| Smoothfun.ppp {spatstat.explore} | R Documentation |
Smooth Interpolation of Marks as a Spatial Function
Description
Perform spatial smoothing of numeric values observed at a set of irregular locations, and return the result as a function of spatial location.
Usage
Smoothfun(X, ...)
## S3 method for class 'ppp'
Smoothfun(X, sigma = NULL, ...,
weights = NULL, edge = TRUE, diggle = FALSE)
Arguments
X |
Marked point pattern (object of class |
sigma |
Smoothing bandwidth, or bandwidth selection function,
passed to |
... |
Additional arguments passed to |
weights |
Optional vector of weights associated with the points of |
edge, diggle |
Logical arguments controlling the edge correction.
Arguments passed to |
Details
The commands Smoothfun and Smooth
both perform kernel-smoothed spatial interpolation
of numeric values observed at irregular spatial locations.
The difference is that Smooth returns a pixel image,
containing the interpolated values at a grid of locations, while
Smoothfun returns a function(x,y) which can be used
to compute the interpolated value at any spatial location.
For purposes such as model-fitting it is more accurate to
use Smoothfun to interpolate data.
Value
A function with arguments x,y.
The function also belongs to the class "Smoothfun" which has
methods for print and as.im.
It also belongs to the class "funxy" which has methods
for plot, contour and persp.
Author(s)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk.
See Also
Examples
f <- Smoothfun(longleaf)
f
f(120, 80)
plot(f)