bca.coinertia: Between-class coinertia analysis

In ade4: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

Between-class coinertia analysis

Description

Performs a between-class analysis after a coinertia analysis

Usage

## S3 method for class 'coinertia'
bca(x, fac, scannf = TRUE, nf = 2, ...) 

Arguments

x	a coinertia analysis (object of class coinertia) obtained by the function coinertia
fac	a factor partitioning the rows in classes
scannf	a logical value indicating whether the eigenvalues barplot should be displayed
nf	if scannf FALSE, an integer indicating the number of kept axes
...	further arguments passed to or from other methods

Details

This analysis is equivalent to do a between-class analysis on each initial dudi, and a coinertia analysis on the two between analyses. This function returns additional outputs for the interpretation.

Value

An object of the class betcoi. Outputs are described by the print function

Note

To avoid conflict names with the base:::within function, the function within is now deprecated and removed. To be consistent, the betweencoinertia function is also deprecated and is replaced by the method bca.coinertia of the new generic bca function.

Author(s)

Stéphane Dray [e-mail] and Jean Thioulouse [e-mail]

References

Franquet E., Doledec S., and Chessel D. (1995) Using multivariate analyses for separating spatial and temporal effects within species-environment relationships. Hydrobiologia, 300, 425–431.

See Also

coinertia, bca

Examples

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)
coib <- coinertia(bet1, bet2, scannf = FALSE)

coi <- coinertia(pca1, pca2, scannf = FALSE, nf = 3)
coi.b <- bca(coi,meaudret$design$site, scannf = FALSE)
## coib and coi.b are equivalent

plot(coi.b)

ade4 documentation built on Feb. 16, 2023, 7:58 p.m.