R: Smooth Interpolation of Marks as a Spatial Function

Smoothfun.ppp {spatstat.core} | 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 `"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`.

### Author(s)

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.

### See Also

`Smooth`

### Examples

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

[Package spatstat.core version 2.4-4 Index]