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class=DataModel name=myDataModel fileName=data2.csv inputColumns=[0,2,3] outputColumns=[] inputNames=[X0,X2,X3] outputNames=[]
class=CopulaInferenceAnalysis name=analysis designOfExperiment=myDataModel interestVariables=[] setOfVariables [X0,X3] distributionFactories=[NormalCopulaFactory,GumbelCopulaFactory]
result= class=CopulaInferenceResult copulaInferenceSetResultCollection=[class=CopulaInferenceSetResult setOfVariablesNames=[X0,X3] testedDistributions=[NormalCopula(R = [[ 1 0.0580361 ]
[ 0.0580361 1 ]]),GumbelCopula(theta = 1.03839)] BIC results=class=Point name=Unnamed dimension=2 values=[0.0177483,0.0207956] error messages=[,]]
class=CopulaInferenceSetResult setOfVariablesNames=[X0,X3] testedDistributions=[NormalCopula(R = [[ 1 0.0580361 ]
[ 0.0580361 1 ]]),GumbelCopula(theta = 1.03839)] BIC results=class=Point name=Unnamed dimension=2 values=[0.0177483,0.0207956] error messages=[,]
#!/usr/bin/env python
import openturns as ot
import persalys
myStudy = persalys.Study('myStudy')
persalys.Study.Add(myStudy)
inputColumns = [0, 2, 3]
outputColumns = []
inputNames = ['X0', 'X2', 'X3']
outputNames = []
myDataModel = persalys.DataModel('myDataModel', 'data2.csv', inputColumns, outputColumns, inputNames, outputNames)
myStudy.add(myDataModel)
analysis = persalys.CopulaInferenceAnalysis('analysis', myDataModel)
variablesSet = ['X0', 'X3']
factories = [ot.NormalCopulaFactory(), ot.GumbelCopulaFactory()]
analysis.setDistributionsFactories(variablesSet, factories)
myStudy.add(analysis)
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