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Statistical inference based on progressively censored samples with random removals from the Burr type XII distribution

Statistical inference based on progressively censored samples with random removals from the Burr... In this article, we study the estimation problems for the Burr type XII distribution based on progressive type II censoring with random removals, where the number of units removed at each failure time has a discrete uniform distribution. We use the method of maximum likelihood to derive the point estimators of the parameters. The main purpose of this article is to construct the exact confidence interval and region for the parameters. Finally, a numerical example is presented to illustrate the methods developed here. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Statistical Computation and Simulation Taylor & Francis

Statistical inference based on progressively censored samples with random removals from the Burr type XII distribution

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References (20)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1563-5163
eISSN
0094-9655
DOI
10.1080/10629360600569204
Publisher site
See Article on Publisher Site

Abstract

In this article, we study the estimation problems for the Burr type XII distribution based on progressive type II censoring with random removals, where the number of units removed at each failure time has a discrete uniform distribution. We use the method of maximum likelihood to derive the point estimators of the parameters. The main purpose of this article is to construct the exact confidence interval and region for the parameters. Finally, a numerical example is presented to illustrate the methods developed here.

Journal

Journal of Statistical Computation and SimulationTaylor & Francis

Published: Jan 1, 2007

Keywords: Confidence interval; Joint confidence region; Maximum likelihood estimator; Pivot; Progressive type II censoring; Random removals

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