Template:Confidence bounds duane: Difference between revisions

From ReliaWiki
Jump to navigation Jump to search
(Created page with '==Confidence Bounds== <br> Least squares confidence bounds can be computed for both the model parameters and metrics of interest for the Duane model. <br> ===Parameter Bounds=== …')
 
(Redirected page to Duane Model#Confidence Bounds)
 
(One intermediate revision by one other user not shown)
Line 1: Line 1:
==Confidence Bounds==
#REDIRECT [[Duane_Model#Confidence_Bounds]]
<br>
Least squares confidence bounds can be computed for both the model parameters and metrics of interest for the Duane model.
<br>
===Parameter Bounds===
<br>
Apply least squares analysis on the Duane model:
 
<br>
::<math>\ln ({{\hat{m}}_{c}})=\ln (b)+\alpha \ln (t)</math>
 
<br>
The unbiased estimator of    can be obtained from:
 
<br>
::<math>{{\sigma }^{2}}=Var\left[ \ln {{m}_{c}}(t) \right]=\frac{SSE}{(n-2)}</math>
 
<br>
:where:
 
<br>
::<math>SSE=\underset{i=1}{\overset{n}{\mathop \sum }}\,{{\left[ \ln {{{\hat{m}}}_{c}}({{t}_{i}})-\ln {{m}_{c}}({{t}_{i}}) \right]}^{2}}</math>
 
<br>
Thus, the confidence bounds on  <math>\alpha </math>  and  <math>b</math>  are:
 
 
::<math>C{{B}_{\alpha }}=\hat{\alpha }\pm {{t}_{n-2,\alpha /2}}SE(\hat{\alpha })</math>
 
 
 
::<math>C{{B}_{b}}=\hat{b}{{e}^{\pm {{t}_{n-2,\alpha /2}}SE\left[ \ln (\hat{b}) \right]}}</math>
 
<br>
where  <math>{{t}_{n-2,\alpha /2}}</math>  denotes the percentage point of the  <math>t</math>  distribution with  <math>n-2</math>  degrees of freedom such that  <math>P\{{{t}_{n-2}}\ge {{t}_{\alpha /2,n-2}}\}=\alpha /2</math>  and:
 
<br>
::<math>SE(\hat{\alpha })=\frac{\sigma }{\sqrt{{{S}_{xx}}}}</math>
 
 
::<math>SE\left[ \ln (\hat{b}) \right]=\sigma \cdot \sqrt{\frac{\underset{i=1}{\overset{n}{\mathop{\sum }}}\,{{(\ln {{t}_{i}})}^{2}}}{n\cdot {{S}_{xx}}}}</math>
 
 
::<math>{{S}_{xx}}=\left[ \underset{i=1}{\overset{n}{\mathop \sum }}\,{{(\ln {{t}_{i}})}^{2}} \right]-\frac{1}{n}{{\left( \underset{i=1}{\overset{n}{\mathop \sum }}\,\ln ({{t}_{i}}) \right)}^{2}}</math>
 
<br>
 
===Other Bounds===
<br>
Confidence bounds also can be obtained on the cumulative MTBF and the cumulative failure intensity:
 
<br>
::<math>C{{B}_{{{m}_{c}}}}={{\hat{m}}_{c}}(t){{e}^{\pm {{z}_{\alpha }}\sqrt{Var\left[ \ln ({{{\hat{m}}}_{c}}) \right]}}}</math>
 
 
 
::<math>\begin{align}
  & {{[{{\lambda }_{c}}(t)]}_{L}}= & \frac{1}{{{[{{m}_{c}}(t)]}_{u}}} \\
& {{[{{\lambda }_{c}}(t)]}_{U}}= & \frac{1}{{{[{{m}_{c}}(t)]}_{l}}} 
\end{align}</math>
 
<br>
When  <math>n</math>  is large, the approximate  <math>100(1-\alpha )%</math>  confidence bounds for instantaneous MTBF are given by:
 
<br>
<br>
::<math>\begin{align}
  & {{m}_{i}}{{(t)}_{L}}= & \frac{{{[{{m}_{c}}(t)]}_{L}}}{{\hat{\beta }}} \\
& {{m}_{i}}{{(t)}_{U}}= & \frac{{{[{{m}_{c}}(t)]}_{U}}}{{\hat{\beta }}} 
\end{align}</math>
 
<br>
and therefore, the confidence bounds on the instantaneous failure intensity are:
 
<br>
<br>
::<math>\begin{align}
  & {{[{{\lambda }_{i}}(t)]}_{L}}= & \frac{1}{{{[{{m}_{i}}(t)]}_{U}}} \\
& {{[{{\lambda }_{c}}(t)]}_{U}}= & \frac{1}{{{[{{m}_{i}}(t)]}_{L}}} 
\end{align}</math>
 
 
'''Example 5<math>{{\lambda }_{i}}(t)=\tfrac{1}{{{m}_{i}}(t)}</math>'''
<br>
For the data given in Table 4.3, calculate the 90% confidence bounds for:
<br>
#The parameters <math>\alpha\text{and} b</math>.
#The cumulative and instantaneous failure intensity.
#The cumulative and instantaneous MTBF.
 
