Template:Example: Lognormal General Example Suspension Data: Difference between revisions
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{{\widehat{\sigma' }}}=0.3064 \\ | {{\widehat{\sigma' }}}=0.3064 \\ | ||
\end{matrix}</math> | \end{matrix}</math> | ||
Published 95% confidence limits on the parameters: | Published 95% confidence limits on the parameters: | ||
::<math>\begin{matrix} | ::<math>\begin{matrix} | ||
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{{\widehat{\sigma'}}}=\left\{ 0.2365,0.3970 \right\} \\ | {{\widehat{\sigma'}}}=\left\{ 0.2365,0.3970 \right\} \\ | ||
\end{matrix}</math> | \end{matrix}</math> | ||
Published variance/covariance matrix: | Published variance/covariance matrix: | ||
::<math>\left[ \begin{matrix} | ::<math>\left[ \begin{matrix} | ||
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• Weibull++ computed parameters for maximum likelihood are: | • Weibull++ computed parameters for maximum likelihood are: | ||
::<math>\begin{matrix} | ::<math>\begin{matrix} | ||
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• Weibull++ computed 95% confidence limits on the parameters: | • Weibull++ computed 95% confidence limits on the parameters: | ||
::<math>\begin{matrix} | ::<math>\begin{matrix} | ||
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{{\widehat{\sigma'}}}=\left\{ 0.2395,0.3920 \right\} \\ | {{\widehat{\sigma'}}}=\left\{ 0.2395,0.3920 \right\} \\ | ||
\end{matrix}</math> | \end{matrix}</math> | ||
• Weibull++ computed/variance covariance matrix: | • Weibull++ computed/variance covariance matrix: | ||
::<math>\left[ \begin{matrix} | ::<math>\left[ \begin{matrix} | ||
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\end{matrix} \right]</math> | \end{matrix} \right]</math> | ||
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|colspan="4" style="text-align:center"|Table - Nelson's Locomotive Data | |colspan="4" style="text-align:center"|Table - Nelson's Locomotive Data | ||
Revision as of 05:09, 8 August 2012
Lognormal Distribution General Example Suspension Data
From Nelson [30, p. 324]. Ninety-six locomotive controls were tested, 37 failed and 59 were suspended after running for 135,000 miles. Table 9.6 below shows their times-to-failure.
Solution
The distribution used in the publication was the base-10 lognormal. Published results (using MLE):
- [math]\displaystyle{ \begin{matrix} {{\widehat{\mu }}^{\prime }}=2.2223 \\ {{\widehat{\sigma' }}}=0.3064 \\ \end{matrix} }[/math]
Published 95% confidence limits on the parameters:
- [math]\displaystyle{ \begin{matrix} {{\widehat{\mu }}^{\prime }}=\left\{ 2.1336,2.3109 \right\} \\ {{\widehat{\sigma'}}}=\left\{ 0.2365,0.3970 \right\} \\ \end{matrix} }[/math]
Published variance/covariance matrix:
- [math]\displaystyle{ \left[ \begin{matrix} \widehat{Var}\left( {{{\hat{\mu }}}^{\prime }} \right)=0.0020 & {} & \widehat{Cov}({{{\hat{\mu }}}^{\prime }},{{{\hat{\sigma' }}}})=0.001 \\ {} & {} & {} \\ \widehat{Cov}({{{\hat{\mu }}}^{\prime }},{{{\hat{\sigma' }}}})=0.001 & {} & \widehat{Var}\left( {{{\hat{\sigma '}}}} \right)=0.0016 \\ \end{matrix} \right] }[/math]
To replicate the published results (since Weibull++ uses a lognormal to the base [math]\displaystyle{ e }[/math] ), take the base-10 logarithm of the data and estimate the parameters using the Normal distribution and MLE.
• Weibull++ computed parameters for maximum likelihood are:
- [math]\displaystyle{ \begin{matrix} {{\widehat{\mu }}^{\prime }}=2.2223 \\ {{\widehat{\sigma' }}}=0.3064 \\ \end{matrix} }[/math]
• Weibull++ computed 95% confidence limits on the parameters:
- [math]\displaystyle{ \begin{matrix} {{\widehat{\mu }}^{\prime }}=\left\{ 2.1364,2.3081 \right\} \\ {{\widehat{\sigma'}}}=\left\{ 0.2395,0.3920 \right\} \\ \end{matrix} }[/math]
• Weibull++ computed/variance covariance matrix:
- [math]\displaystyle{ \left[ \begin{matrix} \widehat{Var}\left( {{{\hat{\mu }}}^{\prime }} \right)=0.0019 & {} & \widehat{Cov}({{{\hat{\mu }}}^{\prime }},{{{\hat{\sigma' }}}})=0.0009 \\ {} & {} & {} \\ \widehat{Cov}({\mu }',{{{\hat{\sigma' }}}})=0.0009 & {} & \widehat{Var}\left( {{{\hat{\sigma' }}}} \right)=0.0015 \\ \end{matrix} \right] }[/math]
| Table - Nelson's Locomotive Data | |||
| Number in State | F or S | Time | |
|---|---|---|---|
| 1 | 1 | F | 22.5 |
| 2 | 1 | F | 37.5 |
| 3 | 1 | F | 46 |
| 4 | 1 | F | 48.5 |
| 5 | 1 | F | 51.5 |
| 6 | 1 | F | 53 |
| 7 | 1 | F | 54.5 |
| 8 | 1 | F | 57.5 |
| 9 | 1 | F | 66.5 |
| 10 | 1 | F | 68 |
| 11 | 1 | F | 69.5 |
| 12 | 1 | F | 76.5 |
| 13 | 1 | F | 77 |
| 14 | 1 | F | 78.5 |
| 15 | 1 | F | 80 |
| 16 | 1 | F | 81.5 |
| 17 | 1 | F | 82 |
| 18 | 1 | F | 83 |
| 19 | 1 | F | 84 |
| 20 | 1 | F | 91.5 |
| 21 | 1 | F | 93.5 |
| 22 | 1 | F | 102.5 |
| 23 | 1 | F | 107 |
| 24 | 1 | F | 108.5 |
| 25 | 1 | F | 112.5 |
| 26 | 1 | F | 113.5 |
| 27 | 1 | F | 116 |
| 28 | 1 | F | 117 |
| 29 | 1 | F | 118.5 |
| 30 | 1 | F | 119 |
| 31 | 1 | F | 120 |
| 32 | 1 | F | 122.5 |
| 33 | 1 | F | 123 |
| 34 | 1 | F | 127.5 |
| 35 | 1 | F | 131 |
| 36 | 1 | F | 132.5 |
| 37 | 1 | F | 134 |
| 38 | 59 | S | 135 |