Modelling heavy-tailed insurance claim data using the hyper-erlang distribution with common scale parameter

When modelling positively skewed insurance claim data, traditional distributions such as lognormal and Weibull often fail to accurately estimate the tail. Several methods have been developed to improve tail estimation without compromising the body fitting, including the transformed kernel density an...

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Bibliographic Details
Main Authors: Seet, Angeline Yuen Chee, Yang, Bowen, Yeoh, Yun Wei
Other Authors: Uditha Balasooriya
Format: Final Year Project
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/44131
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Institution: Nanyang Technological University
Language: English
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