get.tau.permute {IDSpatialStats}

get the null distribution of the get.tau function

Description

Does permutations to calculate the null distribution of get pi if there were no spatial dependence. Randomly reassigns coordinates to each observation permutations times

Usage

get.tau.permute(
  posmat,
  fun,
  r = 1,
  r.low = rep(0, length(r)),
  permutations,
  comparison.type = "representative",
  data.frame = TRUE
)

Arguments

posmat

a matrix appropriate for input to get.tau

fun

a function appropriate for input to get.tau

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

comparison.type

the comparison type to pass as input to get.pi

data.frame

logical indicating whether to return results as a data frame (default = TRUE)

Value

tau values for all the distances we looked at

Author(s)

Justin Lessler and Henrik Salje

See Also

Other get.tau: get.tau(), get.tau.bootstrap(), get.tau.ci(), get.tau.typed(), get.tau.typed.bootstrap(), get.tau.typed.permute()

Examples

#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

tau<-get.tau(x,fun,r=r.max,r.low=r.min,comparison.type = "independent")
tau.null<-get.tau.permute(x,fun,r=r.max,r.low=r.min,permutations=50,comparison.type = "independent")

null.ci<-apply(tau.null[,-(1:2)],1,quantile,probs=c(0.25,0.75))

plot(r.mid, tau$tau, ylim=c(1/max(tau$tau),max(tau$tau)), type="l", log="y")
lines(c(0,100),c(1,1), lty=3, col="grey")
lines(r.mid, null.ci[1,] , lty=2)
lines(r.mid, null.ci[2,] , lty=2)