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Distribution class=SquaredNormal name=SquaredNormal mu=5.2 sigma=11.6
Distribution SquaredNormal(mu = 5.2, sigma = 11.6)
Mean= class=Point name=Unnamed dimension=1 values=[161.6]
Covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[50766.8]
Elliptical = False
oneRealization= class=Point name=Unnamed dimension=1 values=[150.188]
Point= class=Point name=Unnamed dimension=1 values=[9.1]
ddf = class=Point name=Unnamed dimension=1 values=[-0.000581252]
log pdf=-4.601591
pdf =0.010036
cdf=0.185981
ccdf=0.814019
pdf gradient = class=Point name=Unnamed dimension=2 values=[-0.00036172,-0.000656205]
cdf gradient = class=Point name=Unnamed dimension=2 values=[-0.00702671,-0.012596]
quantile= class=Point name=Unnamed dimension=1 values=[617.139]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.64685]
Survival(inverseSurvival)=0.950000
entropy=5.870512
Minimum volume interval= [0, 617.139]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 8.57247} with f=
MinimumVolumeLevelSetEvaluation(SquaredNormal(mu = 5.2, sigma = 11.6))
beta= [0.000189245]
Bilateral confidence interval= [0.161557, 802.599]
beta= [0.95]
Unilateral confidence interval (lower tail)= [0, 617.139]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.64685, 10774.4]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[161.6]
standard deviation= class=Point name=Unnamed dimension=1 values=[225.315]
skewness= class=Point name=Unnamed dimension=1 values=[2.73125]
kurtosis= class=Point name=Unnamed dimension=1 values=[14.0137]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[50766.8]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[mu,sigma] values=[5.2,11.6]]
Standard representative= SquaredNormal(mu = 5.2, sigma = 11.6)
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