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Distribution class=Trapezoidal name=Trapezoidal dimension=1 a=1 b=1.2 c=3 d=14 h=0.135135
Distribution Trapezoidal(a = 1, b = 1.2, c = 3, d = 14)
Mean= class=Point name=Unnamed dimension=1 values=[5.48108]
Covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[9.1428]
Elliptical = False
oneRealization= class=Point name=Unnamed dimension=1 values=[6.23752]
Point= class=Point name=Unnamed dimension=1 values=[1.1]
ddf = class=Point name=Unnamed dimension=1 values=[0.675676]
log pdf=-2.694627
pdf =0.067568
cdf=0.003378
ccdf=0.996622
characteristic function= (-0.115059431951+0.0386019620712j)
pdf gradient = class=Point name=Unnamed dimension=4 values=[-0.333272,-0.333272,-0.00456538,-0.00456538]
log-pdf gradient = class=Point name=Unnamed dimension=4 values=[-4.93243,-4.93243,-0.0675676,-0.0675676]
cdf gradient = class=Point name=Unnamed dimension=4 values=[-0.0504474,-0.0166636,-0.000228269,-0.000228269]
quantile= class=Point name=Unnamed dimension=1 values=[11.1469]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[1.47]
Survival(inverseSurvival)=0.950000
entropy=2.379858
Minimum volume interval= [1.05141, 11.1725]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.35999} with f=
MinimumVolumeLevelSetEvaluation(Trapezoidal(a = 1, b = 1.2, c = 3, d = 14))
beta= [0.0347356]
Bilateral confidence interval= [1.285, 11.9826]
beta= [0.95]
Unilateral confidence interval (lower tail)= [1, 11.1469]
beta= [0.95]
Unilateral confidence interval (upper tail)= [1.47, 14]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[5.48108]
standard deviation= class=Point name=Unnamed dimension=1 values=[3.02371]
skewness= class=Point name=Unnamed dimension=1 values=[0.548305]
kurtosis= class=Point name=Unnamed dimension=1 values=[2.39403]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[9.1428]
parameters= [class=PointWithDescription name=X0 dimension=4 description=[a,b,c,d] values=[1,1.2,3,14]]
Standard representative= Trapezoidal(a = -1, b = -0.969231, c = -0.692308, d = 1)
roughness= [0.101047]
Distribution class=Trapezoidal name=Trapezoidal dimension=1 a=1 b=1 c=3 d=14 h=0.133333
Distribution Trapezoidal(a = 1, b = 1, c = 3, d = 14)
Mean= class=Point name=Unnamed dimension=1 values=[5.42222]
Covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[9.27728]
Elliptical = False
oneRealization= class=Point name=Unnamed dimension=1 values=[5.89233]
Point= class=Point name=Unnamed dimension=1 values=[1.1]
ddf = class=Point name=Unnamed dimension=1 values=[0]
log pdf=-2.014903
pdf =0.133333
cdf=0.013333
ccdf=0.986667
characteristic function= (-0.108371008362+0.0503646282831j)
quantile= class=Point name=Unnamed dimension=1 values=[11.1277]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[1.375]
Survival(inverseSurvival)=0.950000
entropy=2.381570
Minimum volume interval= [1, 11.1277]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.35769} with f=
MinimumVolumeLevelSetEvaluation(Trapezoidal(a = 1, b = 1, c = 3, d = 14))
beta= [0.0348155]
Bilateral confidence interval= [1.1875, 11.969]
beta= [0.95]
Unilateral confidence interval (lower tail)= [1, 11.1277]
beta= [0.95]
Unilateral confidence interval (upper tail)= [1.375, 14]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[5.42222]
standard deviation= class=Point name=Unnamed dimension=1 values=[3.04586]
skewness= class=Point name=Unnamed dimension=1 values=[0.546649]
kurtosis= class=Point name=Unnamed dimension=1 values=[2.39301]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[9.27728]
parameters= [class=PointWithDescription name=X0 dimension=4 description=[a,b,c,d] values=[1,1,3,14]]
Standard representative= Trapezoidal(a = -1, b = -1, c = -0.692308, d = 1)
roughness= [0.100741]
Distribution class=Trapezoidal name=Trapezoidal dimension=1 a=1 b=1.2 c=1.2 d=14 h=0.153846
Distribution Trapezoidal(a = 1, b = 1.2, c = 1.2, d = 14)
Mean= class=Point name=Unnamed dimension=1 values=[5.4]
Covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[9.24667]
Elliptical = False
oneRealization= class=Point name=Unnamed dimension=1 values=[4.72556]
Point= class=Point name=Unnamed dimension=1 values=[1.1]
ddf = class=Point name=Unnamed dimension=1 values=[0.769231]
log pdf=-2.564949
pdf =0.076923
cdf=0.003846
ccdf=0.996154
characteristic function= (-0.1186605461+0.0558853713745j)
quantile= class=Point name=Unnamed dimension=1 values=[11.1156]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[1.42701]
Survival(inverseSurvival)=0.950000
entropy=2.371802
Minimum volume interval= [1.04472, 11.1378]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.36967} with f=
MinimumVolumeLevelSetEvaluation(Trapezoidal(a = 1, b = 1.2, c = 1.2, d = 14))
beta= [0.034401]
Bilateral confidence interval= [1.26265, 11.9604]
beta= [0.95]
Unilateral confidence interval (lower tail)= [1, 11.1156]
beta= [0.95]
Unilateral confidence interval (upper tail)= [1.42701, 14]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[5.4]
standard deviation= class=Point name=Unnamed dimension=1 values=[3.04083]
skewness= class=Point name=Unnamed dimension=1 values=[0.565227]
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=[9.24667]
parameters= [class=PointWithDescription name=X0 dimension=4 description=[a,b,c,d] values=[1,1.2,1.2,14]]
Standard representative= Trapezoidal(a = -1, b = -0.969231, c = -0.969231, d = 1)
roughness= [0.102564]
Distribution class=Trapezoidal name=Trapezoidal dimension=1 a=1 b=1 c=1 d=14 h=0.153846
Distribution Trapezoidal(a = 1, b = 1, c = 1, d = 14)
Mean= class=Point name=Unnamed dimension=1 values=[5.33333]
Covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[9.38889]
Elliptical = False
oneRealization= class=Point name=Unnamed dimension=1 values=[1.36614]
Point= class=Point name=Unnamed dimension=1 values=[1.1]
ddf = class=Point name=Unnamed dimension=1 values=[-0.0118343]
log pdf=-1.879524
pdf =0.152663
cdf=0.015325
ccdf=0.984675
characteristic function= (-0.110887732511+0.0691917799374j)
quantile= class=Point name=Unnamed dimension=1 values=[11.0931]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[1.32917]
Survival(inverseSurvival)=0.950000
entropy=2.371802
Minimum volume interval= [1, 11.0931]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.36967} with f=
MinimumVolumeLevelSetEvaluation(Trapezoidal(a = 1, b = 1, c = 1, d = 14))
beta= [0.034401]
Bilateral confidence interval= [1.16353, 11.9445]
beta= [0.95]
Unilateral confidence interval (lower tail)= [1, 11.0931]
beta= [0.95]
Unilateral confidence interval (upper tail)= [1.32917, 14]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[5.33333]
standard deviation= class=Point name=Unnamed dimension=1 values=[3.06413]
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=[9.38889]
parameters= [class=PointWithDescription name=X0 dimension=4 description=[a,b,c,d] values=[1,1,1,14]]
Standard representative= Trapezoidal(a = -1, b = -1, c = -1, d = 1)
roughness= [0.102564]
Distribution class=Trapezoidal name=Trapezoidal dimension=1 a=1 b=1.2 c=14 d=14 h=0.0775194
Distribution Trapezoidal(a = 1, b = 1.2, c = 14, d = 14)
Mean= class=Point name=Unnamed dimension=1 values=[7.54987]
Covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[13.8692]
Elliptical = False
oneRealization= class=Point name=Unnamed dimension=1 values=[5.84072]
Point= class=Point name=Unnamed dimension=1 values=[1.1]
ddf = class=Point name=Unnamed dimension=1 values=[0.387597]
log pdf=-3.250374
pdf =0.038760
cdf=0.001938
ccdf=0.998062
characteristic function= (-0.0444405891758+0.0919845543507j)
quantile= class=Point name=Unnamed dimension=1 values=[13.355]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[1.745]
Survival(inverseSurvival)=0.950000
entropy=2.561103
Minimum volume interval= [1.3725, 13.6275]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 2.55723} with f=
MinimumVolumeLevelSetEvaluation(Trapezoidal(a = 1, b = 1.2, c = 14, d = 14))
beta= [0.0775194]
