R: Summary plots for clustering analysis

stdiagn {splancs} | R Documentation

## Summary plots for clustering analysis

### Description

Produces some summary plots for clustering analysis

### Usage

    stdiagn(pts, stkh, stse, stmc=0,Dzero=FALSE)

### Arguments

`pts` | A set of points, as used in Splancs
`stkh` | An object returned from `stkhat`
`stse` | An object returned from `stsecal`
`stmc` | An object returned from `stmctest`
`Dzero` | FALSE - default D plot, TRUE Dzero plot

### Details

Four plots are produced on the current graphics device. The first plot is simply a map of the data. The second is a perspective plot of the difference between space-time K-function and the product of spatial and temporal K-functions. The third plot is of the standardised residuals against the product of spatial and temporal K-functions. If the Monte-Carlo data is given the fourth plot is a a histogram of the test statistics, with the value for the data indicated with a vertical line. See Diggle, Chetwynd, Haggkvist, and Morris (1995) for details.

### References

Diggle, P., Chetwynd, A., Haggkvist, R. and Morris, S. 1995 Second-order analysis of space-time clustering. Statistical Methods in Medical Research, 4, 124-136;Bailey, T. C. and Gatrell, A. C. 1995, Interactive spatial data analysis. Longman, Harlow, pp. 122-125; Rowlingson, B. and Diggle, P. 1993 Splancs: spatial point pattern analysis code in S-Plus. Computers and Geosciences, 19, 627-655; the original sources can be accessed at: http://www.maths.lancs.ac.uk/~rowlings/Splancs/. See also Bivand, R. and Gebhardt, A. 2000 Implementing functions for spatial statistical analysis using the R language. Journal of Geographical Systems, 2, 307-317.

### See Also

`stkhat`, `stsecal`, `stvmat`, `stmctest`

### Examples

    example(stkhat)
    example(stsecal)
    example(stmctest)
    stdiagn(burpts, bur1, bur1se, bur1mc)

[Package splancs version 2.01-40 Index]