Computational Statistics

, Volume 32, Issue 4, pp 1285–1308 | Cite as

Resampling based inference for a distribution function using censored ranked set samples

Original Paper
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Abstract

This article deals with constructing confidence intervals/bands for a distribution function based on censored ranked set samples. Toward this end, a resampling plan is suggested and its validity is investigated. Monte Carlo simulations are used to compare performances of the bootstrap confidence intervals with their asymptotic analogs, and their modifications by jackknife. An environmental data set is finally analyzed.

Keywords

Asymptotic inference Confidence interval Nonparametric bootstrap Ranked set sampling 

Notes

Acknowledgements

We sincerely thank the reviewers for constructive criticisms and valuable comments, which were of great help in revising the manuscript.

Supplementary material

180_2017_716_MOESM1_ESM.pdf (38 kb)
Supplementary material 1 (pdf 37 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Department of StatisticsHakim Sabzevari UniversitySabzevarIran
  2. 2.Institute of MathematicsCracow University of TechnologyKrakówPoland

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