# bw.scott

##### Scott's Rule for Bandwidth Selection for Kernel Density

Use Scott's rule of thumb to determine the smoothing bandwidth for the kernel estimation of point process intensity.

##### Usage

`bw.scott(X)`

##### Arguments

- X
A point pattern (object of class

`"ppp"`

).

##### Details

This function selects a bandwidth `sigma`

for the kernel estimator of point process intensity
computed by `density.ppp`

.

The bandwidth \(\sigma\) is computed by the rule of thumb of Scott (1992, page 152). It is very fast to compute.

This rule is designed for density
estimation, and typically produces a larger bandwidth
than `bw.diggle`

. It is useful for estimating
gradual trend.

##### Value

A numerical vector of two elements giving the selected
bandwidths in the `x`

and `y`

directions.

##### References

Scott, D.W. (1992)
*Multivariate Density Estimation. Theory, Practice and
Visualization*.
New York: Wiley.

##### See Also

##### Examples

```
# NOT RUN {
data(lansing)
attach(split(lansing))
b <- bw.scott(hickory)
b
# }
# NOT RUN {
plot(density(hickory, b))
# }
```

*Documentation reproduced from package spatstat, version 1.57-1, License: GPL (>= 2)*