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Polynomial power-Pareto quantile function models

Yuzhi Cai Orcid Logo

Extremes, Volume: 13, Issue: 3, Pages: 291 - 314

Swansea University Author: Yuzhi Cai Orcid Logo

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Abstract

In this paper we propose a polynomial power-Pareto quantile function model and a Bayesian method for parameters estimation. We also carried out simulation studies and applied our methodology to real data sets empirically. The results show that a quantile function approach to statistical modelling is...

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Published in: Extremes
ISSN: 1386-1999
Published: Springer 2010
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa6998
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Abstract: In this paper we propose a polynomial power-Pareto quantile function model and a Bayesian method for parameters estimation. We also carried out simulation studies and applied our methodology to real data sets empirically. The results show that a quantile function approach to statistical modelling is very flexible due to the properties of quantile functions, and that the combination of a power and a Pareto distribution enables us to model both the main body and the tails of a distribution, even though the mathematical form of the distribution does not exist. Our research also suggests a new approach to studying extreme values based on a whole data set rather than group maximum/minimum or exceedances above/below a proper threshold value.
Keywords: Bayesian methods · Quantile functions ·, Power-Pareto distribution · Simulation · Speed and stopping distance data ·,Wave and surge data
College: Faculty of Humanities and Social Sciences
Issue: 3
Start Page: 291
End Page: 314