conditioning distribution=ComposedDistribution(Uniform(a = 0, b = 1), Uniform(a = 1, b = 2), IndependentCopula(dimension = 2))
Distribution class=PosteriorDistribution name=PosteriorDistribution dimension=2 conditional distribution=class=ConditionalDistribution name=ConditionalDistribution dimension=1 conditioned distribution=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[0] sigma=class=Point name=Unnamed dimension=1 values=[1] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] conditioning distribution=class=ComposedDistribution name=ComposedDistribution dimension=2 copula=class=IndependentCopula name=IndependentCopula dimension=2 marginal[0]=class=Uniform name=Uniform dimension=1 a=0 b=1 marginal[1]=class=Uniform name=Uniform dimension=1 a=1 b=2 link function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[y0,y1,y0,y1] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] observations=class=Sample name=Normal implementation=class=SampleImplementation name=Normal size=5 dimension=1 description=[X0] data=[[1.4123],[-1.39926],[-0.157398],[2.30822],[-2.77208]]
Distribution PosteriorDistribution(conditional distribution = ConditionalDistribution(X with X|Theta~Normal(Theta), Theta=f(Y), f=[y0,y1]->[y0,y1], Y~ComposedDistribution(Uniform(a = 0, b = 1), Uniform(a = 1, b = 2), IndependentCopula(dimension = 2))), observations = 
    [ X0        ]
0 : [  1.4123   ]
1 : [ -1.39926  ]
2 : [ -0.157398 ]
3 : [  2.30822  ]
4 : [ -2.77208  ])
range=class=Interval name=Unnamed dimension=2 lower bound=class=Point name=Unnamed dimension=2 values=[0,1] upper bound=class=Point name=Unnamed dimension=2 values=[1,2] finite lower bound=[1,1] finite upper bound=[1,1]
Mean class=Point name=Unnamed dimension=2 values=[0.366308,1.48584]
Covariance class=CovarianceMatrix dimension=2 implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.0677337,0.0116648,0.0116648,0.0730088]
Elliptical distribution= false
Elliptical copula= false
Independent copula= false
oneRealization=class=Point name=Unnamed dimension=2 values=[0.714382,1.75489]
oneSample=class=Sample name=PosteriorDistribution implementation=class=SampleImplementation name=PosteriorDistribution size=10 dimension=2 description=[X0,X1] data=[[0.373767,1.81486],[0.883503,1.78061],[0.92851,2],[0.684575,2],[0.359802,1.9376],[0.588615,1.49168],[0.085785,1.6759],[0.210442,1.5383],[0.0245595,1.52709],[0.981841,2]]
Zero point= class=Point name=Unnamed dimension=2 values=[0,0] pdf=0 cdf=0
Quantile=class=Point name=Unnamed dimension=2 values=[0.974679,1.97468]
CDF(quantile)=0.95
margin=class=MarginalDistribution name=MarginalDistribution dimension=1 distribution=class=PosteriorDistribution name=PosteriorDistribution dimension=2 conditional distribution=class=ConditionalDistribution name=ConditionalDistribution dimension=1 conditioned distribution=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[0] sigma=class=Point name=Unnamed dimension=1 values=[1] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] conditioning distribution=class=ComposedDistribution name=ComposedDistribution dimension=2 copula=class=IndependentCopula name=IndependentCopula dimension=2 marginal[0]=class=Uniform name=Uniform dimension=1 a=0 b=1 marginal[1]=class=Uniform name=Uniform dimension=1 a=1 b=2 link function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[y0,y1,y0,y1] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] observations=class=Sample name=Normal implementation=class=SampleImplementation name=Normal size=5 dimension=1 description=[X0] data=[[1.4123],[-1.39926],[-0.157398],[2.30822],[-2.77208]] indices=[0]
margin PDF=0.5
margin CDF=0
margin quantile=class=Point name=Unnamed dimension=1 values=[0.95]
margin realization=class=Point name=Unnamed dimension=1 values=[0.955603]
margin=class=MarginalDistribution name=MarginalDistribution dimension=1 distribution=class=PosteriorDistribution name=PosteriorDistribution dimension=2 conditional distribution=class=ConditionalDistribution name=ConditionalDistribution dimension=1 conditioned distribution=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[0] sigma=class=Point name=Unnamed dimension=1 values=[1] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] conditioning distribution=class=ComposedDistribution name=ComposedDistribution dimension=2 copula=class=IndependentCopula name=IndependentCopula dimension=2 marginal[0]=class=Uniform name=Uniform dimension=1 a=0 b=1 marginal[1]=class=Uniform name=Uniform dimension=1 a=1 b=2 link function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[y0,y1,y0,y1] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] observations=class=Sample name=Normal implementation=class=SampleImplementation name=Normal size=5 dimension=1 description=[X0] data=[[1.4123],[-1.39926],[-0.157398],[2.30822],[-2.77208]] indices=[1]
margin PDF=0
margin CDF=0
margin quantile=class=Point name=Unnamed dimension=1 values=[1.95]
margin realization=class=Point name=Unnamed dimension=1 values=[1.72256]
