| withinpca {ade4} | R Documentation |
performs a normed within Principal Component Analysis.
withinpca(df, fac, scaling = c("partial", "total"),
scannf = TRUE, nf = 2)
df |
a data frame with quantitative variables |
fac |
a factor distributing the rows of df in classes |
scaling |
a string of characters as a scaling option : if "partial", for each factor level, the sub-array is centred and normed. If "total", for each factor level, the sub-array is centred and the total array is then normed. |
scannf |
a logical value indicating whether the eigenvalues bar plot should be displayed |
nf |
if scannf FALSE, an integer indicating the number of kept axes |
returns a list of the sub-class within of class dudi. See within
Daniel Chessel
Anne B Dufour dufour@biomserv.univ-lyon1.fr
Bouroche, J. M. (1975) Analyse des données ternaires: la double analyse en composantes principales. Thèse de 3ème cycle, Université de Paris VI.
data(meaudret)
wit1 <- withinpca(meaudret$mil, meaudret$plan$dat,
scan = FALSE, scal = "partial")
kta1 <- ktab.within(wit1, colnames = rep(c("S1","S2","S3","S4","S5"), 4))
unclass(kta1)
# See pta
plot(wit1)
> library(ade4)
> ### Name: withinpca
> ### Title: Normed within Principal Component Analysis
> ### Aliases: withinpca
> ### Keywords: multivariate
>
> ### ** Examples
>
> data(meaudret)
> wit1 <- withinpca(meaudret$mil, meaudret$plan$dat,
+ scan = FALSE, scal = "partial")
> kta1 <- ktab.within(wit1, colnames = rep(c("S1","S2","S3","S4","S5"), 4))
> unclass(kta1)
$spring
S1 S2 S3 S4 S5
Temp -1.372813e+00 -0.3922323 -0.39223227 0.5883484 1.5689291
Debit -1.615156e+00 -0.4251482 -0.01830782 0.8157149 1.2428973
pH 2.041241e-01 -1.8371173 0.20412415 1.2247449 0.2041241
Condu 9.457838e-17 1.9069252 -0.47673129 -0.4767313 -0.9534626
Dbo5 -9.621078e-01 1.9351487 -0.41545565 -0.3061252 -0.2514600
Oxyd -6.364382e-01 1.9923283 -0.49808208 -0.4980821 -0.3597259
Ammo -7.376580e-01 1.9837018 -0.45854414 -0.4087024 -0.3787973
Nitra -5.281643e-01 -1.6155614 0.40389035 0.4038903 1.3359450
Phos -1.047323e+00 1.6189391 -1.06650488 0.1419449 0.3529441
$summer
S1 S2 S3 S4 S5
Temp -1.1666667 -1.1666667 0.5000000 1.33333333 0.5000000
Debit -1.2683846 -0.7763389 -0.2296214 0.86381368 1.4105312
pH 0.9354143 -1.4031215 -0.7349684 -0.06681531 1.2694909
Condu -1.5297323 0.9448347 1.1697953 0.04499213 -0.6298898
Dbo5 -1.0875080 1.4231586 0.6175971 0.21481639 -1.1680641
Oxyd -0.7664063 1.9508524 -0.2786932 -0.20901990 -0.6967330
Ammo -1.1379075 1.3255250 0.8424990 0.07982640 -1.1099429
Nitra -0.8553618 -1.4868370 0.4936988 0.69462267 1.1538773
Phos -1.6393299 0.6112322 1.1546918 0.48335936 -0.6099535
$autumn
S1 S2 S3 S4 S5
Temp -1.6035675 1.06904497 -0.26726124 1.06904497 -0.2672612
Debit -1.8766905 -0.08487545 0.66957300 0.95249116 0.3395018
pH 0.5619515 -1.31122014 -0.84292723 0.09365858 1.4985373
Condu -0.7012869 1.87009833 0.11688115 -0.35064344 -0.9350492
Dbo5 -0.6044785 1.97542987 -0.19199318 -0.57447961 -0.6044785
Oxyd -0.7363901 1.97092649 -0.23102435 -0.41151212 -0.5919999
Ammo -0.6470895 1.95761335 -0.09597377 -0.57374709 -0.6408030
Nitra -0.5674453 -1.62198962 1.13991221 0.83861383 0.2109089
Phos -1.1374069 1.70830946 0.47677844 -0.44686983 -0.6008112
$winter
S1 S2 S3 S4 S5
Temp 0.5000000 0.5000000 0.500000000 0.5000000 -2.0000000
Debit -1.5362076 -0.4891485 0.003125549 1.4330644 0.5891661
pH -1.8864844 0.6859943 0.685994341 0.6859943 -0.1714986
Condu -0.9819805 0.9274260 1.472970759 -0.7092081 -0.7092081
Dbo5 -1.0927369 1.2659029 1.027053299 -0.1373385 -1.0628807
Oxyd -0.9763927 1.2666716 1.134726600 -0.4486128 -0.9763927
Ammo -1.1833898 1.0449484 1.310452499 -0.3584306 -0.8135805
Nitra -1.9709202 0.4077766 0.577683516 0.2378697 0.7475904
Phos -1.0886790 0.4133145 1.744869109 -0.4175755 -0.6519291
$lw
[1] 1 1 1 1 1 1 1 1 1
$cw
[1] 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2
[20] 0.2
$blo
spring summer autumn winter
5 5 5 5
$TL
T L
1 1 1
2 1 2
3 1 3
4 1 4
5 1 5
6 1 6
7 1 7
8 1 8
9 1 9
10 2 1
11 2 2
12 2 3
13 2 4
14 2 5
15 2 6
16 2 7
17 2 8
18 2 9
19 3 1
20 3 2
21 3 3
22 3 4
23 3 5
24 3 6
25 3 7
26 3 8
27 3 9
28 4 1
29 4 2
30 4 3
31 4 4
32 4 5
33 4 6
34 4 7
35 4 8
36 4 9
$TC
T C
1 1 1
2 1 2
3 1 3
4 1 4
5 1 5
6 2 1
7 2 2
8 2 3
9 2 4
10 2 5
11 3 1
12 3 2
13 3 3
14 3 4
15 3 5
16 4 1
17 4 2
18 4 3
19 4 4
20 4 5
$T4
T 4
1 1 1
2 1 2
3 1 3
4 1 4
5 2 1
6 2 2
7 2 3
8 2 4
9 3 1
10 3 2
11 3 3
12 3 4
13 4 1
14 4 2
15 4 3
16 4 4
$call
ktab.within(dudiwit = wit1, colnames = rep(c("S1", "S2", "S3",
"S4", "S5"), 4))
$tabw
autumn spring summer winter
0.25 0.25 0.25 0.25
> # See pta
> plot(wit1)
> > > >