Standard error for space-time clustering

Computes the standard error for space-time clustering.

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.

See also

stkhat, stsecal, stvmat, stdiagn

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: 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.

Examples

example(stkhat)
#> 
#> stkhat> data(burkitt)
#> 
#> stkhat> bur1 <- stkhat(burpts, burkitt$t, burbdy, c(400, 5800),
#> stkhat+   seq(1,40,2), seq(100, 1500, 100))
#> 
#> stkhat> oldpar <- par(mfrow=c(2,1))
#> 
#> stkhat> plot(bur1$s, bur1$ks, type="l", xlab="distance", ylab="Estimated K",
#> stkhat+   main="spatial K function")
#> 
#> stkhat> plot(bur1$t, bur1$kt, type="l", xlab="time", ylab="Estimated K",
#> stkhat+   main="temporal K function")

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