dist1:class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]
dist1+2:class=RandomMixture name=RandomMixture distribution collection=[class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[3] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] constant=class=Point name=Unnamed dimension=1 values=[0]
dist1-2:class=RandomMixture name=RandomMixture distribution collection=[class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[-1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] constant=class=Point name=Unnamed dimension=1 values=[0]
dist1*2:class=RandomMixture name=RandomMixture distribution collection=[class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[2] 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]] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] constant=class=Point name=Unnamed dimension=1 values=[0]
dist1/2:class=RandomMixture name=RandomMixture distribution collection=[class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[0.5] sigma=class=Point name=Unnamed dimension=1 values=[0.25] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] constant=class=Point name=Unnamed dimension=1 values=[0]
cos(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[cos(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[cos(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[cos(x)] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=4 values=[-2.82531,0,3.14159,4.82531] values=class=Point name=Unnamed dimension=4 values=[-0.950399,1,-1,0.112685] probabilities=class=Point name=Unnamed dimension=4 values=[1e-14,0.0227501,0.999991,1] increasing=[1,0,1]
sin(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[sin(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[sin(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[sin(x)] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=5 values=[-2.82531,-1.5708,1.5708,4.71239,4.82531] values=class=Point name=Unnamed dimension=5 values=[-0.311032,-1,1,-1,-0.993631] probabilities=class=Point name=Unnamed dimension=5 values=[1e-14,1.3621e-07,0.873188,1,1] increasing=[0,1,0,1]
tan(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[tan(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[tan(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[tan(x)] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=8 values=[-2.82531,-1.5708,-1.5708,1.5708,1.5708,4.71239,4.71239,4.82531] values=class=Point name=Unnamed dimension=8 values=[0.327264,4.15834e+11,-4.15834e+11,4.15834e+11,-4.15834e+11,4.15834e+11,-4.15834e+11,-8.81776] probabilities=class=Point name=Unnamed dimension=8 values=[1e-14,1.3621e-07,1.3621e-07,0.873188,0.873188,1,1,1] increasing=[1,0,1,0,1,0,1]
acos(dist0):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[acos(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[acos(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[acos(x)] antecedent=class=Uniform name=Uniform dimension=1 a=-1 b=1 bounds=class=Point name=Unnamed dimension=2 values=[-1,1] values=class=Point name=Unnamed dimension=2 values=[3.14159,0] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[0]
asin(dist0):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[asin(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[asin(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[asin(x)] antecedent=class=Uniform name=Uniform dimension=1 a=-1 b=1 bounds=class=Point name=Unnamed dimension=2 values=[-1,1] values=class=Point name=Unnamed dimension=2 values=[-1.5708,1.5708] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
atan(dist0):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[atan(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[atan(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[atan(x)] antecedent=class=Uniform name=Uniform dimension=1 a=-1 b=1 bounds=class=Point name=Unnamed dimension=2 values=[-1,1] values=class=Point name=Unnamed dimension=2 values=[-0.785398,0.785398] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
cosh(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[cosh(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[cosh(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[cosh(x)] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=3 values=[-2.82531,0,4.82531] values=class=Point name=Unnamed dimension=3 values=[8.46277,1,62.3168] probabilities=class=Point name=Unnamed dimension=3 values=[1e-14,0.0227501,1] increasing=[0,1]
sinh(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[sinh(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[sinh(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[sinh(x)] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=2 values=[-2.82531,4.82531] values=class=Point name=Unnamed dimension=2 values=[-8.40348,62.3088] probabilities=class=Point name=Unnamed dimension=2 values=[1e-14,1] increasing=[1]
tanh(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[tanh(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[tanh(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[tanh(x)] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=2 values=[-2.82531,4.82531] values=class=Point name=Unnamed dimension=2 values=[-0.992994,0.999871] probabilities=class=Point name=Unnamed dimension=2 values=[1e-14,1] increasing=[1]
