ade4 (version 1.01)

coinertia: Coinertia Analysis

Description

The coinertia analysis performs a double inertia analysis of two arrays.

Usage

coinertia(dudiX, dudiY, scannf = TRUE, nf = 2)
plot.coinertia (x, xax = 1, yax = 2, ...) 
print.coinertia (x, ...) 
summary.coinertia (object, ...)

Arguments

dudiX

a duality diagramproviding 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

Value

• 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 array)
• cw
  a numeric vector with the columns weigths (crossed array)
• tab
  a crossed array (CA)
• li
  Y col = CA row: coordinates
• l1
  Y col = CA row: normed scores
• co
  X col = CA column: coordinates
• c1
  X col = CA column: normed scores
• lX
  the row coordinates (X)
• mX
  the normed row scores (X)
• lY
  the row coordinates (Y)
• mY
  the normed row scores (Y)
• aX
  the axis onto co-inertia axis (X)
• aY
  the axis onto co-inertia axis (Y)

WARNING

IMPORTANT : dudi1 and dudi2 must have identical row weights.

References

Dol�dec, S. and Chessel, D. (1994) Co-inertia analysis: an alternative method for studying species-environment relationships. Freshwater Biology, 31, 277--294.

Examples

data(doubs)
dudi1 <- dudi.pca(doubs$mil, scale = TRUE, scan = FALSE, nf = 3)
dudi2 <- dudi.pca(doubs$poi, scale = FALSE, scan = FALSE, nf = 2)
coin1 <- coinertia(dudi1,dudi2, scan = FALSE, nf = 2)
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))
 
coin1
summary(coin1)
plot(coin1)