Testing class FisherSnedecor
checkConstructorAndDestructor()
checkCopyConstructor()
streamObject(const T & anObject)
class=FisherSnedecor name=FisherSnedecor dimension=1 d1=5.5 d2=10.5
streamObject(const T & anObject)
class=FisherSnedecor name=FisherSnedecor dimension=1 d1=5.5 d2=10.5
areSameObjects(const T & firstObject, const T & secondObject)
areDifferentObjects(const T & firstObject, const T & secondObject)
Distribution class=FisherSnedecor name=FisherSnedecor dimension=1 d1=5.5 d2=10.5
Distribution FisherSnedecor(d1 = 5.5, d2 = 10.5)
Elliptical = false
Continuous = true
oneRealization=class=Point name=Unnamed dimension=1 values=[1.85322]
oneSample first=class=Point name=Unnamed dimension=1 values=[2.55996] last=class=Point name=Unnamed dimension=1 values=[1.06184]
mean=class=Point name=Unnamed dimension=1 values=[1.24575]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.20146]
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=[-0.517181]
ddf (FD)=class=Point name=Unnamed dimension=1 values=[-0.517181]
log pdf=-0.659362
pdf     =0.517181
pdf (FD)=0.517181
cdf=0.531405
ccdf=0.468595
survival=0.468595
Inverse survival=class=Point name=Unnamed dimension=1 values=[0.230549]
Survival(inverse survival)=0.95
characteristic function=(0.385738,0.612601)
log characteristic function=(-0.323062,1.00884)
pdf gradient     =class=Point name=Unnamed dimension=2 values=[0.0333323,0.00890862]
pdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[0.0333323,0.00890862]
log-pdf gradient     =class=Point name=Unnamed dimension=2 values=[0.0644499,0.0172253]
log-pdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[0.0644499,0.0172253]
cdf gradient     =class=Point name=Unnamed dimension=2 values=[-0.0101307,0.00377782]
cdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[-0.0101307,0.00377782]
quantile=class=Point name=Unnamed dimension=1 values=[3.2027]
cdf(quantile)=0.95
Minimum volume interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[0.0385599] upper bound=class=Point name=Unnamed dimension=1 values=[3.21723] 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(FisherSnedecor(d1 = 5.5, d2 = 10.5)) gradientImplementation=MinimumVolumeLevelSetGradient(FisherSnedecor(d1 = 5.5, d2 = 10.5)) hessianImplementation=class=CenteredFiniteDifferenceHessian name=Unnamed epsilon=class=Point name=Unnamed dimension=1 values=[0.0001] evaluation=MinimumVolumeLevelSetEvaluation(FisherSnedecor(d1 = 5.5, d2 = 10.5)) level=3.14683
beta=0.0429883
Bilateral confidence interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[0.168551] upper bound=class=Point name=Unnamed dimension=1 values=[4.04601] 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=[3.2027] 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=[0.230549] upper bound=class=Point name=Unnamed dimension=1 values=[2048] finite lower bound=[1] finite upper bound=[1]
beta=0.95
mean=class=Point name=Unnamed dimension=1 values=[1.23529]
standard deviation=class=Point name=Unnamed dimension=1 values=[1.09323]
skewness=class=Point name=Unnamed dimension=1 values=[3.56105]
kurtosis=class=Point name=Unnamed dimension=1 values=[42.039]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.19515]
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=[[d1 : 5.5, d2 : 10.5]]
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=[1.23529]
standard moment n=2, value=class=Point name=Unnamed dimension=1 values=[2.7211]
standard moment n=3, value=class=Point name=Unnamed dimension=1 values=[10.9669]
standard moment n=4, value=class=Point name=Unnamed dimension=1 values=[96.309]
standard moment n=5, value=class=Point name=Unnamed dimension=1 values=[4964.29]
Standard representative=FisherSnedecor(d1 = 5.5, d2 = 10.5)
