Distribution  TruncatedNormal(mu = 0.5, sigma = 3, a = -2, b = 2)
Elliptical =  False
Continuous =  True
oneRealization= class=Point name=Unnamed dimension=1 values=[-0.814797]
oneSample first= class=Point name=Unnamed dimension=1 values=[1.55013]  last= class=Point name=Unnamed dimension=1 values=[-0.505664]
mean= class=Point name=Unnamed dimension=1 values=[0.0635542]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.25177]
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=[-0.0148955]
ddf (FD)= class=Point name=Unnamed dimension=1 values=[-0.0148955]
log pdf=-1.316321
pdf     =0.268120
pdf (FD)=0.268120
cdf=0.743877
ccdf=0.256123
pdf gradient     = class=Point name=Unnamed dimension=4 values=[0.0277138,-0.0118013,0.0515102,-0.0643285]
pdf gradient (FD)= class=Point name=Unnamed dimension=4 values=[0.0277138,-0.0118013,0.0515102,-0.0643285]
log-pdf gradient     = class=Point name=Unnamed dimension=4 values=[0.103363,-0.0440151,0.192116,-0.239924]
log-pdf gradient (FD)= class=Point name=Unnamed dimension=4 values=[0.103363,-0.0440151,0.192116,-0.239924]
cdf gradient     = class=Point name=Unnamed dimension=4 values=[-0.0404404,0.00354582,-0.0492055,-0.178474]
cdf gradient (FD)= class=Point name=Unnamed dimension=4 values=[-0.0404404,0.00354582,-0.0492055,-0.178474]
quantile= class=Point name=Unnamed dimension=1 values=[1.79498]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[-1.74843]
Survival(inverseSurvival)=0.950000
Minimum volume interval= [-1.74843, 2]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 1.58329} with f=
MinimumVolumeLevelSetEvaluation(TruncatedNormal(mu = 0.5, sigma = 3, a = -2, b = 2))
beta= [0.205299]
Bilateral confidence interval= [-1.87213, 1.89667]
beta= [0.95]
Unilateral confidence interval (lower tail)= [-2, 1.79498]
beta= [0.95]
Unilateral confidence interval (upper tail)= [-1.74843, 2]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[0.0697287]
standard deviation= class=Point name=Unnamed dimension=1 values=[1.1195]
skewness= class=Point name=Unnamed dimension=1 values=[-0.0708515]
kurtosis= class=Point name=Unnamed dimension=1 values=[1.86887]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.25327]
parameters= [class=PointWithDescription name=X0 dimension=4 description=[mu,sigma,a,b] values=[0.5,3,-2,2]]
standard moment n= 0  value= [1]
standard moment n= 1  value= [0.0348644]
standard moment n= 2  value= [0.314534]
standard moment n= 3  value= [0.0203874]
standard moment n= 4  value= [0.184018]
standard moment n= 5  value= [0.0143554]
Standard representative= TruncatedNormal(mu = 0.25, sigma = 1.5, a = -1, b = 1)
