Distribution  class=Arcsine name=Arcsine dimension=1 a=5.2 b=11.6
Distribution  Arcsine(a = 5.2, b = 11.6)
Mean=  class=Point name=Unnamed dimension=1 values=[8.4]
Covariance=  class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[5.12]
Elliptical =  True
oneRealization= class=Point name=Unnamed dimension=1 values=[9.66973]
oneSample first= class=Point name=Unnamed dimension=1 values=[11.3856]  last= class=Point name=Unnamed dimension=1 values=[7.65026]
mean= class=Point name=Unnamed dimension=1 values=[8.42467]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[5.18235]
Kolmogorov test for the generator, sample size= 100  is accepted
Kolmogorov test for the generator, sample size= 1000  is accepted
Point=  class=Point name=Unnamed dimension=1 values=[9.1]
ddf     = class=Point name=Unnamed dimension=1 values=[0.00731882]
ddf (FD)= class=Point name=Unnamed dimension=1 values=[0.00731882]
log pdf=-2.283364
pdf     =0.101941
pdf (FD)=0.101941
cdf=0.570198
ccdf=0.429802
pdf gradient     = class=Point name=Unnamed dimension=2 values=[0.0130693,-0.0203881]
pdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[0.0130693,-0.0203881]
cdf gradient     = class=Point name=Unnamed dimension=2 values=[-0.0398206,-0.0621201]
cdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[-0.0398206,-0.0621201]
quantile= class=Point name=Unnamed dimension=1 values=[11.5606]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[5.2394]
Survival(inverseSurvival)=0.950000
Minimum volume interval= [5.20986, 11.5901]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 2.30479} with f=
MinimumVolumeLevelSetEvaluation(Arcsine(a = 5.2, b = 11.6))
beta= [0.0997794]
Bilateral confidence interval= [5.20986, 11.5901]
beta= [0.95]
Unilateral confidence interval (lower tail)= [5.2, 11.5606]
beta= [0.95]
Unilateral confidence interval (upper tail)= [5.2394, 11.6]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[8.4]
standard deviation= class=Point name=Unnamed dimension=1 values=[2.26274]
skewness= class=Point name=Unnamed dimension=1 values=[0]
kurtosis= class=Point name=Unnamed dimension=1 values=[1.5]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[5.12]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[a,b] values=[5.2,11.6]]
standard moment n= 0  value= [1]
standard moment n= 1  value= [0]
standard moment n= 2  value= [0.5]
standard moment n= 3  value= [0]
standard moment n= 4  value= [0.375]
standard moment n= 5  value= [0]
Standard representative= Arcsine(a = -1, b = 1)
