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Distribution class=Rice name=Rice dimension=1 beta=5 nu=4
Distribution Rice(beta = 5, nu = 4)
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[9.46867]
Point= class=Point name=Unnamed dimension=1 values=[1]
pdf = 0.0286533178617
cdf= 0.0144246216851
pdf gradient = class=Point name=Unnamed dimension=2 values=[-0.00771071,-0.00449313]
cdf gradient = class=Point name=Unnamed dimension=2 values=[-0.00390269,-0.00228496]
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
entropy=2.680547
Minimum volume interval= [0.68836, 14.2519]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.91877} with f=
MinimumVolumeLevelSetEvaluation(Rice(beta = 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=[beta,nu] values=[5,4]]
Standard representative= Rice(beta = 1, nu = 0)
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]
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