| bca {ade4} | R Documentation |
Performs a particular case of a Principal Component Analysis with respect to Instrumental Variables (pcaiv), in which there is only a single factor as explanatory variable.
between(dudi, fac, scannf = TRUE, nf = 2) ## S3 method for class 'dudi' bca(x, fac, scannf = TRUE, nf = 2, ...)
dudi |
a duality diagram, object of class |
x |
a duality diagram, object of class |
fac |
a factor partitioning the rows of |
scannf |
a logical value indicating whether the eigenvalues barplot should be displayed |
nf |
if scannf FALSE, a numeric value indicating the number of kept axes |
... |
further arguments passed to or from other methods |
Returns a list of class dudi, subclass 'between' containing
tab |
a data frame class-variables containing the means per class for each variable |
cw |
a numeric vector of the column weigths |
lw |
a numeric vector of the class weigths |
eig |
a numeric vector with all the eigenvalues |
rank |
the rank of the analysis |
nf |
an integer value indicating the number of kept axes |
c1 |
a data frame with the column normed scores |
l1 |
a data frame with the class normed scores |
co |
a data frame with the column coordinates |
li |
a data frame with the class coordinates |
call |
the matching call |
ratio |
the bewteen-class inertia percentage |
ls |
a data frame with the row coordinates |
as |
a data frame containing the projection of inertia axes onto between axes |
To avoid conflict names with the base:::within function, the
function within is now deprecated and will be removed. To be
consistent, the between function is also deprecated and
is replaced by the method bca.dudi of the new generic bca function.
Daniel Chessel
Anne B Dufour anne-beatrice.dufour@univ-lyon1.fr
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.
data(meaudret)
pca1 <- dudi.pca(meaudret$env, scan = FALSE, nf = 4)
pca2 <- dudi.pca(meaudret$spe, scal = FALSE, scan = FALSE, nf = 4)
bet1 <- bca(pca1, meaudret$design$site, scan = FALSE, nf = 2)
bet2 <- bca(pca2, meaudret$design$site, scan = FALSE, nf = 2)
if(adegraphicsLoaded()) {
g1 <- s.class(pca1$li, meaudret$design$site, psub.text = "Principal Component Analysis (env)",
plot = F)
g2 <- s.class(pca2$li, meaudret$design$site, psub.text = "Principal Component Analysis (spe)",
plot = F)
g3 <- s.class(bet1$ls, meaudret$design$site, psub.text = "Between sites PCA (env)", plot = F)
g4 <- s.class(bet2$ls, meaudret$design$site, psub.text = "Between sites PCA (spe)", plot = F)
G <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2))
} else {
par(mfrow = c(2, 2))
s.class(pca1$li, meaudret$design$site, sub = "Principal Component Analysis (env)", csub = 1.75)
s.class(pca2$li, meaudret$design$site, sub = "Principal Component Analysis (spe)", csub = 1.75)
s.class(bet1$ls, meaudret$design$site, sub = "Between sites PCA (env)", csub = 1.75)
s.class(bet2$ls, meaudret$design$site, sub = "Between sites PCA (spe)", csub = 1.75)
par(mfrow = c(1, 1))
}
coib <- coinertia(bet1, bet2, scann = FALSE)
plot(coib)