Testing class Poisson
checkConstructorAndDestructor()
checkCopyConstructor()
streamObject(const T & anObject)
class=Poisson name=Poisson dimension=1 lambda=10
streamObject(const T & anObject)
class=Poisson name=Poisson dimension=1 lambda=10
areSameObjects(const T & firstObject, const T & secondObject)
areDifferentObjects(const T & firstObject, const T & secondObject)
Distribution class=Poisson name=Poisson dimension=1 lambda=10
Distribution Poisson(lambda = 10)
Elliptical = false
Continuous = false
oneRealization=class=Point name=Unnamed dimension=1 values=[14]
oneSample first=class=Point name=Unnamed dimension=1 values=[10] last=class=Point name=Unnamed dimension=1 values=[10]
mean=class=Point name=Unnamed dimension=1 values=[9.9873]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[9.93333]
Point= class=Point name=Unnamed dimension=1 values=[12]
log pdf=-2.35619
pdf     =0.0947803
pdf (FD)=0.0947803
cdf=0.791556
ccdf=0.208444
survival=0.208444
characteristic function=(0.127543,0.166617)
log characteristic function=(-1.56146,-5.36573)
generating function=(0.00068747,0.000599094)
log generating function=(-7,7)
pdf gradient     =class=Point name=Unnamed dimension=1 values=[0.0189561]
pdf gradient (FD)=class=Point name=Unnamed dimension=1 values=[0.0189561]
cdf gradient     =class=Point name=Unnamed dimension=1 values=[-0.0947803]
cdf gradient (FD)=class=Point name=Unnamed dimension=1 values=[-0.0947803]
quantile=class=Point name=Unnamed dimension=1 values=[15]
cdf(quantile)=0.95126
quantile (tail)=class=Point name=Unnamed dimension=1 values=[5]
cdf (tail)=0.932914
mean=class=Point name=Unnamed dimension=1 values=[10]
standard deviation=class=Point name=Unnamed dimension=1 values=[3.16228]
skewness=class=Point name=Unnamed dimension=1 values=[0.316228]
kurtosis=class=Point name=Unnamed dimension=1 values=[3.1]
covariance=class=CovarianceMatrix dimension=1 implementation=class=MatrixImplementation name=Unnamed rows=1 columns=1 values=[10]
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=[[lambda : 10]]
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=[10]
standard moment n=2, value=class=Point name=Unnamed dimension=1 values=[110]
standard moment n=3, value=class=Point name=Unnamed dimension=1 values=[1310]
standard moment n=4, value=class=Point name=Unnamed dimension=1 values=[16710]
standard moment n=5, value=class=Point name=Unnamed dimension=1 values=[226510]
Standard representative=Poisson(lambda = 10)
probabilities=class=Point name=Unnamed dimension=43 values=[4.53999e-05,0.000453999,0.00227,0.00756665,0.0189166,0.0378333,0.0630555,0.0900792,0.112599,0.12511,0.12511,0.113736,0.0947803,0.0729079,0.0520771,0.0347181,0.0216988,0.012764,0.00709111,0.00373216,0.00186608,0.00088861,0.000403914,0.000175615,7.31728e-05,2.92691e-05,1.12573e-05,4.16939e-06,1.48907e-06,5.13472e-07,1.71157e-07,5.5212e-08,1.72537e-08,5.22841e-09,1.53777e-09,4.39362e-10,1.22045e-10,3.29851e-11,8.6803e-12,2.22572e-12,5.56429e-13,1.35715e-13,3.2313e-14]