acosh(distG1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[acosh(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[acosh(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[acosh(x)] antecedent=class=LogNormal name=LogNormal dimension=1 muLog=1 sigmaLog=1 gamma=1 bounds=class=Point name=Unnamed dimension=2 values=[1,5714.73] values=class=Point name=Unnamed dimension=2 values=[0,9.34395] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
asinh(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[asinh(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[asinh(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[asinh(x)] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=2 values=[-2.82531,4.82531] values=class=Point name=Unnamed dimension=2 values=[-1.76171,2.27759] probabilities=class=Point name=Unnamed dimension=2 values=[1e-14,1] increasing=[1]
atanh(dist0):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[atanh(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[atanh(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[atanh(x)] antecedent=class=Uniform name=Uniform dimension=1 a=-1 b=1 bounds=class=Point name=Unnamed dimension=2 values=[-1,1] values=class=Point name=Unnamed dimension=2 values=[-13.8155,13.8155] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
exp(dist1):class=LogNormal name=LogNormal dimension=1 muLog=1 sigmaLog=0.5 gamma=0
log(distG1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[log(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[log(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[log(x)] antecedent=class=LogNormal name=LogNormal dimension=1 muLog=1 sigmaLog=1 gamma=1 bounds=class=Point name=Unnamed dimension=2 values=[1,5714.73] values=class=Point name=Unnamed dimension=2 values=[0,8.6508] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
ln(distG1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[log(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[log(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[log(x)] antecedent=class=LogNormal name=LogNormal dimension=1 muLog=1 sigmaLog=1 gamma=1 bounds=class=Point name=Unnamed dimension=2 values=[1,5714.73] values=class=Point name=Unnamed dimension=2 values=[0,8.6508] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
dist1^3:class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[x^3] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[x^3] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[x^3] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=2 values=[-2.82531,4.82531] values=class=Point name=Unnamed dimension=2 values=[-22.5528,112.351] probabilities=class=Point name=Unnamed dimension=2 values=[1e-14,1] increasing=[1]
dist1^2.5:class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[x^2.5] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[x^2.5] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[x^2.5] antecedent=class=LogNormal name=LogNormal dimension=1 muLog=1 sigmaLog=1 gamma=1 bounds=class=Point name=Unnamed dimension=2 values=[1,5714.73] values=class=Point name=Unnamed dimension=2 values=[1,2.46882e+09] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
inverse(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[1.0 / x] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[1.0 / x] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[1.0 / x] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=4 values=[-2.83,0,0,4.83] values=class=Point name=Unnamed dimension=4 values=[0,-1.08e+11,1.08e+11,0] probabilities=class=Point name=Unnamed dimension=4 values=[1e-14,0.0228,0.0228,1] increasing=[0,1,0]
sqr(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[x^2] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[x^2] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[x^2] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=3 values=[-2.82531,0,4.82531] values=class=Point name=Unnamed dimension=3 values=[7.9824,0,23.2837] probabilities=class=Point name=Unnamed dimension=3 values=[1e-14,0.0227501,1] increasing=[0,1]
sqrt(distG1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[sqrt(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[sqrt(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[sqrt(x)] antecedent=class=LogNormal name=LogNormal dimension=1 muLog=1 sigmaLog=1 gamma=1 bounds=class=Point name=Unnamed dimension=2 values=[1,5714.73] values=class=Point name=Unnamed dimension=2 values=[1,75.5959] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
cbrt(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[cbrt(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[cbrt(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[cbrt(x)] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=2 values=[-2.82531,4.82531] values=class=Point name=Unnamed dimension=2 values=[-1.41369,1.68983] probabilities=class=Point name=Unnamed dimension=2 values=[1e-14,1] increasing=[1]
abs(dist1):class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[abs(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[abs(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[abs(x)] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] bounds=class=Point name=Unnamed dimension=3 values=[-2.82531,0,4.82531] values=class=Point name=Unnamed dimension=3 values=[2.82531,0,4.82531] probabilities=class=Point name=Unnamed dimension=3 values=[1e-14,0.0227501,1] increasing=[0,1]
