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The Poisson--exponential distribution: a Bayesian approach

Author

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  • Francisco Louzada-Neto
  • Vicente G. Cancho
  • Gladys D.C. Barriga

Abstract

In this paper, we proposed a new two-parameter lifetime distribution with increasing failure rate. The new distribution arises on a latent complementary risk scenario. The properties of the proposed distribution are discussed, including a formal proof of its density function and an explicit algebraic formulae for its quantiles and survival and hazard functions. Also, we have discussed inference aspects of the model proposed via Bayesian inference by using Markov chain Monte Carlo simulation. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumptions of non-informative priors. Further, some discussions on models selection criteria are given. The developed methodology is illustrated on a real data set.

Suggested Citation

  • Francisco Louzada-Neto & Vicente G. Cancho & Gladys D.C. Barriga, 2011. "The Poisson--exponential distribution: a Bayesian approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(6), pages 1239-1248, April.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:6:p:1239-1248
    DOI: 10.1080/02664763.2010.491862
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    References listed on IDEAS

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    1. Kaifeng Lu & Anastasios A. Tsiatis, 2001. "Multiple Imputation Methods for Estimating Regression Coefficients in the Competing Risks Model with Missing Cause of Failure," Biometrics, The International Biometric Society, vol. 57(4), pages 1191-1197, December.
    2. B. Reiser & I. Guttman & Dennis K. J. Lin & Frank M. Guess & John S. Usher, 1995. "Bayesian Inference for Masked System Lifetime Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 44(1), pages 79-90, March.
    3. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
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    Cited by:

    1. Manoj Kumar & Sanjay Kumar Singh & Umesh Singh, 2018. "Bayesian inference for Poisson-inverse exponential distribution under progressive type-II censoring with binomial removal," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(6), pages 1235-1249, December.
    2. Giovani Carrara Rodrigues & Francisco Louzada & Pedro Luiz Ramos, 2018. "Poisson–exponential distribution: different methods of estimation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(1), pages 128-144, January.

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