Distribution  class=Student name=Student dimension=1 nu=6.5 mean=class=Point name=Unnamed dimension=1 values=[-0.5] sigma=class=Point name=Unnamed dimension=1 values=[2] correlationMatrix=class=CorrelationMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]
Distribution  Student(nu = 6.5, mu = -0.5, sigma = 2)
Elliptical =  True
Continuous =  True
oneRealization= class=Point name=Unnamed dimension=1 values=[1.46561]
oneSample first= class=Point name=Unnamed dimension=1 values=[3.53872]  last= class=Point name=Unnamed dimension=1 values=[-0.636935]
mean= class=Point name=Unnamed dimension=1 values=[-0.517373]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[5.598]
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=[-0.0560023]
ddf (FD)= class=Point name=Unnamed dimension=1 values=[-0.0560023]
log pdf=-1.961638
pdf     =0.140628
pdf (FD)=0.140628
cdf=0.760243
ccdf=0.239757
pdf gradient     = class=Point name=Unnamed dimension=3 values=[0.00144865,0.0560023,-0.0283123]
pdf gradient (FD)= class=Point name=Unnamed dimension=3 values=[0.00144865,0.0560023,-0.0283123]
cdf gradient     = class=Point name=Unnamed dimension=3 values=[0.00194826,-0.140628,-0.105471]
cdf gradient (FD)= class=Point name=Unnamed dimension=3 values=[0.00194826,-0.140628,-0.105471]
quantile= class=Point name=Unnamed dimension=1 values=[3.33347]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[-4.33347]
Survival(inverseSurvival)=0.950000
Minimum volume interval= [-5.304, 4.304]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 4.03286} with f=
MinimumVolumeLevelSetEvaluation(Student(nu = 6.5, mu = -0.5, sigma = 2))
beta= [0.0177235]
Bilateral confidence interval= [-5.304, 4.304]
beta= [0.95]
Unilateral confidence interval (lower tail)= [-543.532, 3.33347]
beta= [0.95]
Unilateral confidence interval (upper tail)= [-4.33347, 542.532]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[-0.5]
standard deviation= class=Point name=Unnamed dimension=1 values=[2.4037]
skewness= class=Point name=Unnamed dimension=1 values=[0]
kurtosis= class=Point name=Unnamed dimension=1 values=[5.4]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[5.77778]
parameters= [class=PointWithDescription name=Unnamed dimension=3 description=[nu,mean_0,standard_deviation_0] values=[6.5,-0.5,2]]
standard moment n= 0  value= [1]
standard moment n= 1  value= [0]
standard moment n= 2  value= [1.44444]
standard moment n= 3  value= [0]
standard moment n= 4  value= [11.2667]
standard moment n= 5  value= [0]
Standard representative= Student(nu = 6.5, mu = 0, sigma = 1)
density generator=0.224500
pdf via density generator=0.140628
density generator derivative     =-0.112250
density generator derivative (FD)=-0.112250
density generator second derivative     =0.071092
density generator second derivative (FD)=0.071092
