Smooth.locppm {spatstat.local}

Smooth a locally fitted Gibbs model

Description

Applies kernel smoothing to one of the components of a locally-fitted Gibbs point process model.

Usage

## S3 method for class 'locppm'
Smooth(X, ..., what = "cg")

Arguments

X

A locally-fitted Gibbs point process model (object of class "locppm").

...

Arguments passed to Smooth.ppp to control the smoothing.

what

Component to be smoothed. A character string. The default is to smooth the fitted coefficient vectors.

Details

This function extracts the selected quantity from the fitted object and spatially smooths it using Smooth.ppp. The result is a pixel image or a list of pixel images.

Value

A pixel image or a list of pixel images.

Author(s)

Adrian Baddeley [e-mail].

References

Baddeley, A. (2017) Local composite likelihood for spatial point patterns. Spatial Statistics 22, 261–295. DOI: 10.1016/j.spasta.2017.03.001

Baddeley, A., Rubak, E. and Turner, R. (2015) Spatial Point Patterns: Methodology and Applications with R. Chapman and Hall/CRC Press.

See Also

locppm, Smooth.ppp

Examples

  fit <- locppm(cells, sigma=0.1, use.fft=TRUE)
  plot(Smooth(fit))