Robust nonparametric inference for the median

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We 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.
Published 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)

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Statistics Theory, 62F35 (Primary) 62G35 (Secondary)

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http://salesiana.dossiersoluciones.com/handle/123456789/130715

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/math/0503665
 http://arxiv.org/abs/math/0503665
 Annals of Statistics 2004, Vol. 32, No. 5, 1841-1857
 doi:10.1214/009053604000000634

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