Robust nonparametric inference for the median

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dc.creatorYohai, Victor J.
dc.creatorZamar, Ruben H.
dc.date2005-03-29
dc.date.accessioned2026-07-07T08:06:45Z
dc.date.available2026-07-07T08:06:45Z
dc.descriptionWe consider the problem of constructing robust nonparametric confidence intervals and tests of hypothesis for the median when the data distribution is unknown and the data may contain a small fraction of contamination. We propose a modification of the sign test (and its associated confidence interval) which attains the nominal significance level (probability coverage) for any distribution in the contamination neighborhood of a continuous distribution. We also define some measures of robustness and efficiency under contamination for confidence intervals and tests. These measures are computed for the proposed procedures.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053604000000634 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0503665
dc.identifierhttp://arxiv.org/abs/math/0503665
dc.identifierAnnals of Statistics 2004, Vol. 32, No. 5, 1841-1857
dc.identifierdoi:10.1214/009053604000000634
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130715
dc.subjectStatistics Theory
dc.subject62F35 (Primary) 62G35 (Secondary)
dc.titleRobust nonparametric inference for the median
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