R: Force Spatial Logistic Regression Model to be Valid

emend.slrm {spatstat.core} | R Documentation

## Force Spatial Logistic Regression Model to be Valid

### Description

Ensures that a fitted spatial logistic regression specifies a well-defined model.

### Usage

    ## S3 method for class 'slrm'
    emend(object, ..., fatal=FALSE, trace=FALSE)

### Arguments

`object` | Fitted point process model (object of class `"slrm"`).
`...` | Ignored.
`fatal` | Logical value indicating whether to generate an error if the model cannot be projected to a valid model.
`trace` | Logical value indicating whether to print a trace of the decision process.

### Details

`emend.slrm` is a method for the generic `emend`,

The purpose of the function is to ensure that a fitted model is valid.

The model-fitting function `slrm` fits spatial logistic regression models to point pattern data.

In some circumstances, the fitted model returned by `slrm` may not specify a well-defined model, because some of the fitted coefficients of the model may be `NA` or infinite values. This usually occurs when the data are insufficient to estimate all the parameters. The model is said to be unidentifiable or confounded.

The function `emend.slrm` modifies the model `object` so that the model is valid. It identifies the terms in the model `object` that are associated with illegal parameter values (i.e. parameter values which are either `NA`, infinite, or outside their permitted range). It considers all possible sub-models of `object` obtained by deleting one or more of these terms. It identifies which of these submodels are valid, and chooses the valid submodel with the largest pseudolikelihood. The result of `emend.slrm` or `project.slrm` is the true maximum pseudolikelihood fit to the data.

For large datasets or complex models, the algorithm used in `emend.slrm` may be time-consuming, because it takes time to compute all the sub-models. A faster, approximate algorithm can be applied by setting `spatstat.options(project.fast=TRUE)`. This produces a valid submodel, which may not be the maximum likelihood submodel.

Use the function `valid.slrm` to check whether a fitted model object specifies a well-defined model.

### Value

Another point process model (object of class `"slrm"`).

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.

### See Also

`slrm`, `valid.slrm`, `emend`, `spatstat.options`

### Examples

       fit <- slrm(redwood ~ x + I(x))
       coef(fit)
       fit2 <- emend(fit)
       coef(fit2)

[Package spatstat.core version 2.3-1 Index]