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Distribution class=NonCentralStudent name=NonCentralStudent dimension=1 nu=7.2 delta=4.8 gamma=-3.7
Distribution NonCentralStudent(nu = 7.2, delta = 4.8, gamma = -3.7)
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[4.76055]
oneSample first= class=Point name=Unnamed dimension=1 values=[3.3233] last= class=Point name=Unnamed dimension=1 values=[3.54549]
mean= class=Point name=Unnamed dimension=1 values=[1.6744]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[4.22198]
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf = class=Point name=Unnamed dimension=1 values=[-0.0278822]
log pdf=-1.409597
pdf =0.244242
cdf=0.426086
ccdf=0.573914
pdf gradient = class=Point name=Unnamed dimension=3 values=[0.0110231,-0.00328889,0.0278822]
cdf gradient = class=Point name=Unnamed dimension=3 values=[0.0041357,-0.246592,-0.244242]
quantile= class=Point name=Unnamed dimension=1 values=[5.47724]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[-0.864277]
Survival(inverseSurvival)=0.950000
entropy=2.01
Minimum volume interval= [-1.61544, 5.7747]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.75705} with f=
MinimumVolumeLevelSetEvaluation(NonCentralStudent(nu = 7.2, delta = 4.8, gamma = -3.7))
beta= [0.0233525]
Bilateral confidence interval= [-1.17995, 6.75359]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[1.68455]
standard deviation= class=Point name=Unnamed dimension=1 values=[2.07189]
skewness= class=Point name=Unnamed dimension=1 values=[1.67602]
kurtosis= class=Point name=Unnamed dimension=1 values=[10.0582]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[4.29272]
parameters= [class=PointWithDescription name=X0 dimension=3 description=[nu,delta,gamma] values=[7.2,4.8,-3.7]]
Standard representative= NonCentralStudent(nu = 7.2, delta = 4.8, gamma = 0)
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