XploRe Help : SPPPkenvl

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library:	spatial
See also:	SPPPinit SPPPinitrandom SPPPsetregion SPPPgetregion SPPPkfn SPPPpsim SPPPstrauss SPPPssi SPPPkaver

Quantlet:		SPPPkenvl
Description:		computes envelope (upper and lower limits) and average of simulations of K-fns

Reference(s):

Venables, W. N., Ripley, B. D. (1999): Modern Applied Statistics with S-Plus, Third Edition, Springer, New York

Link:

Tutorial: Spatial statistics

Usage:	`res = SPPPkenvl(fs, k, obj)`
Input:
	`fs`	scalar, full scale of the plot
	`k`	scalar, number of regularly spaced distances in (0, fs)
	`obj`	list, consisting of xmat, ymat, and type, caculated by SPPPpsim, SPPPstrauss, or SPPPssi (list type = "PSIM", "STRAUSS", or "SSI")
Output:
	`res`	list, consisting of components hx, hl, hu and aver:
	`res.hx`	k x 1 vector, distances
	`res.hl`	k x 1 vector, min of K-fn
	`res.hu`	k x 1 vector, max of K-fn
	`res.aver`	k x 1 vector, averages of K-fn

Note:

C-Code from Venables, Ripley (1999) forms the basis of this quantlet. Also check this reference for more details.

Example:

; 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 Binomial point processes, each consisting ; of 72 points, in the previously determined domain ppsim = SPPPpsim(100, 72) ; calculates the envelope in interval(0, 5), split ; into 100 segments ppkenvl = SPPPkenvl(5, 100, ppsim) ppkenvl

Result:

List consisting of distances and min, max, and averages
of K-fn:

Contents of ppkenvl.hx
[  1,]     0.05
[  2,]      0.1
[  3,]     0.15
...
[ 99,]     4.95
[100,]        5

Contents of ppkenvl.hl
[  1,]        0
[  2,]        0
[  3,]        0
...
[ 99,]   4.6822
[100,]   4.7263

Contents of ppkenvl.hu
[  1,]  0.15355
[  2,]  0.21716
[  3,]  0.26596
...
[ 99,]   5.1452
[100,]    5.204

Contents of ppkenvl.aver
[  1,]  0.049757
[  2,]  0.096131
[  3,]  0.15146
...
[ 99,]   4.9111
[100,]   4.9623

Author: J. Symanzik, 20000725 license MD*Tech