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Parameter estimations for generalized exponential distribution under progressive type-I interval censoring

Research output: Contribution to journalArticlepeer-review

Abstract

The estimates, via maximum likelihood, moment method and probability plot, of the parameters in the generalized exponential distribution under progressive type-I interval censoring are studied. A simulation is conducted to compare these estimates in terms of mean squared errors and biases. Finally, these estimate methods are applied to a real data set based on patients with plasma cell myeloma in order to demonstrate the applicabilities.

Original languageEnglish (US)
Pages (from-to)1581-1591
Number of pages11
JournalComputational Statistics and Data Analysis
Volume54
Issue number6
DOIs
StatePublished - Jun 1 2010
Externally publishedYes

Keywords

  • EM algorithm
  • Maximum likelihood estimate
  • Method of moments
  • Type-I interval censoring

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

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