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Distribution class=LogUniform name=LogUniform dimension=1 aLog=-0.5 bLog=1.5 a=0.606531 b=4.48169
Distribution LogUniform(aLog = -0.5, bLog = 1.5)
Mean= class=Point name=Unnamed dimension=1 values=[1.93758]
Covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.1752]
Elliptical = False
oneRealization= class=Point name=Unnamed dimension=1 values=[2.13775]
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf = class=Point name=Unnamed dimension=1 values=[-0.5]
log pdf=-0.693147
pdf =0.500000
cdf=0.250000
ccdf=0.750000
characteristic function=-0.089620+0.531924j
log characteristic function=-0.617260+1.737711j
pdf gradient = class=Point name=Unnamed dimension=2 values=[0.25,-0.25]
cdf gradient = class=Point name=Unnamed dimension=2 values=[-0.375,-0.125]
quantile= class=Point name=Unnamed dimension=1 values=[4.0552]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.67032]
Survival(inverseSurvival)=0.950000
entropy=1.193147
Minimum volume interval= [0.606531, 4.0552]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 2.09315} with f=
MinimumVolumeLevelSetEvaluation(LogUniform(aLog = -0.5, bLog = 1.5))
beta= [0.123298]
Bilateral confidence interval= [0.637628, 4.26311]
beta= [0.95]
Unilateral confidence interval (lower tail)= [0.606531, 4.0552]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.67032, 4.48169]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[1.93758]
standard deviation= class=Point name=Unnamed dimension=1 values=[1.08407]
skewness= class=Point name=Unnamed dimension=1 values=[0.67539]
kurtosis= class=Point name=Unnamed dimension=1 values=[0.623015]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.1752]
parameters= [class=PointWithDescription name=X0 dimension=2 description=[aLog,bLog] values=[-0.5,1.5]]
Standard representative= LogUniform(aLog = -0.5, bLog = 1.5)
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