R: Simulate a Fitted Spatial Logistic Regression Model

simulate.slrm {spatstat.core} | R Documentation

## Simulate a Fitted Spatial Logistic Regression Model

### Description

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 to `set.seed` before simulating the point patterns.
`...` | 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` and `drop=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.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au

and Rolf Turner r.turner@auckland.ac.nz

### See Also

`slrm`, `rpoispp`, `simulate.ppm`, `simulate.kppm`, `simulate`

### Examples

      X <- copper$SouthPoints
      fit <- slrm(X ~ 1)
      simulate(fit, 2)
      fitxy <- slrm(X ~ x+y)
      simulate(fitxy, 2, window=square(2))

[Package spatstat.core version 2.4-4 Index]