Distribution  class=Uniform name=Uniform dimension=1 a=-0.5 b=1.5
Distribution  Uniform(a = -0.5, b = 1.5)
Mean=  class=Point name=Unnamed dimension=1 values=[0.5]
Covariance=  class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.333333]
Elliptical =  True
oneRealization= class=Point name=Unnamed dimension=1 values=[0.759753]
oneSample first= class=Point name=Unnamed dimension=1 values=[1.26561]  last= class=Point name=Unnamed dimension=1 values=[0.349444]
mean= class=Point name=Unnamed dimension=1 values=[0.506426]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.339061]
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=[1]
ddf     = class=Point name=Unnamed dimension=1 values=[0]
ddf (FD)= class=Point name=Unnamed dimension=1 values=[0]
log pdf=-0.693147
pdf     =0.500000
pdf (FD)=0.500000
cdf=0.750000
ccdf=0.250000
characteristic function= (0.738460262604+0.403422680111j)
pdf gradient     = class=Point name=Unnamed dimension=2 values=[0.25,-0.25]
pdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[0.25,-0.25]
cdf gradient     = class=Point name=Unnamed dimension=2 values=[-0.125,-0.375]
cdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[-0.125,-0.375]
quantile= class=Point name=Unnamed dimension=1 values=[1.4]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[-0.4]
Survival(inverseSurvival)=0.950000
Minimum volume interval= [-0.45, 1.45]
threshold= 0.95
Minimum volume level set= {x | f(x) <= 0.95} with f=
[x]->[1 * abs(x - (0.5))]
beta= 0.95
Bilateral confidence interval= [-0.45, 1.45]
beta= 0.95
Unilateral confidence interval (lower tail)= [-0.5, 1.4]
beta= 0.95
Unilateral confidence interval (upper tail)= [-0.4, 1.5]
beta= 0.95
mean= class=Point name=Unnamed dimension=1 values=[0.5]
standard deviation= class=Point name=Unnamed dimension=1 values=[0.57735]
skewness= class=Point name=Unnamed dimension=1 values=[0]
kurtosis= class=Point name=Unnamed dimension=1 values=[1.8]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.333333]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[a,b] values=[-0.5,1.5]]
standard moment n= 0  value= [1]
standard moment n= 1  value= [0]
standard moment n= 2  value= [0.333333]
standard moment n= 3  value= [0]
standard moment n= 4  value= [0.2]
standard moment n= 5  value= [0]
Standard representative= Uniform(a = -1, b = 1)
