TY - GEN

T1 - Derivation of the probability plot correlation coefficient test statistics for the generalized logistic and the generalized Pareto distributions

AU - Kim, Sooyoung

AU - Kho, Younwoo

AU - Shin, Hongjoon

AU - Heo, Jun Haeng

N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.

PY - 2008

Y1 - 2008

N2 - The selection of appropriate probability distribution is important in frequency analysis to estimate the accurate quantile. Generally, the selection of appropriate probability model is based on the goodness of fit test. The probability plot correlation coefficient (PPCC) test has been known as powerful and easy test among the goodness of fit tests. In this study, the derivation of the PPCC test statistics for the generalized logistic distribution and the generalized Pareto distribution was performed by considering sample sizes, significance levels, and shape parameters. In addition, the correlation coefficients between orderly generated data sets and fitted quantiles were computed by using various plotting position formulas. Monte Carlo simulation was performed to select an appropriate plotting position formula for assumed probability distributions. As the results, the Gringorten's plotting position formula was selected for given distributions. Finally, the PPCC test statistics for given probability distributions were derived from correlation coefficient values based on the selected plotting position formula considering various shape parameters.

AB - The selection of appropriate probability distribution is important in frequency analysis to estimate the accurate quantile. Generally, the selection of appropriate probability model is based on the goodness of fit test. The probability plot correlation coefficient (PPCC) test has been known as powerful and easy test among the goodness of fit tests. In this study, the derivation of the PPCC test statistics for the generalized logistic distribution and the generalized Pareto distribution was performed by considering sample sizes, significance levels, and shape parameters. In addition, the correlation coefficients between orderly generated data sets and fitted quantiles were computed by using various plotting position formulas. Monte Carlo simulation was performed to select an appropriate plotting position formula for assumed probability distributions. As the results, the Gringorten's plotting position formula was selected for given distributions. Finally, the PPCC test statistics for given probability distributions were derived from correlation coefficient values based on the selected plotting position formula considering various shape parameters.

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U2 - 10.1061/40976(316)569

DO - 10.1061/40976(316)569

M3 - Conference contribution

AN - SCOPUS:79251493025

SN - 9780784409763

T3 - World Environmental and Water Resources Congress 2008: Ahupua'a - Proceedings of the World Environmental and Water Resources Congress 2008

BT - World Environmental and Water Resources Congress 2008

T2 - World Environmental and Water Resources Congress 2008: Ahupua'a

Y2 - 12 May 2008 through 16 May 2008

ER -