WeibullDataSet.CalculateBestFit: Difference between revisions

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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.


==Syntax==
*{{APIName|'''CalculateBestFit'''()}}<br>


== Usage Example ==
<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>


{{APIComment|Declare the WeibullDataSet. See [[New WeibullDataSet]] for additional details.}}
        Dim WDS as New WeibullDataSet


{{APIComment|Add values to the raw data. See [[WeibullDataSet.AddFailure]] for additional details.}}
'''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.
        WDS.AddFailure(1, 1)
        WDS.AddFailure(2, 1)
        WDS.AddFailure(3, 1)


{{APIComment|Calculate the Fitted Model using the raw data.}}
== Syntax  ==
        WDS.CalculateBestFit
'''.CalculateBestFit


{{APIComment|Use the Fitted Model using the raw data.}}
== Example ==
        Dim WDSFittedModel as cModel
'''VBA'''
        WDSFittedModel = WDS.FittedModel
{{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|'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()
 
{{APIComment|'Calculate the reliability at 100 hrs and display the result.}}
  {{APIPrefix|Dim}} r {{APIPrefix|As}} Double
  r = WDS.FittedModel.Reliability(100)
  MsgBox({{APIString|"Reliability at 100 hrs: "}} & r)
 
'''VB.NET'''
{{APIComment|'Declare a new WeibullDataSet object.}}
  {{APIPrefix|Dim}} WDS {{APIPrefix|As New}} WeibullDataSet
{{APIComment|'Add failure times to the data set.}}
  WDS.AddFailure(100, 1)
  WDS.AddFailure(120, 1)
  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|'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.}}
  WDS.CalculateBestFit()
 
{{APIComment|'Calculate the reliability at 100 hrs and display the result.}}
  {{APIPrefix|Dim}} r {{APIPrefix|As}} Double
  r = WDS.FittedModel.Reliability(100)
  MsgBox({{APIString|"Reliability at 100 hrs: "}} & r)

Latest revision as of 16:07, 17 August 2016

APIWiki.png


Member of: SynthesisAPI.WeibullDataSet


Determines which of the selected life distributions best fits the data set (similar to the Distribution Wizard feature in Weibull++) and creates a cModel object that represents the fitted model of the recommended distribution.


Remarks: To specify the distributions, parameter estimation method and other criteria for evaluating the fit, use the BestFitSettings property of the object. To return the cModel object that is produced, use the FittedModel property of the object.

Syntax

.CalculateBestFit

Example

VBA

 'Declare a new WeibullDataSet object.  
  Dim WDS As New WeibullDataSet

 'Add failure times to the data set. 
  Call WDS.AddFailure(100, 1)
  Call WDS.AddFailure(120, 1)
  Call WDS.AddFailure(130, 1)  
 
 '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
 
 'Use the MLE parameter estimation method. 
  WDS.BestFitSettings.Analysis = WeibullSolverMethod_MLE

 'Determine which distribution best fits the data set, based on the MLE method. 
  Call WDS.CalculateBestFit()
  
 'Calculate the reliability at 100 hrs and display the result. 
  Dim r As Double
  r = WDS.FittedModel.Reliability(100)
  MsgBox("Reliability at 100 hrs: " & r)

VB.NET

 'Declare a new WeibullDataSet object.  
  Dim WDS As New WeibullDataSet

 'Add failure times to the data set. 
  WDS.AddFailure(100, 1)
  WDS.AddFailure(120, 1)
  WDS.AddFailure(130, 1)  
 
 '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

 'Use the MLE parameter estimation method. 
  WDS.BestFitSettings.Analysis = WeibullSolverMethod.MLE
 
 'Determine which distribution best fits the data set, based on the MLE method. 
  WDS.CalculateBestFit()
  
 'Calculate the reliability at 100 hrs and display the result. 
  Dim r As Double
  r = WDS.FittedModel.Reliability(100)
  MsgBox("Reliability at 100 hrs: " & r)
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