SmoothHeat.ppp {spatstat.explore} | R Documentation |
Spatial Smoothing of Observations using Diffusion Estimate of Density
Description
Performs spatial smoothing of numeric values observed at a set of irregular locations, using the diffusion estimate of the density.
Usage
## S3 method for class 'ppp'
SmoothHeat(X, sigma, ..., weights=NULL)
Arguments
X |
Point pattern (object of class |
sigma |
Smoothing bandwidth. A single number giving the equivalent standard deviation of the smoother. |
... |
Arguments passed to |
weights |
Optional numeric vector of weights associated with each data point. |
Details
This is the analogue of the Nadaraya-Watson smoother, using the
diffusion smoothing estimation procedure (Baddeley et al, 2022).
The numerator and denominator of the Nadaraya-Watson smoother are
calculated using densityHeat.ppp
.
Value
Pixel image (object of class "im"
) giving the smoothed
mark value.
Author(s)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Tilman Davies Tilman.Davies@otago.ac.nz and Suman Rakshit.
References
Baddeley, A., Davies, T., Rakshit, S., Nair, G. and McSwiggan, G. (2022) Diffusion smoothing for spatial point patterns. Statistical Science 37, 123–142.
See Also
Smooth.ppp
for the usual kernel-based
smoother (the Nadaraya-Watson smoother)
and densityHeat
for the diffusion estimate of density.
Examples
plot(SmoothHeat(longleaf, 10))