IDSpatialStats (version 0.4.0)

get.pi.bootstrap: Bootstrap get.pi values.

Description

Runs get.pi on multiple bootstraps of the data. Is formulated such that the relationships between points and themselves will not be calculated.

Usage

get.pi.bootstrap(
  posmat,
  fun,
  r = 1,
  r.low = rep(0, length(r)),
  boot.iter = 500,
  data.frame = TRUE
)

Value

pi values for all the distances we looked at

Arguments

posmat

a matrix with columns type, x and y

fun

the function to decide relationships

r

the series of spatial distances we are interested in

r.low

the low end of each range. 0 by default

boot.iter

the number of bootstrap iterations

data.frame

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

Author

Justin Lessler and Henrik Salje

See Also

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

Examples

# \donttest{

#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.boot<-get.pi.bootstrap(x,fun,r=r.max,r.low=r.min,boot.iter=100)

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

plot(r.mid, pi$pi , type="l")
lines(r.mid, pi.ci[1,] , lty=2)
lines(r.mid, pi.ci[2,] , lty=2)

# }