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

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The one-parameter Weibull ''pdf'' is obtained by again setting  
The one-parameter Weibull distribution is a special case of obtained by setting  
<math>\gamma=0 \,\!</math> and assuming <math>\beta=C=Constant \,\!</math> assumed value or:
::<math>\gamma=0 \,\!</math>  
and assuming  
::<math>\beta=C=Constant \,\!</math>  


<math> f(t)={ \frac{C}{\eta }}\left( {\frac{t}{\eta }}\right) ^{C-1}e^{-\left( {\frac{t}{ \eta }}\right) ^{C}} \,\!</math>  
<math> f(t)={ \frac{C}{\eta }}\left( {\frac{t}{\eta }}\right) ^{C-1}e^{-\left( {\frac{t}{ \eta }}\right) ^{C}} \,\!</math>  

Revision as of 23:21, 10 February 2012

 

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The One-Parameter Weibull Distribution

The one-parameter Weibull distribution is a special case of obtained by setting

[math]\displaystyle{ \gamma=0 \,\! }[/math]

and assuming

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


[math]\displaystyle{ f(t)={ \frac{C}{\eta }}\left( {\frac{t}{\eta }}\right) ^{C-1}e^{-\left( {\frac{t}{ \eta }}\right) ^{C}} \,\! }[/math]

where the only unknown parameter is the scale parameter, [math]\displaystyle{ \eta\,\! }[/math].

Note that in the formulation of the one-parameter Weibull, we assume that the shape parameter [math]\displaystyle{ \beta \,\! }[/math] 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.


The Weibull Distribution
See an Example...


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