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Distribution Triangular(a = -0.5, m = 1.5, b = 2.5)
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[1.44403]
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf = class=Point name=Unnamed dimension=1 values=[0.333333]
log pdf=-0.693147
pdf =0.500000
cdf=0.375000
ccdf=0.625000
characteristic function= (0.312305424736+0.758322070069j)
pdf gradient = class=Point name=Unnamed dimension=3 values=[0.0833333,-0.25,-0.166667]
cdf gradient = class=Point name=Unnamed dimension=3 values=[-0.1875,-0.1875,-0.125]
quantile= class=Point name=Unnamed dimension=1 values=[0.724745]
cdf(quantile)=0.250000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.0477226]
Survival(inverseSurvival)=0.950000
entropy=0.905465
Minimum volume interval= [-0.0527864, 2.27639]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 1.90333} with f=
MinimumVolumeLevelSetEvaluation(Triangular(a = -0.5, m = 1.5, b = 2.5))
beta= [0.149071]
Bilateral confidence interval= [-0.112702, 2.22614]
beta= [0.95]
Unilateral confidence interval (lower tail)= [-0.5, 2.1127]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.0477226, 2.5]
beta= [0.95]
Point= class=Point name=Unnamed dimension=1 values=[2]
ddf = class=Point name=Unnamed dimension=1 values=[-0.666667]
log pdf=-1.098612
pdf =0.333333
cdf=0.916667
ccdf=0.083333
pdf gradient = class=Point name=Unnamed dimension=3 values=[0.111111,0.333333,0.222222]
cdf gradient = class=Point name=Unnamed dimension=3 values=[-0.0277778,-0.0833333,-0.222222]
quantile= class=Point name=Unnamed dimension=1 values=[2.1127]
cdf(quantile)=0.950000
mean= class=Point name=Unnamed dimension=1 values=[1.16667]
standard deviation= class=Point name=Unnamed dimension=1 values=[0.62361]
skewness= class=Point name=Unnamed dimension=1 values=[-0.305441]
kurtosis= class=Point name=Unnamed dimension=1 values=[2.4]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.388889]
parameters= [class=PointWithDescription name=X0 dimension=3 description=[a,m,b] values=[-0.5,1.5,2.5]]
Distribution Triangular(a = -0.5, m = -0.5, b = 2.5)
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[0.606457]
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf = class=Point name=Unnamed dimension=1 values=[-0.222222]
log pdf=-1.098612
pdf =0.333333
cdf=0.750000
ccdf=0.250000
characteristic function= (0.692667287389+0.345522222881j)
quantile= class=Point name=Unnamed dimension=1 values=[-0.0980762]
cdf(quantile)=0.250000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[-0.424038]
Survival(inverseSurvival)=0.950000
entropy=0.905465
Minimum volume interval= [-0.5, 1.82918]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 1.90333} with f=
MinimumVolumeLevelSetEvaluation(Triangular(a = -0.5, m = -0.5, b = 2.5))
beta= [0.149071]
Bilateral confidence interval= [-0.462263, 2.02566]
beta= [0.95]
Unilateral confidence interval (lower tail)= [-0.5, 1.82918]
beta= [0.95]
Unilateral confidence interval (upper tail)= [-0.424038, 2.5]
beta= [0.95]
Point= class=Point name=Unnamed dimension=1 values=[2]
ddf = class=Point name=Unnamed dimension=1 values=[-0.222222]
log pdf=-2.197225
pdf =0.111111
cdf=0.972222
ccdf=0.027778
quantile= class=Point name=Unnamed dimension=1 values=[1.82918]
cdf(quantile)=0.950000
mean= class=Point name=Unnamed dimension=1 values=[0.5]
standard deviation= class=Point name=Unnamed dimension=1 values=[0.707107]
skewness= class=Point name=Unnamed dimension=1 values=[0.565685]
kurtosis= class=Point name=Unnamed dimension=1 values=[2.4]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.5]
parameters= [class=PointWithDescription name=X0 dimension=3 description=[a,m,b] values=[-0.5,-0.5,2.5]]
Distribution Triangular(a = -0.5, m = 2.5, b = 2.5)
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[1.58512]
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf = class=Point name=Unnamed dimension=1 values=[0.222222]
log pdf=-1.098612
pdf =0.333333
cdf=0.250000
ccdf=0.750000
characteristic function= (0.0259311677499+0.773628562078j)
quantile= class=Point name=Unnamed dimension=1 values=[1]
cdf(quantile)=0.250000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[0.17082]
Survival(inverseSurvival)=0.950000
entropy=0.905465
Minimum volume interval= [0.17082, 2.5]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 1.90333} with f=
MinimumVolumeLevelSetEvaluation(Triangular(a = -0.5, m = 2.5, b = 2.5))
beta= [0.149071]
Bilateral confidence interval= [-0.0256584, 2.46226]
beta= [0.95]
Unilateral confidence interval (lower tail)= [-0.5, 2.42404]
beta= [0.95]
Unilateral confidence interval (upper tail)= [0.17082, 2.5]
beta= [0.95]
Point= class=Point name=Unnamed dimension=1 values=[2]
ddf = class=Point name=Unnamed dimension=1 values=[0.222222]
log pdf=-0.587787
pdf =0.555556
cdf=0.694444
ccdf=0.305556
quantile= class=Point name=Unnamed dimension=1 values=[2.42404]
cdf(quantile)=0.950000
mean= class=Point name=Unnamed dimension=1 values=[1.5]
standard deviation= class=Point name=Unnamed dimension=1 values=[0.707107]
skewness= class=Point name=Unnamed dimension=1 values=[-0.565685]
kurtosis= class=Point name=Unnamed dimension=1 values=[2.4]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.5]
parameters= [class=PointWithDescription name=X0 dimension=3 description=[a,m,b] values=[-0.5,2.5,2.5]]
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