Inverse Power Law Example: Difference between revisions

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<noinclude>{{Banner ALTA Examples}}
<noinclude>{{Banner ALTA Examples}}
''This example appears in the [[Inverse_Power_Law_(IPL)_Relationship#IPL-Weibull|Accelerated Life Testing Data Analysis Reference]] book.''
''This example appears in the [https://help.reliasoft.com/reference/accelerated_life_testing_data_analysis Accelerated life testing reference].''




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The data set was analyzed jointly in an ALTA standard folio using the IPL-Weibull relationship model, with a complete MLE solution over the entire data set. The analysis yields:
The data set was analyzed jointly in an ALTA standard folio using the IPL-Weibull model, with a complete MLE solution over the entire data set. The analysis yields:


::<math>\widehat{\beta }=2.616464</math>
::<math>\widehat{\beta }=2.616464\,\!</math>


::<math>\widehat{K}=0.001022</math>
::<math>\widehat{K}=0.001022\,\!</math>


::<math>\widehat{n}=1.327292</math>
::<math>\widehat{n}=1.327292\,\!</math>

Latest revision as of 19:02, 18 September 2023

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This example appears in the Accelerated life testing reference.


Consider the following times-to-failure data at two different stress levels.

Pdf of the lognormal distribution with different log-std values.


The data set was analyzed jointly in an ALTA standard folio using the IPL-Weibull model, with a complete MLE solution over the entire data set. The analysis yields:

[math]\displaystyle{ \widehat{\beta }=2.616464\,\! }[/math]
[math]\displaystyle{ \widehat{K}=0.001022\,\! }[/math]
[math]\displaystyle{ \widehat{n}=1.327292\,\! }[/math]