Confidence limits to the distance of the true distribution from a misspecified family by bootstrap

G. Jogesh Babu; C. R. Rao

doi:10.1016/S0378-3758(02)00176-3

Confidence limits to the distance of the true distribution from a misspecified family by bootstrap

G. Jogesh Babu, C. R. Rao

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

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.

Original language	English (US)
Pages (from-to)	471-478
Number of pages	8
Journal	Journal of Statistical Planning and Inference
Volume	115
Issue number	2
DOIs	https://doi.org/10.1016/S0378-3758(02)00176-3
State	Published - Aug 1 2003

All Science Journal Classification (ASJC) codes

Statistics and Probability
Statistics, Probability and Uncertainty
Applied Mathematics

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10.1016/S0378-3758(02)00176-3

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Confidence limits to the distance of the true distribution from a misspecified family by bootstrap

Abstract

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