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

In IDSpatialStats: Estimate Global Clustering in Infectious Disease

Description

Version of the get.pi function that is optimized for statically typed data. That is data where we are interested in the probability of points within some distance of points of typeA are of typeB.

Usage

get.pi.typed(
  posmat,
  typeA = -1,
  typeB = -1,
  r = 1,
  r.low = rep(0, length(r)),
  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 wer are interested in
r.low	the low end of each range....0 by default
data.frame	logical indicating whether to return results as a data frame (default = TRUE)

Value

pi values for all the distances we looked at

Author(s)

Justin Lessler and Henrik Salje

See Also

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

Examples

data(DengueSimR02)

r.max<-seq(20,1000,20)
r.min<-seq(0,980,20)

#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.pi<-get.pi.typed(tmp,typeA=1,typeB=2,r=r.max,r.low=r.min)

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