Distribution  class=GeneralizedPareto name=GeneralizedPareto dimension=1 sigma=1.5 xi=-0.2
Distribution  GeneralizedPareto(sigma = 1.5, xi=-0.2)
Elliptical =  False
Continuous =  True
oneRealization= class=Point name=Unnamed dimension=1 values=[0.662264]
oneSample first= class=Point name=Unnamed dimension=1 values=[0.184665]  last= class=Point name=Unnamed dimension=1 values=[1.18051]
mean= class=Point name=Unnamed dimension=1 values=[1.24428]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.12783]
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 (FD)= class=Point name=Unnamed dimension=1 values=[-0.231453]
pdf     = 0.376111934156
pdf (FD)= 0.376111934
cdf= 0.511054485597
pdf gradient     = class=Point name=Unnamed dimension=2 values=[-0.096439,-0.188281]
pdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[-0.096439,-0.188281]
cdf gradient     = class=Point name=Unnamed dimension=2 values=[-0.250741,-0.131347]
cdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[-0.250741,-0.131347]
quantile= class=Point name=Unnamed dimension=1 values=[3.3804]
cdf(quantile)= 0.95
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.0765466]
Survival(inverseSurvival)=0.950000
Minimum volume interval= [0, 3.3804]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 2.80205} with f=
MinimumVolumeLevelSetEvaluation(GeneralizedPareto(sigma = 1.5, xi=-0.2))
beta= [0.0606855]
Bilateral confidence interval= [0.0378807, 3.91368]
beta= [0.95]
Unilateral confidence interval (lower tail)= [0, 3.3804]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.0765466, 7.5]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[1.25]
standard deviation= class=Point name=Unnamed dimension=1 values=[1.05644]
skewness= class=Point name=Unnamed dimension=1 values=[1.18322]
kurtosis= class=Point name=Unnamed dimension=1 values=[4.2]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.11607]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[sigma,xi] values=[1.5,-0.2]]
standard moment n= 0  value= [1]
standard moment n= 1  value= [0.833333]
standard moment n= 2  value= [1.19048]
standard moment n= 3  value= [2.23214]
standard moment n= 4  value= [4.96032]
standard moment n= 5  value= [12.4008]
Standard representative= GeneralizedPareto(sigma = 1, xi=-0.2)
Distribution  class=GeneralizedPareto name=GeneralizedPareto dimension=1 sigma=1.5 xi=0
Distribution  GeneralizedPareto(sigma = 1.5, xi=0)
Elliptical =  False
Continuous =  True
oneRealization= class=Point name=Unnamed dimension=1 values=[2.26806]
oneSample first= class=Point name=Unnamed dimension=1 values=[0.873113]  last= class=Point name=Unnamed dimension=1 values=[1.8084]
mean= class=Point name=Unnamed dimension=1 values=[1.49864]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[2.31994]
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 (FD)= class=Point name=Unnamed dimension=1 values=[-0.228185]
pdf     = 0.342278079355
pdf (FD)= 0.342278079
cdf= 0.486582880967
pdf gradient     = class=Point name=Unnamed dimension=2 values=[-0.0760618,-0.152124]
pdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[-0.0760618,-0.152124]
cdf gradient     = class=Point name=Unnamed dimension=2 values=[-0.228185,-0.114093]
cdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[-0.228185,-0.114093]
quantile= class=Point name=Unnamed dimension=1 values=[4.4936]
cdf(quantile)= 0.95
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.0769399]
Survival(inverseSurvival)=0.950000
Minimum volume interval= [0, 4.4936]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.4012} with f=
MinimumVolumeLevelSetEvaluation(GeneralizedPareto(sigma = 1.5, xi=0))
beta= [0.0333333]
Bilateral confidence interval= [0.0379767, 5.53332]
beta= [0.95]
Unilateral confidence interval (lower tail)= [0, 4.4936]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.0769399, 54.0655]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[1.5]
standard deviation= class=Point name=Unnamed dimension=1 values=[1.5]
skewness= class=Point name=Unnamed dimension=1 values=[2]
kurtosis= class=Point name=Unnamed dimension=1 values=[9]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[2.25]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[sigma,xi] values=[1.5,0]]
standard moment n= 0  value= [1]
standard moment n= 1  value= [1]
standard moment n= 2  value= [2]
standard moment n= 3  value= [6]
standard moment n= 4  value= [24]
standard moment n= 5  value= [120]
Standard representative= GeneralizedPareto(sigma = 1, xi=0)
Distribution  class=GeneralizedPareto name=GeneralizedPareto dimension=1 sigma=1.5 xi=0.2
Distribution  GeneralizedPareto(sigma = 1.5, xi=0.2)
Elliptical =  False
Continuous =  True
oneRealization= class=Point name=Unnamed dimension=1 values=[1.47575]
oneSample first= class=Point name=Unnamed dimension=1 values=[5.37434]  last= class=Point name=Unnamed dimension=1 values=[0.15915]
mean= class=Point name=Unnamed dimension=1 values=[1.88187]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[5.82491]
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 (FD)= class=Point name=Unnamed dimension=1 values=[-0.222073]
pdf     = 0.31460293288
pdf (FD)= 0.314602933
cdf= 0.465175014104
pdf gradient     = class=Point name=Unnamed dimension=2 values=[-0.0616868,-0.125946]
pdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[-0.0616868,-0.125946]
cdf gradient     = class=Point name=Unnamed dimension=2 values=[-0.209735,-0.100495]
cdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[-0.209735,-0.100495]
quantile= class=Point name=Unnamed dimension=1 values=[6.15423]
cdf(quantile)= 0.95
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.0773359]
Survival(inverseSurvival)=0.950000
Minimum volume interval= [0, 6.15423]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 4.00034} with f=
MinimumVolumeLevelSetEvaluation(GeneralizedPareto(sigma = 1.5, xi=0.2))
beta= [0.0183093]
Bilateral confidence interval= [0.038073, 8.18459]
beta= [0.95]
Unilateral confidence interval (lower tail)= [0, 6.15423]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.0773359, 10126.3]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[1.875]
standard deviation= class=Point name=Unnamed dimension=1 values=[2.42061]
skewness= class=Point name=Unnamed dimension=1 values=[4.64758]
kurtosis= class=Point name=Unnamed dimension=1 values=[73.8]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[5.85938]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[sigma,xi] values=[1.5,0.2]]
standard moment n= 0  value= [1]
standard moment n= 1  value= [1.25]
standard moment n= 2  value= [4.16667]
standard moment n= 3  value= [31.25]
standard moment n= 4  value= [625]
NotDefinedException : Error: the standard moments are defined up to order 5 and n=5
Standard representative= GeneralizedPareto(sigma = 1, xi=0.2)
