Template:Example: Lognormal General Example Complete Data: Difference between revisions
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'''Lognormal Distribution General Example Complete Data''' | '''Lognormal Distribution General Example Complete Data''' | ||
Determine the lognormal parameter estimates for the data given in the following | Determine the lognormal parameter estimates for the data given in the following table. | ||
{|align="center" border= | {|border="1" align="center" style="border-collapse: collapse;" cellpadding="5" cellspacing="5" | ||
|- | |- | ||
|colspan="3" style="text-align:center"| | |colspan="3" style="text-align:center"| Non-Grouped Times-to-Failure Data | ||
|- | |- | ||
!Data point index | !Data point index | ||
Line 35: | Line 35: | ||
& {\hat{\sigma '}}= & 1.10 | & {\hat{\sigma '}}= & 1.10 | ||
\end{align}</math> | \end{align}</math> | ||
For rank regression on <math>X</math> | For rank regression on <math>X</math> | ||
Line 43: | Line 42: | ||
& {{{\hat{\sigma' }}}}= & 1.24 | & {{{\hat{\sigma' }}}}= & 1.24 | ||
\end{align}</math> | \end{align}</math> | ||
For rank regression on <math>Y:</math> | For rank regression on <math>Y:</math> |
Revision as of 04:52, 8 August 2012
Lognormal Distribution General Example Complete Data
Determine the lognormal parameter estimates for the data given in the following table.
Non-Grouped Times-to-Failure Data | ||
Data point index | State F or S | State End Time |
---|---|---|
1 | F | 2 |
2 | F | 5 |
3 | F | 11 |
4 | F | 23 |
5 | F | 29 |
6 | F | 37 |
7 | F | 43 |
8 | F | 59 |
Solution
Using Weibull++, the computed parameters for maximum likelihood are:
- [math]\displaystyle{ \begin{align} & {{{\hat{\mu }}}^{\prime }}= & 2.83 \\ & {\hat{\sigma '}}= & 1.10 \end{align} }[/math]
For rank regression on [math]\displaystyle{ X }[/math]
- [math]\displaystyle{ \begin{align} & {{{\hat{\mu }}}^{\prime }}= & 2.83 \\ & {{{\hat{\sigma' }}}}= & 1.24 \end{align} }[/math]
For rank regression on [math]\displaystyle{ Y: }[/math]
- [math]\displaystyle{ \begin{align} & {{{\hat{\mu }}}^{\prime }}= & 2.83 \\ & {{{\hat{\sigma' }}}}= & 1.36 \end{align} }[/math]