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Distribution class=Beta name=Beta dimension=1 alpha=2 beta=3 a=-1 b=2
Distribution Beta(alpha = 2, beta = 3, a = -1, b = 2)
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[0.456966]
Point= class=Point name=Unnamed dimension=1 values=[1.5]
ddf = class=Point name=Unnamed dimension=1 values=[-0.333333]
log pdf=-2.379546
pdf =0.092593
cdf=0.983796
ccdf=0.016204
pdf gradient = class=Point name=Unnamed dimension=4 values=[0.083427,-0.111891,0.0864198,0.246914]
cdf gradient = class=Point name=Unnamed dimension=4 values=[-0.0154012,0.0251751,-0.0154321,-0.0771605]
quantile= class=Point name=Unnamed dimension=1 values=[1.25419]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[-0.707166]
Survival(inverseSurvival)=0.950000
entropy=0.863706
Minimum volume interval= [-0.868627, 1.31692]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 1.83159} with f=
MinimumVolumeLevelSetEvaluation(Beta(alpha = 2, beta = 3, a = -1, b = 2))
beta= [0.160159]
Bilateral confidence interval= [-0.797242, 1.41764]
beta= [0.95]
Unilateral confidence interval (lower tail)= [-1, 1.25419]
beta= [0.95]
Unilateral confidence interval (upper tail)= [-0.707166, 2]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[0.2]
standard deviation= class=Point name=Unnamed dimension=1 values=[0.6]
skewness= class=Point name=Unnamed dimension=1 values=[0.285714]
kurtosis= class=Point name=Unnamed dimension=1 values=[2.35714]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.36]
parameters= [class=PointWithDescription name=X0 dimension=4 description=[alpha,beta,a,b] values=[2,3,-1,2]]
Standard representative= Beta(alpha = 2, beta = 3, a = -1, b = 1)
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