WeibullDataSet.CalculateBestFit - Revision history

Kate Racaza at 16:07, 17 August 2016

2016-08-17T16:07:55Z

← Older revision		Revision as of 16:07, 17 August 2016
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	<onlyinclude>Determines which of the selected life distributions best fits the data set (similar to the Distribution Wizard feature in Weibull++) and creates a [[CModel Class\|cModel]] object that represents the fitted model of the recommended distribution~~. Returns a message box that shows the estimated parameters of the fitted model~~.</onlyinclude>		<onlyinclude>Determines which of the selected life distributions best fits the data set (similar to the Distribution Wizard feature in Weibull++) and creates a [[CModel Class\|cModel]] object that represents the fitted model of the recommended distribution.</onlyinclude>

	To specify the ~~life~~ distributions ~~to be considered~~, ~~the~~ parameter estimation method and other criteria for evaluating the fit, use the <code>BestFitSettings</code> property of the ~~associated~~ <code>~~WeibullDataSet~~</code> object.
			'''Remarks''': To specify the distributions, parameter estimation method and other criteria for evaluating the fit, use the <code>BestFitSettings</code> property of the object. To return the <code>cModel</code> object that is produced, use the <code>FittedModel</code> property of the object.

	== Syntax ==		== Syntax ==

Kate Racaza at 22:19, 17 June 2016

2016-06-17T22:19:02Z

← Older revision		Revision as of 22:19, 17 June 2016
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	{{APIComment\|'Determine which distribution best fits the data set, based on the MLE method.}}		{{APIComment\|'Determine which distribution best fits the data set, based on the MLE method.}}
	{{APIPrefix\|Call}} WDS.CalculateBestFit()		{{APIPrefix\|Call}} WDS.CalculateBestFit()

	~~{{APIComment\|'Retrieve the fitted life distribution model.}}~~		{{APIComment\|'Calculate the reliability at 100 hrs and display the result.}}
	~~{{APIPrefix\|Dim}} model {{APIPrefix\|As}} cModel~~
	~~{{APIPrefix\|Set}} model = WDS.FittedModel~~

	{{APIComment\|'~~Using the model, calculate~~ the reliability at 100 hrs and display the result.}}
	{{APIPrefix\|Dim}} r {{APIPrefix\|As}} Double		{{APIPrefix\|Dim}} r {{APIPrefix\|As}} Double
	r = ~~model~~.~~reliability~~(100)		r = WDS.FittedModel.Reliability(100)
	MsgBox({{APIString\|"Reliability at 100 hrs: "}} & r)		MsgBox({{APIString\|"Reliability at 100 hrs: "}} & r)

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	{{APIComment\|'Determine which distribution best fits the data set, based on the MLE method.}}		{{APIComment\|'Determine which distribution best fits the data set, based on the MLE method.}}
	WDS.CalculateBestFit()		WDS.CalculateBestFit()

	~~{{APIComment\|'Retrieve the fitted life distribution model.}}~~		{{APIComment\|'Calculate the reliability at 100 hrs and display the result.}}
	~~{{APIPrefix\|Dim}} model {{APIPrefix\|As}} cModel~~
	~~model = WDS.FittedModel~~

	{{APIComment\|'~~Using the model, calculate~~ the reliability at 100 hrs and display the result.}}
	{{APIPrefix\|Dim}} r {{APIPrefix\|As}} Double		{{APIPrefix\|Dim}} r {{APIPrefix\|As}} Double
	r = ~~model~~.~~reliability~~(100)		r = WDS.FittedModel.Reliability(100)
	MsgBox({{APIString\|"Reliability at 100 hrs: "}} & r)		MsgBox({{APIString\|"Reliability at 100 hrs: "}} & r)

Kate Racaza at 22:00, 17 June 2016

2016-06-17T22:00:12Z

← Older revision		Revision as of 22:00, 17 June 2016
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	<onlyinclude>Determines which of the selected life distributions best fits the data set (similar to the Distribution Wizard feature in Weibull++) and creates a [[CModel Class\|cModel]] object that represents the fitted model of the recommended distribution. Returns a message box that shows the estimated parameters of the fitted model.</onlyinclude>		<onlyinclude>Determines which of the selected life distributions best fits the data set (similar to the Distribution Wizard feature in Weibull++) and creates a [[CModel Class\|cModel]] object that represents the fitted model of the recommended distribution. Returns a message box that shows the estimated parameters of the fitted model.</onlyinclude>

	~~Use~~ the <code>BestFitSettings</code> property of the associated <code>WeibullDataSet</code> object ~~to specify the life distributions to be considered, the parameter estimation method and other criteria for evaluating the fit~~.		To specify the life distributions to be considered, the parameter estimation method and other criteria for evaluating the fit, use the <code>BestFitSettings</code> property of the associated <code>WeibullDataSet</code> object.

