Distribution  class=Rice name=Rice dimension=1 sigma=5 nu=4
Distribution  Rice(sigma = 5, nu = 4)
Elliptical =  False
Continuous =  True
oneRealization= class=Point name=Unnamed dimension=1 values=[9.46867]
oneSample first= class=Point name=Unnamed dimension=1 values=[6.29291]  last= class=Point name=Unnamed dimension=1 values=[2.16415]
mean= class=Point name=Unnamed dimension=1 values=[7.26091]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[13.4082]
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]
pdf     = 0.0286533178617
pdf (FD)= 0.028653318
cdf= 0.0144246216851
pdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[-0.00771071,-0.00449313]
cdf gradient (FD)= class=Point name=Unnamed dimension=2 values=[-0.00390269,-0.00470084]
quantile= class=Point name=Unnamed dimension=1 values=[13.9273]
cdf(quantile)= 0.95
InverseSurvival= class=Point name=Unnamed dimension=1 values=[1.87781]
Survival(inverseSurvival)=0.950000
Minimum volume interval= [0.68836, 14.2519]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.91877} with f=
MinimumVolumeLevelSetEvaluation(Rice(sigma = 5, nu = 4))
beta= [0.0198656]
Bilateral confidence interval= [1.31981, 15.3859]
beta= [0.95]
Unilateral confidence interval (lower tail)= [0, 13.9273]
beta= [0.95]
Unilateral confidence interval (upper tail)= [1.87781, 63]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[7.23115]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[13.7104]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[sigma,nu] values=[5,4]]
standard moment n= 0  value= [1]
standard moment n= 1  value= [7.23115]
standard moment n= 2  value= [66]
standard moment n= 3  value= [704.457]
standard moment n= 4  value= [8456]
standard moment n= 5  value= [111488]
Standard representative= Rice(sigma = 5, nu = 4)
nu= 4.0
standard deviation= class=Point name=Unnamed dimension=1 values=[3.70276]
skewness= class=Point name=Unnamed dimension=1 values=[0.569607]
kurtosis= class=Point name=Unnamed dimension=1 values=[3.10633]
sigma= 5.0
