# Global test of clustering using difference in K functions

### Description

`kdplus.test`

performs a global test of clustering for comparing cases and controls using the method of Diggle and Chetwynd (1991). It relies on the difference in estimated K functions.

### Usage

1 | ```
kdplus.test(x)
``` |

### Arguments

`x` |
A |

### Value

A list providing the observed test statistic (`kdplus`

) and the estimate p-value `pvalue`

.

### Author(s)

Joshua French

### References

Waller, L.A. and Gotway, C.A. (2005). Applied Spatial Statistics for Public Health Data. Hoboken, NJ: Wiley. Diggle, Peter J., and Amanda G. Chetwynd. "Second-order analysis of spatial clustering for inhomogeneous populations." Biometrics (1991): 1155-1163.

### See Also

`kdest`

### Examples

1 2 3 | ```
data(grave)
kdsim = kdest(grave, nsim = 9)
kdplus.test(kdsim)
``` |