	== Syntax ==		== Syntax ==

Kate Racaza at 21:01, 17 June 2016

2016-06-17T21:01:45Z

← Older revision		Revision as of 21:01, 17 June 2016
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	<onlyinclude>Determines the best ~~distribution for a~~ data set ~~based on a chosen parameter estimation method~~ (similar to the Distribution Wizard feature in Weibull++)~~. Returns a message box that shows the estimated parameters of the distribution that best fits the data. In addition, it~~ creates a ~~retrievable~~ [[CModel Class\|cModel]] object that represents the fitted model ~~from~~ the ~~life data analysis~~.</onlyinclude>		<onlyinclude>Determines which of the selected life distributions best fits the data set (similar to the Distribution Wizard feature in Weibull++) and creates a [[CModel Class\|cModel]] object that represents the fitted model of the recommended distribution. Returns a message box that shows the estimated parameters of the fitted model.</onlyinclude>

	Use the BestFitSettings property of the WeibullDataSet object to specify the parameter estimation method and other criteria for evaluating the fit.		Use the <code>BestFitSettings</code> property of the associated <code>WeibullDataSet</code> object to specify the life distributions to be considered, the parameter estimation method and other criteria for evaluating the fit.

	== Syntax ==		== Syntax ==

Kate Racaza at 22:39, 25 April 2016

2016-04-25T22:39:27Z

← Older revision		Revision as of 22:39, 25 April 2016
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	<onlyinclude>~~Performs goodness of fit tests to find~~ the distribution ~~that best fits the~~ data set (similar to the Distribution Wizard feature in Weibull++). Returns a message box that shows the estimated parameters of the distribution that best fits the data. In addition, it creates a retrievable [[CModel Class\|cModel]] object that represents the fitted model from the life data analysis.</onlyinclude>		<onlyinclude>Determines the best distribution for a data set based on a chosen parameter estimation method (similar to the Distribution Wizard feature in Weibull++). Returns a message box that shows the estimated parameters of the distribution that best fits the data. In addition, it creates a retrievable [[CModel Class\|cModel]] object that represents the fitted model from the life data analysis.</onlyinclude>

	Use the BestFitSettings property of the WeibullDataSet object to specify the criteria for evaluating the fit.		Use the BestFitSettings property of the WeibullDataSet object to specify the parameter estimation method and other criteria for evaluating the fit.

	== Syntax ==		== Syntax ==
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	WDS.BestFitSettings.AllowGumbel = False		WDS.BestFitSettings.AllowGumbel = False

	{{APIComment\|'~~Perform~~ the ~~goodness of fit tests~~.}}		{{APIComment\|'Use the MLE parameter estimation method.}}
			WDS.BestFitSettings.Analysis = WeibullSolverMethod_MLE

			{{APIComment\|'Determine which distribution best fits the data set, based on the MLE method.}}
	{{APIPrefix\|Call}} WDS.CalculateBestFit()		{{APIPrefix\|Call}} WDS.CalculateBestFit()

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	WDS.BestFitSettings.AllowLoglogistic = False		WDS.BestFitSettings.AllowLoglogistic = False
	WDS.BestFitSettings.AllowGumbel = False		WDS.BestFitSettings.AllowGumbel = False

			{{APIComment\|'Use the MLE parameter estimation method.}}
			WDS.BestFitSettings.Analysis = WeibullSolverMethod.MLE

	{{APIComment\|'~~Perform~~ the ~~goodness of fit tests~~.}}		{{APIComment\|'Determine which distribution best fits the data set, based on the MLE method.}}
	WDS.CalculateBestFit()		WDS.CalculateBestFit()

