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

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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:
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:


Table 6.5 - The test data for Example 16
<center>{| border="1"
 
Data point index
Last Inspection
Time-to-failure
{| border="1"
| align="center" style="background:#f0f0f0;"|'''Data Point Index'''
| align="center" style="background:#f0f0f0;"|'''Data Point Index'''
| align="center" style="background:#f0f0f0;"|'''Last Inspection'''
| align="center" style="background:#f0f0f0;"|'''Last Inspection'''
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|-
|-
|  
|  
|}
|}</center>
 
Analyze the data using several different parameter estimation techniques and compare the results.
Analyze the data using several different parameter estimation techniques and compare the results.



Revision as of 22:46, 29 February 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:

{| border="1"

| align="center" style="background:#f0f0f0;"|Data Point Index | align="center" style="background:#f0f0f0;"|Last Inspection | align="center" style="background:#f0f0f0;"|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 to Weibull Distribution Example 12

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.


The data is entered as follows,


The computed parameters using maximum likelihood are:


using RRX or rank regression on X:


and using RRY or rank regression on Y:


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