ALTA Simumatic Data Arrhenius-Weibull - Revision history

Richard House: Redirected page to Template:WebNotes/ALTASimuMatic Data

2015-07-08T20:09:33Z

Redirected page to Template:WebNotes/ALTASimuMatic Data

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2012-07-18T13:27:06Z

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	ALTA SimuMatic generates multiple data sets using Monte Carlo simulation. It then analyzes each data set individually (e.g., to find the reliability at a specified time) and the group of data sets as a whole (e.g., to find the average reliability at a specified time across the data sets).
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Chris Kahn at 15:57, 3 May 2012

2012-05-03T15:57:30Z

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Nikki Helms at 17:51, 22 March 2012

2012-03-22T17:51:13Z

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	~~Reliability analysis using simulation, in which reliability analyses are performed a large number of times on~~ data sets ~~that have been created~~ using Monte Carlo simulation, ~~can be a valuable tool for~~ reliability ~~practitioners. Such simulation analyses can assist the analyst to~~ a) ~~better understand life~~ data ~~analysis concepts~~, ~~b) experiment with~~ the ~~influences of sample sizes and censoring schemes on analysis methods, c) construct simulation-based confidence intervals, d) better understand~~ the ~~concepts behind confidence intervals and e~~) ~~design reliability tests~~. ~~This section explores some of the results that can be obtained from simulation analyses with the SimuMatic utility in Weibull++~~		ALTA SimuMatic generates multiple data sets using Monte Carlo simulation. It then analyzes each data set individually (e.g., to find the reliability at a specified time) and the group of data sets as a whole (e.g., to find the average reliability at a specified time across the data sets).
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Nikki Helms at 17:48, 22 March 2012

2012-03-22T17:48:42Z

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Nikki Helms at 16:03, 22 March 2012

2012-03-22T16:03:25Z

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Chuck Smith at 22:21, 8 March 2012

2012-03-08T22:21:34Z

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Chuck Smith at 22:19, 8 March 2012

2012-03-08T22:19:35Z

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Chuck Smith at 22:18, 8 March 2012

2012-03-08T22:18:43Z

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 Reliability analysis using simulation, in which reliability analyses are performed a large number of times on data sets that have been created using Monte Carlo simulation, can be a valuable tool for reliability practitioners. Such simulation analyses can assist the analyst to a) better understand life data analysis concepts, b) experiment with the influences of sample sizes and censoring schemes on analysis methods, c) construct simulation-based confidence intervals, d) better understand the concepts behind confidence intervals and e) design reliability tests. This section explores some of the results that can be obtained from simulation analyses with the SimuMatic utility in Weibull++
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Nicolette Young at 18:24, 14 February 2012

2012-02-14T18:24:06Z

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