R: Methods for Spatial Logistic Regression Models

methods.slrm {spatstat.core} | R Documentation

## Methods for Spatial Logistic Regression Models

### Description

These are methods for the class `"slrm"`.

### Usage

    ## S3 method for class 'slrm'
    formula(x, ...)
    ## S3 method for class 'slrm'
    print(x, ...)
    ## S3 method for class 'slrm'
    summary(object, ...)
    ## S3 method for class 'slrm'
    terms(x, ...)
    ## S3 method for class 'slrm'
    labels(object, ...)
    ## S3 method for class 'slrm'
    deviance(object, ...)
    ## S3 method for class 'slrm'
    update(object, ..., evaluate = TRUE, env = parent.frame())

### Arguments

`x,object` | An object of class `"slrm"`, representing a fitted spatial logistic regression model.
`...` | Arguments passed to other methods.
`evaluate` | Logical value. If `TRUE`, evaluate the updated call to `slrm`, so that the model is refitted; if `FALSE`, simply return the updated call.
`env` | Optional environment in which the model should be updated.

### Details

These functions are methods for the generic commands `formula`, `update`, `print`, `summary`, `terms`, `labels` and `deviance` for the class `"slrm"`.

An object of class `"slrm"` represents a fitted spatial logistic regression model. It is obtained from `slrm`.

### Value

See the help files for the corresponding generic functions.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au

### See Also

`slrm`, `plot.slrm`, `predict.slrm`, `simulate.slrm`, `vcov.slrm`, `coef.slrm`.

### Examples

      fit <- slrm(redwood ~ x)
      coef(fit)
      formula(fit)
      tf <- terms(fit)
      labels(fit)
      deviance(fit)

[Package spatstat.core version 2.3-1 Index]