Maximum Likelihood Estimation For The 2-Parameter Weibull Distribution Based On Interval-Data

MLE techniques are presented for estimating time-to-failure distributions from interval-data. Interval-data consist of adjacent inspection times that surround an unknown failure time. Censored interval-data bound the unknown failure time with only a lower time. The 2-parameter Weibull distribution i...

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Bibliographic Details
Published in:IEEE transactions on reliability 1985-04, Vol.R-34 (1), p.57-59
Main Authors: Flygare, Mark E., Austin, John A., Buckwalter, Ross M.
Format: Article
Language:English
Subjects:
Applied sciences
Cities and towns
Equations
Exact sciences and technology
Grouped samples
Inspection
Interval-data
Life estimation
Maximum likelihood estimation
Operational research and scientific management
Operational research. Management science
Parameter estimation
Reliability theory. Replacement problems
Shape
Statistical distributions
Testing
Weibull distribution
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Summary:MLE techniques are presented for estimating time-to-failure distributions from interval-data. Interval-data consist of adjacent inspection times that surround an unknown failure time. Censored interval-data bound the unknown failure time with only a lower time. The 2-parameter Weibull distribution is examined as the failure distribution. Parameter estimates from interval-data and from the midpoints of the intervals are compared for 6 shapes of the Weibull distribution. The results from Monte Carlo simulation runs are used to examine the s-bias and S-variability of the parameter estimates.
ISSN:0018-9529
1558-1721
DOI:10.1109/TR.1985.5221930