Adaptive Nonparametric Procedures and Applications

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dc.contributor.authorPuri, Madan L.
dc.contributor.authorHill, N.J.
dc.contributor.authorPadmanabhan, A. R.
dc.date.accessioned2018-06-01T15:52:31Z
dc.date.available2018-06-01T15:52:31Z
dc.date.issued1988
dc.descriptionPublisher's, offprint version
dc.description.abstractTwo adaptive nonparametric procedures are proposed for multiple comparisons and testing for ordered alternatives in the one-way ANOVA model. The first procedure resembles a proposal of Hogg, Fisher and Randles (for hypothesis testing) while the second is a variation of the first. Applications to data on lung cancer illustrate the theory.The supremacy of these procedures over the parametric normal theory procedures and the rank-based procedures is established. Monte Carlo studies show that these procedures can be safely applied when the size of each sample is at least 20.
dc.identifier.citationPuri, M. L. "Adaptive nonparametric procedures and applications." Journal of the Royal Statistical Society, Series C (Applied Statistics) (1988), Volume 37 Issue 2, 205–218. Co-authors: N.J. Hill and A.R. Padmanabhan.
dc.identifier.doihttps://doi.org/10.2307/2347340
dc.identifier.urihttps://hdl.handle.net/2022/22169
dc.language.isoen
dc.publisherJournal of the Royal Statistical Society, Series C (Applied Statistics)
dc.subjectConfidence interval
dc.subjectGaussian distributions
dc.subjectSampling distributions
dc.subjectMathematical procedures
dc.subjectRank tests
dc.subjectT tests
dc.subjectStatistical variance
dc.subjectLung neoplasms
dc.titleAdaptive Nonparametric Procedures and Applications
dc.typeArticle

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