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| ==Parameter Estimation==
| | #REDIRECT [[Duane_Model#Parameter_Estimation]] |
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| The Duane model is a two parameter model. Therefore, to use this model as a basis for predicting the reliability growth that could be expected in an equipment development program, procedures must be defined for estimating these parameters as a function of equipment characteristics. Note that, while these parameters can be estimated for a given data set using curve-fitting methods, there exists no underlying theory for the Duane model that could provide a basis for a priori estimation.
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| {{graphical method duane}}
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| {{least squares (linear regression)}}
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| ===Maximum Likelihood Estimators===
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| In Reliability Analysis for Complex, Repairable Systems (1974), L. H. Crow noted that the Duane model could be stochastically represented as a Weibull process, allowing for statistical procedures to be used in the application of this model in reliability growth. This statistical extension became what is known as the Crow-AMSAA (NHPP) model. The Crow-AMSAA provides a complete Maximum Likelihood Estimation (MLE) solution to the Duane model. This is described in detail in Chapter 5.
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