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Distribution class=MeixnerDistribution name=MeixnerDistribution dimension=1 beta=1.5 alpha=0.5 delta=2.5 gamma=-0.5 logNormalizationFactor=-2.11357 b=0.492762 c=-0.56861 dc=1.37171
Distribution MeixnerDistribution(beta = 1.5, alpha = 0.5, delta = 2.5, gamma = -0.5)
Elliptical = False
Continuous = True
oneRealization= [2.06954]
Point= [1]
log pdf=-1.517348
pdf =0.219293
PDF gradient= [-0.0855978,0.0793061,-0.0152517,0.0605973]
cdf=0.640774
CDF gradient= [-0.219293,-0.4305,-0.1123,-0.219293]
ccdf=0.359226
characteristic function=(0.0679463313303-0.248507038511j)
log characteristic function=(-1.35623659307-1.30390135592j)
quantile= [3.39477]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[-2.27095]
Survival(inverseSurvival)=0.950000
entropy=1.961981
Minimum volume interval= [-2.90577, 3.94843]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.50547} with f=
MinimumVolumeLevelSetEvaluation(MeixnerDistribution(beta = 1.5, alpha = 0.5, delta = 2.5, gamma = -0.5))
beta= [0.0300325]
Bilateral confidence interval= [-2.80555, 4.06095]
beta= [0.95]
Unilateral confidence interval (lower tail)= [-18.5819, 3.39477]
beta= [0.95]
Unilateral confidence interval (upper tail)= [-2.27095, 24.6896]
beta= [0.95]
mean= [0.457532]
covariance= [[ 2.99587 ]]
parameters= [[beta : 1.5, alpha : 0.5, delta : 2.5, gamma : -0.5]]
Standard representative= MeixnerDistribution(beta = 1, alpha = 0.5, delta = 2.5, gamma = 0)
alpha=0.500000
beta=1.500000
delta=2.500000
gamma=-0.500000
standard deviation= [1.73086]
skewness= [0.221285]
kurtosis= [3.44897]
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