Weibull++ Standard Folio Data 1P-Weibull: Difference between revisions
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<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> assumed value or: | ||
<math> 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>\eta\,\!</math>. | where the only unknown parameter is the scale parameter, <math>\eta\,\!</math>. | ||
Revision as of 21:17, 7 February 2012
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The One-Parameter Weibull DistributionThe one-parameter Weibull pdf is obtained by again setting [math]\displaystyle{ \gamma=0 \,\! }[/math] and assuming [math]\displaystyle{ \beta=C=Constant \,\! }[/math] assumed value or: [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.
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| The Weibull Distribution |