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Point= class=Point name=Unnamed dimension=7 values=[0.3,0.3,0.3,0.3,0.3,0.3,0.3]
ddf =class=Point name=Unnamed dimension=7 values=[-0.000319153,-0.000319153,-0.000370522,-0.000346163,-0.000389754,-0.000368254,-0.000368254]
ddf (ref)=class=Point name=Unnamed dimension=7 values=[-0.000319153,-0.000319153,-0.000370522,-0.000346163,-0.000389754,-0.000368254,-0.000368254]
pdf =0.00159577
pdf (ref)=0.00159577
cdf =0.0540595
cdf (ref)=0.0540595
Survival =0.00349838
Survival (ref)=0.00349838
Inverse survival =class=Point name=Unnamed dimension=7 values=[-2.43216,-2.43216,-2.43216,-2.43216,-2.43216,-2.43216,-2.43216]
Inverse survival (ref)=class=Point name=Unnamed dimension=7 values=[-2.43216,-2.43216,-2.43216,-2.43216,-2.43216,-2.43216,-2.43216]
Survival(inverse survival)=0.95
Quantile =class=Point name=Unnamed dimension=7 values=[1.26874,1.26874,1.26874,1.26874,1.26874,1.26874,1.26874]
Quantile (ref)=class=Point name=Unnamed dimension=7 values=[1.26874,1.26874,1.26874,1.26874,1.26874,1.26874,1.26874]
CDF(quantile)=0.5
Distribution class=BlockIndependentDistribution name=BlockIndependentDistribution dimension=7 distribution[0]=class=JointDistribution name=JointDistribution dimension=2 copula=class=AliMikhailHaqCopula name=AliMikhailHaqCopula dimension=2 theta=0.5 marginal[0]=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] marginal[1]=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] distribution[1]=class=Normal name=Normal dimension=3 mean=class=Point name=Unnamed dimension=3 values=[1,1,1] sigma=class=Point name=Unnamed dimension=3 values=[2,2,2] correlationMatrix=class=CorrelationMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1,0.5,0.25,0.5,1,0,0.25,0,1] distribution[2]=class=JointDistribution name=JointDistribution dimension=2 copula=class=FrankCopula name=FrankCopula dimension=2 theta=0.5 marginal[0]=class=Exponential name=Exponential dimension=1 lambda=1 gamma=0 marginal[1]=class=Exponential name=Exponential dimension=1 lambda=1 gamma=0
Distribution BlockIndependentDistribution(JointDistribution(Normal(mu = 0, sigma = 1), Normal(mu = 0, sigma = 1), AliMikhailHaqCopula(theta = 0.5)), Normal(mu = [1,1,1], sigma = [2,2,2], R = [[ 1 0.5 0.25 ]
[ 0.5 1 0 ]
[ 0.25 0 1 ]]), JointDistribution(Exponential(lambda = 1, gamma = 0), Exponential(lambda = 1, gamma = 0), FrankCopula(theta = 0.5)))
Elliptical distribution= false
Continuous = true
Elliptical = false
Independent = false
oneRealization=class=Point name=Unnamed dimension=7 values=[0.331526,1.25776,-1.53235,-1.02527,2.80174,0.065292,0.288526]
oneSample first=class=Point name=Unnamed dimension=7 values=[0.566232,-0.12788,0.289986,3.13438,1.95991,1.15383,1.83149] last=class=Point name=Unnamed dimension=7 values=[0.81246,-0.486535,-0.92893,-0.796484,-2.04345,0.0598465,0.191726]
mean=class=Point name=Unnamed dimension=7 values=[0.000343667,-0.000446093,0.993879,1.0073,1.00388,1.00092,1.00104]
