2008Journal of China HydrologyRequires access

Application of Nonparametric Weighted Kernel Density Estimation in Flood Frequency Analysis

Wei Yu-hua

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Abstract

This paper introduced the weighted kernel density estimation for flood frequency analysis and calculation. Monte-Carlo method was compared with parameter estimation method --LM method, the result shows that the unbiasedness of design value through weighted kernel density estimation closes to LM method, but the effectiveness is better than LM method. A comparison with conventional nonparametric density estimation in the last, the result displays that the unbiasedness and effectiveness using weighted kernel density estimation are better than traditional methods, especially the precision of effectiveness is higher. So, nonparametric weighted kernel density estimation is an applied and valuable method.

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What this paper is about

This paper introduced the weighted kernel density estimation for flood frequency analysis and calculation. Monte-Carlo method was compared with parameter estimation method --LM method, the result shows that the unbiasedness of design value through weighted kernel density estimation closes to LM method, but the effectiveness is better than LM method. A comparison with conventional nonparametric density estimation in the last, the result displays that the unbiasedness and effectiveness using weighted kernel density estimation are better than traditional methods, especially the precision of effectiveness is higher. So, nonparametric weighted kernel density estimation is an applied and valuable method.

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Available abstract

This paper introduced the weighted kernel density estimation for flood frequency analysis and calculation. Monte-Carlo method was compared with parameter estimation method --LM method, the result shows that the unbiasedness of design value through weighted kernel density estimation closes to LM method, but the effectiveness is better than LM method. A comparison with conventional nonparametric density estimation in the last, the result displays that the unbiasedness and effectiveness using weighted kernel density estimation are better than traditional methods, especially the precision of effectiveness is higher. So, nonparametric weighted kernel density estimation is an applied and valuable method.

Key concepts: Kernel density estimation, Multivariate kernel density estimation, Variable kernel density estimation, Nonparametric statistics, Kernel (algebra), Mathematics, Density estimation, Statistics

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