Weibull++ Standard Folio Data 1P-Weibull: Difference between revisions

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==== The One-Parameter Weibull Distribution ====
==== The One-Parameter Weibull Distribution ====
 
Like the exponential distribution, one-parameter Weibull distribution is a one-parameter model. However, the advantage of the one-parameter Weibull distribution is its ability to model products with increasing failure rate, constant failure rate and decreasing failure rate. This distribution is based on the common Weibull distribution, but assumes that the shape parameter, β, is a known value. This distribution is sometimes known as the "WeiBayes" distribution.


The one-parameter Weibull distribution is a special case of the two parameter Weibull that assumes that shape parameter is known constant,  
The one-parameter Weibull distribution is a special case of the two parameter Weibull that assumes that shape parameter is known constant,  

Revision as of 14:53, 19 February 2012

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The One-Parameter Weibull Distribution

Like the exponential distribution, one-parameter Weibull distribution is a one-parameter model. However, the advantage of the one-parameter Weibull distribution is its ability to model products with increasing failure rate, constant failure rate and decreasing failure rate. This distribution is based on the common Weibull distribution, but assumes that the shape parameter, β, is a known value. This distribution is sometimes known as the "WeiBayes" distribution.

The one-parameter Weibull distribution is a special case of the two parameter Weibull that assumes that shape parameter is known constant,

[math]\displaystyle{ \beta=C \,\! }[/math]

or

[math]\displaystyle{ R(t)=e^{-\left( {\frac{t}{ \eta }}\right) ^{C}} \,\! }[/math]

In this formulation we assume that the shape parameter is known a priori from past experience on identical or similar products. The advantage of doing this is that data sets with few or no failures can be analyzed.

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See also The Weibull Distribution
See also Analysis Example


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