Distribution  class=Chi name=Chi dimension=1 nu=1.5
Distribution  Chi(nu = 1.5)
Elliptical =  False
Continuous =  True
oneRealization= class=Point name=Unnamed dimension=1 values=[1.66733]
oneSample first= class=Point name=Unnamed dimension=1 values=[1.58636]  last= class=Point name=Unnamed dimension=1 values=[1.02264]
mean= class=Point name=Unnamed dimension=1 values=[1.04589]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.399002]
Kolmogorov test for the generator, sample size= 100  is accepted
Kolmogorov test for the generator, sample size= 1000  is accepted
Point=  class=Point name=Unnamed dimension=1 values=[1]
ddf     = class=Point name=Unnamed dimension=1 values=[-0.294304]
ddf (FD)= class=Point name=Unnamed dimension=1 values=[-0.294304]
pdf     = 0.588608409324
pdf (FD)= 0.588608409
cdf= 0.527937109835
characteristic function= (0.433495931529+0.694719223625j)
pdf gradient     = class=Point name=Unnamed dimension=1 values=[0.115577]
pdf gradient (FD)= class=Point name=Unnamed dimension=1 values=[0.115577]
cdf gradient     = class=Point name=Unnamed dimension=1 values=[-0.291714]
cdf gradient (FD)= class=Point name=Unnamed dimension=1 values=[-0.291714]
quantile= class=Point name=Unnamed dimension=1 values=[2.23164]
cdf(quantile)= 0.95
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.182299]
Survival(inverseSurvival)=0.950000
Minimum volume interval= [0.0147509, 2.24137]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 2.13833} with f=
MinimumVolumeLevelSetEvaluation(Chi(nu = 1.5))
beta= [0.117852]
Bilateral confidence interval= [0.114512, 2.50516]
beta= [0.95]
Unilateral confidence interval (lower tail)= [0, 2.23164]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.182299, 7.89498]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[1.04605]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.40578]
parameters= [class=PointWithDescription name=X0 dimension=1 description=[nu] values=[1.5]]
standard moment n= 0  value= [1]
standard moment n= 1  value= [1.04605]
standard moment n= 2  value= [1.5]
standard moment n= 3  value= [2.61512]
standard moment n= 4  value= [5.25]
standard moment n= 5  value= [11.7681]
Standard representative= Chi(nu = 1.5)
nu= 1.5
standard deviation= class=Point name=Unnamed dimension=1 values=[0.637009]
skewness= class=Point name=Unnamed dimension=1 values=[0.762585]
kurtosis= class=Point name=Unnamed dimension=1 values=[3.42425]
