• DocumentCode
    1084112
  • Title

    Bayes estimation of the piece-wise exponential distribution

  • Author

    Gamerman, Dani

  • Author_Institution
    Inst. de Matematica, Univ. Federal de Rio de Janeiro, Brazil
  • Volume
    43
  • Issue
    1
  • fYear
    1994
  • fDate
    3/1/1994 12:00:00 AM
  • Firstpage
    128
  • Lastpage
    131
  • Abstract
    A Bayes method to infer an unknown failure time distribution is presented. The method is based on the piecewise exponential distribution and a relationship between values of the failure rate in successive intervals; it provides smooth estimates of the survival and hazard functions of the distribution. This is accomplished in a model-based framework without resorting to smoothing procedures that require ad-hoc specification of parameters that have no bearing on the data. It is a useful procedure whenever the failure rate is anticipated to be reasonably continuous. Incorporating these beliefs into the model allows a more rational solution to the nonparametric estimation problem. The advantages are illustrated using a real data-set where a smooth estimate of the failure rate is obtained. The method can be used with any possibly-censored data-set and is easily implemented on a microcomputer. The Bayes solution is compared with the classical solution for the problem
  • Keywords
    Bayes methods; estimation theory; failure analysis; nonparametric statistics; probability; reliability theory; Bayes estimation; failure rate; failure time distribution; hazard function; microcomputer; model-based framework; nonparametric estimation problem; piecewise exponential distribution; successive intervals; survival function; Exponential distribution; Failure analysis; Hazards; Maximum likelihood estimation; Microcomputers; Probability; Smoothing methods; Statistical analysis; Statistical distributions; Stochastic processes;
  • fLanguage
    English
  • Journal_Title
    Reliability, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9529
  • Type

    jour

  • DOI
    10.1109/24.285126
  • Filename
    285126