# bw.scott

From spatstat v1.28-1
by Adrian Baddeley

##### 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

```
data(lansing)
attach(split(lansing))
b <- bw.scott(hickory)
b
plot(density(hickory, b))
```

*Documentation reproduced from package spatstat, version 1.28-1, License: GPL (>= 2)*

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