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Copula class=BlockIndependentCopula name=BlockIndependentCopula dimension=7 copula[0]=class=FrankCopula name=FrankCopula dimension=2 theta=3 copula[1]=class=NormalCopula name=NormalCopula dimension=3 correlation=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] copula[2]=class=ClaytonCopula name=ClaytonCopula dimension=2 theta=2
Copula BlockIndependentCopula(FrankCopula(theta = 3), NormalCopula(R = [[ 1 0.5 0.25 ]
[ 0.5 1 0 ]
[ 0.25 0 1 ]]), ClaytonCopula(theta = 2))
Elliptical distribution= False
Continuous = True
Elliptical = False
Independent = False
oneRealization= class=Point name=Unnamed dimension=7 values=[0.629877,0.893758,0.102726,0.155617,0.816172,0.0632061,0.0560402]
oneSample first= class=Point name=Unnamed dimension=7 values=[0.714382,0.535485,0.551694,0.0925633,0.483697,0.62669,0.843177] last= class=Point name=Unnamed dimension=7 values=[0.2804,0.270203,0.982939,0.934468,0.850723,0.698151,0.981738]
mean= class=Point name=Unnamed dimension=7 values=[0.502996,0.501561,0.498392,0.504034,0.49464,0.502793,0.500715]
covariance= class=CovarianceMatrix dimension=7 implementation=class=MatrixImplementation name=Unnamed rows=7 columns=7 values=[0.0845126,0.0382404,-0.0013059,-0.000645958,-0.00102304,0.000286105,0.000520833,0.0382404,0.0836032,-0.001033,-0.000314606,-0.000448824,0.000484917,0.00115831,-0.0013059,-0.001033,0.084547,0.0395462,0.0209758,-0.000875805,-0.00199626,-0.000645958,-0.000314606,0.0395462,0.0839577,-0.001105,-0.00173284,-0.000908655,-0.00102304,-0.000448824,0.0209758,-0.001105,0.0837096,-0.0004662,-0.0010621,0.000286105,0.000484917,-0.000875805,-0.00173284,-0.0004662,0.0841872,0.0568939,0.000520833,0.00115831,-0.00199626,-0.000908655,-0.0010621,0.0568939,0.0826949]
Point= class=Point name=Unnamed dimension=7 values=[0.6,0.6,0.6,0.6,0.6,0.6,0.6]
ddf = class=Point name=Unnamed dimension=7 values=[0.580905,0.580905,0.91183,0.260523,0.130261,0.177648,0.177648]
pdf =2.185069
cdf=0.058797
quantile= class=Point name=Unnamed dimension=7 values=[0.992521,0.992521,0.992521,0.992521,0.992521,0.992521,0.992521]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=7 values=[0.00832738,0.00832738,0.00832738,0.00832738,0.00832738,0.00832738,0.00832738]
Survival(inverseSurvival)=0.950000
entropy=-0.729844
mean= class=Point name=Unnamed dimension=7 values=[0.5,0.5,0.5,0.5,0.5,0.5,0.5]
covariance= class=CovarianceMatrix dimension=7 implementation=class=MatrixImplementation name=Unnamed rows=7 columns=7 values=[0.0833333,0.0373929,0,0,0,0,0,0.0373929,0.0833333,0,0,0,0,0,0,0,0.0833333,0.0402153,0.0199465,0,0,0,0,0.0402153,0.0833333,0,0,0,0,0,0.0199465,0,0.0833333,0,0,0,0,0,0,0,0.0833333,0.0568528,0,0,0,0,0,0.0568528,0.0833333]
parameters= [class=PointWithDescription name=BlockIndependentCopula dimension=5 description=[copula_0_theta,copula_1_R_2_1,copula_1_R_3_1,copula_1_R_3_2,copula_2_theta] values=[3,0.5,0.25,0,2]]
covariance= 7x7
[[ 0.08333 0.03739 0 0 0 0 0 ]
[ 0.03739 0.08333 0 0 0 0 0 ]
[ 0 0 0.08333 0.04022 0.01995 0 0 ]
[ 0 0 0.04022 0.08333 0 0 0 ]
[ 0 0 0.01995 0 0.08333 0 0 ]
[ 0 0 0 0 0 0.08333 0.05685 ]
[ 0 0 0 0 0 0.05685 0.08333 ]]
correlation= 7x7
[[ 1 0.4487 0 0 0 0 0 ]
[ 0.4487 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 0.6822 ]
[ 0 0 0 0 0 0.6822 1 ]]
spearman= 7x7
[[ 1 0.4487 0 0 0 0 0 ]
[ 0.4487 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 0.6822 ]
[ 0 0 0 0 0 0.6822 1 ]]
kendall= 7x7
[[ 1 0.3072 0 0 0 0 0 ]
[ 0.3072 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 0.5 ]
