get.pi.ci: Calculate bootstrapped confidence intervals for 'get.pi'...

In IDSpatialStats: Estimate Global Clustering in Infectious Disease

Description

Wrapper to get.pi.bootstrap that takes care of calculating the confidence intervals based on the bootstrapped values..

Usage

get.pi.ci(
  posmat,
  fun,
  r = 1,
  r.low = rep(0, length(r)),
  boot.iter = 1000,
  ci.low = 0.025,
  ci.high = 0.975,
  data.frame = TRUE
)

Arguments

posmat	a matrix with columns type, x and y
fun	the function to decide relationships
r	the series of spatial distances wer are interested in
r.low	the low end of each range. 0 by default
boot.iter	the number of bootstrap iterations
ci.low	the low end of the ci...0.025 by default
ci.high	the high end of the ci...0.975 by default
data.frame	logical indicating whether to return results as a data frame (default = TRUE)

Value

a matrix with a row for the high and low values and a column per distance

Author(s)

Justin Lessler

See Also

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

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


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

plot(r.mid, pi$pi, type="l")
lines(r.mid, pi.ci[,2] , lty=2)
lines(r.mid, pi.ci[,3] , lty=2)

IDSpatialStats documentation built on Aug. 9, 2021, 9:08 a.m.