get.pi.permute | R Documentation |
get.pi
functionDoes permutations to calculate the null distribution of get pi if there were no spatial dependence. Randomly reassigns coordinates to each observation permutations times
get.pi.permute(
posmat,
fun,
r = 1,
r.low = rep(0, length(r)),
permutations,
data.frame = TRUE
)
posmat |
a matrix with columns type, x and y |
fun |
the function to evaluate |
r |
the series of spatial distances we are interested in |
r.low |
the low end of each range....0 by default |
permutations |
the number of permute iterations |
data.frame |
logical indicating whether to return results as a data frame (default = TRUE) |
pi values for all the distances we looked at
Other get.pi:
get.pi()
,
get.pi.bootstrap()
,
get.pi.ci()
,
get.pi.typed()
,
get.pi.typed.bootstrap()
,
get.pi.typed.permute()
#compare normally distributed with uniform points
x<-cbind(1,runif(100,-100,100), runif(100,-100,100))
x<-rbind(x, cbind(2,rnorm(100,0,20), rnorm(100,0,20)))
colnames(x) <- c("type","x","y")
fun<-function(a,b) {
if(a[1]!=2) return(3)
if (b[1]==2) return(1)
return(2)
}
r.max<-seq(10,100,10)
r.min<-seq(0,90,10)
r.mid <- (r.max+r.min)/2
pi<-get.pi(x,fun,r=r.max,r.low=r.min)
pi.null<-get.pi.permute(x,fun,r=r.max,r.low=r.min,permutations=100)
null.ci<-apply(pi.null[,-(1:2)],1,quantile,probs=c(0.25,0.75))
plot(r.mid, pi$pi, type="l")
lines(r.mid, null.ci[1,] , lty=2)
lines(r.mid, null.ci[2,] , lty=2)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.