covariance=class=CovarianceMatrix dimension=7 implementation=class=MatrixImplementation name=Unnamed rows=7 columns=7 values=[1.03,0.2051,-0.03965,-0.02592,-0.01009,0.01133,0.00288,0.2051,1.002,-0.03296,-0.00766,0.0216,0.01271,0.004583,-0.03965,-0.03296,4.004,2.014,1.019,0.01587,-0.003804,-0.02592,-0.00766,2.014,3.967,-0.00237,-0.02184,-0.003111,-0.01009,0.0216,1.019,-0.00237,4.137,0.002132,-0.01288,0.01133,0.01271,0.01587,-0.02184,0.002132,1.002,0.07562,0.00288,0.004583,-0.003804,-0.003111,-0.01288,0.07562,1.007]
Point= class=Point name=Unnamed dimension=7 values=[0.3,0.3,0.3,0.3,0.3,0.3,0.3]
ddf =class=Point name=Unnamed dimension=7 values=[-0.000161544,-0.000161544,4.80573e-05,0.000108129,0.000120143,-0.000877177,-0.000877177]
ddf (FD)=class=Point name=Unnamed dimension=7 values=[-0.000161544,-0.000161544,4.80573e-05,0.000108129,0.000120143,-0.000877177,-0.000877177]
pdf =0.000755186
cdf=0.00284149
Survival =0.0321913
Survival (ref)=0.0321913
Inverse survival=class=Point name=Unnamed dimension=7 values=[-2.4345,-2.4345,-3.869,-3.869,-3.869,0.0074841,0.0074841]
Survival(inverse survival)=0.95
Quantile=class=Point name=Unnamed dimension=7 values=[1.28123,1.28123,3.56246,3.56246,3.56246,2.30202,2.30202]
CDF(quantile)=0.5
entropy=10.964
entropy (MC)=10.9656
covariance=class=CovarianceMatrix dimension=7 implementation=class=MatrixImplementation name=Unnamed rows=7 columns=7 values=[1,0.184,0,0,0,0,0,0.184,1,0,0,0,0,0,0,0,4,2,1,0,0,0,0,2,4,0,0,0,0,0,1,0,4,0,0,0,0,0,0,0,1,0.06227,0,0,0,0,0,0.06227,1]
correlation=class=CorrelationMatrix dimension=7 implementation=class=MatrixImplementation name=Unnamed rows=7 columns=7 values=[1,0.184,0,0,0,0,0,0.184,1,0,0,0,0,0,0,0,1,0.5,0.25,0,0,0,0,0.5,1,0,0,0,0,0,0.25,0,1,0,0,0,0,0,0,0,1,0.06227,0,0,0,0,0,0.06227,1]
spearman=class=CorrelationMatrix dimension=7 implementation=class=MatrixImplementation name=Unnamed rows=7 columns=7 values=[1,0.1924,0,0,0,0,0,0.1924,1,0,0,0,0,0,0,0,1,0.4826,0.2394,0,0,0,0,0.4826,1,0,0,0,0,0,0.2394,0,1,0,0,0,0,0,0,0,1,0.08306,0,0,0,0,0,0.08306,1]
kendall=class=CorrelationMatrix dimension=7 implementation=class=MatrixImplementation name=Unnamed rows=7 columns=7 values=[1,0.1288,0,0,0,0,0,0.1288,1,0,0,0,0,0,0,0,1,0.3333,0.1609,0,0,0,0,0.3333,1,0,0,0,0,0,0.1609,0,1,0,0,0,0,0,0,0,1,0.05542,0,0,0,0,0,0.05542,1]
conditional PDF=0.556752
conditional CDF=0.490621
conditional quantile=0.823038
sequential conditional PDF=class=Point name=Unnamed dimension=7 values=[0.398444,0.407104,0.185928,0.227445,0.203657,0.57695,0.525447]
sequential conditional CDF(class=Point name=Unnamed dimension=7 values=[0.05,0.15,0.25,0.35,0.45,0.55,0.65])=class=Point name=Unnamed dimension=7 values=[0.519939,0.545655,0.35383,0.436925,0.415568,0.42305,0.487447]
sequential conditional quantile(class=Point name=Unnamed dimension=7 values=[0.519939,0.545655,0.35383,0.436925,0.415568,0.42305,0.487447])=class=Point name=Unnamed dimension=7 values=[0.05,0.15,0.25,0.35,0.45,0.55,0.65]
indices=[1,2,3,5,6]