Kate Racaza at 15:18, 14 April 2016

2016-04-14T15:18:37Z

← Older revision		Revision as of 15:18, 14 April 2016
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	<onlyinclude>Performs goodness of fit tests to find the distribution that best fits the data set (similar to the Distribution Wizard feature in Weibull++). Returns a message box that shows the estimated parameters of the distribution that best fits the data. In addition, it creates a retrievable [[CModel Class\|cModel]] object that represents the fitted model from the life data analysis.</onlyinclude>		<onlyinclude>Performs goodness of fit tests to find the distribution that best fits the data set (similar to the Distribution Wizard feature in Weibull++). Returns a message box that shows the estimated parameters of the distribution that best fits the data. In addition, it creates a retrievable [[CModel Class\|cModel]] object that represents the fitted model from the life data analysis.</onlyinclude>

	Use the ~~<code>~~BestFitSettings~~</code>~~ property of the WeibullDataSet object to specify the criteria for evaluating the fit.		Use the BestFitSettings property of the WeibullDataSet object to specify the criteria for evaluating the fit.

	== Syntax ==		== Syntax ==

Kate Racaza at 21:16, 13 April 2016

2016-04-13T21:16:53Z

← Older revision		Revision as of 21:16, 13 April 2016
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	<onlyinclude>Performs goodness of fit tests to find the distribution that best fits the data set (similar to the Distribution Wizard feature in Weibull++). Returns a message box that shows the estimated parameters of the distribution that best fits the data ~~and~~ creates a retrievable [[CModel Class\|cModel]] object that represents the fitted model from the life data analysis.</onlyinclude>		<onlyinclude>Performs goodness of fit tests to find the distribution that best fits the data set (similar to the Distribution Wizard feature in Weibull++). Returns a message box that shows the estimated parameters of the distribution that best fits the data. In addition, it creates a retrievable [[CModel Class\|cModel]] object that represents the fitted model from the life data analysis.</onlyinclude>

	Use the <code>BestFitSettings</code> property of the ~~class~~ to specify the criteria for evaluating the fit.		Use the <code>BestFitSettings</code> property of the WeibullDataSet object to specify the criteria for evaluating the fit.

	== Syntax ==		== Syntax ==

Kate Racaza at 21:39, 7 April 2016

2016-04-07T21:39:10Z

← Older revision		Revision as of 21:39, 7 April 2016
Line 2:		Line 2:


	<onlyinclude>Performs goodness of fit tests to find the distribution that best fits the data set (similar to the Distribution Wizard feature in Weibull++). Returns a message box that shows the estimated parameters of the distribution that best fits the data and creates a retrievable [[CModel Class\|cModel]] object that represents the fitted model from the life data analysis.		<onlyinclude>Performs goodness of fit tests to find the distribution that best fits the data set (similar to the Distribution Wizard feature in Weibull++). Returns a message box that shows the estimated parameters of the distribution that best fits the data and creates a retrievable [[CModel Class\|cModel]] object that represents the fitted model from the life data analysis.</onlyinclude>

	Use the <code>BestFitSettings</code> property of the class to specify the criteria for evaluating the fit. ~~</onlyinclude>~~		Use the <code>BestFitSettings</code> property of the class to specify the criteria for evaluating the fit.

	== Syntax ==		== Syntax ==

Kate Racaza at 21:29, 7 April 2016

2016-04-07T21:29:13Z

← Older revision		Revision as of 21:29, 7 April 2016
Line 2:		Line 2:


	<onlyinclude>Performs goodness of fit tests to find the distribution that best fits the data set. Returns a message box that shows the estimated parameters of the distribution that best fits the data~~. (Similar to~~ the ~~Distribution Wizard feature in Weibull++). Use~~ the ~~<code>BestFitSettings</code> property of the class to specify the criteria for evaluating the fit~~. ~~</onlyinclude>~~		<onlyinclude>Performs goodness of fit tests to find the distribution that best fits the data set (similar to the Distribution Wizard feature in Weibull++). Returns a message box that shows the estimated parameters of the distribution that best fits the data and creates a retrievable [[CModel Class\|cModel]] object that represents the fitted model from the life data analysis.