dist1+dist2:class=RandomMixture name=RandomMixture distribution collection=[class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[-1] sigma=class=Point name=Unnamed dimension=1 values=[1.11803] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] constant=class=Point name=Unnamed dimension=1 values=[0]
dist1-dist2:class=RandomMixture name=RandomMixture distribution collection=[class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[3] sigma=class=Point name=Unnamed dimension=1 values=[1.11803] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] constant=class=Point name=Unnamed dimension=1 values=[0]
dist1*dist2:class=ProductDistribution name=ProductDistribution left=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] right=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[-2] 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]
dist1/dist2:class=ProductDistribution name=ProductDistribution left=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[1] sigma=class=Point name=Unnamed dimension=1 values=[0.5] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] right=class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[1.0 / x] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[1.0 / x] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[1.0 / x] antecedent=class=Normal name=Normal dimension=1 mean=class=Point name=Unnamed dimension=1 values=[-2] 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] bounds=class=Point name=Unnamed dimension=4 values=[-9.65,0,0,5.65] values=class=Point name=Unnamed dimension=4 values=[0,-5.4e+10,5.4e+10,0] probabilities=class=Point name=Unnamed dimension=4 values=[1e-14,0.977,0.977,1] increasing=[0,1,0]
logn*logn:class=LogNormal name=LogNormal dimension=1 muLog=0 sigmaLog=1.41421 gamma=0
logu*logu:class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[exp(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[exp(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[exp(x)] antecedent=class=RandomMixture name=RandomMixture distribution collection=[class=Triangular name=Triangular dimension=1 a=-2 m=0 b=2] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1] constant=class=Point name=Unnamed dimension=1 values=[0] bounds=class=Point name=Unnamed dimension=2 values=[-2,2] values=class=Point name=Unnamed dimension=2 values=[0.135335,7.38906] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
logu*logn:class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[exp(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[exp(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[exp(x)] antecedent=class=RandomMixture name=RandomMixture distribution collection=[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],class=Uniform name=Uniform dimension=1 a=-1 b=1] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=2 values=[1,1] constant=class=Point name=Unnamed dimension=1 values=[0] bounds=class=Point name=Unnamed dimension=2 values=[-8.65063,8.65063] values=class=Point name=Unnamed dimension=2 values=[0.000175017,5713.73] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
logn*logu:class=CompositeDistribution name=CompositeDistribution function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[exp(x)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[exp(x)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[exp(x)] antecedent=class=RandomMixture name=RandomMixture distribution collection=[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],class=Uniform name=Uniform dimension=1 a=-1 b=1] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=2 values=[1,1] constant=class=Point name=Unnamed dimension=1 values=[0] bounds=class=Point name=Unnamed dimension=2 values=[-8.65063,8.65063] values=class=Point name=Unnamed dimension=2 values=[0.000175017,5713.73] probabilities=class=Point name=Unnamed dimension=2 values=[0,1] increasing=[1]
result=class=RandomMixture name=RandomMixture distribution collection=[class=Weibull name=Weibull dimension=1 alpha=1 beta=1 gamma=0,class=Exponential name=Exponential dimension=1 lambda=1 gamma=0] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=2 values=[1,1] constant=class=Point name=Unnamed dimension=1 values=[0]
cdf(1.0)=0.264241
result=class=RandomMixture name=RandomMixture distribution collection=[class=Weibull name=Weibull dimension=1 alpha=1 beta=1 gamma=0,class=Exponential name=Exponential dimension=1 lambda=1 gamma=0] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=2 values=[-1,1] constant=class=Point name=Unnamed dimension=1 values=[0]
cdf(1.0)=0.81606
result=class=RandomMixture name=RandomMixture distribution collection=[class=Weibull name=Weibull dimension=1 alpha=1 beta=1 gamma=0,class=Exponential name=Exponential dimension=1 lambda=1 gamma=0] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=2 values=[1,-1] constant=class=Point name=Unnamed dimension=1 values=[0]
cdf(1.0)=0.81606
result=class=RandomMixture name=RandomMixture distribution collection=[class=Weibull name=Weibull dimension=1 alpha=1 beta=1 gamma=0,class=Exponential name=Exponential dimension=1 lambda=1 gamma=0] weights =class=Matrix implementation=class=MatrixImplementation name=Unnamed rows=1 columns=2 values=[-1,-1] constant=class=Point name=Unnamed dimension=1 values=[0]
cdf(-1.0)=0.735759
