model.matrix.slrm: Extract Design Matrix from Spatial Logistic Regression Model

In spatstat.core: Core Functionality of the 'spatstat' Family

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

and \rolf

See Also

model.matrix, model.images, slrm.

Examples

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

spatstat.core documentation built on May 18, 2022, 9:05 a.m.