WeibullDataSet.CalculateBestFit: Difference between revisions

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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>  


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.  
 
'''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  ==
Line 38: Line 39:
  {{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)


Line 76: Line 73:
  {{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)

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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