	~~In addition,~~ the ~~method automatically creates a retrievable [[CModel Class\|cModel]] object that represents~~ the ~~fitted model from~~ the ~~life data analysis~~.		Use the <code>BestFitSettings</code> property of the class to specify the criteria for evaluating the fit. </onlyinclude>

	== Syntax ==		== Syntax ==

Kate Racaza at 22:38, 30 March 2016

2016-03-30T22:38:06Z

← Older revision		Revision as of 22:38, 30 March 2016
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	{{Template:~~APIClass\|WeibullDataSet Class\|WeibullDataSet~~}}		{{Template:API}}{{Template:APIBreadcrumb\|.[[WeibullDataSet Class\|WeibullDataSet]]}}
	{{Template:WeibullDataSet~~.CalculateBestFit.Cmt~~}}

	~~This is equivalent~~ to ~~clicking~~ the ~~'''Implement''' button in~~ the Distribution Wizard.
			<onlyinclude>Performs goodness of fit tests to find the distribution that best fits the data set. Returns a message box that shows the estimated parameters of the distribution that best fits the data. (Similar to the Distribution Wizard feature in Weibull++). Use the <code>BestFitSettings</code> property of the class to specify the criteria for evaluating the fit. </onlyinclude>

			In addition, the method automatically creates a retrievable [[CModel Class\|cModel]] object that represents the fitted model from the life data analysis.

	== Syntax ==		== Syntax ==
	*CalculateBestFit()		'''.CalculateBestFit

	== ~~Usage~~ Example ==		== Example ==
			'''VBA'''

			{{APIComment\|'Declare a new WeibullDataSet object.}}
			{{APIPrefix\|Dim}} WDS {{APIPrefix\|As New}} WeibullDataSet

			{{APIComment\|'Add failure times to the data set.}}
			{{APIPrefix\|Call}} WDS.AddFailure(100, 1)
			{{APIPrefix\|Call}} WDS.AddFailure(120, 1)
			{{APIPrefix\|Call}} WDS.AddFailure(130, 1)

			{{APIComment\|'Consider the normal, lognormal and 2-parameter Weibull distributions in the evaluation.}}
			WDS.BestFitSettings.AllowExponential1 = False
			WDS.BestFitSettings.AllowExponential2 = False
			WDS.BestFitSettings.AllowNormal = True
			WDS.BestFitSettings.AllowLognormal = True
			WDS.BestFitSettings.AllowWeibull2 = True
			WDS.BestFitSettings.AllowWeibull3 = False
			WDS.BestFitSettings.AllowGamma = False
			WDS.BestFitSettings.AllowGenGamma = False
			WDS.BestFitSettings.AllowLogistic = False
			WDS.BestFitSettings.AllowLoglogistic = False
			WDS.BestFitSettings.AllowGumbel = False

			{{APIComment\|'Perform the goodness of fit tests.}}
			{{APIPrefix\|Call}} WDS.CalculateBestFit()

			{{APIComment\|'Retrieve the fitted life distribution model.}}
			{{APIPrefix\|Dim}} model {{APIPrefix\|As}} cModel
			{{APIPrefix\|Set}} model = WDS.FittedModel

			{{APIComment\|'Using the model, calculate the reliability at 100 hrs and display the result.}}
			{{APIPrefix\|Dim}} r {{APIPrefix\|As}} Double
			r = model.reliability(100)
			MsgBox({{APIString\|"Reliability at 100 hrs: "}} & r)

	{{APIComment\|'Declare a new WeibullDataSet object~~. See [[WeibullDataSet Class\|WeibullDataSet]]~~.}}		'''VB.NET'''
	Dim WDS As New WeibullDataSet~~("AddFailure_Example")~~
			{{APIComment\|'Declare a new WeibullDataSet object.}}
			{{APIPrefix\|Dim}} WDS {{APIPrefix\|As New}} WeibullDataSet

	{{APIComment\|'Add failure times to the data set.}}		{{APIComment\|'Add failure times to the data set.}}
	WDS.AddFailure(100, 1)		WDS.AddFailure(100, 1)
	WDS.AddFailure(120, 1)		WDS.AddFailure(120, 1)
	WDS.AddFailure(130, 1)		WDS.AddFailure(130, 1)

