Template:Example: Weibull Distribution Interval Data Example: Difference between revisions

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The computed parameters using maximum likelihood are:
The computed parameters using maximum likelihood are:


<center><math>\begin{align}
::<math>\begin{align}
   & \hat{\beta }=5.76 \\  
   & \hat{\beta }=5.76 \\  
  & \hat{\eta }=44.68 \\  
  & \hat{\eta }=44.68 \\  
\end{align}</math></center>
\end{align}</math>


using RRX or rank regression on X:
using RRX or rank regression on X:


<center><math>\begin{align}
::<math>\begin{align}
   & \hat{\beta }=5.70 \\  
   & \hat{\beta }=5.70 \\  
  & \hat{\eta }=44.54 \\  
  & \hat{\eta }=44.54 \\  
\end{align}</math></center>
\end{align}</math>


and using RRY or rank regression on Y:
and using RRY or rank regression on Y:


<center><math>\begin{align}
::<math>\begin{align}
   & \hat{\beta }=5.41 \\  
   & \hat{\beta }=5.41 \\  
  & \hat{\eta }=44.76 \\  
  & \hat{\eta }=44.76 \\  
\end{align}</math></center>
\end{align}</math>


The plot of the MLE solution with the two-sided 90% confidence bounds is:
The plot of the MLE solution with the two-sided 90% confidence bounds is:
[[Image: MLE Plot.png|center|550px]]
[[Image: MLE Plot.png|center|550px]]

Revision as of 05:27, 6 August 2012

Weibull Distribution Interval Data Example

Suppose that we have run an experiment with eight units being tested and the following is a table of their last inspection times and times-to-failure:

Data Point Index Last Inspection Time to Failure
1 30 32
2 32 35
3 35 37
4 37 40
5 42 42
6 45 45
7 50 50
8 55 55

Analyze the data using several different parameter estimation techniques and compare the results.

Solution

This data set can be entered into Weibull++ by opening a new Data Folio and choosing Times-to-failure and My data set contains interval and/or left censored data.

Data Type.png

The data is entered as follows,

Data Folio.png

The computed parameters using maximum likelihood are:

[math]\displaystyle{ \begin{align} & \hat{\beta }=5.76 \\ & \hat{\eta }=44.68 \\ \end{align} }[/math]

using RRX or rank regression on X:

[math]\displaystyle{ \begin{align} & \hat{\beta }=5.70 \\ & \hat{\eta }=44.54 \\ \end{align} }[/math]

and using RRY or rank regression on Y:

[math]\displaystyle{ \begin{align} & \hat{\beta }=5.41 \\ & \hat{\eta }=44.76 \\ \end{align} }[/math]

The plot of the MLE solution with the two-sided 90% confidence bounds is:

MLE Plot.png