# 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)
# }
```

*Documentation reproduced from package spatstat, version 1.59-0, License: GPL (>= 2)*