1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
|
distribution= class=PythonDistribution name=ChaospyDistribution
realization= [3.06001]
sample= [ v0 ]
0 : [ 3.778 ]
1 : [ 3.48188 ]
2 : [ 3.34014 ]
3 : [ 2.68415 ]
4 : [ 2.68409 ]
pdf= 0.4
cdf= 0.12
mean= [3.16667]
mean(sampling)= [3.15869]
std= [0.424918]
std(sampling)= [0.423824]
skewness= [-0.422404]
skewness(sampling)= [-0.40352]
kurtosis= [2.4]
kurtosis(sampling)= [2.37795]
moment(1)= [3.16667]
moment(2)= [10.2083]
moment(3)= [33.4375]
moment(4)= [111.088]
range= [2, 4]
quantile= [2.6]
quantile (tail)= [3.65359]
scalar quantile=2.6
scalar quantile (tail)=3.65359
distribution= class=PythonDistribution name=ChaospyDistribution
realization= [0.902645]
sample= [ v0 ]
0 : [ 2.97919 ]
1 : [ 1.9802 ]
2 : [ 1.56111 ]
3 : [ 0.172315 ]
4 : [ 0.172219 ]
pdf= 0.200395
cdf= 0.888298
mean= [1.28571]
mean(sampling)= [1.26516]
std= [1.01267]
std(sampling)= [1.00695]
skewness= [0.0711194]
skewness(sampling)= [0.0875428]
kurtosis= [2.26575]
kurtosis(sampling)= [2.26804]
moment(1)= [1.28571]
moment(2)= [2.67857]
moment(3)= [6.15476]
moment(4)= [15.6667]
range= [-1, 4]
quantile= [2.6]
quantile (tail)= [-0.0162159]
scalar quantile=2.6
scalar quantile (tail)=-0.0162159
distribution= class=PythonDistribution name=ChaospyDistribution
realization= [3.06001,2.97919]
sample= [ v0 v1 ]
0 : [ 3.48188 0.250487 ]
1 : [ 3.34014 1.5869 ]
2 : [ 2.68415 1.20294 ]
3 : [ 2.68409 2.49248 ]
4 : [ 2.41743 -0.479908 ]
pdf= 0.080158
cdf= 0.106596
mean= [3.16667,1.28571]
mean(sampling)= [3.15861,1.3021]
std= [0.424918,1.01267]
std(sampling)= [0.423782,1.01734]
skewness= [-0.422404,0.0711194]
skewness(sampling)= [-0.403407,0.0619493]
kurtosis= [2.4,2.26575]
kurtosis(sampling)= [2.37814,2.27103]
range= [2, 4]
[-1, 4]
|
