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Distribution class=WeibullMax name=WeibullMax dimension=1 beta=2 alpha=1.5 gamma=-0.5
Distribution WeibullMax(beta = 2, alpha = 1.5, gamma = -0.5)
Elliptical = False
Continuous = True
oneRealization= class=Point name=Unnamed dimension=1 values=[-2.49188]
Point= class=Point name=Unnamed dimension=1 values=[-1]
ddf = class=Point name=Unnamed dimension=1 values=[-0.206835]
log pdf=-1.105829
pdf =0.330936
cdf=0.882497
pdf gradient = class=Point name=Unnamed dimension=3 values=[-0.217177,-0.180804,0.206835]
cdf gradient = class=Point name=Unnamed dimension=3 values=[0.0827341,0.152925,-0.330936]
quantile= class=Point name=Unnamed dimension=1 values=[-0.776103]
cdf(quantile)=0.950000
InverseSurvival= class=Point name=Unnamed dimension=1 values=[-4.65622]
Survival(inverseSurvival)=0.950000
entropy=1.480087
Minimum volume interval= [-4.66304, -0.510263]
threshold= [0.95]
Minimum volume level set= {x | f(x) <= 2.92424} with f=
MinimumVolumeLevelSetEvaluation(WeibullMax(beta = 2, alpha = 1.5, gamma = -0.5))
beta= [0.0537054]
Bilateral confidence interval= [-5.27485, -0.672444]
beta= [0.95]
Unilateral confidence interval (lower tail)= [-20.7578, -0.776103]
beta= [0.95]
Unilateral confidence interval (upper tail)= [-4.65622, -0.5]
beta= [0.95]
mean= class=Point name=Unnamed dimension=1 values=[-2.30549]
standard deviation= class=Point name=Unnamed dimension=1 values=[1.22587]
skewness= class=Point name=Unnamed dimension=1 values=[-1.07199]
kurtosis= class=Point name=Unnamed dimension=1 values=[4.3904]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1.50276]
parameters= [class=PointWithDescription name=X0 dimension=3 description=[beta,alpha,gamma] values=[2,1.5,-0.5]]
Standard representative= WeibullMax(beta = 1, alpha = 1.5, gamma = 0)
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