[R] Princomp(), prcomp() and loadings()
F.Tusell
etptupaf at bs.ehu.es
Wed Nov 3 17:06:22 CET 2004
In comparing the results of princomp and prcomp I find:
1. The reported standard deviations are similar but about 1% from
each other, which seems well above round-off error.
2. princomp returns what I understand are variances and cumulative
variances accounted for by each principal component which are
all equal. "SS loadings" is always 1.
3. Same happens after the loadings are varimax-rotated, which in
general should alter the proportions of variance accounted by
each component.
It looks as if the loadings() function were expecting the eigenvectors
to be normalized to the corresponding eigenvalue.
Transcript and version information follow signature. Thank you for any
clues.
ft.
--
Fernando TUSELL e-mail:
Departamento de EconometrÃa y EstadÃstica etptupaf at bs.ehu.es
Facultad de CC.EE. y Empresariales Tel: (+34)94.601.3733
Avenida Lendakari Aguirre, 83 Fax: (+34)94.601.3754
E-48015 BILBAO (Spain) Secr: (+34)94.601.3740
----------------------------------------------------------------------
> pca.1 <- prcomp(USArrests)
> pca.1
Standard deviations:
[1] 83.732400 14.212402 6.489426 2.482790
Rotation:
PC1 PC2 PC3 PC4
Murder 0.04170432 -0.04482166 0.07989066 -0.99492173
Assault 0.99522128 -0.05876003 -0.06756974 0.03893830
UrbanPop 0.04633575 0.97685748 -0.20054629 -0.05816914
Rape 0.07515550 0.20071807 0.97408059 0.07232502
> pca.2 <- princomp(USArrests)
> pca.2
Call:
princomp(x = USArrests)
Standard deviations:
Comp.1 Comp.2 Comp.3 Comp.4
82.890847 14.069560 6.424204 2.457837
4 variables and 50 observations.
> summary(pca.2)
Importance of components:
Comp.1 Comp.2 Comp.3 Comp.4
Standard deviation 82.8908472 14.06956001 6.424204055 2.4578367034
Proportion of Variance 0.9655342 0.02781734 0.005799535 0.0008489079
Cumulative Proportion 0.9655342 0.99335156 0.999151092 1.0000000000
> loadings(pca.2)
Loadings:
Comp.1 Comp.2 Comp.3 Comp.4
Murder 0.995
Assault -0.995
UrbanPop -0.977 -0.201
Rape -0.201 0.974
Comp.1 Comp.2 Comp.3 Comp.4
SS loadings 1.00 1.00 1.00 1.00
Proportion Var 0.25 0.25 0.25 0.25
Cumulative Var 0.25 0.50 0.75 1.00
> varimax(pca.2$loadings[,1:3])
$loadings
Loadings:
Comp.1 Comp.2 Comp.3
Murder
Assault -0.998
UrbanPop -0.997
Rape 0.995
Comp.1 Comp.2 Comp.3
SS loadings 1.00 1.00 1.00
Proportion Var 0.25 0.25 0.25
Cumulative Var 0.25 0.50 0.75
$rotmat
[,1] [,2] [,3]
[1,] 0.99211386 0.03604908 -0.1200439
[2,] -0.05442524 0.98664663 -0.1535132
[3,] 0.11290692 0.15883603 0.9808278
> R.Version()
$platform
[1] "i386-pc-linux-gnu"
$arch
[1] "i386"
$os
[1] "linux-gnu"
$system
[1] "i386, linux-gnu"
$status
[1] ""
$major
[1] "2"
$minor
[1] "0.0"
$year
[1] "2004"
$month
[1] "10"
$day
[1] "04"
$language
[1] "R"
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