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ade4 (version 1.6-2)

rlq: RLQ analysis

Description

RLQ analysis performs a double inertia analysis of two arrays (R and Q) with a link expressed by a contingency table (L). The rows of L correspond to the rows of R and the columns of L correspond to the rows of Q.

Usage

rlq(dudiR, dudiL, dudiQ, scannf = TRUE, nf = 2)
## S3 method for class 'rlq':
print(x, ...)
## S3 method for class 'rlq':
plot(x, xax = 1, yax = 2, ...)
## S3 method for class 'rlq':
summary(object, ...)
## S3 method for class 'rlq':
randtest(xtest,nrepet = 999, modeltype = 6,...)

Arguments

dudiR
a duality diagram providing from one of the functions dudi.hillsmith, dudi.pca, ...
dudiL
a duality diagram of the function dudi.coa
dudiQ
a duality diagram providing from one of the functions dudi.hillsmith, 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
an rlq object
xax
the column number for the x-axis
yax
the column number for the y-axis
object
an rlq object
xtest
an rlq object
nrepet
the number of permutations
modeltype
the model used to permute data(2: permute rows of R, 4: permute rows of Q, 5: permute both, 6: sequential approach, see ter Braak et al. 2012)
...
further arguments passed to or from other methods

Value

  • Returns a list of class 'dudi', sub-class 'rlq' containing:
  • callcall
  • rankrank
  • nfa numeric value indicating the number of kept axes
  • RVa numeric value, the RV coefficient
  • eiga numeric vector with all the eigenvalues
  • lwa numeric vector with the rows weigths (crossed array)
  • cwa numeric vector with the columns weigths (crossed array)
  • taba crossed array (CA)
  • liR col = CA row: coordinates
  • l1R col = CA row: normed scores
  • coQ col = CA column: coordinates
  • c1Q col = CA column: normed scores
  • lRthe row coordinates (R)
  • mRthe normed row scores (R)
  • lQthe row coordinates (Q)
  • mQthe normed row scores (Q)
  • aRthe axis onto co-inertia axis (R)
  • aQthe axis onto co-inertia axis (Q)

WARNING

IMPORTANT : row weights for dudiR and dudiQ must be taken from dudiL.

References

Doledec, S., Chessel, D., ter Braak, C.J.F. and Champely, S. (1996) Matching species traits to environmental variables: a new three-table ordination method. Environmental and Ecological Statistics, 3, 143--166.

Dray, S., Pettorelli, N., Chessel, D. (2002) Matching data sets from two different spatial samplings. Journal of Vegetation Science, 13, 867--874.

Dray, S. and Legendre, P. (2008) Testing the species traits-environment relationships: the fourth-corner problem revisited. Ecology, 89, 3400--3412.

ter Braak, C., Cormont, A., Dray, S. (2012) Improved testing of species traits-environment relationships in the fourth corner problem. Ecology, 93, 1525--1526.

See Also

coinertia, fourthcorner

Examples

Run this code
data(aviurba)
   coa1 <- dudi.coa(aviurba$fau, scannf = FALSE, nf = 2)
   dudimil <- dudi.hillsmith(aviurba$mil, scannf = FALSE, nf = 2, row.w = coa1$lw)
   duditrait <- dudi.hillsmith(aviurba$traits, scannf = FALSE, nf = 2, row.w = coa1$cw)
   rlq1 <- rlq(dudimil, coa1, duditrait, scannf = FALSE, nf = 2)
   plot(rlq1)
   summary(rlq1)
   randtest(rlq1)
   fourthcorner.rlq(rlq1,type="Q.axes")
   fourthcorner.rlq(rlq1,type="R.axes")

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