Testing class NormalGamma
checkConstructorAndDestructor()
checkCopyConstructor()
streamObject(const T & anObject)
class=NormalGamma name=NormalGamma mu=1 kappa=2 alpha=3 beta=4
streamObject(const T & anObject)
class=NormalGamma name=NormalGamma mu=1 kappa=2 alpha=3 beta=4
areSameObjects(const T & firstObject, const T & secondObject)
areDifferentObjects(const T & firstObject, const T & secondObject)
Distribution class=NormalGamma name=NormalGamma mu=1 kappa=2 alpha=3 beta=4
Distribution NormalGamma(mu=1, kappa=2, alpha=3, beta=4)
Elliptical = false
Continuous = true
oneRealization=class=Point name=Unnamed dimension=2 values=[0.52143,0.947065]
oneSample first=class=Point name=Unnamed dimension=2 values=[-0.149655,1.80011] last=class=Point name=Unnamed dimension=2 values=[1.22109,0.934319]
mean=class=Point name=Unnamed dimension=2 values=[0.988408,0.752078]
covariance=class=CovarianceMatrix dimension=2 implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[0.979077,0.0089155,0.0089155,0.191922]
Point= class=Point name=Unnamed dimension=2 values=[1.5,1.5]
ddf     =class=Point name=Unnamed dimension=2 values=[-0.127136,-0.218956]
ddf (FD)=class=Point name=Unnamed dimension=2 values=[-0.127136,-0.218956]
log pdf=-2.46797
pdf     =0.0847571
pdf (FD)=0.0847571cdf=0.198227
ccdf=0.801773
survival=0.0105935
Inverse survival=class=Point name=Unnamed dimension=2 values=[-0.941338,0.160511]
Survival(inverse survival)=0.95
pdf gradient     =class=Point name=Unnamed dimension=4 values=[0.127136,0.00529732,0.0736518,-0.0635678]
pdf gradient (FD)=class=Point name=Unnamed dimension=4 values=[0.127136,0.00529732,0.0736518,-0.0635678]
cdf gradient     =class=Point name=Unnamed dimension=4 values=[-0.349393,0.0436741,0.0135182,-0.00130662]
cdf gradient (FD)=class=Point name=Unnamed dimension=4 values=[-0.349393,0.0436741,0.0135182,-0.00130662]
quantile=class=Point name=Unnamed dimension=2 values=[4.59228,2.55849]
cdf(quantile)=0.997715
Minimum volume interval=class=Interval name=Unnamed dimension=2 lower bound=class=Point name=Unnamed dimension=2 values=[-1.80326,0.0390431] upper bound=class=Point name=Unnamed dimension=2 values=[3.80326,2.00954] finite lower bound=[1,1] finite upper bound=[1,1]
threshold=0.986085
Minimum volume level set=class=LevelSet name=Unnamed dimension=2 function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x0,x1,y0] evaluationImplementation=MinimumVolumeLevelSetEvaluation(NormalGamma(mu=1, kappa=2, alpha=3, beta=4)) gradientImplementation=MinimumVolumeLevelSetGradient(NormalGamma(mu=1, kappa=2, alpha=3, beta=4)) hessianImplementation=class=CenteredFiniteDifferenceHessian name=Unnamed epsilon=class=Point name=Unnamed dimension=2 values=[0.0001,0.0001] evaluation=MinimumVolumeLevelSetEvaluation(NormalGamma(mu=1, kappa=2, alpha=3, beta=4)) level=3.73137
beta=0.0239601
Bilateral confidence interval=class=Interval name=Unnamed dimension=2 lower bound=class=Point name=Unnamed dimension=2 values=[-1.77733,0.0966867] upper bound=class=Point name=Unnamed dimension=2 values=[3.77733,2.20341] finite lower bound=[1,1] finite upper bound=[1,1]
beta=0.985531
Unilateral confidence interval (lower tail)=class=Interval name=Unnamed dimension=2 lower bound=class=Point name=Unnamed dimension=2 values=[-368.978,0] upper bound=class=Point name=Unnamed dimension=2 values=[4.59228,2.55849] finite lower bound=[1,1] finite upper bound=[1,1]
beta=0.997715
Unilateral confidence interval (upper tail)=class=Interval name=Unnamed dimension=2 lower bound=class=Point name=Unnamed dimension=2 values=[-0.941338,0.160511] upper bound=class=Point name=Unnamed dimension=2 values=[370.978,9.72932] finite lower bound=[1,1] finite upper bound=[1,1]
beta=0.972528
mean=class=Point name=Unnamed dimension=2 values=[1,0.75]
standard deviation=class=Point name=Unnamed dimension=2 values=[1,0.433013]
skewness=class=Point name=Unnamed dimension=2 values=[0,1.1547]
kurtosis=class=Point name=Unnamed dimension=2 values=[6,5]
covariance=class=CovarianceMatrix dimension=2 implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[1,0,0,0.1875]
correlation=class=CovarianceMatrix dimension=2 implementation=class=MatrixImplementation name=Unnamed rows=2 columns=2 values=[1,0,0,1]
parameters=[[mu : 1, kappa : 2, alpha : 3, beta : 4]]
standard moment n=0, value=class=Point name=Unnamed dimension=2 values=[1,1]
standard moment n=1, value=class=Point name=Unnamed dimension=2 values=[1,0.75]
standard moment n=2, value=class=Point name=Unnamed dimension=2 values=[2,0.75]
standard moment n=3, value=class=Point name=Unnamed dimension=2 values=[4,0.9375]
standard moment n=4, value=class=Point name=Unnamed dimension=2 values=[13,1.40625]
standard moment n=5, value=class=Point name=Unnamed dimension=2 values=[41,2.46094]
Standard representative=NormalGamma(mu=1, kappa=2, alpha=3, beta=4)
