econometrics. The use of the symmetric alpha stable model is often supported by empirical evidence, where qualitative criteria are used to judge the fit, leading to subjective decisions. Objective decisions can only be made through quantitative statistical tests. Here, a goodness-of-fit hypothesis test for symmetric alpha-stable distributions is developed based on their unique stability property. Critical values for the test are found using both asymptotic theory and from bootstrap estimates. Experiments show that the stability test, using bootstrap estimates of the critical values, is better able to discriminate between symmetric alpha stable distributions and other heavy-tailed distributions than classical tests such as the Kolmogorov-Smirnov test.
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|Item Type:||Journal Article|
|Keywords:||Alpha stable, bootstrap, goodness, of, fit, heavy, tailed distributions, hypothesis tests|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
|Copyright Owner:||Copyright 2005 IEEE|
|Copyright Statement:||Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Deposited On:||10 Feb 2006 00:00|
|Last Modified:||29 Feb 2012 13:15|
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