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Reliability analysis of repairable systems from in–service failure count data

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  • R. Calabria
  • M. Guida
  • G. Pulcini

Abstract

Point maximum likelihood estimators for parameters, mean number of failures, and failure rate in a non–homogeneous Poisson process are derived, when only count data from k identical processes are available. Approximate confidence intervals based on the parametric bootstrap technique are considered. The performances of both the point and interval estimation procedures are assessed via Monte Carlo simulation.

Suggested Citation

  • R. Calabria & M. Guida & G. Pulcini, 1994. "Reliability analysis of repairable systems from in–service failure count data," Applied Stochastic Models and Data Analysis, John Wiley & Sons, vol. 10(3), pages 141-151.
    • Handle: RePEc:wly:apsmda:v:10:y:1994:i:3:p:141-151
    DOI: 10.1002/asm.3150100302
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