distribution=class=ConditionalDistribution name=ConditionalDistribution dimension=2 conditioned distribution=class=ComposedDistribution name=ComposedDistribution dimension=2 copula=class=IndependentCopula name=IndependentCopula dimension=2 marginal[0]=class=Uniform name=Uniform dimension=1 a=-1 b=1 marginal[1]=class=Uniform name=Uniform dimension=1 a=-1 b=1 conditioning distribution=class=ComposedDistribution name=ComposedDistribution dimension=4 copula=class=IndependentCopula name=IndependentCopula dimension=4 marginal[0]=class=Dirac name=Dirac dimension=1 point=class=Point name=Unnamed dimension=1 values=[1] marginal[1]=class=Dirac name=Dirac dimension=1 point=class=Point name=Unnamed dimension=1 values=[2] marginal[2]=class=Bernoulli name=Bernoulli dimension=1 p=0.7 marginal[3]=class=Uniform name=Uniform dimension=1 a=3 b=4 link function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[y0,y1,y2,y3,y0,y1,y2,y3] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1,y2,y3] outputVariablesNames=[y0,y1,y2,y3] formulas=[y0,y1,y2,y3] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1,y2,y3] outputVariablesNames=[y0,y1,y2,y3] formulas=[y0,y1,y2,y3] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[y0,y1,y2,y3] outputVariablesNames=[y0,y1,y2,y3] formulas=[y0,y1,y2,y3]
Parameters [[point_0_marginal_0 : 1],[point_0_marginal_1 : 2],[p_marginal_2 : 0.7],[a_marginal_3 : 3, b_marginal_3 : 4],[]]
Mean class=Point name=Unnamed dimension=2 values=[1.5,2.1]
Covariance class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.0833333,0,0,0.751111]
Elliptical distribution= false
Elliptical copula= false
Independent copula= false
oneRealization=class=Point name=Unnamed dimension=2 values=[1.13528,1.0937]
oneSample=class=Sample name=ConditionalDistribution implementation=class=SampleImplementation name=ConditionalDistribution size=10 dimension=2 description=[X0,X1] data=[[1.92068,2.49374],[1.71438,1.87896],[1.8835,1.80748],[1.68457,3.16374],[1.58862,1.53788],[1.21044,2.02765],[1.98184,3.21605],[1.25986,2.2968],[1.11108,1.85243],[1.97898,2.729]]
anotherSample mean=class=Point name=Unnamed dimension=2 values=[1.50538,2.09375]
anotherSample covariance=class=CovarianceMatrix dimension=2 implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.0847776,-0.000929088,-0.000929088,0.74965]
Zero point= class=Point name=Unnamed dimension=2 values=[0,0] pdf=0 cdf=0
Quantile=class=Point name=Unnamed dimension=2 values=[1.97468,3.60341]
CDF(quantile)=0.95
conditioning distribution=ComposedDistribution(Uniform(a = 0, b = 1), Uniform(a = 1, b = 2), IndependentCopula(dimension = 2))
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]
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)))
Parameters [[a_marginal_0 : 0, b_marginal_0 : 1],[a_marginal_1 : 1, b_marginal_1 : 2],[]]
Mean class=Point name=Unnamed dimension=1 values=[0.5]
Covariance class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[2.41667]
Elliptical distribution= false
Elliptical copula= true
Independent copula= true
oneRealization=class=Point name=Unnamed dimension=1 values=[-0.21251]
oneSample=class=Sample name=ConditionalDistribution implementation=class=SampleImplementation name=ConditionalDistribution size=10 dimension=1 description=[X0] data=[[1.04021],[-0.768799],[-0.0327311],[1.95381],[1.43698],[1.31895],[2.05226],[-1.44045],[2.03224],[0.258808]]
anotherSample mean=class=Point name=Unnamed dimension=1 values=[0.503649]
anotherSample covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[2.41134]
Zero point= class=Point name=Unnamed dimension=1 values=[0] pdf=0.253748 cdf=0.367604
Quantile=class=Point name=Unnamed dimension=1 values=[3.05046]
CDF(quantile)=0.95
margin=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]
margin PDF=0.253748
margin CDF=0.367604
margin quantile=class=Point name=Unnamed dimension=1 values=[3.05046]
margin realization=class=Point name=Unnamed dimension=1 values=[0.141979]
conditioning distribution=ComposedDistribution(Binomial(n = 3, p = 0.5), Uniform(a = 1, b = 2), IndependentCopula(dimension = 2))
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=Binomial name=Binomial dimension=1 n=3 p=0.5 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]
Distribution ConditionalDistribution(X with X|Theta~Normal(Theta), Theta=f(Y), f=[y0,y1]->[y0,y1], Y~ComposedDistribution(Binomial(n = 3, p = 0.5), Uniform(a = 1, b = 2), IndependentCopula(dimension = 2)))
Parameters [[n_marginal_0 : 3, p_marginal_0 : 0.5],[a_marginal_1 : 1, b_marginal_1 : 2],[]]
Mean class=Point name=Unnamed dimension=1 values=[1.5]
Covariance class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[3.08333]
Elliptical distribution= false
Elliptical copula= true
Independent copula= true
oneRealization=class=Point name=Unnamed dimension=1 values=[0.106685]
oneSample=class=Sample name=ConditionalDistribution implementation=class=SampleImplementation name=ConditionalDistribution size=10 dimension=1 description=[X0] data=[[1.52532],[3.2931],[4.70326],[2.99546],[5.81408],[2.47839],[3.09905],[4.94457],[-0.310612],[0.910042]]
anotherSample mean=class=Point name=Unnamed dimension=1 values=[1.49603]
anotherSample covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[3.16539]
Zero point= class=Point name=Unnamed dimension=1 values=[0] pdf=0.156744 cdf=0.192205
Quantile=class=Point name=Unnamed dimension=1 values=[4.38019]
CDF(quantile)=0.95
margin=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=Binomial name=Binomial dimension=1 n=3 p=0.5 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]
margin PDF=0.156744
margin CDF=0.192205
margin quantile=class=Point name=Unnamed dimension=1 values=[4.38019]
margin realization=class=Point name=Unnamed dimension=1 values=[0.843042]
conditioning distribution=ComposedDistribution(Dirac(point = [0]), Uniform(a = 1, b = 2), IndependentCopula(dimension = 2))
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]
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)))
Parameters [[point_0_marginal_0 : 0],[a_marginal_1 : 1, b_marginal_1 : 2],[]]
Mean class=Point name=Unnamed dimension=1 values=[0]
Covariance class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[2.33333]
Elliptical distribution= false
Elliptical copula= true
Independent copula= true
oneRealization=class=Point name=Unnamed dimension=1 values=[0.190984]
oneSample=class=Sample name=ConditionalDistribution implementation=class=SampleImplementation name=ConditionalDistribution size=10 dimension=1 description=[X0] data=[[-0.217096],[-1.35136],[-1.30765],[0.789252],[1.43663],[0.580832],[-1.41361],[0.000383335],[-0.00807902],[-1.82229]]
anotherSample mean=class=Point name=Unnamed dimension=1 values=[0.0285016]
anotherSample covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[2.34231]
Zero point= class=Point name=Unnamed dimension=1 values=[0] pdf=0.276526 cdf=0.5
Quantile=class=Point name=Unnamed dimension=1 values=[2.50635]
CDF(quantile)=0.95
margin=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]
margin PDF=0.276526
margin CDF=0.5
margin quantile=class=Point name=Unnamed dimension=1 values=[2.50635]
margin realization=class=Point name=Unnamed dimension=1 values=[-0.479683]
