Testing class LogUniform
checkConstructorAndDestructor()
checkCopyConstructor()
streamObject(const T & anObject)
class=LogUniform name=LogUniform dimension=1 aLog=-0.5 bLog=1.5 a=0.606531 b=4.48169
streamObject(const T & anObject)
class=LogUniform name=LogUniform dimension=1 aLog=-0.5 bLog=1.5 a=0.606531 b=4.48169
areSameObjects(const T & firstObject, const T & secondObject)
areDifferentObjects(const T & firstObject, const T & secondObject)
Distribution class=LogUniform name=LogUniform dimension=1 aLog=-0.5 bLog=1.5 a=0.606531 b=4.48169
Distribution LogUniform(aLog = -0.5, bLog = 1.5)
Elliptical = false
Continuous = true
oneRealization=class=Point name=Unnamed dimension=1 values=[2.13775]
oneSample first=class=Point name=Unnamed dimension=1 values=[3.54526] last=class=Point name=Unnamed dimension=1 values=[1.41828]
mean=class=Point name=Unnamed dimension=1 values=[1.95442]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.20332]
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=[-0.5]
ddf (FD)=class=Point name=Unnamed dimension=1 values=[-0.5]
log pdf=-0.693147
pdf     =0.5
pdf (FD)=0.5
cdf=0.25
ccdf=0.75
survival=0.75
Inverse survival=class=Point name=Unnamed dimension=1 values=[0.67032]
Survival(inverse survival)=0.95
pdf gradient     =class=Point name=Unnamed dimension=2 values=[0.25,-0.25]
pdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[0.25,-0.25]
cdf gradient     =class=Point name=Unnamed dimension=2 values=[-0.375,-0.125]
cdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[-0.375,-0.125]
characteristic function=(-0.0896196,0.531924)
log characteristic function=(-0.61726,1.73771)
quantile=class=Point name=Unnamed dimension=1 values=[4.0552]
cdf(quantile)=0.95
Minimum volume interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[0.606531] upper bound=class=Point name=Unnamed dimension=1 values=[4.0552] 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(LogUniform(aLog = -0.5, bLog = 1.5)) gradientImplementation=MinimumVolumeLevelSetGradient(LogUniform(aLog = -0.5, bLog = 1.5)) hessianImplementation=class=CenteredFiniteDifferenceHessian name=Unnamed epsilon=class=Point name=Unnamed dimension=1 values=[0.0001] evaluation=MinimumVolumeLevelSetEvaluation(LogUniform(aLog = -0.5, bLog = 1.5)) level=2.09315
beta=0.123298
Bilateral confidence interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[0.637628] upper bound=class=Point name=Unnamed dimension=1 values=[4.26311] 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=[0.606531] upper bound=class=Point name=Unnamed dimension=1 values=[4.0552] 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=[0.67032] upper bound=class=Point name=Unnamed dimension=1 values=[4.48169] finite lower bound=[1] finite upper bound=[1]
beta=0.95
mean=class=Point name=Unnamed dimension=1 values=[1.93758]
standard deviation=class=Point name=Unnamed dimension=1 values=[1.08407]
skewness=class=Point name=Unnamed dimension=1 values=[0.67539]
kurtosis=class=Point name=Unnamed dimension=1 values=[0.623015]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.1752]
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=[[aLog : -0.5, bLog : 1.5]]
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=[1.93758]
standard moment n=2, value=class=Point name=Unnamed dimension=1 values=[4.92941]
standard moment n=3, value=class=Point name=Unnamed dimension=1 values=[14.9657]
standard moment n=4, value=class=Point name=Unnamed dimension=1 values=[50.4117]
standard moment n=5, value=class=Point name=Unnamed dimension=1 values=[180.796]
Standard representative=LogUniform(aLog = -0.5, bLog = 1.5)
