Smoothfun.ppp
Smooth Interpolation of Marks as a Spatial Function
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 ppp
Smoothfun(X, sigma = NULL, …,
weights = NULL, edge = TRUE, diggle = FALSE)
Arguments
- X
Marked point pattern (object of class
"ppp"
).- sigma
Smoothing bandwidth, or bandwidth selection function, passed to
Smooth.ppp
.- …
Additional arguments passed to
Smooth.ppp
.- weights
Optional vector of weights associated with the points of
X
.- edge,diggle
Logical arguments controlling the edge correction. Arguments passed to
Smooth.ppp
.
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
.
See Also
Examples
# NOT RUN {
f <- Smoothfun(longleaf)
f
f(120, 80)
plot(f)
# }