| ps_quantize | R Documentation |
Generates a randomized version of a phylospatial object by extracting the
tip community matrix, permuting it using nullcat::quantize(), and rebuilding
the phylospatial object using the permuted tip matrix.
ps_quantize(ps, wt_row = NULL, wt_col = NULL, ...)
ps |
Object of class |
wt_row, wt_col |
Optional square numeric weight matrices controlling which pairs of
rows (sites) or columns (species) are likely to exchange values during randomization.
Enables spatially constrained or functional-group constrained null models; e.g. a
geographic distance decay matrix from ps_geodist can be transformed and used as
|
... |
Additional arguments passed to quantize, such as |
The nullcat quantize routine involves three steps: converting a
quantitative matrix to categorical strata, permuting the resulting categorical
matrix using one of several categorical null model algorithms, and mapping the
randomized categories back to quantitative values. Supply arguments via ...
to control options for each of these stages.
For repeated randomizations to generate a null distribution, it is more efficient
to use ps_rand(fun = "quantize"), which is structured to avoid unnecessarily
recomputing overhead that is shared across randomizations.
A randomized version of ps
ps_rand(), ps_geodist()
if (requireNamespace("nullcat", quietly = TRUE)) {
ps <- ps_simulate(data_type = "prob")
ps_rand <- ps_quantize(ps, n_strata = 4,
n_iter = 1000,
method = "curvecat", fixed = "cell")
# spatially constrained randomization
geo <- as.matrix(ps_geodist(ps))
W <- exp(-geo / median(geo))
ps_rand <- ps_quantize(ps, n_strata = 4,
n_iter = 1000,
method = "curvecat", fixed = "cell",
wt_row = W)
}
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