Bootstrap Confidence Interval for Median
| Main Authors: | Suprihatin, Bambang, Guritno, Suryo, Haryatmi, Sri |
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| Format: | BookSection PeerReviewed application/msword |
| Terbitan: |
International Statistical Institute, The Hague, The Netherlands
, 2013
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| Subjects: | |
| Online Access: |
http://eprints.unsri.ac.id/4352/1/Proceeding_of_the_59th_World_Statistics_Congress%2DHong_Kong%2D2014.docx http://eprints.unsri.ac.id/4352/ |
Daftar Isi:
- . Given sample of size n from an unknown distribution F. If all elements of X are distinct, then the number of different possible resamples with replacement equals . In general, this number obvious very large in amount. For n = 10, think of the number , which is an enormous number. Let be the estimate value of statistic computed from , where t is functional. In most cases of practical interest, each distinct (without regard for order), gives rise to a distinct . Accordingly, we concern only on so-called atoms of nonparametric bootstrap. The number of atoms is far less than Based on these atoms, the nonparametric bootstrap used to estimate a statistic computed from X. This paper presents how to find the number of atoms. The implementation of the uses of atoms is applied in bootstrapping bias estimate of sample median. Bootstrap version of standar error as a measure of accuracy of estimator is considered, as well. The main purpose of this paper is to construct a confidence interval for median. Results from Monte Carlo simulation for these cases are also presented.