Between-Class RLQ analysis

Performs a particular RLQ analysis where a partition of sites (rows of R) is taken into account. The between-class RLQ analysis search for linear combinations of traits and environmental variables maximizing the covariances between the traits and the average environmental conditions of classes.

Usage

# S3 method for rlq
bca(x, fac, scannf = TRUE, nf = 2, ...)
# S3 method for betrlq
plot(x, xax = 1, yax = 2, ...)
# S3 method for betrlq
print(x, ...)

Arguments

x: an object of class rlq (created by the rlq function) for the bca.rlq function. An object of class betrlq for the print and plot functions
fac: a factor partitioning the rows of R
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
xax: the column number for the x-axis
yax: the column number for the y-axis
...: further arguments passed to or from other methods

Value

The bca.rlq function returns an object of class 'betrlq' (sub-class of 'dudi'). See the outputs of the print function for more details.

References

Wesuls, D., Oldeland, J. and Dray, S. (2012) Disentangling plant trait responses to livestock grazing from spatio-temporal variation: the partial RLQ approach. Journal of Vegetation Science, 23, 98--113.

Author

Stéphane Dray stephane.dray@univ-lyon1.fr

Examples

data(piosphere)
afcL <- dudi.coa(log(piosphere$veg + 1), scannf = FALSE)
acpR <- dudi.pca(piosphere$env, scannf = FALSE, row.w = afcL$lw)
acpQ <- dudi.hillsmith(piosphere$traits, scannf = FALSE, row.w =
  afcL$cw)
rlq1 <- rlq(acpR, afcL, acpQ, scannf = FALSE)

brlq1 <- bca(rlq1, fac = piosphere$habitat, scannf = FALSE)
brlq1
#> Between RLQ analysis
#> call: bca.rlq(x = rlq1, fac = piosphere$habitat, scannf = FALSE)
#> class: betrlq dudi 
#> 
#> $rank (rank): 3
#> $nf (axis saved): 2
#> 
#> eigen values: 1.726 0.5024 0.1789
#> 
#>   vector length mode    content                    
#> 1 $eig   3      numeric eigen values               
#> 2 $lw    25     numeric row weigths (crossed array)
#> 3 $cw    54     numeric col weigths (crossed array)
#> 
#>    data.frame nrow ncol content                           
#> 1  $tab       25   54   crossed array (CA)                
#> 2  $li        25   2    R col = CA row: coordinates       
#> 3  $l1        25   2    R col = CA row: normed scores     
#> 4  $co        54   2    Q col = CA column: coordinates    
#> 5  $c1        54   2    Q col = CA column: normed scores  
#> 6  $lR        4    2    class coordinates (R)             
#> 7  $lsR       378  2    supplementary row coordinates (R) 
#> 8  $mR        4    2    class normed scores (R)           
#> 9  $lQ        87   2    row coordinates (Q)               
#> 10 $mQ        87   2    normed row scores (Q)             
#> 11 $aR        2    2    axes onto between-RLQ axes (R)    
#> 12 $aQ        2    2    axes onto between-RLQ axes (Q)    
#> 13 $acR       2    2    RLQ axes onto between-RLQ axes (R)
#> 14 $acQ       2    2    RLQ axes onto between-RLQ axes (Q)
#> 
plot(brlq1)
#> Error in s.class(dfxy = brlq1$lsR, fac = piosphere$habitat, xax = 1, yax = 2,     plot = FALSE, storeData = TRUE, pos = -3, psub = list(text = "R row scores and classes"),     plabels = list(cex = 1.25)): non convenient selection for dfxy (can not be converted to dataframe)