R: Variance matrix for space-time clustering

stvmat {splancs} | R Documentation

## Variance matrix for space-time clustering

### Description

Compute the variance matrix for space-time clustering

### Usage

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

### Arguments

`pts` | A set of points.
`times` | A vector of times, the same length as the number of points in `pts`
`poly` | A polygon that encloses 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 four-dimensional matrix is returned. The covariance between space-time `t1,s1` and `t2,s2` is given by the corresponding element `[t1,s1,t2,s2]` For full details, see Diggle, Chetwynd, Haggkvist and Morris (1995)

### 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; 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: https://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`, `stmctest`, `stdiagn`

[Package splancs version 2.01-43 Index]