Weibull++ Parameteric RDA Data: Difference between revisions

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Weibull++'s Parametric RDA Specialized Folio is a tool to model recurrent event data.  It can capture the trend, estimate the rate and predict the total number of recurrences. The failure and repair data of a repairable system can be treated as one type of recurrence data. Past and current repairs may affect the future failure process. For most recurrence events, time (distance, cycles, etc.) is a key factor. With the time, the recurrence rate may keep constant, increase or decrease. For other recurrence events, not only the time, but also the number of events can affect the recurrence process, e.g. the debugging process in software development.
Weibull++'s Parametric RDA Specialized Folio is a tool to model recurrent event data.  It can capture the trend, estimate the rate and predict the total number of recurrences. The failure and repair data of a repairable system can be treated as one type of recurrence data. Past and current repairs may affect the future failure process. For most recurrence events, time (distance, cycles, etc.) is a key factor. With the time, the recurrence rate may keep constant, increase or decrease. For other recurrence events, not only the time, but also the number of events can affect the recurrence process, e.g. the debugging process in software development.
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| align="center" valign="middle" | [http://reliawiki.com/index.php/Template:Parametric_recurrence_data_analysis#Parametric_Recurrence_Data_Analysis Get More Details...]
| valign="middle" | [http://reliawiki.com/index.php/Template:Parametric_recurrence_data_analysis#Parametric_Recurrence_Data_Analysis Get More Details...]
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| align="center" valign="middle" | [http://reliawiki.com/index.php/Template:Parametric_rda_example#Example_4 See Examples...]
| valign="middle" | [http://reliawiki.com/index.php/Template:Parametric_rda_example#Example_4 See Examples...]
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Revision as of 22:04, 9 February 2012

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Parametric RDA Data
Weibull++

Weibull++'s Parametric RDA Specialized Folio is a tool to model recurrent event data. It can capture the trend, estimate the rate and predict the total number of recurrences. The failure and repair data of a repairable system can be treated as one type of recurrence data. Past and current repairs may affect the future failure process. For most recurrence events, time (distance, cycles, etc.) is a key factor. With the time, the recurrence rate may keep constant, increase or decrease. For other recurrence events, not only the time, but also the number of events can affect the recurrence process, e.g. the debugging process in software development.

Get More Details...
See Examples...



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