R: Extract Design Matrix from Spatial Logistic Regression Model

model.matrix.slrm {spatstat.core} | R Documentation

## Extract Design Matrix from Spatial Logistic Regression Model

### Description

This function extracts the design matrix of a spatial logistic regression model.

### Usage

       ## S3 method for class 'slrm'
    model.matrix(object, ..., keepNA=TRUE)

### Arguments

`object` | A fitted spatial logistic regression model. An object of class `"slrm"`.
`...` | Other arguments (such as `na.action`) passed to `model.matrix.lm`.
`keepNA` | Logical. Determines whether rows containing `NA` values will be deleted or retained.

### Details

This command is a method for the generic function `model.matrix`. It extracts the design matrix of a spatial logistic regression.

The `object` must be a fitted spatial logistic regression (object of class `"slrm"`). Such objects are produced by the model-fitting function `slrm`.

Usually the result is a matrix with one column for every constructed covariate in the model, and one row for every pixel in the grid used to fit the model.

If `object` was fitted using split pixels (by calling `slrm` using the argument `splitby`) then the matrix has one row for every pixel or half-pixel.

### Value

A matrix. Columns of the matrix are canonical covariates in the model.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au

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

### See Also

`model.matrix`, `model.images`, `slrm`.

### Examples

       fit <- slrm(japanesepines ~x)
       head(model.matrix(fit))
       # matrix with two columns: '(Intercept)' and 'x'

[Package spatstat.core version 2.0-0 Index]