stsecal: Standard error for space-time clustering

In splancs: Spatial and Space-Time Point Pattern Analysis

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: 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, stvmat, stdiagn

Examples

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

splancs documentation built on May 29, 2024, 6:22 a.m.