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Testing class Chi
checkConstructorAndDestructor()
checkCopyConstructor()
streamObject(const T & anObject)
class=Chi name=Chi dimension=1 nu=1.5
streamObject(const T & anObject)
class=Chi name=Chi dimension=1 nu=1.5
areSameObjects(const T & firstObject, const T & secondObject)
areDifferentObjects(const T & firstObject, const T & secondObject)
Distribution class=Chi name=Chi dimension=1 nu=1.5
Distribution Chi(nu = 1.5)
Elliptical = false
Continuous = true
oneRealization=class=Point name=Unnamed dimension=1 values=[1.66733]
oneSample first=class=Point name=Unnamed dimension=1 values=[1.58636] last=class=Point name=Unnamed dimension=1 values=[1.02264]
mean=class=Point name=Unnamed dimension=1 values=[1.04589]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.399002]
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=[-0.294304]
log pdf=-0.529994
pdf =0.588608
pdf (FD)=0.588608
cdf=0.527937
ccdf=0.472063
survival=0.472063
Inverse survival=class=Point name=Unnamed dimension=1 values=[0.182299]
Survival(inverse survival)=0.95
characteristic function=(0.433496,0.694719)
log characteristic function=(-0.199826,1.01293)
pdf gradient =class=Point name=Unnamed dimension=1 values=[0.115577]
pdf gradient (FD)=class=Point name=Unnamed dimension=1 values=[0.115577]
cdf gradient =class=Point name=Unnamed dimension=1 values=[-0.291714]
cdf gradient (FD)=class=Point name=Unnamed dimension=1 values=[-0.291714]
quantile=class=Point name=Unnamed dimension=1 values=[2.23164]
cdf(quantile)=0.95
Minimum volume interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[0.0147509] upper bound=class=Point name=Unnamed dimension=1 values=[2.24137] 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,-logPDF] evaluationImplementation=MinimumVolumeLevelSetEvaluation(Chi(nu = 1.5)) gradientImplementation=MinimumVolumeLevelSetGradient(Chi(nu = 1.5)) hessianImplementation=class=CenteredFiniteDifferenceHessian name=Unnamed epsilon=class=Point name=Unnamed dimension=1 values=[0.0001] evaluation=MinimumVolumeLevelSetEvaluation(Chi(nu = 1.5)) level=2.13833
beta=0.117852
Bilateral confidence interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[0.114512] upper bound=class=Point name=Unnamed dimension=1 values=[2.50516] 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=[2.23164] 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=[0.182299] upper bound=class=Point name=Unnamed dimension=1 values=[7.89498] finite lower bound=[1] finite upper bound=[1]
beta=0.95
entropy=0.878173
entropy (MC)=0.877773
mean=class=Point name=Unnamed dimension=1 values=[1.04605]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.40578]
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=[[nu : 1.5]]
Standard representative=Chi(nu = 1.5)
nu=1.5
standard deviation=class=Point name=Unnamed dimension=1 values=[0.637009]
skewness=class=Point name=Unnamed dimension=1 values=[0.762585]
kurtosis=class=Point name=Unnamed dimension=1 values=[3.42425]
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