R: Standard error for space-time clustering

stsecal {splancs} | R Documentation

## Standard error for space-time clustering

### Description

Computes the standard error for space-time clustering.

### Usage

    stsecal(pts, times, poly, tlim, s, tm)

### Arguments

`pts` | A set of points, as defined in Splancs.
`times` | A vector of times, the same length as the number of points in `pts`
`poly` | A polygon enclosing the points
`tlim` | A vector of length 2 specifying the upper and lower temporal domain.
`s` | A vector of spatial distances for the analysis
`tm` | A vector of times for the analysis

### Value

A matrix of dimension `[length(s),length(t)]` is returned. Element `[i,j]` is the standard error at `s[i],t[j]`. 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`, `stdiagn`

### Examples

    example(stkhat)
    bur1se <- stsecal(burpts, burkitt$t, burbdy, c(400, 5800),
     seq(1,40,2), seq(100, 1500, 100))

[Package splancs version 2.01-40 Index]