get.tau.typed: Optimized version of 'get.tau' for typed data

In IDSpatialStats: Estimate Global Clustering in Infectious Disease

Description

Version of th e get.tau function that is optimized for statically typed data. That is data where we want the relationship between points of type A and points of type B

Usage

get.tau.typed(
  posmat,
  typeA = -1,
  typeB = -1,
  r = 1,
  r.low = rep(0, length(r)),
  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
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

data frame of tau values for all the distances

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.permute(), get.tau()

Examples

data(DengueSimR02)

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")

plot(r.mid,typed.tau$tau,log="y",cex.axis=1.25,
     xlab="Distance (m)",ylab="Tau",cex.main=0.9,lwd=2,type="l")
abline(h=1,lty=2)

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