get.tau.typed.permute: get the null distribution for the 'get.tau.typed' function

In IDSpatialStats: Estimate Global Clustering in Infectious Disease

Description

get the null distribution for the get.tau.typed function

Usage

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

Arguments

posmat	a matrix with columns type, x and y
typeA	the "from" type that we are interested in, -1 is wildcard
typeB	the "to" type that we are interested i, -1 is wildcard
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	what type of points are included in the comparison set. "representative" if comparison set is representative of the underlying population "independent" if comparison set is cases/events coming from an indepedent process
data.frame	logical indicating whether to return results as a data frame (default = TRUE)

Value

a matrix with permutation tau values for each distance specified

Author(s)

Justin Lessler and Henrik Salje

See Also

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

Examples

data(DengueSimulationR02)

r.max<-seq(20,1000,20)
r.min<-seq(0,980,20)
r.mid<-(r.max+r.min)/2

#Lets see if there's a difference in spatial dependence by time case occurs
type <- 2 - (DengueSimR02[,"time"] < 120)
tmp <- cbind(DengueSimR02, type=type)

typed.tau <- get.tau.typed(tmp, typeA=1, typeB=2, r=r.max, r.low=r.min, 
                           comparison.type = "independent")

typed.tau.type.null<-get.tau.typed.permute(tmp, typeA=1, typeB=2, r=r.max, r.low=r.min, 
                                           permutations=100, comparison.type = "independent")

null.ci <- apply(typed.tau.type.null[,-(1:2)], 1, quantile, probs=c(0.025,0.975))

plot(r.mid, typed.tau$tau, ylim=c(0.3,4), log="y", cex.axis=1.25, 
     xlab="Distance (m)", ylab="Tau", cex.main=0.9, lwd=2, type="n")
abline(h=1,lty=1)
lines(r.mid,typed.tau$tau,pch=20,col=1,lwd=3)
lines(r.mid, null.ci[1,] , lty=2)
lines(r.mid, null.ci[2,] , lty=2)

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