Application of multi criteria method to identify the best-fit statistical distribution

Generally, researchers are faced to identify the true statistical distributions for the analysis of a various hydrologic data sets. Using traditional statistical analysis methods one choose a hypothesized distribution to describe the observed data, estimate the distribution parameters and then apply...

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Main Authors: Shabri, Ani, Jemain, Abdul Aziz
Format: Article
Language:English
Published: Asian Network for Scientific Information 2006
Subjects:
Online Access:http://eprints.utm.my/7626/
http://eprints.utm.my/7626/1/Abdul_Aziz_Jemain_2006_Application_Of_Multi_Criteria_Method.pdf
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author Shabri, Ani
Jemain, Abdul Aziz
author_facet Shabri, Ani
Jemain, Abdul Aziz
author_sort Shabri, Ani
building UTeM Institutional Repository
collection Online Access
description Generally, researchers are faced to identify the true statistical distributions for the analysis of a various hydrologic data sets. Using traditional statistical analysis methods one choose a hypothesized distribution to describe the observed data, estimate the distribution parameters and then apply the goodness of fit test such as the Chi Square test (CS) or Kolmogorov Smirnov (KS) test. For more accurate, several factors or criteria should be considered in selection of the best distribution. However when more than two criteria are used to identify the best distribution, it is more difficult and more subjective. In this paper, we propose a new Multi Criteria Decision Making method (MCDM) based on nonlinear programming for selection of the best distribution to fit a set of data. The Generalized Extreme Value (GEV), Generalized Pareto (GP), Pearson 3 (P3) and Lognormal 3 (LN3) are used and their goodness of fit has been examined by various test statistics. A numerical example is used to illustrate the applicability of the proposed approach.
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spelling utm-76262010-06-01T15:54:04Z http://eprints.utm.my/7626/ Application of multi criteria method to identify the best-fit statistical distribution Shabri, Ani Jemain, Abdul Aziz QA Mathematics Generally, researchers are faced to identify the true statistical distributions for the analysis of a various hydrologic data sets. Using traditional statistical analysis methods one choose a hypothesized distribution to describe the observed data, estimate the distribution parameters and then apply the goodness of fit test such as the Chi Square test (CS) or Kolmogorov Smirnov (KS) test. For more accurate, several factors or criteria should be considered in selection of the best distribution. However when more than two criteria are used to identify the best distribution, it is more difficult and more subjective. In this paper, we propose a new Multi Criteria Decision Making method (MCDM) based on nonlinear programming for selection of the best distribution to fit a set of data. The Generalized Extreme Value (GEV), Generalized Pareto (GP), Pearson 3 (P3) and Lognormal 3 (LN3) are used and their goodness of fit has been examined by various test statistics. A numerical example is used to illustrate the applicability of the proposed approach. Asian Network for Scientific Information 2006 Article PeerReviewed application/pdf en http://eprints.utm.my/7626/1/Abdul_Aziz_Jemain_2006_Application_Of_Multi_Criteria_Method.pdf Shabri, Ani and Jemain, Abdul Aziz (2006) Application of multi criteria method to identify the best-fit statistical distribution. Journal of Applied Sciences, 6 (4). pp. 926-932. ISSN 1812-5654 http://www.scialert.net/jindex.php?issn=1812-5654
spellingShingle QA Mathematics
Shabri, Ani
Jemain, Abdul Aziz
Application of multi criteria method to identify the best-fit statistical distribution
title Application of multi criteria method to identify the best-fit statistical distribution
title_full Application of multi criteria method to identify the best-fit statistical distribution
title_fullStr Application of multi criteria method to identify the best-fit statistical distribution
title_full_unstemmed Application of multi criteria method to identify the best-fit statistical distribution
title_short Application of multi criteria method to identify the best-fit statistical distribution
title_sort application of multi criteria method to identify the best-fit statistical distribution
topic QA Mathematics
url http://eprints.utm.my/7626/
http://eprints.utm.my/7626/
http://eprints.utm.my/7626/1/Abdul_Aziz_Jemain_2006_Application_Of_Multi_Criteria_Method.pdf