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Distribution class=NonCentralChiSquare name=NonCentralChiSquare dimension=1 nu=1.5 lambda=2.5
Distribution NonCentralChiSquare(nu = 1.5, lambda = 2.5)
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[5.14874]
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf = class=Point name=Unnamed dimension=1 values=[-0.0277166]
pdf = 0.168124667122
cdf= 0.205327699996
characteristic function= (0.0479067415537+0.195396095873j)
pdf gradient = class=Point name=Unnamed dimension=2 values=[-0.0269116,-0.0447116]
cdf gradient = class=Point name=Unnamed dimension=2 values=[-0.127286,-0.0787015]
quantile= class=Point name=Unnamed dimension=1 values=[11.1286]
cdf(quantile)= 0.95
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.169073]
Survival(inverseSurvival)=0.950000
entropy=2.375571
Minimum volume interval= [0, 11.1286]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 4.1499} with f=
MinimumVolumeLevelSetEvaluation(NonCentralChiSquare(nu = 1.5, lambda = 2.5))
beta= [0.015766]
Bilateral confidence interval= [0.068294, 13.2884]
beta= [0.95]
Unilateral confidence interval (lower tail)= [0, 11.1286]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.169073, 127]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[4]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[13]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[nu,lambda] values=[1.5,2.5]]
Standard representative= NonCentralChiSquare(nu = 1.5, lambda = 2.5)
nu= 1.5
standard deviation= class=Point name=Unnamed dimension=1 values=[3.60555]
skewness= class=Point name=Unnamed dimension=1 values=[1.53609]
kurtosis= class=Point name=Unnamed dimension=1 values=[6.26627]
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