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Distribution class=KernelMixture name=KernelMixture kernel=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] bandwidth=class=Point name=Unnamed dimension=3 values=[2,3,1] sample=class=Sample name=Unnamed implementation=class=SampleImplementation name=Unnamed size=3 dimension=3 data=[[0.5,-0.5,1],[1.5,0.5,2],[2.5,1.5,3]]
Distribution KernelMixture(kernel = Normal(mu = 0, sigma = 1), bandwidth = [2,3,1], sample =
0 : [ 0.5 -0.5 1 ]
1 : [ 1.5 0.5 2 ]
2 : [ 2.5 1.5 3 ]
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=3 values=[2.07328,-2.47593,2.92288]
oneSample first= class=Point name=Unnamed dimension=3 values=[-1.86277,2.55013,2.64499] last= class=Point name=Unnamed dimension=3 values=[2.81013,-1.29834,1.89856]
mean= class=Point name=Unnamed dimension=3 values=[1.63854,0.0623536,2.01459]
covariance= class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[4.5743,-0.738335,-0.178015,-0.738335,6.42657,0.306325,-0.178015,0.306325,1.37246]
Point= [1.0, 1.0, 1.0]
ddf = class=Point name=Unnamed dimension=3 values=[1.17543e-05,-0.000596732,0.00275582]
ddf (ref)= class=Point name=Unnamed dimension=3 values=[1.17543e-05,-0.000596732,0.00275582]
log pdf=-5.218101
pdf =0.005418
pdf (ref)=0.005418
cdf=0.081759
ccdf=0.918241
cdf (ref)=0.081759
quantile= class=Point name=Unnamed dimension=3 values=[6.05991,7.07458,4.66827]
quantile (ref)= class=Point name=Unnamed dimension=3 values=[6.05991,7.07458,4.66827]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=3 values=[-3.05991,-6.07458,-0.668274]
Survival(inverseSurvival)=0.950000
cond. cdf=0.615836
cond. cdf (vect)= [0.615836,0.657634,0.707868]
cond. pdf=0.123311
cond. pdf (vect)= [0.123311,0.118288,0.110573]
cond. quantile=-3.77006
cond. quantile (vect)= [-3.77006,-1.28752,2.12927]
cond. cdf(cond. quantile)= [0.1,0.3,0.7]
sequential conditional PDF= [0.179079,0.126183,0.239751]
sequential conditional CDF( [1.5,2.5,3.5] )= [0.5,0.740131,0.855175]
sequential conditional quantile( [0.5,0.740131,0.855175] )= [1.5,2.5,3.5]
mean= class=Point name=Unnamed dimension=3 values=[1.5,0.5,2]
mean (ref)= class=Point name=Unnamed dimension=3 values=[1.5,0.5,2]
covariance= class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[4.66667,0.666667,0.666667,0.666667,9.66667,0.666667,0.666667,0.666667,1.66667]
covariance (ref)= class=CovarianceMatrix dimension=3 implementation=class=MatrixImplementation name=Unnamed rows=3 columns=3 values=[4.66667,0.666667,0.666667,0.666667,9.66667,0.666667,0.666667,0.666667,1.66667]
parameters= [0.5,-0.5,1,1.5,0.5,2,2.5,1.5,3,2,3,1]#12
parametersDesc= [x_0^0,x_0^1,x_0^2,x_1^0,x_1^1,x_1^2,x_2^0,x_2^1,x_2^2,h_0,h_1,h_2]#12
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