Probabilistic evaluation of quantile estimators

Matti Pajari, Maria Tikanmäki, Lasse Makkonen (Corresponding Author)

    Research output: Contribution to journalArticleScientificpeer-review

    Abstract

    The foundations of the criteria to assess the goodness of quantile estimators for continuous random variables are reviewed and the probabilistic justification for a novel bin-criterion is presented. It is shown that the bin-criterion is a more appropriate measure of goodness of a quantile estimator than those based on minimizing the bias of the quantiles or the parameters of the distribution.
    Original languageEnglish
    Number of pages19
    JournalCommunications in Statistics: Theory and Methods
    DOIs
    Publication statusE-pub ahead of print - 10 Dec 2019
    MoE publication typeA1 Journal article-refereed

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    Quantile
    Estimator
    Evaluation
    Continuous random variable
    Justification

    Cite this

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    abstract = "The foundations of the criteria to assess the goodness of quantile estimators for continuous random variables are reviewed and the probabilistic justification for a novel bin-criterion is presented. It is shown that the bin-criterion is a more appropriate measure of goodness of a quantile estimator than those based on minimizing the bias of the quantiles or the parameters of the distribution.",
    author = "Matti Pajari and Maria Tikanm{\"a}ki and Lasse Makkonen",
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    Probabilistic evaluation of quantile estimators. / Pajari, Matti; Tikanmäki, Maria; Makkonen, Lasse (Corresponding Author).

    In: Communications in Statistics: Theory and Methods, 10.12.2019.

    Research output: Contribution to journalArticleScientificpeer-review

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    AU - Makkonen, Lasse

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