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Distribution class=Epanechnikov name=Epanechnikov dimension=1
Distribution Epanechnikov()
Elliptical = True
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[0.174954]
oneSample first= class=Point name=Unnamed dimension=1 values=[0.573175] last= class=Point name=Unnamed dimension=1 values=[-0.100711]
mean= class=Point name=Unnamed dimension=1 values=[0.00498178]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.203765]
Point= class=Point name=Unnamed dimension=1 values=[0.5]
ddf = class=Point name=Unnamed dimension=1 values=[-0.75]
log pdf=-0.575364
pdf =0.562500
cdf=0.843750
ccdf=0.156250
pdf gradient = class=Point name=Unnamed dimension=0 values=[]
cdf gradient = class=Point name=Unnamed dimension=0 values=[]
quantile= class=Point name=Unnamed dimension=1 values=[0.729299]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[-0.729299]
Survival(inverseSurvival)=0.950000
entropy=0.568054
Minimum volume interval= [-0.811401, 0.811401]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 1.36172} with f=
MinimumVolumeLevelSetEvaluation(Epanechnikov())
beta= [0.256221]
Bilateral confidence interval= [-0.811401, 0.811401]
beta= [0.95]
Unilateral confidence interval (lower tail)= [-1, 0.729299]
beta= [0.95]
Unilateral confidence interval (upper tail)= [-0.729299, 1]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[0]
standard deviation= class=Point name=Unnamed dimension=1 values=[0.447214]
skewness= class=Point name=Unnamed dimension=1 values=[0]
kurtosis= class=Point name=Unnamed dimension=1 values=[2.14286]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.2]
parameters= [class=PointWithDescription name=X0 dimension=0 description=[] values=[]]
Standard representative= Beta(alpha = 2, beta = 2, a = -1, b = 1)
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