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Effects of L-Moments, Maximum Likelihood and Maximum Product of Spacing Estimation Methods in Using Pearson Type-3 Distribution for Modeling Extreme Values

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  • Muhammad Shafeeq ul Rehman Khan

    (International Islamic University)

  • Zamir Hussain

    (National University of Sciences and Technology (NUST))

  • Ishfaq Ahmad

    (International Islamic University)

Abstract

Modeling of extreme values like annual maxima’s is important in many applications. Pearson Type-3 (PE3) distribution is an important probability distribution, widely used for modeling of extreme values with a variety of estimation methods. The focus of this study is to assess the effects of three methods of estimation of parameters for PE3 distribution namely L-moments (LM), maximum likelihood estimation (MLE) and maximum product of spacing (MPS). Assessment is based on a two-step approach. The first step uses simulation experiments while the second is based on empirical analyses, by varying size and shape characteristics of the sample. The study concluded that the estimates using LM method have low bias in case of small sample and when data exhibits small to moderate skewness and kurtosis. MPS is a reasonable alternative and provides efficient estimates, especially when the data shows large skewness and kurtosis with small to moderate size of sample. MLE method is useful in case of very large sample size with low values of shape characteristics of data. The results of this study provide useful guidelines for fitting PE3 distribution, especially to extreme values.

Suggested Citation

  • Muhammad Shafeeq ul Rehman Khan & Zamir Hussain & Ishfaq Ahmad, 2021. "Effects of L-Moments, Maximum Likelihood and Maximum Product of Spacing Estimation Methods in Using Pearson Type-3 Distribution for Modeling Extreme Values," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1415-1431, March.
    • Handle: RePEc:spr:waterr:v:35:y:2021:i:5:d:10.1007_s11269-021-02767-w
    DOI: 10.1007/s11269-021-02767-w
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    References listed on IDEAS

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    1. Zamir Hussain, 2017. "Estimation of flood quantiles at gauged and ungauged sites of the four major rivers of Punjab, Pakistan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(1), pages 107-123, March.
    2. T. K. Drissia & V. Jothiprakash & A. B. Anitha, 2019. "Flood Frequency Analysis Using L Moments: a Comparison between At-Site and Regional Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(3), pages 1013-1037, February.
    3. El-Sherpieny, El-Sayed A. & Almetwally, Ehab M. & Muhammed, Hiba Z., 2020. "Progressive Type-II hybrid censored schemes based on maximum product spacing with application to Power Lomax distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    4. Takvor Soukissian & Christos Tsalis, 2015. "The effect of the generalized extreme value distribution parameter estimation methods in extreme wind speed prediction," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 78(3), pages 1777-1809, September.
    5. Guan-Jun Lei & Jun-Xian Yin & Wen-Chuan Wang & Hao Wang, 2018. "The Analysis and Improvement of the Fuzzy Weighted Optimum Curve-Fitting Method of Pearson – Type III Distribution," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4511-4526, November.
    6. Wei Li & Jianzhong Zhou & Huaiwei Sun & Kuaile Feng & Hairong Zhang & Muhammad Tayyab, 2017. "Impact of Distribution Type in Bayes Probability Flood Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(3), pages 961-977, February.
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    Cited by:

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