Testing class InverseGamma
checkConstructorAndDestructor()
checkCopyConstructor()
streamObject(const T & anObject)
class=InverseGamma name=InverseGamma dimension=1 k=1.5 lambda=2.5
streamObject(const T & anObject)
class=InverseGamma name=InverseGamma dimension=1 k=1.5 lambda=2.5
areSameObjects(const T & firstObject, const T & secondObject)
areDifferentObjects(const T & firstObject, const T & secondObject)
Distribution class=InverseGamma name=InverseGamma dimension=1 k=5.5 lambda=2.5
Distribution InverseGamma(k = 5.5, lambda = 2.5)
Elliptical = false
Continuous = true
oneRealization=class=Point name=Unnamed dimension=1 values=[0.0599153]
oneSample first=class=Point name=Unnamed dimension=1 values=[0.105001] last=class=Point name=Unnamed dimension=1 values=[0.114865]
mean=class=Point name=Unnamed dimension=1 values=[0.0892908]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.00236759]
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=[0.145455]
ddf     =class=Point name=Unnamed dimension=1 values=[-56.4599]
ddf (FD)=class=Point name=Unnamed dimension=1 values=[-56.4599]
log pdf=0.783883
pdf     =2.18996
pdf (FD)=2.18996
cdf=0.904561
ccdf=0.0954395
survival=0.0954395
Inverse survival=class=Point name=Unnamed dimension=1 values=[0.0406605]
Survival(inverse survival)=0.95
characteristic function=(0.999937,0.0129291)
log characteristic function=(2.03228e-05,0.0129292)
pdf gradient     =class=Point name=Unnamed dimension=2 values=[-1.31286,-2.40895]
pdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[-1.31286,-2.40895]
cdf gradient     =class=Point name=Unnamed dimension=2 values=[0.082705,0.127416]
cdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[0.082705,0.127416]
quantile=class=Point name=Unnamed dimension=1 values=[0.174871]
cdf(quantile)=0.95
Minimum volume interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[0.0280966] upper bound=class=Point name=Unnamed dimension=1 values=[0.177562] 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(InverseGamma(k = 5.5, lambda = 2.5)) gradientImplementation=MinimumVolumeLevelSetGradient(InverseGamma(k = 5.5, lambda = 2.5)) hessianImplementation=class=CenteredFiniteDifferenceHessian name=Unnamed epsilon=class=Point name=Unnamed dimension=1 values=[0.0001] evaluation=MinimumVolumeLevelSetEvaluation(InverseGamma(k = 5.5, lambda = 2.5)) level=34.4467
beta=1.09642e-15
Bilateral confidence interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[0.0364963] upper bound=class=Point name=Unnamed dimension=1 values=[0.209657] 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=[0] upper bound=class=Point name=Unnamed dimension=1 values=[0.174871] 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=[0.0406605] upper bound=class=Point name=Unnamed dimension=1 values=[50.1015] finite lower bound=[1] finite upper bound=[1]
beta=0.95
mean=class=Point name=Unnamed dimension=1 values=[0.0888889]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.0022575]
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=[[k : 5.5, lambda : 2.5]]
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=[0.222222]
standard moment n=2, value=class=Point name=Unnamed dimension=1 values=[0.0634921]
standard moment n=3, value=class=Point name=Unnamed dimension=1 values=[0.0253968]
standard moment n=4, value=class=Point name=Unnamed dimension=1 values=[0.0169312]
standard moment n=5, value=class=Point name=Unnamed dimension=1 values=[0.0338624]
Standard representative=InverseGamma(k = 5.5, lambda = 1)
standard deviation=class=Point name=Unnamed dimension=1 values=[0.0475131]
skewness=class=Point name=Unnamed dimension=1 values=[2.99333]
kurtosis=class=Point name=Unnamed dimension=1 values=[29.4]
Distribution class=InverseGamma name=InverseGamma dimension=1 k=15 lambda=2.5
Distribution InverseGamma(k = 15, lambda = 2.5)
Elliptical = false
Continuous = true
oneRealization=class=Point name=Unnamed dimension=1 values=[0.0272144]
oneSample first=class=Point name=Unnamed dimension=1 values=[0.0286215] last=class=Point name=Unnamed dimension=1 values=[0.0158049]
mean=class=Point name=Unnamed dimension=1 values=[0.0284817]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[6.38042e-05]
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=[0.0533333]
ddf     =class=Point name=Unnamed dimension=1 values=[-253.351]
ddf (FD)=class=Point name=Unnamed dimension=1 values=[-253.352]
log pdf=0.463518
pdf     =1.58966
pdf (FD)=1.58966
cdf=0.98974
ccdf=0.0102604
survival=0.0102604
Inverse survival=class=Point name=Unnamed dimension=1 values=[0.0182761]
Survival(inverse survival)=0.95
characteristic function=(0.999999,0.00152381)
log characteristic function=(-8.93075e-08,0.00152381)
pdf gradient     =class=Point name=Unnamed dimension=2 values=[-1.04829,-4.76897]
pdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[-1.04829,-4.76897]
cdf gradient     =class=Point name=Unnamed dimension=2 values=[0.00792151,0.0339127]
cdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[0.00792151,0.0339127]
quantile=class=Point name=Unnamed dimension=1 values=[0.0432604]
cdf(quantile)=0.95
Minimum volume interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[0.0154445] upper bound=class=Point name=Unnamed dimension=1 values=[0.0443646] 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(InverseGamma(k = 15, lambda = 2.5)) gradientImplementation=MinimumVolumeLevelSetGradient(InverseGamma(k = 15, lambda = 2.5)) hessianImplementation=class=CenteredFiniteDifferenceHessian name=Unnamed epsilon=class=Point name=Unnamed dimension=1 values=[0.0001] evaluation=MinimumVolumeLevelSetEvaluation(InverseGamma(k = 15, lambda = 2.5)) level=-1.89324
beta=6.64087
Bilateral confidence interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[0.0170288] upper bound=class=Point name=Unnamed dimension=1 values=[0.0476452] 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=[0] upper bound=class=Point name=Unnamed dimension=1 values=[0.0432604] 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=[0.0182761] upper bound=class=Point name=Unnamed dimension=1 values=[0.508519] finite lower bound=[1] finite upper bound=[1]
beta=0.95
mean=class=Point name=Unnamed dimension=1 values=[0.0285714]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[6.27943e-05]
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=[[k : 15, lambda : 2.5]]
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=[0.0714286]
standard moment n=2, value=class=Point name=Unnamed dimension=1 values=[0.00549451]
standard moment n=3, value=class=Point name=Unnamed dimension=1 values=[0.000457875]
standard moment n=4, value=class=Point name=Unnamed dimension=1 values=[4.1625e-05]
standard moment n=5, value=class=Point name=Unnamed dimension=1 values=[4.1625e-06]
Standard representative=InverseGamma(k = 15, lambda = 1)
standard deviation=class=Point name=Unnamed dimension=1 values=[0.00792429]
skewness=class=Point name=Unnamed dimension=1 values=[1.20185]
kurtosis=class=Point name=Unnamed dimension=1 values=[5.90909]
