# 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 class 'ppp':
Smoothfun(X, sigma = NULL, \dots,
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

```
f <- Smoothfun(longleaf)
f
f(120, 80)
plot(f)
```

*Documentation reproduced from package spatstat, version 1.41-1, License: GPL (>= 2)*