<br>
<br>
'''Solution'''
:1.  Using the values of  <math>\widehat{b}</math>  and  <math>\widehat{\alpha }</math>  estimated from the least squares analysis in Example 3:
<br>
<br>
::<math>\widehat{b}=1.9453</math>
::<math>\widehat{\alpha}=0.6133
 
<br>
Eqn. (duanec9) is:
 
<br>
::<math>\begin{align}
  & {{S}_{xx}}= & 1400.9084-1301.4545 \\
& = & 99.4539 
\end{align}</math>
 
 
Eqn. (duanec7) is:
 
<br>
::<math>\begin{align}
  & SE(\hat{\alpha })= & \frac{\sigma }{\sqrt{{{S}_{xx}}}} \\
& = & \frac{0.08428}{9.9727} \\
& = & 0.008452 
\end{align}</math>
 
<br>
Eqn. (duanec8) is:
 
<br>
::<math>\begin{align}
  & SE(\ln \hat{b})= & \sigma \cdot \sqrt{\frac{\underset{i=1}{\overset{n}{\mathop{\sum }}}\,{{(\ln {{T}_{i}})}^{2}}}{n\cdot {{S}_{xx}}}} \\
& = & 0.065960 
\end{align}</math>
 
Thus, 90% confidence bounds on parameter  <math>\alpha </math>  using Eqn. (duanec1) are:
 
<br>
::<math>\begin{align}
  & {{\alpha }_{L}}= & 0.602050 \\
& {{\alpha }_{U}}= & 0.624417 
\end{align}</math>
 
<br>
And 90% confidence bounds on parameter  <math>b</math>  using Eqn. (duanec2) are:
<br>
 
<br>
::<math>\begin{align}
  & {{b}_{L}}= & 1.7831 \\
& {{b}_{U}}= & 2.1231 
\end{align}</math>
 
<br>
:2.  The cumulative failure intensity is:
 
<br>
::<math>\begin{align}
  & {{\lambda }_{c}}= & \frac{1}{1.9453}\cdot {{22000}^{-0.6133}} \\
& = & 0.00111689 
\end{align}</math>
 
<br>
And the instantaneous failure intensity is equal to:
 
<br>
::<math>\begin{align}
  & {{\lambda }_{i}}= & \frac{1}{1.9453}\cdot (1-0.6133)\cdot {{22000}^{-0.6133}} \\
& = & 0.00043198 
\end{align}</math>
 
<br>
So, at the 90% confidence level and for  <math>T=22,000</math>  hr, the confidence bounds on cumulative failure intensity are:
 
<br>
::<math>\begin{align}
  & {{[{{\lambda }_{c}}(t)]}_{L}}= & 0.00100254 \\
& {{[{{\lambda }_{c}}(t)]}_{U}}= & 0.00124429 
\end{align}</math>
 
<br>
For the instantaneous failure intensity:
 
<br>
::<math>\begin{align}
  & {{[{{\lambda }_{i}}(t)]}_{L}}= & 0.00038775 \\
& {{[{{\lambda }_{c}}(t)]}_{U}}= & 0.00048125 
\end{align}</math>
 
<br>
Figures figure75 and figure76 show the graphs of the cumulative and instantaneous failure intensity. Both are plotted with confidence bounds.
<br>
<br>
[[Image:rga4.7.png|thumb|center|400px|Cumulative Failure Intensity plot with 2-sided 90% confidence bounds.]]
<br>
<br>
[[Image:rga4.8.png|thumb|center|400px|Instantaneous Failure Intensity plot with 2-sided 90% confidence bounds.]]
 
<br>
:3.  The cumulative MTBF is:
 
<br>
::<math>\begin{align}
  & {{m}_{c}}(T)= & 1.9453\cdot {{22000}^{0.6133}} \\
& = & 895.3395 
\end{align}</math>
 
<br>
And the instantaneous MTBF is:
 
<br>
::<math>\begin{align}
  & {{m}_{i}}(T)= & \frac{1.9453}{1-0.6133}\cdot {{22000}^{0.6133}} \\
& = & 2314.9369 
\end{align}</math>
 
<br>
So, at 90% confidence level and for  <math>T=22,000</math>  hr, the confidence bounds on the cumulative MTBF are:
 
<br>
::<math>\begin{align}
  & {{m}_{c}}{{(t)}_{l}}= & 803.6695 \\
& {{m}_{c}}{{(t)}_{u}}= & 997.4658 
\end{align}</math>
 
<br>
The confidence bounds for the instantaneous MTBF are:
 
<br>
::<math>\begin{align}
  & {{m}_{i}}{{(t)}_{l}}= & 2077.9204 \\
& {{m}_{i}}{{(t)}_{u}}= & 2578.9886 
\end{align}</math>
 
<br>
Figure CumMTBFCB displays the cumulative MTBF while Figure InstMTBFCB displays the instantaneous MTBF. Both are plotted with confidence bounds.
<br>
<br>
[[Image:rga4.9.png|thumb|center|400px|Cumulative MTBF plot with 2-sided 90% condfidence bounds.]]
<br>
<br>
[[Image:rga4.10.png|thumb|center|400px|Instantaneous MTBF plot with 2-sided 90% confidence bounds.]]
<br>

Latest revision as of 02:01, 24 August 2012