Edgeworth expansion for the kernel quantile estimator

Yoshihiko Maesono, Spiridon Penev

    Research output: Contribution to journalArticlepeer-review

    1 Citation (Scopus)


    Using the kernel estimator of the pth quantile of a distribution brings about an improvement in comparison to the sample quantile estimator. The size and order of this improvement is revealed when studying the Edgeworth expansion of the kernel estimator. Using one more term beyond the normal approximation significantly improves the accuracy for small to moderate samples. The investigation is nonstandard since the influence function of the resulting L-statistic explicitly depends on the sample size. We obtain the expansion, justify its validity and demonstrate the numerical gains in using it.

    Original languageEnglish
    Pages (from-to)617-644
    Number of pages28
    JournalAnnals of the Institute of Statistical Mathematics
    Issue number3
    Publication statusPublished - Jun 2011

    All Science Journal Classification (ASJC) codes

    • Statistics and Probability


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