Abstract
Elamir and Seheult (Comput Stat Data Anal 43:299–314, 2003) extended L-moments to new moment called trimmed L-moments (TL-moment). TL-moments is introduced as an alternative way to estimate floods for high return periods. The TL-moments have an ability to reduce the undesirable influence that a small value in the statistical sample might have on a large return period. The main objective of this study is to derive the TL-moments (1,0), (2,0), (3,0), and (4,0) for the generalized logistic (GLO) distribution. The performance of the TL-moments (2,0), (3,0), and (4,0) was compared with TL-moments (1,0) through Monte Carlo simulation based on the streamflow data of Sg. Serting at Jam. Padang Gudang, located in Pahang, Malaysia, for various sample sizes and return periods.
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References
Stedinger, J. R., Vogel, R. M., & Foufoula-Georgiou, E. (1993). Handbook of hydrology. New York: Mc Graw Hill.
Hosking, J. R. M., & Wallis, J. R. (1997). Regional frequency analysis: An approach based on L-moments. Cambridge: Cambridge University Press.
Elamir, E. A. H., & Seheult, A. H. (2003). Trimmed L-moments. Computational Statistics and Data Analysis, 43, 299–314.
Ahmad, U. N., Shabri, A., & Zakaria, Z. A. (2011). TL-moments and TL-moments estimation of the generalized logistic distribution. Journal of Mathematics Research, 3(1), 97–106.
Shabri, A., & Jemain, A. A. (2007). LQ-moments for statistical analysis of extreme events. Journal of Modern Applied Statistical Methods, 6(1), 228–238.
Wang, Q. J. (1990). Estimation of the GEV distribution from censored samples by method of partial probability weighted moments. Journal of Hydrology, 120, 103–114.
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© 2014 Springer Science+Business Media Singapore
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Mat Jan, N.A., Shabri, A., Azuardi, S.D. (2014). TL-Moments: Application to the Generalized Logistic Distribution. In: Kasim, A., Wan Omar, W., Abdul Razak, N., Wahidah Musa, N., Ab. Halim, R., Mohamed, S. (eds) Proceedings of the International Conference on Science, Technology and Social Sciences (ICSTSS) 2012. Springer, Singapore. https://doi.org/10.1007/978-981-287-077-3_62
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DOI: https://doi.org/10.1007/978-981-287-077-3_62
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