Statistical modeling of extremes under linear and power normalizations with applications to air pollution

Kuwait Journal of Science

H. M. BARAKAT¹  E. M. NIGM¹  O. M. KHALED² 

[1] Department of Mathematics, Faculty of Science, Zagazig University, Zagazig-EGYPT;Department of Mathematics, Faculty of Science, Port Said University – Port Said - EGYPT

关键词: Air pollution;    bootstrap technique;    generalized extreme value model;    generalized Pareto distribution;    Kolmogorov-Smirnov test;   

DOI  :  

学科分类：社会科学、人文和艺术（综合）

来源: Kuwait University * Academic Publication Council

【 摘 要 】

In this paper the Block Maxima (BM) and the Peak Over Threshold (POT) methods are used to model the air pollution in two cities in Egypt. A simulation technique is suggested to choose a suitable threshold value. The validity of full bootstrapping technique for improving the estimation parameters in extreme value models has been checked by Kolmogorov-Smirnov (K-S) test. A new efficiency approach for modeling extreme values is suggested. This approach can convert any ordered data to enlarged block data by using sub-sample bootstrap. By using power normaliziation, for the first time in litrarure, the BM and sub-sample bootstrap methods are applied to model the air pollution. Although, this study is applied on three pollutants in two cities in Egypt, the suggested approaches may be applied on other pollutants in other regions in any country.

【 授权许可】

Unknown