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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]
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf = class=Point name=Unnamed dimension=1 values=[-0.294304]
pdf = 0.588608409324
cdf= 0.527937109835
characteristic function= (0.433495931529+0.694719223625j)
pdf gradient = class=Point name=Unnamed dimension=1 values=[0.115577]
cdf gradient = 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
entropy=0.878173
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 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]
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