ALTA Simumatic Data IPL-Weibull - Revision history

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

2015-07-08T20:17:12Z

Redirected page to Template:WebNotes/ALTASimuMatic Data

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Richard House: Replaced content with '{{WebNotes ALTA SimuMatic Data}}'

2012-07-19T06:59:25Z

Replaced content with '{{WebNotes ALTA SimuMatic Data}}'

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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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Nikki Helms at 18:14, 22 March 2012

2012-03-22T18:14:03Z

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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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	\| [http://reliawiki.com/index.php/~~Inverse_Power_Law_(IPL)_Relationship~~ the theory textbook...]		\| [http://reliawiki.com/index.php/SimuMatic the theory textbook...]
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Chuck Smith at 22:52, 8 March 2012

2012-03-08T22:52:21Z

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Chuck Smith at 22:45, 8 March 2012

2012-03-08T22:45:31Z

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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

2012-02-14T18:24:52Z

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Nicolette Young at 17:15, 14 February 2012

2012-02-14T17:15:21Z

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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++.		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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	\| ~~align="center"~~ valign="middle" \| [http://www.reliawiki.com/index.php/Template:Ipl_weibull IPL Weibull]		\| valign="middle" \| [http://www.reliawiki.com/index.php/Template:Ipl_weibull IPL Weibull]
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Nicolette Young at 18:52, 18 January 2012

2012-01-18T18:52:10Z

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	~~Content 1~~		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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2012-01-13T22:10:14Z

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