Template:Example: Published 2P Weibull Distribution Interval Data MLE Example: Difference between revisions
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'''Published 2P Weibull Distribution Interval Data MLE Example''' | |||
From Wayne Nelson, Applied Life Data Analysis, Page 415 [30]. One hundred and sixty-seven (167) identical parts were inspected for cracks. The following is a table of their last inspection times and times-to-failure: | From Wayne Nelson, Applied Life Data Analysis, Page 415 [[Appendix: Weibull References|[30]]]. One hundred and sixty-seven (167) identical parts were inspected for cracks. The following is a table of their last inspection times and times-to-failure: | ||
[[Image:example16table.png|center]] | [[Image:example16table.png|center]] | ||
'''Published Results:''' | |||
Published results (using MLE): | Published results (using MLE): | ||
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[[Image:example16formula3.png|center]] | [[Image:example16formula3.png|center]] | ||
This same data set can be entered into Weibull++ | '''Computed Results in Weibull++''' | ||
This same data set can be entered into Weibull++ by selecting the data sheet Times to Failure, with Right Censored Data (Suspensions), with Interval and Left Censored Data and with Grouped Observations options, and using MLE. | |||
Weibull++ computed parameters for maximum likelihood are: | Weibull++ computed parameters for maximum likelihood are: |
Revision as of 21:29, 29 February 2012
Published 2P Weibull Distribution Interval Data MLE Example
From Wayne Nelson, Applied Life Data Analysis, Page 415 [30]. One hundred and sixty-seven (167) identical parts were inspected for cracks. The following is a table of their last inspection times and times-to-failure:
Published Results:
Published results (using MLE):
Published 95% FM confidence limits on the parameters:
Published variance/covariance matrix:
Computed Results in Weibull++
This same data set can be entered into Weibull++ by selecting the data sheet Times to Failure, with Right Censored Data (Suspensions), with Interval and Left Censored Data and with Grouped Observations options, and using MLE.
Weibull++ computed parameters for maximum likelihood are:
Weibull++ computed 95% FM confidence limits on the parameters:
Weibull++ computed/variance covariance matrix: