Perform spatial smoothing of numeric values observed at a set of irregular locations, and return the result as a function of spatial location.
Smoothfun(X, ...)# S3 method for ppp
Smoothfun(X, sigma = NULL, ...,
weights = NULL, edge = TRUE, diggle = FALSE)
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.
Marked point pattern (object of class "ppp").
Smoothing bandwidth, or bandwidth selection function,
passed to Smooth.ppp.
Additional arguments passed to Smooth.ppp.
Optional vector of weights associated with the points of X.
Logical arguments controlling the edge correction.
Arguments passed to Smooth.ppp.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk.
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.
Smooth
f <- Smoothfun(longleaf)
f
f(120, 80)
plot(f)
Run the code above in your browser using DataLab