get.tau.permute: get the null distribution of the 'get.tau' function
In IDSpatialStats: Estimate Global Clustering in Infectious Disease

get.tau.permute

R Documentation

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

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)

IDSpatialStats documentation built on Sept. 11, 2024, 5:14 p.m.