Kenv.tor | R Documentation |
Compute envelope of K12hat from random toroidal shifts of two point patterns.
Kenv.tor(pts1,pts2,poly,nsim,s,quiet=FALSE)
pts1 |
First point data set. |
pts2 |
Second point data set. |
poly |
Polygon containing the points. |
nsim |
Number of random toroidal shifts to do. |
s |
Vector of distances at which to calculate the envelope. |
quiet |
If FALSE, print a message after every simulation for progress monitoring. If true, print no messages. |
The second point data set is randomly shifted using rtor.shift
in the rectangle defined by poly
. Then k12hat
is called
to compute K12hat for the two patterns.
The upper and lower values of K12hat over the ntor
toroidal shifts are returned.
A list with two components, called $upper
and $lower
. Each
component is a vector like s
.
Rowlingson, B. and Diggle, P. 1993 Splancs: spatial point pattern analysis code in S-Plus. Computers and Geosciences, 19, 627-655; the original sources can be accessed at: https://www.maths.lancs.ac.uk/~rowlings/Splancs/. See also Bivand, R. and Gebhardt, A. 2000 Implementing functions for spatial statistical analysis using the R language. Journal of Geographical Systems, 2, 307-317.
rtor.shift
,k12hat
data(okwhite)
data(okblack)
okpoly <- list(x=c(okwhite$x, okblack$x), y=c(okwhite$y, okblack$y))
plot(seq(5,80,5), sqrt(k12hat(as.points(okwhite), as.points(okblack),
bboxx(bbox(as.points(okpoly))), seq(5,80,5))/pi) - seq(5,80,5), xlab="distance",
ylab=expression(hat(L)[12]), ylim=c(-35,35), type="l",
main="Simulation envelopes, random toroidal shifts")
env.ok <- Kenv.tor(as.points(okwhite), as.points(okblack),
bboxx(bbox(as.points(okpoly))), nsim=29, s=seq(5,80,5))
lines(seq(5,80,5), sqrt(env.ok$upper/pi)-seq(5,80,5), lty=2)
lines(seq(5,80,5), sqrt(env.ok$lower/pi)-seq(5,80,5), lty=2)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.