| coinertia {ade4} | R Documentation |
The coinertia analysis performs a double inertia analysis of two tables.
coinertia(dudiX, dudiY, scannf = TRUE, nf = 2) ## S3 method for class 'coinertia' plot(x, xax = 1, yax = 2, ...) ## S3 method for class 'coinertia' print(x, ...) ## S3 method for class 'coinertia' summary(object, ...)
dudiX |
a duality diagram providing from one of the functions dudi.coa, dudi.pca, ... |
dudiY |
a duality diagram providing from one of the functions dudi.coa, dudi.pca, ... |
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 |
x, object |
an object of class 'coinertia' |
xax, yax |
the numbers of the x-axis and the y-axis |
... |
further arguments passed to or from other methods |
Returns a list of class 'coinertia', sub-class 'dudi' containing:
call |
call |
rank |
rank |
nf |
a numeric value indicating the number of kept axes |
RV |
a numeric value, the RV coefficient |
eig |
a numeric vector with all the eigenvalues |
lw |
a numeric vector with the rows weigths (crossed table) |
cw |
a numeric vector with the columns weigths (crossed table) |
tab |
a crossed table (CT) |
li |
CT row scores (cols of dudiY) |
l1 |
Principal components (loadings for cols of dudiY) |
co |
CT col scores (cols of dudiX) |
c1 |
Principal axes (cols of dudiX) |
lX |
Row scores (rows of dudiX) |
mX |
Normed row scores (rows of dudiX) |
lY |
Row scores (rows of dudiY) |
mY |
Normed row scores (rows of dudiY) |
aX |
Correlations between dudiX axes and coinertia axes |
aY |
Correlations between dudiY axes and coinertia axes |
IMPORTANT : dudi1 and dudi2 must have identical row weights.
Daniel Chessel
Anne B Dufour anne-beatrice.dufour@univ-lyon1.fr
Dolédec, S. and Chessel, D. (1994) Co-inertia analysis: an alternative method for studying species-environment relationships.
Freshwater Biology, 31, 277–294.
Dray, S., Chessel, D. and J. Thioulouse (2003) Co-inertia analysis and the linking of the ecological data tables. Ecology, 84, 11, 3078–3089.
data(doubs)
dudi1 <- dudi.pca(doubs$env, scale = TRUE, scan = FALSE, nf = 3)
dudi2 <- dudi.pca(doubs$fish, scale = FALSE, scan = FALSE, nf = 2)
coin1 <- coinertia(dudi1,dudi2, scan = FALSE, nf = 2)
coin1
summary(coin1)
if(adegraphicsLoaded()) {
g1 <- s.arrow(coin1$l1, plab.cex = 0.7)
g2 <- s.arrow(coin1$c1, plab.cex = 0.7)
g3 <- s.corcircle(coin1$aX, plot = FALSE)
g4 <- s.corcircle(coin1$aY, plot = FALSE)
cbindADEg(g3, g4, plot = TRUE)
g5 <- plot(coin1)
} else {
s.arrow(coin1$l1, clab = 0.7)
s.arrow(coin1$c1, clab = 0.7)
par(mfrow = c(1,2))
s.corcircle(coin1$aX)
s.corcircle(coin1$aY)
par(mfrow = c(1,1))
plot(coin1)
}