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- W2029427894 abstract "In statistical practice, an estimated distribution function (d.f.) from a specified family is used for taking decisions. When the true d.f. from which samples are drawn does not belong to the specified family, it is of interest to know how close the true d.f. is to the specified family. In this paper, we use non-parametric bootstrap to obtain confidence limits to the difference between the true d.f. and a member of the specified family closest to it in the sense of Kullback-Leibler measure." @default.
- W2029427894 created "2016-06-24" @default.
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- W2029427894 date "2003-08-01" @default.
- W2029427894 modified "2023-09-26" @default.
- W2029427894 title "Confidence limits to the distance of the true distribution from a misspecified family by bootstrap" @default.
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- W2029427894 doi "https://doi.org/10.1016/s0378-3758(02)00176-3" @default.
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