Bilateral confidence interval= [1.4225, 13.6775]
beta= [0.95]
Unilateral confidence interval (lower tail)= [1, 13.355]
beta= [0.95]
Unilateral confidence interval (upper tail)= [1.745, 14]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[7.54987]
standard deviation= class=Point name=Unnamed dimension=1 values=[3.72413]
skewness= class=Point name=Unnamed dimension=1 values=[-0.000208124]
kurtosis= class=Point name=Unnamed dimension=1 values=[1.80029]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[13.8692]
parameters= [class=PointWithDescription name=X0 dimension=4 description=[a,b,c,d] values=[1,1.2,14,14]]
Standard representative= Trapezoidal(a = -1, b = -0.969231, c = 1, d = 1)
roughness= [0.0773191]
Distribution class=Trapezoidal name=Trapezoidal dimension=1 a=1 b=1 c=14 d=14 h=0.0769231
Distribution Trapezoidal(a = 1, b = 1, c = 14, d = 14)
Mean= class=Point name=Unnamed dimension=1 values=[7.5]
Covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[14.0833]
Elliptical = True
oneRealization= class=Point name=Unnamed dimension=1 values=[10.6537]
Point= class=Point name=Unnamed dimension=1 values=[1.1]
ddf = class=Point name=Unnamed dimension=1 values=[0]
log pdf=-2.564949
pdf =0.076923
cdf=0.007692
ccdf=0.992308
characteristic function= (-0.041125105127+0.0983600726093j)
quantile= class=Point name=Unnamed dimension=1 values=[13.35]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[1.65]
Survival(inverseSurvival)=0.950000
entropy=2.564949
Minimum volume interval= [1.325, 13.675]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 2.56495} with f=
MinimumVolumeLevelSetEvaluation(Trapezoidal(a = 1, b = 1, c = 14, d = 14))
beta= [0.0769231]
Bilateral confidence interval= [1.325, 13.675]
beta= [0.95]
Unilateral confidence interval (lower tail)= [1, 13.35]
beta= [0.95]
Unilateral confidence interval (upper tail)= [1.65, 14]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[7.5]
standard deviation= class=Point name=Unnamed dimension=1 values=[3.75278]
skewness= class=Point name=Unnamed dimension=1 values=[0]
kurtosis= class=Point name=Unnamed dimension=1 values=[1.8]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[14.0833]
parameters= [class=PointWithDescription name=X0 dimension=4 description=[a,b,c,d] values=[1,1,14,14]]
Standard representative= Trapezoidal(a = -1, b = -1, c = 1, d = 1)
roughness= [0.0769231]
Distribution class=Trapezoidal name=Trapezoidal dimension=1 a=1 b=14 c=14 d=14 h=0.153846
Distribution Trapezoidal(a = 1, b = 14, c = 14, d = 14)
Mean= class=Point name=Unnamed dimension=1 values=[9.66667]
Covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[9.38889]
Elliptical = False
oneRealization= class=Point name=Unnamed dimension=1 values=[13.4634]
Point= class=Point name=Unnamed dimension=1 values=[1.1]
ddf = class=Point name=Unnamed dimension=1 values=[0.0118343]
log pdf=-6.739337
pdf =0.001183
cdf=0.000059
ccdf=0.999941
characteristic function= (0.0286375222568+0.127528365281j)
quantile= class=Point name=Unnamed dimension=1 values=[13.6708]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[3.90689]
Survival(inverseSurvival)=0.950000
entropy=2.371802
Minimum volume interval= [3.90689, 14]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 3.36967} with f=
MinimumVolumeLevelSetEvaluation(Trapezoidal(a = 1, b = 14, c = 14, d = 14))
beta= [0.034401]
Bilateral confidence interval= [3.05548, 13.8365]
beta= [0.95]
Unilateral confidence interval (lower tail)= [1, 13.6708]
beta= [0.95]
Unilateral confidence interval (upper tail)= [3.90689, 14]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[9.66667]
standard deviation= class=Point name=Unnamed dimension=1 values=[3.06413]
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=[9.38889]
parameters= [class=PointWithDescription name=X0 dimension=4 description=[a,b,c,d] values=[1,14,14,14]]
Standard representative= Trapezoidal(a = -1, b = 1, c = 1, d = 1)
roughness= [0.102564]
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