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Testing class CombinationsDistribution
checkConstructorAndDestructor()
checkCopyConstructor()
streamObject(const T & anObject)
class=CombinationsDistribution name=CombinationsDistribution dimension=5 k=5 n=12
streamObject(const T & anObject)
class=CombinationsDistribution name=CombinationsDistribution dimension=5 k=5 n=12
areSameObjects(const T & firstObject, const T & secondObject)
areDifferentObjects(const T & firstObject, const T & secondObject)
Distribution class=CombinationsDistribution name=CombinationsDistribution dimension=5 k=5 n=12
Distribution CombinationsDistribution(k = 5, n = 12)
Elliptical = false
Continuous = false
oneRealization=class=Point name=Unnamed dimension=5 values=[0,3,4,8,9]
oneSample first=class=Point name=Unnamed dimension=5 values=[1,2,4,8,9] last=class=Point name=Unnamed dimension=5 values=[0,5,7,9,11]
mean=class=Point name=Unnamed dimension=5 values=[1.1363,3.3014,5.478,7.6634,9.8246]
covariance=class=CovarianceMatrix dimension=5 implementation=class=MatrixImplementation name=Unnamed rows=5 columns=5 values=[1.7443,1.39566,1.04845,0.701149,0.354242,1.39566,2.82124,2.10584,1.40299,0.702136,1.04845,2.10584,3.19264,2.11881,1.05895,0.701149,1.40299,2.11881,2.86319,1.42,0.354242,0.702136,1.05895,1.42,1.77381]
Point= class=Point name=Unnamed dimension=5 values=[1,3,6,8,10]
log-pdf =-6.67456
log-pdf ref =-6.67456
pdf =0.00126263
pdf ref =0.00126263
cdf =0.286616
cdf ref =0.286616
ccdf =0.713384
ccdf ref =0.713384
quantile =class=Point name=Unnamed dimension=5 values=[11,11,11,11,11]
quantile ref =class=Point name=Unnamed dimension=5 values=[4,7,9,10,11]
cdf(quantile)=1
entropy =6.67456
entropy ref =6.67456
entropy (MC)=6.67456
mean =class=Point name=Unnamed dimension=5 values=[1.16667,3.33333,5.5,7.66667,9.83333]
mean ref =class=Point name=Unnamed dimension=5 values=[1.16667,3.33333,5.5,7.66667,9.83333]
covariance =class=CovarianceMatrix dimension=5 implementation=class=MatrixImplementation name=Unnamed rows=5 columns=5 values=[1.80556,1.44444,1.08333,0.722222,0.361111,1.44444,2.88889,2.16667,1.44444,0.722222,1.08333,2.16667,3.25,2.16667,1.08333,0.722222,1.44444,2.16667,2.88889,1.44444,0.361111,0.722222,1.08333,1.44444,1.80556]
covariance ref =class=CovarianceMatrix dimension=5 implementation=class=MatrixImplementation name=Unnamed rows=5 columns=5 values=[1.80556,1.44444,1.08333,0.722222,0.361111,1.44444,2.88889,2.16667,1.44444,0.722222,1.08333,2.16667,3.25,2.16667,1.08333,0.722222,1.44444,2.16667,2.88889,1.44444,0.361111,0.722222,1.08333,1.44444,1.80556]
correlation =class=CovarianceMatrix dimension=5 implementation=class=MatrixImplementation name=Unnamed rows=5 columns=5 values=[1,0.632456,0.447214,0.316228,0.2,0.632456,1,0.707107,0.5,0.316228,0.447214,0.707107,1,0.707107,0.447214,0.316228,0.5,0.707107,1,0.632456,0.2,0.316228,0.447214,0.632456,1]
correlation ref =class=CorrelationMatrix dimension=5 implementation=class=MatrixImplementation name=Unnamed rows=5 columns=5 values=[1,0.632456,0.447214,0.316228,0.2,0.632456,1,0.707107,0.5,0.316228,0.447214,0.707107,1,0.707107,0.447214,0.316228,0.5,0.707107,1,0.632456,0.2,0.316228,0.447214,0.632456,1]
parameters=[[n : 12],[n : 12],[n : 12],[n : 12],[n : 12],[k : 5, n : 12]]
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