Testing class Beta
checkConstructorAndDestructor()
checkCopyConstructor()
streamObject(const T & anObject)
class=Beta name=Beta dimension=1 r=2 t=5 a=-1 b=2
streamObject(const T & anObject)
class=Beta name=Beta dimension=1 r=2 t=5 a=-1 b=2
areSameObjects(const T & firstObject, const T & secondObject)
areDifferentObjects(const T & firstObject, const T & secondObject)
Distribution class=Beta name=Beta dimension=1 r=2 t=5 a=-1 b=2
Distribution Beta(r = 2, t = 5, a = -1, b = 2)
Elliptical = false
Continuous = true
oneRealization=class=Point name=Unnamed dimension=1 values=[0.456966]
oneSample first=class=Point name=Unnamed dimension=1 values=[-0.504347] last=class=Point name=Unnamed dimension=1 values=[-0.367645]
mean=class=Point name=Unnamed dimension=1 values=[0.203901]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.365788]
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=[-0.444444]
ddf (FD)=class=Point name=Unnamed dimension=1 values=[-0.444444]
log pdf=-1.2164
pdf     =0.296296
pdf (FD)=0.296296
cdf=0.888889
ccdf=0.111111
survival=0.111111
Inverse survival=class=Point name=Unnamed dimension=1 values=[-0.707166]
Survival(inverse survival)=0.95
quantile=class=Point name=Unnamed dimension=1 values=[1.25419]
cdf(quantile)=0.95
quantile (tail)=class=Point name=Unnamed dimension=1 values=[-0.707166]
cdf (tail)=0.95
characteristic function=(0.817458,0.156352)
log characteristic function=(-0.183591,0.188983)
pdf gradient     =class=Point name=Unnamed dimension=4 values=[0.353525,-0.152675,0.246914,0.197531]
pdf gradient (FD)=class=Point name=Unnamed dimension=4 values=[0.353525,-0.152675,0.246914,0.197531]
cdf gradient     =class=Point name=Unnamed dimension=4 values=[-0.186185,0.0973767,-0.0987654,-0.197531]
cdf gradient (FD)=class=Point name=Unnamed dimension=4 values=[-0.186185,0.0973767,-0.0987654,-0.197531]
Minimum volume interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[-0.868627] upper bound=class=Point name=Unnamed dimension=1 values=[1.31692] 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(Beta(r = 2, t = 5, a = -1, b = 2)) gradientImplementation=MinimumVolumeLevelSetGradient(Beta(r = 2, t = 5, a = -1, b = 2)) hessianImplementation=class=CenteredFiniteDifferenceHessian name=Unnamed epsilon=class=Point name=Unnamed dimension=1 values=[0.0001] evaluation=MinimumVolumeLevelSetEvaluation(Beta(r = 2, t = 5, a = -1, b = 2)) level=1.83159
beta=0.160159
Bilateral confidence interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[-0.797242] upper bound=class=Point name=Unnamed dimension=1 values=[1.41764] 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=[-1] upper bound=class=Point name=Unnamed dimension=1 values=[1.25419] 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=[-0.707166] upper bound=class=Point name=Unnamed dimension=1 values=[2] finite lower bound=[1] finite upper bound=[1]
beta=0.95
mean=class=Point name=Unnamed dimension=1 values=[0.2]
standard deviation=class=Point name=Unnamed dimension=1 values=[0.6]
skewness=class=Point name=Unnamed dimension=1 values=[0.285714]
kurtosis=class=Point name=Unnamed dimension=1 values=[2.35714]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.36]
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=[[r : 2, t : 5, a : -1, b : 2]]
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=[-0.2]
standard moment n=2, value=class=Point name=Unnamed dimension=1 values=[0.2]
standard moment n=3, value=class=Point name=Unnamed dimension=1 values=[-0.0857143]
standard moment n=4, value=class=Point name=Unnamed dimension=1 values=[0.0857143]
standard moment n=5, value=class=Point name=Unnamed dimension=1 values=[-0.047619]
Standard representative=Beta(r = 2, t = 5, a = -1, b = 1)
