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Kernel quantite function estimator for flood frequency analysis
Author(s) -
Moon YoungIl,
Lall Upmanu
Publication year - 1994
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/94wr01217
Subject(s) - estimator , quantile , mathematics , quantile function , bootstrapping (finance) , statistics , minimum variance unbiased estimator , minimax estimator , consistent estimator , kernel smoother , confidence interval , kernel method , econometrics , computer science , probability density function , cumulative distribution function , artificial intelligence , radial basis function kernel , support vector machine
A kernel estimator (KQ) of the quantile function is presented here. Boundary kernels are used for extrapolation of tail quantiles. The bandwidth of the estimator is chosen using an automatic, “plug‐in” method. Confidence intervals for the estimated quantile are estimated by bootstrapping. Comparisons of the estimator with selected tail probability estimators are offered. The KQ estimator presented here is shown to be competitive with other estimators.