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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