Library: | spatial |
See also: | SPPPinit SPPPinitrandom SPPPsetregion SPPPgetregion SPPPkfn SPPPpsim SPPPssi SPPPkenvl SPPPkaver |
Quantlet: | SPPPstrauss | |
Description: | simulates a Strauss spatial point process. It uses a spatial birth-and-death process for (4 n) steps (or for (40 n) steps when starting from a binomial pattern on the first call from another function). Note that SPPPinit or SPPPsetregion must have been called before to set the domain. To be able to reproduce results, reset the random number generator for point processes by calling SPPPinitrandom first. |
Usage: | res = SPPPstrauss(nsim, n, c, r) | |
Input: | ||
nsim | scalar, number of simulations | |
n | scalar, number of points in the domain | |
c | scalar, in [0, 1]; c = 0 corresponds to complete inhibition at distances up to r | |
r | scalar, inhibition distance | |
Output: | ||
res | list, consisting of components xmat, ymat and type: | |
xmat | n x nsim matrix, x coordinates | |
ymat | n x nsim matrix, y coordinates | |
type | string, "STRAUSS" |
; loads the spatial statistics library library("spatial") ; reads a spatial data set pines = read("pines.dat") ; initializes a point process pinesobj = SPPPinit(pines, 0, 96, 0, 100, 10) ; resets random number generator SPPPinitrandom(0) ; simulates 100 Strauss point processes(with c = 0.15 ; and r = 0.7), each consisting of 72 points, ; in the previously determined domain ppstrauss = SPPPstrauss(100, 72, 0.15, 0.7) ppstrauss.xmat[1:3,1:3] ppstrauss.ymat[1:3,1:3]
List ppstrauss consists of x and y coordinates of 100 Strauss point processes, each consisting of 72 points. Contents of _tmp [1,] 3.405 4.3925 7.2541 [2,] 6.7804 8.3313 9.1502 [3,] 8.5118 8.757 5.2338 Contents of _tmp [1,] 4.0346 2.5354 9.0886 [2,] 1.0608 2.3618 6.5437 [3,] 5.603 5.6731 1.4222