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Journal of Applied Sciences
  Year: 2008 | Volume: 8 | Issue: 18 | Page No.: 3242-3248
DOI: 10.3923/jas.2008.3242.3248
 
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Parametric and Nonparametric Frequency Analysis of Monthly Precipitation in Iran

P. Haghighat Jou, A.M. Akhoond-Ali, A. Behnia and R. Chinipardaz

Abstract:
This study is devoted to compare the goodness of fitting of the monthly precipitation for five old raingauge stations (Bushehr, Isfahan, Meshed, Tehran and Jask) in Iran using parametric and nonparametric methods. The parametric methods include normal, two and three parameter log-normal, two parameter gamma, Pearson and log-Pearson type III and Gumbel extreme value type I distributions. The nonparametric approach is Gaussian (normal) kernel function. The smoothing parameter were calculated by four methods including rule of thumb, Adamowski criterion, least squares cross-validation and Sheater and Jones plug-in. Results from the least squares cross-validation were better comparing to other methods due to goodness of fit tests applied in this study. The results of this study showed that the monthly precipitation data fitted to the parametric methods much better than nonparametric method.
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How to cite this article:

P. Haghighat Jou, A.M. Akhoond-Ali, A. Behnia and R. Chinipardaz, 2008. Parametric and Nonparametric Frequency Analysis of Monthly Precipitation in Iran. Journal of Applied Sciences, 8: 3242-3248.

DOI: 10.3923/jas.2008.3242.3248

URL: https://scialert.net/abstract/?doi=jas.2008.3242.3248

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