[ 0 0 0 0 0 0.5 1 ]]
conditional PDF=0.467887
conditional CDF=0.902087
conditional quantile=0.299570
sequential conditional PDF= [1,1.21219,1,1.17967,1.05262,1,1.45164]
sequential conditional CDF( [0.05,0.15,0.25,0.35,0.45,0.55,0.65] )= [0.05,0.346653,0.25,0.477865,0.514559,0.55,0.595069]
sequential conditional quantile( [0.05,0.346653,0.25,0.477865,0.514559,0.55,0.595069] )= [0.05,0.15,0.25,0.35,0.45,0.55,0.65]
indices= [1,2,3,5,6]
margins= class=BlockIndependentCopula name=BlockIndependentCopula dimension=5 copula[0]=class=IndependentCopula name=IndependentCopula dimension=1 copula[1]=class=NormalCopula name=NormalCopula dimension=2 correlation=class=CorrelationMatrix dimension=2 implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[1,0.5,0.5,1] copula[2]=class=ClaytonCopula name=ClaytonCopula dimension=2 theta=2
margins PDF=3.086065
margins CDF=0.005401
margins quantile= class=Point name=Unnamed dimension=5 values=[0.989493,0.989493,0.989493,0.989493,0.989493]
margins CDF(quantile)=0.950000
margins realization= class=Point name=Unnamed dimension=5 values=[0.66202,0.528162,0.684545,0.181369,0.289273]
isoprobabilistic transformation (general normal)= [(RosenblattEvaluation(FrankCopula(theta = 3)->Normal(2))o([x0,x1,x2,x3,x4,x5,x6]->[x0,x1]),(NatafEllipticalCopulaEvaluation(Copula(inverseCholesky=[[ 1 0 0 ]
[ -0.57735 1.1547 0 ]
[ -0.348155 0.174078 1.04447 ]], E=Normal(mu = 0, sigma = 1))->Normal(mu = [0,0,0], sigma = [1,1,1], R = [[ 1 0 0 ]
[ 0 1 0 ]
[ 0 0 1 ]])))o([x0,x1,x2,x3,x4,x5,x6]->[x2,x3,x4]),(RosenblattEvaluation(ClaytonCopula(theta = 2)->Normal(2))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]),(NatafEllipticalCopulaEvaluation(Copula(inverseCholesky=[[ 1 0 0 ]
[ -0.57735 1.1547 0 ]
[ -0.348155 0.174078 1.04447 ]], E=Normal(mu = 0, sigma = 1))->Normal(mu = [0,0,0], sigma = [1,1,1], R = [[ 1 0 0 ]
[ 0 1 0 ]
[ 0 0 1 ]])))o([x0,x1,x2,x3,x4,x5,x6]->[x2,x3,x4]),(RosenblattEvaluation(ClaytonCopula(theta = 2)->Normal(2))o([x0,x1,x2,x3,x4,x5,x6]->[x5,x6])]
conditional PDF=0.467887
conditional CDF=0.902087
conditional quantile=0.299570
sequential conditional PDF= [1,1.06099,1,1.24177,1.05204,1,1.39119]
sequential conditional CDF( [0.05,0.15,0.25,0.35,0.45,0.55,0.65] )= [0.05,0.220267,0.25,0.477865,0.514559,0.55,0.595069]
sequential conditional quantile( [0.05,0.220267,0.25,0.477865,0.514559,0.55,0.595069] )= [0.05,0.15,0.25,0.35,0.45,0.55,0.65]
isoprobabilistic transformation (independent)= NatafIndependentCopulaEvaluation(IndependentCopula(6)->Normal(6))
conditional PDF=1.000000
conditional CDF=0.600000
conditional quantile=0.600000
sequential conditional PDF= [1,1,1,1,1,1]
sequential conditional CDF( [0.05,0.15,0.25,0.35,0.45,0.55] )= [0.05,0.15,0.25,0.35,0.45,0.55]
sequential conditional quantile( [0.05,0.15,0.25,0.35,0.45,0.55] )= [0.05,0.15,0.25,0.35,0.45,0.55]
isoprobabilistic transformation (single contributor)= (class=LinearEvaluation name=Unnamed center=[1,1] constant=[0,0] linear=[[ 0.333333 0 ]
[ 0 0.333333 ]])o(| y0 = Uniform(a = 0, b = 1) -> y0 : Student(nu = 3, mu = 1, sigma = 3)
| y1 = Uniform(a = 0, b = 1) -> y1 : Student(nu = 3, mu = 1, sigma = 3)
)
conditional PDF=1.028301
conditional CDF=0.602660
conditional quantile=0.597413
sequential conditional PDF= [1,1.06099]
sequential conditional CDF( [0.05,0.15] )= [0.05,0.220267]
sequential conditional quantile( [0.05,0.220267] )= [0.05,0.15]
BlockIndependentCopula(NormalCopula(R = [[ 1 0 ]
[ 0 1 ]]), IndependentCopula(dimension = 2))
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