R: Make Predictions From a Recursively Partitioned Point Process...

predict.rppm {spatstat} | R Documentation

## Make Predictions From a Recursively Partitioned Point Process Model

### Description

Given a model which has been fitted to point pattern data by recursive partitioning, compute the predicted intensity of the model.

### Usage

    ## S3 method for class 'rppm'
    predict(object, ...)

    ## S3 method for class 'rppm'
    fitted(object, ...)

### Arguments

`object` | Fitted point process model of class `"rppm"` produced by the function `rppm`.
`...` | Optional arguments passed to `predict.ppm` to specify the locations where prediction is required. (Ignored by `fitted.rppm`)

### Details

These functions are methods for the generic functions `fitted` and `predict`. They compute the fitted intensity of a point process model. The argument `object` should be a fitted point process model of class `"rppm"` produced by the function `rppm`.

The `fitted` method computes the fitted intensity at the original data points, yielding a numeric vector with one entry for each data point.

The `predict` method computes the fitted intensity at any locations. By default, predictions are calculated at a regular grid of spatial locations, and the result is a pixel image giving the predicted intensity values at these locations.

Alternatively, predictions can be performed at other locations, or a finer grid of locations, or only at certain specified locations, using additional arguments `...` which will be interpreted by `predict.ppm`. Common arguments are `ngrid` to increase the grid resolution, `window` to specify the prediction region, and `locations` to specify the exact locations of predictions. See `predict.ppm` for details of these arguments.

Predictions are computed by evaluating the explanatory covariates at each desired location, and applying the recursive partitioning rule to each set of covariate values.

### Value

The result of `fitted.rppm` is a numeric vector.

The result of `predict.rppm` is a pixel image, a list of pixel images, or a numeric vector.

### 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

`rppm`, `plot.rppm`

### Examples

        fit <- rppm(unmark(gorillas) ~ vegetation, data=gorillas.extra)
        plot(predict(fit))
        lambdaX <- fitted(fit)
        lambdaX[1:5]
        # Mondriaan pictures
        plot(predict(rppm(redwoodfull ~ x + y)))
        points(redwoodfull)

[Package spatstat version 1.63-3 Index]