ade4 (version 1.5-2)

bca: Between-Class Analysis

Description

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.

Usage

between(dudi, fac, scannf = TRUE, nf = 2)
## S3 method for class 'dudi':
bca(x, fac, scannf = TRUE, nf = 2, \dots)

Arguments

dudi

a duality diagram, object of class dudi obtained from the functions dudi.coa, dudi.pca,...

x

a duality diagram, object of class dudi from one of the functions dudi.coa, dudi.pca,...

fac

a factor partitioning the rows of dudi$tab in classes

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

Value

• 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

encoding

latin1

References

Dol�dec, 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)
par(mfrow = c(2,2))
pca1 <- dudi.pca(meaudret$env, scan = FALSE, nf = 4)
s.class(pca1$li, meaudret$design$site,
    sub = "Principal Component Analysis (env)", csub = 1.75)
pca2 <- dudi.pca(meaudret$spe, scal = FALSE, scan = FALSE, nf = 4)
s.class(pca2$li, meaudret$design$site,
    sub = "Principal Component Analysis (spe)", csub = 1.75)
bet1 <- bca(pca1, meaudret$design$site, scan = FALSE, nf = 2)
bet2 <- bca(pca2, meaudret$design$site, scan = FALSE, nf = 2)
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)