margins=class=BlockIndependentDistribution name=BlockIndependentDistribution dimension=5 distribution[0]=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] distribution[1]=class=Normal name=Normal dimension=2 mean=class=Point name=Unnamed dimension=2 values=[1,1] sigma=class=Point name=Unnamed dimension=2 values=[2,2] correlationMatrix=class=CorrelationMatrix dimension=2 implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[1,0.5,0.5,1] distribution[2]=class=JointDistribution name=JointDistribution dimension=2 copula=class=FrankCopula name=FrankCopula dimension=2 theta=0.5 marginal[0]=class=Exponential name=Exponential dimension=1 lambda=1 gamma=0 marginal[1]=class=Exponential name=Exponential dimension=1 lambda=1 gamma=0
margins PDF=0.0105741
margins CDF=0.00675333
margins quantile=class=Point name=Unnamed dimension=5 values=[2.30912,5.61824,5.61824,4.55939,4.55939]
margins CDF(quantile)=0.95
margins realization=class=Point name=Unnamed dimension=5 values=[-0.866905,0.766798,0.522253,0.432364,3.37405]
isoprobabilistic transformation (general normal)=[((RosenblattEvaluation(AliMikhailHaqCopula(theta = 0.5)->Normal(2))o(| y0 = Normal(mu = 0, sigma = 1) -> y0 : Uniform(a = 0, b = 1)
| y1 = Normal(mu = 0, sigma = 1) -> y1 : Uniform(a = 0, b = 1)
))o([x0,x1,x2,x3,x4,x5,x6]->[x0,x1]),(RosenblattEvaluation(Normal(mu = [1,1,1], sigma = [2,2,2], R = [[ 1 0.5 0.25 ]
[ 0.5 1 0 ]
[ 0.25 0 1 ]])->Normal(3))o([x0,x1,x2,x3,x4,x5,x6]->[x2,x3,x4]),((RosenblattEvaluation(FrankCopula(theta = 0.5)->Normal(2))o(| y0 = Exponential(lambda = 1, gamma = 0) -> y0 : Uniform(a = 0, b = 1)
| y1 = Exponential(lambda = 1, gamma = 0) -> y1 : Uniform(a = 0, b = 1)
))o([x0,x1,x2,x3,x4,x5,x6]->[x5,x6])]
isoprobabilistic transformation (general non-normal)=[(RosenblattEvaluation(class=SklarCopula name=SklarCopula dimension=2 distribution=class=Student name=Student dimension=2 nu=3 mean=class=Point name=Unnamed dimension=2 values=[1,1] sigma=class=Point name=Unnamed dimension=2 values=[3,3] correlationMatrix=class=CorrelationMatrix dimension=2 implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[1,0,0,1]->Normal(2))o([x0,x1,x2,x3,x4,x5,x6]->[x0,x1]),(RosenblattEvaluation(Normal(mu = [1,1,1], sigma = [2,2,2], R = [[ 1 0.5 0.25 ]
[ 0.5 1 0 ]
[ 0.25 0 1 ]])->Normal(3))o([x0,x1,x2,x3,x4,x5,x6]->[x2,x3,x4]),((RosenblattEvaluation(FrankCopula(theta = 0.5)->Normal(2))o(| y0 = Exponential(lambda = 1, gamma = 0) -> y0 : Uniform(a = 0, b = 1)
| y1 = Exponential(lambda = 1, gamma = 0) -> y1 : Uniform(a = 0, b = 1)
))o([x0,x1,x2,x3,x4,x5,x6]->[x5,x6])]
conditional PDF=0.556752
conditional CDF=0.490621
conditional quantile=0.823038
sequential conditional PDF=class=Point name=Unnamed dimension=7 values=[1,1.06099,0.185928,0.227445,0.203657,0.57695,0.525447]
sequential conditional CDF(class=Point name=Unnamed dimension=7 values=[0.05,0.15,0.25,0.35,0.45,0.55,0.65])=class=Point name=Unnamed dimension=7 values=[0.05,0.220267,0.35383,0.436925,0.415568,0.42305,0.487447]
sequential conditional quantile(class=Point name=Unnamed dimension=7 values=[0.05,0.220267,0.35383,0.436925,0.415568,0.42305,0.487447])=class=Point name=Unnamed dimension=7 values=[0.05,0.15,0.25,0.35,0.45,0.55,0.65]
|
