simulate.slrm
Simulate a Fitted Spatial Logistic Regression Model
Generates simulated realisations from a fitted spatial logistic regresson model
Usage
## S3 method for class 'slrm':
simulate(object, nsim = 1, seed=NULL, ...,
window=NULL, covariates=NULL, verbose=TRUE, drop=FALSE)
Arguments
- object
- Fitted spatial logistic regression model. An object of class
"slrm"
. - nsim
- Number of simulated realisations.
- seed
- an object specifying whether and how to initialise
the random number generator. Either
NULL
or an integer that will be used in a call toset.seed
before simulating the p - ...
- Ignored.
- window
- Optional. Window (object of class
"owin"
) in which the model should be simulated. - covariates
- Optional. A named list containing new values for the covariates in the model.
- verbose
- Logical. Whether to print progress reports (when
nsim > 1
). - drop
- Logical. If
nsim=1
anddrop=TRUE
, the result will be a point pattern, rather than a list containing a point pattern.
Details
This function is a method for the generic function
simulate
for the class "slrm"
of fitted
spatial logistic regression models.
Simulations are performed by rpoispp
after the intensity has been computed by predict.slrm
.
The return value is a list of point patterns.
It also carries an attribute "seed"
that
captures the initial state of the random number generator.
This follows the convention used in
simulate.lm
(see simulate
).
It can be used to force a sequence of simulations to be
repeated exactly, as shown in the examples for simulate
.
Value
- A list of length
nsim
containing simulated point patterns (objects of class"ppp"
).The return value also carries an attribute
"seed"
that captures the initial state of the random number generator. See Details.
See Also
Examples
X <- copper$SouthPoints
fit <- slrm(X ~ 1)
simulate(fit, 2)
fitxy <- slrm(X ~ x+y)
simulate(fitxy, 2, window=square(2))