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
Link To Document :
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