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Distribution class=ChiSquare name=ChiSquare dimension=1 nu=1.5
Distribution ChiSquare(nu = 1.5)
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[2.77998]
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf = class=Point name=Unnamed dimension=1 values=[-0.220728]
pdf = 0.294304204662
cdf= 0.527937109835
characteristic function= (0.368925208371+0.403687932533j)
pdf gradient = class=Point name=Unnamed dimension=1 values=[0.0577886]
cdf gradient = class=Point name=Unnamed dimension=1 values=[-0.291714]
quantile= class=Point name=Unnamed dimension=1 values=[4.9802]
cdf(quantile)= 0.95
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.0332328]
Survival(inverseSurvival)=0.950000
entropy=1.374963
Minimum volume interval= [0, 4.9802]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.61461} with f=
MinimumVolumeLevelSetEvaluation(ChiSquare(nu = 1.5))
beta= [0.0269275]
Bilateral confidence interval= [0.013113, 6.27581]
beta= [0.95]
Unilateral confidence interval (lower tail)= [0, 4.9802]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.0332328, 39.9307]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[1.5]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[3]
parameters= [class=PointWithDescription name=X0 dimension=1 description=[nu] values=[1.5]]
Standard representative= Gamma(k = 0.75, lambda = 1, gamma = 0)
nu= 1.5
standard deviation= class=Point name=Unnamed dimension=1 values=[1.73205]
skewness= class=Point name=Unnamed dimension=1 values=[2.3094]
kurtosis= class=Point name=Unnamed dimension=1 values=[11]
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