Description Usage Arguments Details Value Author(s) See Also Examples
Function simulates a response data frame so that it adds
Gaussian error to the fitted responses of Redundancy Analysis
(rda
), Constrained Correspondence Analysis
(cca
) or distance-based RDA (capscale
).
The function is a special case of generic simulate
, and
works similarly as simulate.lm
.
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object |
an object representing a fitted |
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
|
indx |
Index of residuals added to the fitted values, such as
produced by |
rank |
The rank of the constrained component: passed to
|
... |
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. Alternatively, the function can take a
permutation index that is used to add permuted residuals
(unconstrained component) to the fitted values. Raw data are used in
rda
. Internal Chi-square transformed data in
cca
within the function, but the returned data frame is
similar to the original input data. The simulation is performed on
internal metric scaling data in capscale
, but the
function returns the Euclidean distances calculated from the simulated
data. The simulation uses only the real components, and the imaginary
dimensions are ignored.
Returns a data frame with similar additional arguments on
random number seed as simulate
.
Jari Oksanen
simulate
for the generic case and for
lm
objects. Functions fitted.rda
and
fitted.cca
return fitted values without the error
component.
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