• DocumentCode
    299765
  • Title

    Estimating the cumulative downtime distribution of highly reliable components

  • Author

    Jeske, Daniel R.

  • Author_Institution
    AT&T Bell Labs., USA
  • Volume
    1
  • fYear
    1995
  • fDate
    18-22 Jun 1995
  • Firstpage
    177
  • Abstract
    Compound Bernoulli processes are motivated as satisfactory approximations to alternating renewal processes that model the availability of highly reliable components. The cumulative downtime distribution derived from a compound Bernoulli process is more tractable and can easily be estimated from data using maximum likelihood techniques. The special case of exponential repair times is examined in detail and a uniformly minimum variance unbiased estimator for the cumulative downtime distribution is derived and compared to the maximum likelihood estimator and a nonparametric estimator in terms of mean-squared error
  • Keywords
    maximum likelihood estimation; minimisation; reliability theory; statistical analysis; telecommunication network reliability; alternating renewal processes; compound Bernoulli processes; cumulative downtime distribution; exponential repair times; highly reliable components; maximum likelihood techniques; mean-squared error; nonparametric estimator; uniformly minimum variance unbiased estimator; Exponential distribution; Probability distribution; Random variables; Thumb;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, 1995. ICC '95 Seattle, 'Gateway to Globalization', 1995 IEEE International Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-2486-2
  • Type

    conf

  • DOI
    10.1109/ICC.1995.525160
  • Filename
    525160