Inference on Marshall-Olkin Bivariate Exponential in the Presence of Dependent Left Censoring

Nasser Davarzani, Leila Golparvar, Ahmad Parsian*

*Corresponding author for this work

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1 Citation (Web of Science)


This paper deals with the dependent left censoring scheme when the survival time variable and censoring variable are dependent and have Marshal-Olkin bivariate exponential distribution. We use the expectation-conditional maximization algorithm for finding the maximum likelihood estimates of the unknown parameters. From Bayesian point of view, based on a particular choice of hyperparameters of prior distribution we obtain the exact Bayes estimates of the unknown parameters. We employ importance sampling MCMC technique and an approximate Bayes estimation method to compute Bayes estimates of the unknown parameters. Finally, a Monte Carlo simulation and a real data analysis are studied.

Original languageEnglish
Article number21
Number of pages17
JournalJournal of Statistical Theory and Practice
Issue number1
Publication statusPublished - Mar 2019


  • Bayes estimation
  • Dependent censoring
  • Left-censored data
  • Maximum likelihood estimation
  • Marshall-Olkin bivariate exponential

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