R: Estimate Intensity of Point Pattern Using Nearest Neighbour...

nndensity.ppp {spatstat} | R Documentation

## Estimate Intensity of Point Pattern Using Nearest Neighbour Distances

### Description

Estimates the intensity of a point pattern using the distance from each spatial location to the `k`th nearest data point.

### Usage

    nndensity(x, ...)

    ## S3 method for class 'ppp'
    nndensity(x, k, ..., verbose = TRUE)

### Arguments

`x` | A point pattern (object of class `"ppp"`) or some other spatial object.
`k` | Integer. The distance to the `k`th nearest data point will be computed. There is a sensible default.
`...` | Arguments passed to `nnmap` and `as.mask` controlling the pixel resolution.
`verbose` | Logical. If `TRUE`, print the value of `k` when it is automatically selected. If `FALSE`, remain silent.

### Details

This function computes a quick estimate of the intensity of the point process that generated the point pattern `x`.

For each spatial location s, let d(s) be the distance from s to the k-th nearest point in the dataset `x`. If the data came from a homogeneous Poisson process with intensity lambda, then pi * d(s)^2 would follow a negative exponential distribution with mean 1/lambda, and the maximum likelihood estimate of lambda would be 1/(pi * d(s)^2). This is the estimate computed by `nndensity`, apart from an edge effect correction.

This estimator of intensity is relatively fast to compute, and is spatially adaptive (so that it can handle wide variation in the intensity function). However, it implicitly assumes the points are independent, so it does not perform well if the pattern is strongly clustered or strongly inhibited.

The value of `k` should be greater than 1 in order to avoid infinite peaks in the intensity estimate around each data point. The default value of `k` is the square root of the number of points in `x`, which seems to work well in many cases.

The window of `x` is digitised using `as.mask` and the values d(s) are computed using `nnmap`. To control the pixel resolution, see `as.mask`.

### Value

A pixel image (object of class `"im"`) giving the estimated intensity of the point process at each spatial location. Pixel values are intensities (number of points per unit area).

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au

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

### References

NEED REFERENCES. TRY CRESSIE

### See Also

`density.ppp`, `intensity` for alternative estimates of point process intensity.

### Examples

       plot(nndensity(swedishpines))

[Package spatstat version 1.54-0 Index]