# ksmooth.ppp

From spatstat v1.5-4
by Adrian Baddeley

##### Kernel Smoothed Intensity of Point Pattern

Compute a kernel smoothed intensity function from a point pattern.

- Keywords
- spatial

##### Usage

`ksmooth.ppp(x, sigma, weights, edge=TRUE)`

##### Arguments

- x
- Point pattern (object of class
`"ppp"`

) to be smoothed. - sigma
- Standard deviation of isotropic Gaussian smoothing kernel.
- weights
- Optional vector of weights to be attached to the points. May include negative values.
- edge
- Logical flag: if
`TRUE`

, apply edge correction.

##### Details

A kernel estimate of the intensity of the point pattern
is computed. The result is
the convolution of the isotropic Gaussian kernel with
standard deviation `sigma`

and point masses at each of the data
points. The default is to assign
a unit weight to each point.
If `weights`

is present, the point masses have these
weights (which may be signed real numbers).

Computation is performed using the Fast Fourier Transform.

##### Value

- A pixel image (object of class
`"im"`

).

##### synopsis

ksmooth.ppp(x, sigma, ..., edge=TRUE)

##### See Also

##### Examples

```
data(cells)
Z <- ksmooth.ppp(cells, 0.05)
plot(Z)
```

*Documentation reproduced from package spatstat, version 1.5-4, License: GPL version 2 or newer*

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