Testing class Uniform
checkConstructorAndDestructor()
checkCopyConstructor()
streamObject(const T & anObject)
class=Uniform name=Uniform dimension=1 a=-0.5 b=1.5
streamObject(const T & anObject)
class=Uniform name=Uniform dimension=1 a=-0.5 b=1.5
areSameObjects(const T & firstObject, const T & secondObject)
areDifferentObjects(const T & firstObject, const T & secondObject)
Distribution class=Uniform name=Uniform dimension=1 a=-0.5 b=1.5
Distribution Uniform(a = -0.5, b = 1.5)
Elliptical = true
Continuous = true
oneRealization=class=Point name=Unnamed dimension=1 values=[0.759753]
oneSample first=class=Point name=Unnamed dimension=1 values=[1.26561] last=class=Point name=Unnamed dimension=1 values=[0.349444]
mean=class=Point name=Unnamed dimension=1 values=[0.506426]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[0.339061]
Kolmogorov test for the generator, sample size=100 is accepted
Kolmogorov test for the generator, sample size=1000 is accepted
Point= class=Point name=Unnamed dimension=1 values=[1]
ddf     =class=Point name=Unnamed dimension=1 values=[0]
ddf (FD)=class=Point name=Unnamed dimension=1 values=[0]
log pdf=-0.693147
pdf     =0.5
pdf (FD)=0.5
cdf=0.75
ccdf=0.25
survival=0.25
Inverse survival=class=Point name=Unnamed dimension=1 values=[-0.4]
Survival(inverse survival)=0.95
characteristic function=(0.73846,0.403423)
log characteristic function=(-0.172604,0.5)
pdf gradient     =class=Point name=Unnamed dimension=2 values=[0.25,-0.25]
pdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[0.25,-0.25]
cdf gradient     =class=Point name=Unnamed dimension=2 values=[-0.125,-0.375]
cdf gradient (FD)=class=Point name=Unnamed dimension=2 values=[-0.125,-0.375]
quantile=class=Point name=Unnamed dimension=1 values=[1.4]
cdf(quantile)=0.95
Minimum volume interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[-0.45] upper bound=class=Point name=Unnamed dimension=1 values=[1.45] finite lower bound=[1] finite upper bound=[1]
threshold=0.95
Minimum volume level set=class=LevelSet name=Unnamed dimension=1 function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[x,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[1 * abs(x - (0.5))] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[1 * abs(x - (0.5))] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[x] outputVariablesNames=[y0] formulas=[1 * abs(x - (0.5))] level=0.95
beta=0.95
Bilateral confidence interval=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[-0.45] upper bound=class=Point name=Unnamed dimension=1 values=[1.45] finite lower bound=[1] finite upper bound=[1]
beta=0.95
Unilateral confidence interval (lower tail)=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[-0.5] upper bound=class=Point name=Unnamed dimension=1 values=[1.4] finite lower bound=[1] finite upper bound=[1]
beta=0.95
Unilateral confidence interval (upper tail)=class=Interval name=Unnamed dimension=1 lower bound=class=Point name=Unnamed dimension=1 values=[-0.4] upper bound=class=Point name=Unnamed dimension=1 values=[1.5] finite lower bound=[1] finite upper bound=[1]
beta=0.95
mean=class=Point name=Unnamed dimension=1 values=[0.5]
standard deviation=class=Point name=Unnamed dimension=1 values=[0.57735]
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=[0.333333]
correlation=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]
spearman=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]
kendall=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[1]
parameters=[[a : -0.5, b : 1.5]]
standard moment n=0, value=class=Point name=Unnamed dimension=1 values=[1]
standard moment n=1, value=class=Point name=Unnamed dimension=1 values=[0]
standard moment n=2, value=class=Point name=Unnamed dimension=1 values=[0.333333]
standard moment n=3, value=class=Point name=Unnamed dimension=1 values=[0]
standard moment n=4, value=class=Point name=Unnamed dimension=1 values=[0.2]
standard moment n=5, value=class=Point name=Unnamed dimension=1 values=[0]
Standard representative=Uniform(a = -1, b = 1)
