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Distribution class=Beta name=Beta dimension=1 r=2 t=5 a=-1 b=2
Distribution Beta(r = 2, t = 5, a = -1, b = 2)
Elliptical = False
Continuous = True
oneRealization= class=NumericalPoint name=Unnamed dimension=1 values=[0.456966]
oneSample first= class=NumericalPoint name=Unnamed dimension=1 values=[-0.504347] last= class=NumericalPoint name=Unnamed dimension=1 values=[-0.367645]
mean= class=NumericalPoint name=Unnamed dimension=1 values=[0.203901]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.365788]
Kolmogorov test for the generator, sample size= 100 is accepted
Kolmogorov test for the generator, sample size= 1000 is accepted
Point= class=NumericalPoint name=Unnamed dimension=1 values=[1]
ddf = class=NumericalPoint name=Unnamed dimension=1 values=[-0.444444]
ddf (FD)= class=NumericalPoint name=Unnamed dimension=1 values=[-0.444444]
log pdf=-1.216395
pdf =0.296296
pdf (FD)=0.296296
cdf=0.888889
ccdf=0.111111
pdf gradient = class=NumericalPoint name=Unnamed dimension=4 values=[0.353525,-0.152675,0.246914,0.197531]
pdf gradient (FD)= class=NumericalPoint name=Unnamed dimension=4 values=[0.353525,-0.152675,0.246914,0.197531]
cdf gradient = class=NumericalPoint name=Unnamed dimension=4 values=[-0.186185,0.0973767,-0.0987654,-0.197531]
cdf gradient (FD)= class=NumericalPoint name=Unnamed dimension=4 values=[-0.186185,0.0973767,-0.0987654,-0.197531]
quantile= class=NumericalPoint name=Unnamed dimension=1 values=[1.25419]
cdf(quantile)=0.950000
mean= class=NumericalPoint name=Unnamed dimension=1 values=[0.2]
standard deviation= class=NumericalPoint name=Unnamed dimension=1 values=[0.6]
skewness= class=NumericalPoint name=Unnamed dimension=1 values=[0.285714]
kurtosis= class=NumericalPoint name=Unnamed dimension=1 values=[2.35714]
covariance= class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.36]
parameters= [class=NumericalPointWithDescription name=marginal 1 dimension=4 description=[r,t,a,b] values=[2,5,-1,2]]
standard moment n= 0 value= [1]
standard moment n= 1 value= [-0.2]
standard moment n= 2 value= [0.2]
standard moment n= 3 value= [-0.0857143]
standard moment n= 4 value= [0.0857143]
standard moment n= 5 value= [-0.047619]
Standard representative= Beta(r = 2, t = 5, a = -1, b = 1)
mu=0.200000
sigma=0.600000
r from (mu, sigma)=2.000000
t from (mu, sigma)=5.000000
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