Testing class Gumbel
checkConstructorAndDestructor()
checkCopyConstructor()
streamObject(const T & anObject)
class=Gumbel name=Gumbel dimension=1 alpha=2 beta=-0.5
streamObject(const T & anObject)
class=Gumbel name=Gumbel dimension=1 alpha=2 beta=-0.5
areSameObjects(const T & firstObject, const T & secondObject)
areDifferentObjects(const T & firstObject, const T & secondObject)
Distribution class=Gumbel name=Gumbel dimension=1 alpha=2 beta=-0.5
Distribution Gumbel(alpha = 2, beta = -0.5)
Elliptical = false
Continuous = true
oneRealization=class=Point name=Unnamed dimension=1 values=[-0.114155]
oneSample first=class=Point name=Unnamed dimension=1 values=[0.54112] last=class=Point name=Unnamed dimension=1 values=[-0.422444]
mean=class=Point name=Unnamed dimension=1 values=[-0.20325]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.416712]
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf     =class=Point name=Unnamed dimension=1 values=[-0.180043]
ddf (FD)=class=Point name=Unnamed dimension=1 values=[-0.180043]
log pdf=-2.35664
pdf     =0.094738
pdf (FD)=0.094738
cdf=0.951432
ccdf=0.048568
survival=0.048568
Inverse survival=class=Point name=Unnamed dimension=1 values=[-1.04859]
Survival(inverse survival)=0.95
pdf gradient     =class=Point name=Unnamed dimension=2 values=[-0.0876629,0.180043]
pdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[-0.0876629,0.180043]
cdf gradient     =class=Point name=Unnamed dimension=2 values=[0.0710535,-0.094738]
cdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[0.0710535,-0.094738]
characteristic function=(0.799265,-0.209152)
log characteristic function=(-0.190945,-0.255942)
quantile=class=Point name=Unnamed dimension=1 values=[0.985098]
cdf(quantile)=0.95
Minimum volume interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[-1.28067] upper bound=class=Point name=Unnamed dimension=1 values=[1.08074] finite lower bound=[1] finite upper bound=[1]
threshold=0.95
Minimum volume level set=class=LevelSet name=Unnamed dimension=1 function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x0,y0] evaluationImplementation=MinimumVolumeLevelSetEvaluation(Gumbel(alpha = 2, beta = -0.5)) gradientImplementation=MinimumVolumeLevelSetGradient(Gumbel(alpha = 2, beta = -0.5)) hessianImplementation=class=CenteredFiniteDifferenceHessian name=Unnamed epsilon=class=Point name=Unnamed dimension=1 values=[0.0001] evaluation=MinimumVolumeLevelSetEvaluation(Gumbel(alpha = 2, beta = -0.5)) level=2.51069
beta=0.0812123
Bilateral confidence interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[-1.15266] upper bound=class=Point name=Unnamed dimension=1 values=[1.33812] finite lower bound=[1] finite upper bound=[1]
beta=0.95
Unilateral confidence interval (lower tail)=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[-2.23654] upper bound=class=Point name=Unnamed dimension=1 values=[0.985098] finite lower bound=[1] finite upper bound=[1]
beta=0.95
Unilateral confidence interval (upper tail)=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[-1.04859] upper bound=class=Point name=Unnamed dimension=1 values=[15.6181] finite lower bound=[1] finite upper bound=[1]
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]
correlation=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]
spearman=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]
kendall=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]
parameters=[[alpha : 2, beta : -0.5]]
standard moment n=0, value=class=Point name=Unnamed dimension=1 values=[1]
standard moment n=1, value=class=Point name=Unnamed dimension=1 values=[0.577216]
standard moment n=2, value=class=Point name=Unnamed dimension=1 values=[1.97811]
standard moment n=3, value=class=Point name=Unnamed dimension=1 values=[5.44487]
standard moment n=4, value=class=Point name=Unnamed dimension=1 values=[23.5615]
standard moment n=5, value=class=Point name=Unnamed dimension=1 values=[117.839]
Standard representative=Gumbel(alpha = 1, beta = 0)
