wrda {douconca} | R Documentation |
Performs a weighted redundancy analysis
Description
wrda
is formula-based implementation of weighted redundancy analysis.
Usage
wrda(formula, response, data, weights = rep(1, nrow(data)), verbose = TRUE)
Arguments
formula |
one or two-sided formula for the rows (samples) with row
predictors in |
response |
matrix or data frame of the abundance data (dimension
n x m). Rownames of |
data |
matrix or data frame of the row predictors, with rows
corresponding to those in |
weights |
row weights (a vector). If not specified unit weights are used. |
verbose |
logical for printing a simple summary (default: TRUE) |
Details
The algorithm is a modified version of published R-code for weighted redundancy analysis (ter Braak, 2022).
In the current implementation, formula
should contain variable names
as is, i.e. transformations of variables in the formulas gives
an error ('undefined columns selected') when the scores
function is applied.
Compared to rda
, wrda
does not have residual
axes, i.e. no SVD or PCA of the residuals is performed.
Value
All scores in the dcca
object are in scaling "sites"
(1):
the scaling with Focus on Case distances.
References
ter Braak C.J.F. and P. Ć milauer (2018). Canoco reference manual and user's guide: software for ordination (version 5.1x). Microcomputer Power, Ithaca, USA, 536 pp.
Oksanen, J., et al. (2022) vegan: Community Ecology Package. R package version 2.6-4. https://CRAN.R-project.org/package=vegan.
See Also
scores.wrda
, anova.wrda
,
print.wrda
Examples
data("dune_trait_env")
# rownames are carried forward in results
rownames(dune_trait_env$comm) <- dune_trait_env$comm$Sites
response <- dune_trait_env$comm[, -1] # must delete "Sites"
w <- rep(1, 20)
w[1:10] <- 8
w[17:20] <- 0.5
object <- wrda(formula = ~ A1 + Moist + Mag + Use + Condition(Manure),
response = response,
data = dune_trait_env$envir,
weights = w)
object # Proportions equal to those Canoco 5.15
mod_scores <- scores(object, display = "all")
scores(object, which_cor = c("A1", "X_lot"), display = "cor")
anova(object)