Wakeby Distribution and the Maximum Likelihood Estimation Algorithm in Which Probability Density Function Is Not Explicitly Expressed

Title & Authors
Wakeby Distribution and the Maximum Likelihood Estimation Algorithm in Which Probability Density Function Is Not Explicitly Expressed
Park Jeong-Soo;

Abstract
The studied in this paper is a new algorithm for searching the maximum likelihood estimate(MLE) in which probability density function is not explicitly expressed. Newton-Raphson's root-finding routine and a nonlinear numerical optimization algorithm with constraint (so-called feasible sequential quadratic programming) are used. This algorithm is applied to the Wakeby distribution which is importantly used in hydrology and water resource research for analysis of extreme rainfall. The performance comparison between maximum likelihood estimates and method of L-moment estimates (L-ME) is studied by Monte-carlo simulation. The recommended methods are L-ME for up to 300 observations and MLE for over the sample size, respectively. Methods for speeding up the algorithm and for computing variances of estimates are discussed.
Keywords
L-moment estimation;Numerical optimization;Hydrology;Quantile function;Newton-Raphson algorithm;
Language
Korean
Cited by
1.
현장타설말뚝 콘크리트 공시체 압축강도 데이터 분석을 통한 강도 영향인자 분석,이기철;정문경;김소연;김동욱;

한국지반공학회논문집, 2015. vol.31. 10, pp.37-47
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