Information Technology Reference
In-Depth Information
Ta b l e 4 . 5
CVA quality associated with CVA biplots of three
variable
Ocotea
data.
CVA quality with respect to canonical variables
Weighted
Unweighted I
Unweighted centred
Dim_1
63
.
013
73
.
277
74
.
837
Dim_2
100
.
000
100
.
000
100
.
000
Dim_3
100
.
000 100
.
000 100
.
000
CVA quality with respect to original variables
Weighted
Unweighted I
Unweighted centred
Dim_1
96
.
459
97
.
614
98
.
232
Dim_2
100
.
000
100
.
000
100
.
000
Dim_3
100
.
000
100
.
000
100
.
000
Ta b l e 4 . 6
Adequacies associated with CVA biplots of three-variable
Ocotea
data.
Axis adequacies
Weighted
Unweighted I
Unweighted centred
Ve s D
Ve s L
F i b L
Ve s D
Ve s L
F i b L
Ve s D
Ve s L
F i b L
Dim_1
0.000
0.139
0.926
0.000
0.147
0.918
0.006
0.117
0.948
Dim_2
0.933
0.416
0.978
0.933
0.416
0.978
0.933
0.416
0.978
Dim_3
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Ta b l e 4 . 7
Axis predictivities associated with CVA biplots of three-variable
Ocotea
data.
Axis predictivities
Weighted
Unweighted I
Unweighted centred
Ve s D
Ve s L
F i b L
Ve s D
Ve s L
F i b L
Ve s D
Ve s L
F i b L
Dim_1
0.190
0.170
0.995
0.297
0.225
0.995
0.219
0.335
1.000
Dim_2
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Dim_3
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Ta b l e 4 . 8
Class predictivities associated with CVA biplots of three-variable
Ocotea
data.
Class predictivities
Weighted
Unweighted I
Unweighted centred
Obul
Oken
Opor
Obul
Oken
Opor
Obul
Oken
Opor
Dim_1
0.137
0.962
0.394
0.151
0.969
0.375
0.213
0.982
0.724
Dim_2
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Dim_3
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
