stmctest
Perform a MonteCarlo test of spacetime clustering.
 Keywords
 spatial
Usage
stmctest(pts, times, poly, tlimits, s, tt, nsim, quiet=FALSE, returnSims=FALSE)
Arguments
 pts
 A set of points as used by Splancs.
 times

A vector of times, the same length as the number of points in
pts
.  poly
 A polygon enclosing the points.
 tlimits
 A vector of length 2, specifying the upper and lower temporal domain.
 s
 A vector of spatial distances for the analysis.
 tt
 A vector of times for the analysis.
 nsim
 The number of simulations to do.
 quiet

If
quiet=TRUE
then no output is produced, otherwise the function prints the number of simulations completed so far, and also how the test statistic for the data ranks with the simulations.  returnSims
 default FALSE, if TRUE, return the
stkhat
output for the observed data and each simulation as attributesobs
andsims
Details
The function uses a sum of residuals as a test statistic, randomly permutes the times of the set of points and recomputes the test statistic for a number of simulations. See Diggle, Chetwynd, Haggkvist and Morris (1995) for details.
Value
A list with components:
nsim
values each of which is a simulated value of the statisticNote
The example of using returned simulated values is included only to show how the values might be used, not to indicate that this constitutes a way of examining which observed values of the spacetime measure are exceptional.
References
Diggle, P., Chetwynd, A., Haggkvist, R. and Morris, S. 1995 Secondorder analysis of spacetime clustering. Statistical Methods in Medical Research, 4, 124136;Bailey, T. C. and Gatrell, A. C. 1995, Interactive spatial data analysis. Longman, Harlow, pp. 122125; Rowlingson, B. and Diggle, P. 1993 Splancs: spatial point pattern analysis code in SPlus. Computers and Geosciences, 19, 627655; 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, 307317.
See Also
Examples
example(stkhat)
bur1mc < stmctest(burpts, burkitt$t, burbdy, c(400, 5800),
seq(1,40,2), seq(100, 1500, 100), nsim=49, quiet=TRUE, returnSims=TRUE)
plot(density(bur1mc$t), xlim=range(c(bur1mc$t0, bur1mc$t)))
abline(v=bur1mc$t0)
r0 < attr(bur1mc, "obs")$kstouter(attr(bur1mc, "obs")$ks, attr(bur1mc, "obs")$kt)
rsimlist < lapply(attr(bur1mc, "sims"), function(x) x$kst  outer(x$ks, x$kt))
rarray < array(do.call("cbind", rsimlist), dim=c(20, 15, 49))
rmin < apply(rarray, c(1,2), min)
rmax < apply(rarray, c(1,2), max)
r0 < rmin
r0 > rmax