Weibull++ Standard Folio Data 1P-Weibull: Difference between revisions
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<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> | ||
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Only the scale parameter (eta) is estimated from data. You will be prompted to specify the shape parameter value. Eta represents the time by which 63.2% of the units fail. | |||
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| align="center" valign="middle" | [http://www.reliawiki.com/index.php/The_Weibull_Distribution Get More Details...] | | align="center" valign="middle" | [http://www.reliawiki.com/index.php/The_Weibull_Distribution Get More Details...] | ||
Revision as of 18:03, 11 November 2011
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Reliability Web Notes |
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| Weibull Folio |
| Life Data Analysis |
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The One-parameter Weibull distribution is a special case of the general Weibull distribution. With the one-parameter Weibull, we assume that the shape parameter is Constant and known a priori, and must be supplied by the analyst. This in turn sets the failure rate behavior. The advantage of doing this is that data sets with few or no failures can be analyzed. |
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[math]\displaystyle{ f(T)={ \frac{C}{\eta }}\left( {\frac{T}{\eta }}\right) ^{C-1}e^{-\left( {\frac{T}{ \eta }}\right) ^{C}} \,\! }[/math]
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| See Examples... |