conditioning distribution=ComposedDistribution(Dirac(point = [0]), Uniform(a = 1, b = 2), IndependentCopula(dimension = 2))
Distribution class=PosteriorDistribution name=PosteriorDistribution dimension=2 conditional distribution=class=ConditionalDistribution name=ConditionalDistribution dimension=1 conditioned distribution=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[0] sigma=class=Point name=Unnamed dimension=1 values=[1] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] conditioning distribution=class=ComposedDistribution name=ComposedDistribution dimension=2 copula=class=IndependentCopula name=IndependentCopula dimension=2 marginal[0]=class=Dirac name=Dirac dimension=1 point=class=Point name=Unnamed dimension=1 values=[0] marginal[1]=class=Uniform name=Uniform dimension=1 a=1 b=2 link function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[y0,y1,y0,y1] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] observations=class=Sample name=Normal implementation=class=SampleImplementation name=Normal size=5 dimension=1 description=[X0] data=[[-0.030543],[-1.82832],[0.495255],[4.28437],[-1.55711]]
Distribution PosteriorDistribution(conditional distribution = ConditionalDistribution(X with X|Theta~Normal(Theta), Theta=f(Y), f=[y0,y1]->[y0,y1], Y~ComposedDistribution(Dirac(point = [0]), Uniform(a = 1, b = 2), IndependentCopula(dimension = 2))), observations = 
    [ X0        ]
0 : [ -0.030543 ]
1 : [ -1.82832  ]
2 : [  0.495255 ]
3 : [  4.28437  ]
4 : [ -1.55711  ])
range=class=Interval name=Unnamed dimension=2 lower bound=class=Point name=Unnamed dimension=2 values=[0,1] upper bound=class=Point name=Unnamed dimension=2 values=[0,2] finite lower bound=[1,1] finite upper bound=[1,1]
Mean class=Point name=Unnamed dimension=2 values=[0,1.37194]
Covariance class=CovarianceMatrix dimension=2 implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0,0,0,0.129721]
Elliptical distribution= false
Elliptical copula= false
Independent copula= false
oneRealization=class=Point name=Unnamed dimension=2 values=[0,2]
oneSample=class=Sample name=PosteriorDistribution implementation=class=SampleImplementation name=PosteriorDistribution size=10 dimension=2 description=[X0,X1] data=[[0,2],[0,2],[0,2],[0,2],[0,2],[0,2],[0,2],[0,2],[0,2],[0,2]]
Zero point= class=Point name=Unnamed dimension=2 values=[0,0] pdf=0 cdf=0
Quantile=class=Point name=Unnamed dimension=2 values=[0,1.95]
CDF(quantile)=0.95
margin=class=MarginalDistribution name=MarginalDistribution dimension=1 distribution=class=PosteriorDistribution name=PosteriorDistribution dimension=2 conditional distribution=class=ConditionalDistribution name=ConditionalDistribution dimension=1 conditioned distribution=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[0] sigma=class=Point name=Unnamed dimension=1 values=[1] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] conditioning distribution=class=ComposedDistribution name=ComposedDistribution dimension=2 copula=class=IndependentCopula name=IndependentCopula dimension=2 marginal[0]=class=Dirac name=Dirac dimension=1 point=class=Point name=Unnamed dimension=1 values=[0] marginal[1]=class=Uniform name=Uniform dimension=1 a=1 b=2 link function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[y0,y1,y0,y1] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] observations=class=Sample name=Normal implementation=class=SampleImplementation name=Normal size=5 dimension=1 description=[X0] data=[[-0.030543],[-1.82832],[0.495255],[4.28437],[-1.55711]] indices=[0]
margin PDF=23207.9
margin CDF=1
margin quantile=class=Point name=Unnamed dimension=1 values=[0]
margin realization=class=Point name=Unnamed dimension=1 values=[0]
margin=class=MarginalDistribution name=MarginalDistribution dimension=1 distribution=class=PosteriorDistribution name=PosteriorDistribution dimension=2 conditional distribution=class=ConditionalDistribution name=ConditionalDistribution dimension=1 conditioned distribution=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[0] sigma=class=Point name=Unnamed dimension=1 values=[1] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] conditioning distribution=class=ComposedDistribution name=ComposedDistribution dimension=2 copula=class=IndependentCopula name=IndependentCopula dimension=2 marginal[0]=class=Dirac name=Dirac dimension=1 point=class=Point name=Unnamed dimension=1 values=[0] marginal[1]=class=Uniform name=Uniform dimension=1 a=1 b=2 link function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[y0,y1,y0,y1] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1] outputVariablesNames=[y0,y1] formulas=[y0,y1] observations=class=Sample name=Normal implementation=class=SampleImplementation name=Normal size=5 dimension=1 description=[X0] data=[[-0.030543],[-1.82832],[0.495255],[4.28437],[-1.55711]] indices=[1]
margin PDF=0
margin CDF=0
margin quantile=class=Point name=Unnamed dimension=1 values=[1.95]
margin realization=class=Point name=Unnamed dimension=1 values=[2]
