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Distribution class=MarginalDistribution name=MarginalDistribution dimension=3 distribution=class=Normal name=Normal dimension=5 mean=class=Point name=Unnamed dimension=5 values=[0,0,0,0,0] sigma=class=Point name=Unnamed dimension=5 values=[1,1,1,1,1] correlationMatrix=class=CorrelationMatrix dimension=5 implementation=class=MatrixImplementation name=Unnamed rows=5 columns=5 values=[1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1] indices=[2,0,1]
Distribution MarginalDistribution(distribution=Normal(mu = [0,0,0,0,0], sigma = [1,1,1,1,1], R = 5x5
[[ 1 0 0 0 0 ]
[ 0 1 0 0 0 ]
[ 0 0 1 0 0 ]
[ 0 0 0 1 0 ]
[ 0 0 0 0 1 ]]), indices=[2,0,1])
Elliptical = true
Continuous = true
Discrete = false
Integral = false
oneRealization=class=Point name=Unnamed dimension=3 values=[-0.438266,0.608202,-1.26617]
oneSample first=class=Point name=Unnamed dimension=3 values=[1.43725,0.350042,-0.355007] last=class=Point name=Unnamed dimension=3 values=[0.859992,-2.2281,0.884963]
mean=class=Point name=Unnamed dimension=3 values=[-0.000164216,0.00955544,0.000744822]
covariance=class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1.00735,0.0155386,-0.00400052,0.0155386,1.02164,-0.0214975,-0.00400052,-0.0214975,0.997907]
Point= class=Point name=Unnamed dimension=3 values=[1,1,1]
ddf =class=Point name=Unnamed dimension=3 values=[-0.0141673,-0.0141673,-0.0141673]
log pdf=-4.25682
pdf =0.0141673
cdf=0.595555
ccdf=0.404445
survival=0.00399359
Inverse survival=class=Point name=Unnamed dimension=3 values=[-2.1212,-2.1212,-2.1212]
Survival(inverse survival)=0.95
quantile=class=Point name=Unnamed dimension=3 values=[2.1212,2.1212,2.1212]
cdf(quantile)=0.95
quantile (tail)=class=Point name=Unnamed dimension=3 values=[-0.336086,-0.336086,-0.336086]
cdf (tail)=0.95
mean=class=Point name=Unnamed dimension=3 values=[0,0,0]
standard deviation=class=Point name=Unnamed dimension=3 values=[1,1,1]
skewness=class=Point name=Unnamed dimension=3 values=[0,0,0]
kurtosis=class=Point name=Unnamed dimension=3 values=[3,3,3]
covariance=class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1,0,0,0,1,0,0,0,1]
correlation=class=CorrelationMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1,0,0,0,1,0,0,0,1]
spearman=class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1,0,0,0,1,0,0,0,1]
kendall=class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1,0,0,0,1,0,0,0,1]
Standard representative=MarginalDistribution(distribution=Normal(mu = [0,0,0,0,0], sigma = [1,1,1,1,1], R = 5x5
[[ 1 0 0 0 0 ]
[ 0 1 0 0 0 ]
[ 0 0 1 0 0 ]
[ 0 0 0 1 0 ]
[ 0 0 0 0 1 ]]), indices=[2,0,1])
Distribution class=MarginalDistribution name=MarginalDistribution dimension=3 distribution=class=Multinomial name=Multinomial dimension=5 p=class=Point name=Unnamed dimension=5 values=[0.142857,0.142857,0.142857,0.142857,0.142857] n=10 indices=[2,0,1]
Distribution MarginalDistribution(distribution=Multinomial(n = 10, p = [0.142857,0.142857,0.142857,0.142857,0.142857]), indices=[2,0,1])
Elliptical = false
Continuous = false
Discrete = true
Integral = true
oneRealization=class=Point name=Unnamed dimension=3 values=[2,3,0]
oneSample first=class=Point name=Unnamed dimension=3 values=[2,3,1] last=class=Point name=Unnamed dimension=3 values=[1,1,0]
mean=class=Point name=Unnamed dimension=3 values=[1.4254,1.434,1.4148]
covariance=class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1.22176,-0.210245,-0.186975,-0.210245,1.24377,-0.217845,-0.186975,-0.217845,1.21306]
Point= class=Point name=Unnamed dimension=3 values=[1,1,1]
pdf =0.00250271
cdf=0.135956
ccdf=0.864044
survival=0.457828
quantile=class=Point name=Unnamed dimension=3 values=[4,4,4]
cdf(quantile)=0.976008
quantile (tail)=class=Point name=Unnamed dimension=3 values=[1,1,1]
cdf (tail)=0.996288
mean=class=Point name=Unnamed dimension=3 values=[1.42857,1.42857,1.42857]
standard deviation=class=Point name=Unnamed dimension=3 values=[1.10657,1.10657,1.10657]
skewness=class=Point name=Unnamed dimension=3 values=[0.645497,0.645497,0.645497]
kurtosis=class=Point name=Unnamed dimension=3 values=[3.21667,3.21667,3.21667]
covariance=class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1.22449,-0.204082,-0.204082,-0.204082,1.22449,-0.204082,-0.204082,-0.204082,1.22449]
correlation=class=CorrelationMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[1,-0.166667,-0.166667,-0.166667,1,-0.166667,-0.166667,-0.166667,1]
Standard representative=MarginalDistribution(distribution=Multinomial(n = 10, p = [0.142857,0.142857,0.142857,0.142857,0.142857]), indices=[2,0,1])
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