	{{APIComment\|'~~Specify that~~ the normal, lognormal and 2-parameter Weibull}}		{{APIComment\|'Consider the normal, lognormal and 2-parameter Weibull distributions in the evaluation.}}
	~~{{APIComment\|'~~distributions ~~will be considered~~.}}		WDS.BestFitSettings.AllowExponential1 = False
	WDS.BestFitSettings.AllowExponential1 = False		WDS.BestFitSettings.AllowExponential2 = False
	WDS.BestFitSettings.AllowExponential2 = False		WDS.BestFitSettings.AllowNormal = True
	WDS.BestFitSettings.AllowNormal = True		WDS.BestFitSettings.AllowLognormal = True
	WDS.BestFitSettings.AllowLognormal = True		WDS.BestFitSettings.AllowWeibull2 = True
	WDS.BestFitSettings.AllowWeibull2 = True		WDS.BestFitSettings.AllowWeibull3 = False
	WDS.BestFitSettings.AllowWeibull3 = False		WDS.BestFitSettings.AllowGamma = False
	WDS.BestFitSettings.AllowGamma = False		WDS.BestFitSettings.AllowGenGamma = False
	WDS.BestFitSettings.AllowGenGamma = False		WDS.BestFitSettings.AllowLogistic = False
	WDS.BestFitSettings.AllowLogistic = False		WDS.BestFitSettings.AllowLoglogistic = False
	WDS.BestFitSettings.AllowLoglogistic = False		WDS.BestFitSettings.AllowGumbel = False
	WDS.BestFitSettings.AllowGumbel = False

	{{APIComment\|'~~Fit~~ the ~~data to the life distribution that is estimated to have the best~~ fit.}}		{{APIComment\|'Perform the goodness of fit tests.}}
	WDS.CalculateBestFit()		WDS.CalculateBestFit()

	{{APIComment\|'Retrieve the fitted life distribution model~~. See [[cModel Class\|cModel]]~~.}}		{{APIComment\|'Retrieve the fitted life distribution model.}}
	Dim model As cModel		{{APIPrefix\|Dim}} model {{APIPrefix\|As}} cModel
	model = WDS.FittedModel		model = WDS.FittedModel

			{{APIComment\|'Using the model, calculate the reliability at 100 hrs and display the result.}}
			{{APIPrefix\|Dim}} r {{APIPrefix\|As}} Double
			r = model.reliability(100)
			MsgBox({{APIString\|"Reliability at 100 hrs: "}} & r)

← Older revision		Revision as of 22:19, 17 June 2016
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	{{APIComment\|'Determine which distribution best fits the data set, based on the MLE method.}}		{{APIComment\|'Determine which distribution best fits the data set, based on the MLE method.}}
	{{APIPrefix\|Call}} WDS.CalculateBestFit()		{{APIPrefix\|Call}} WDS.CalculateBestFit()

	~~{{APIComment\|'Retrieve the fitted life distribution model.}}~~		{{APIComment\|'Calculate the reliability at 100 hrs and display the result.}}
	~~{{APIPrefix\|Dim}} model {{APIPrefix\|As}} cModel~~
	~~{{APIPrefix\|Set}} model = WDS.FittedModel~~

	{{APIComment\|'~~Using the model, calculate~~ the reliability at 100 hrs and display the result.}}
	{{APIPrefix\|Dim}} r {{APIPrefix\|As}} Double		{{APIPrefix\|Dim}} r {{APIPrefix\|As}} Double
	r = ~~model~~.~~reliability~~(100)		r = WDS.FittedModel.Reliability(100)
	MsgBox({{APIString\|"Reliability at 100 hrs: "}} & r)		MsgBox({{APIString\|"Reliability at 100 hrs: "}} & r)

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	{{APIComment\|'Determine which distribution best fits the data set, based on the MLE method.}}		{{APIComment\|'Determine which distribution best fits the data set, based on the MLE method.}}
	WDS.CalculateBestFit()		WDS.CalculateBestFit()

	~~{{APIComment\|'Retrieve the fitted life distribution model.}}~~		{{APIComment\|'Calculate the reliability at 100 hrs and display the result.}}
	~~{{APIPrefix\|Dim}} model {{APIPrefix\|As}} cModel~~
	~~model = WDS.FittedModel~~

	{{APIComment\|'~~Using the model, calculate~~ the reliability at 100 hrs and display the result.}}
	{{APIPrefix\|Dim}} r {{APIPrefix\|As}} Double		{{APIPrefix\|Dim}} r {{APIPrefix\|As}} Double
	r = ~~model~~.~~reliability~~(100)		r = WDS.FittedModel.Reliability(100)
	MsgBox({{APIString\|"Reliability at 100 hrs: "}} & r)		MsgBox({{APIString\|"Reliability at 100 hrs: "}} & r)