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]
log pdf=-0.659362
pdf     =0.517181
pdf (FD)=0.517181
cdf=0.531405
ccdf=0.468595
characteristic function=(0.385738+0.612601j)
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]
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]
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]
quantile= class=Point name=Unnamed dimension=1 values=[3.2027]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.230549]
Survival(inverseSurvival)=0.950000
Minimum volume interval= [0.0385599, 3.21723]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.14683} with f=
MinimumVolumeLevelSetEvaluation(FisherSnedecor(d1 = 5.5, d2 = 10.5))
beta= [0.0429883]
Bilateral confidence interval= [0.168551, 4.04601]
beta= [0.95]
Unilateral confidence interval (lower tail)= [0, 3.2027]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.230549, 2048]
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]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[d1,d2] values=[5.5,10.5]]
standard moment n= 0  value= [1]
standard moment n= 1  value= [1.23529]
standard moment n= 2  value= [2.7211]
standard moment n= 3  value= [10.9669]
standard moment n= 4  value= [96.309]
standard moment n= 5  value= [4964.29]
Standard representative= FisherSnedecor(d1 = 5.5, d2 = 10.5)
