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Distribution class=Gumbel name=Gumbel dimension=1 beta=0.5 gamma=-0.5
Distribution Gumbel(beta = 0.5, gamma = -0.5)
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[-0.114155]
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf = class=Point name=Unnamed dimension=1 values=[-0.180043]
log pdf=-2.356640
pdf =0.094738
cdf=0.951432
ccdf=0.048568
pdf gradient = class=Point name=Unnamed dimension=2 values=[0.350652,0.180043]
cdf gradient = class=Point name=Unnamed dimension=2 values=[-0.284214,-0.094738]
quantile= class=Point name=Unnamed dimension=1 values=[0.985098]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[-1.04859]
Survival(inverseSurvival)=0.950000
entropy=0.884068
Minimum volume interval= [-1.28067, 1.08074]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 2.51069} with f=
MinimumVolumeLevelSetEvaluation(Gumbel(beta = 0.5, gamma = -0.5))
beta= [0.0812123]
Bilateral confidence interval= [-1.15266, 1.33812]
beta= [0.95]
Unilateral confidence interval (lower tail)= [-2.23654, 0.985098]
beta= [0.95]
Unilateral confidence interval (upper tail)= [-1.04859, 15.6181]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[-0.211392]
standard deviation= class=Point name=Unnamed dimension=1 values=[0.641275]
skewness= class=Point name=Unnamed dimension=1 values=[1.13955]
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=[0.411234]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[beta,gamma] values=[0.5,-0.5]]
Standard representative= Gumbel(beta = 1, gamma = 0)
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