Statistical M
Statistical
Modeling of Extreme Values with Applications to Air Pollution
H. M. Barakat1,
E. M. Nigm1 and O. M. Khaled2
1Department of Mathematics Faculty of Science Zagazig University, Zagazig, Egypt
2Department of Basic Science Faculty of Engineering, Sinai University, El-Arish, Egypt Email
[email protected] [email protected] [email protected]
Abstract: In
this paper the Block Maxima and the Peak Over Threshold 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 test. A new efficiency
approach for modeling extreme values is suggested. This approach can convert
any ordered data to enlarged block data by using sup-sample bootstrap.
Although, this study is applied on three pollutants in two cities in Egypt,
but the suggested approaches may be applied on other pollutants in other
regions in any country.
[H. M. Barakat, E. M. Nigm and O. M. Khaled. Statistical
Modeling of Extreme Values with Applications to Air Pollution. Life
Sci J 2012;9(1):124-132] (ISSN: 1097-8135). http://www.lifesciencesite.com. 19
Key words: Air pollution; Generalized extreme value model;
Generalized Pareto distribution; Kolmogorov-Smirnov test; Bootstrap
technique. Full Text 19
