# 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)
```

##### 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 to`set.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`

).

##### 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))
```

*Documentation reproduced from package spatstat, version 1.37-0, License: GPL (>= 2)*