simulate.rda {vegan} | R Documentation |
Function simulates a response data frame so that it adds
Gaussian error to the fitted responses of Redundancy Analysis
(rda
). The function is a special case of generic
simulate
, and works similarly as simulate.lm
.
## S3 method for class 'rda': simulate(object, nsim = 1, seed = NULL, indx = NULL, ...)
object |
an object representing a fitted rda model. |
nsim |
number of response vectors to simulate. (Not yet used, and values above 1 will give an error). |
seed |
an object specifying if and how the random number
generator should be initialized (‘seeded’). See
simulate for details. |
indx |
Index of residuals added to the fitted values, such as
produced by permuted.index ,
permuted.index2 or sample . The index can
have duplicate entries so that bootstrapping is allowed. If null,
parametric simulation is used and Gaussian error is added to the
fitted values. |
... |
additional optional arguments (ignored). |
The implementation follows "lm"
method of
simulate
, and adds Gaussian (Normal) error to the
fitted values (fitted.rda
using function
rnorm
. The standard deviations are estimated
independently for each species (column) from the residuals after
fitting the constraints.
Returns a data frame with similar additional arguments on
random number seed as simulate
.
The function is not implemented for cca
or
capscale
objects, but only for rda
.
Jari Oksanen
simulate
for the generic case and for
lm
objects. Function fitted.rda
returns
fitted values without the error component.
data(dune) data(dune.env) mod <- rda(dune ~ Moisture + Management, dune.env) ## One simulation update(mod, simulate(mod) ~ .) ## An impression of confidence regions of site scores plot(mod, display="sites") for (i in 1:5) lines(procrustes(mod, update(mod, simulate(mod) ~ .)), col="blue")