# density.lpp

##### Kernel Estimate of Intensity on a Linear Network

Estimates the intensity of a point process on a linear network by applying kernel smoothing to the point pattern data, using the equal-split continuous algorithm.

##### Usage

```
## S3 method for class 'lpp':
density(x, sigma, \dots,
epsilon = 1e-06, verbose = TRUE, debug = FALSE, savehistory = TRUE)
```## S3 method for class 'splitppx':
density(x, sigma, \dots)

##### Arguments

- x
- Point pattern on a linear network (object of class
`"lpp"`

) to be smoothed. - sigma
- Smoothing bandwidth (standard deviation of the Gaussian kernel)
in the same units as the spatial coordinates of
`x`

. - ...
- Arguments passed to
`as.mask`

determining the resolution of the result. - epsilon
- Tolerance value. A tail of the Gaussian kernel with total mass
less than
`epsilon`

may be deleted. - verbose
- Logical value indicating whether to print progress reports.
- debug
- Logical value indicating whether to print debugging information.
- savehistory
- Logical value indicating whether to save the entire history of the algorithm, for the purposes of evaluating performance.

##### Details

Kernel smoothing using the Gaussian kernel with the
equal-split continuous rule is applied to the points of `x`

.
The result is a pixel image on the linear network (class
`"linim"`

) which can be plotted.

There is also a method for split point patterns on a linear network
(class `"splitppx"`

) which will return a list of pixel images.

##### Value

- Pixel image on the linear network (class
`"linim"`

).

##### WARNING

**THIS ALGORITHM CAN BE EXTREMELY SLOW** for large values of `sigma`

.

The computational complexity increases exponentially with
`sigma`

.
You Have Been Warned.

##### References

Okabe, A. and Sugihara, K. (2012)
*Spatial analysis along networks*.
Wiley.

##### See Also

##### Examples

```
X <- runiflpp(3, simplenet)
D <- density(X, 0.2, verbose=FALSE)
plot(D, style="w", main="", adjust=2)
```

*Documentation reproduced from package spatstat, version 1.42-2, License: GPL (>= 2)*