Title of article :
A test procedure for detecting super-heavy tails
Author/Authors :
Alves، نويسنده , , Isabel Fraga and de Haan، نويسنده , , Laurens and Neves، نويسنده , , Clلudia، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Pages :
15
From page :
213
To page :
227
Abstract :
The aim of this work is to develop a test to distinguish between heavy and super-heavy tailed probability distributions. These classes of distributions are relevant in areas such as telecommunications and insurance risk, among others. By heavy tailed distributions we mean probability distribution functions with polynomially decreasing upper tails (regularly varying tails). The term super-heavy is reserved for right tails decreasing to zero at a slower rate, such as logarithmic, or worse (slowly varying tails). Simulations are presented for several models and an application with telecommunications data is provided.
Keywords :
Estimation , Max-domain of attraction , Test of hypothesis , Regular variation theory
Journal title :
Journal of Statistical Planning and Inference
Serial Year :
2009
Journal title :
Journal of Statistical Planning and Inference
Record number :
2219785
Link To Document :
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