wca {ade4} | R Documentation |
Within-Class Analysis
Description
Performs a particular case of an Orthogonal Principal Component Analysis with respect to Instrumental Variables (orthopcaiv), in which there is only a single factor as covariable.
Usage
## S3 method for class 'dudi'
wca(x, fac, scannf = TRUE, nf = 2, ...)
Arguments
x |
a duality diagram, object of class |
fac |
a factor partitioning the rows of |
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 |
... |
further arguments passed to or from other methods |
Value
Returns a list of the sub-class within
in the class dudi
tab |
a data frame containing the transformed data (substraction of the class mean) |
call |
the matching call |
nf |
number of kept axes |
rank |
the rank of the analysis |
ratio |
percentage of within-class inertia |
eig |
a numeric vector containing the eigenvalues |
lw |
a numeric vector of row weigths |
cw |
a numeric vector of column weigths |
tabw |
a numeric vector of class weigths |
fac |
the factor defining the classes |
li |
data frame row coordinates |
l1 |
data frame row normed scores |
co |
data frame column coordinates |
c1 |
data frame column normed scores |
ls |
data frame supplementary row coordinates |
as |
data frame inertia axis onto within axis |
Note
To avoid conflict names with the base:::within
function, the
function within
is now deprecated and removed. It
is replaced by the method wca.dudi
of the new generic wca
function.
Author(s)
Daniel Chessel
Anne-Béatrice Dufour anne-beatrice.dufour@univ-lyon1.fr
References
Benzécri, J. P. (1983) Analyse de l'inertie intra-classe par l'analyse d'un
tableau de correspondances. Les Cahiers de l'Analyse des données, 8, 351–358.
Dolédec, S. and Chessel, D. (1987) Rythmes saisonniers et composantes stationnelles
en milieu aquatique I- Description d'un plan d'observations complet par projection de
variables. Acta Oecologica, Oecologia Generalis, 8, 3, 403–426.
Examples
data(meaudret)
pca1 <- dudi.pca(meaudret$env, scan = FALSE, nf = 4)
wit1 <- wca(pca1, meaudret$design$site, scan = FALSE, nf = 2)
if(adegraphicsLoaded()) {
g1 <- s.traject(pca1$li, meaudret$design$site, psub.text = "Principal Component Analysis",
plines.lty = 1:nlevels(meaudret$design$site), psub.cex = 1.5, plot = FALSE)
g2 <- s.traject(wit1$li, meaudret$design$site,
psub.text = "Within site Principal Component Analysis",
plines.lty = 1:nlevels(meaudret$design$site), psub.cex = 1.5, plot = FALSE)
g3 <- s.corcircle (wit1$as, plot = FALSE)
G <- ADEgS(list(g1, g2, g3), layout = c(2, 2))
} else {
par(mfrow = c(2, 2))
s.traject(pca1$li, meaudret$design$site, sub = "Principal Component Analysis", csub = 1.5)
s.traject(wit1$li, meaudret$design$site, sub = "Within site Principal Component Analysis",
csub = 1.5)
s.corcircle (wit1$as)
par(mfrow = c(1,1))
}
plot(wit1)