get.theta.typed.permute: get the null distribution of the get.theta.typed function

In IDSpatialStats: Estimate Global Clustering in Infectious Disease

Description

Does permutations to calculate the null distribution of get theta if there were no spatial dependence. Randomly reassigns coordinates to each observation permutations times

Usage

get.theta.typed.permute(posmat, typeA = -1, typeB = -1, r = 1,
  r.low = rep(0, length(r)), permutations, 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
data.frame	logical indicating whether to return results as a data frame (default = TRUE)

Value

theta values for all the distances we looked at

Author(s)

Justin Lessler and Henrik Salje

See Also

Other get.theta: get.theta.bootstrap, get.theta.ci, get.theta.permute, get.theta.typed.bootstrap, get.theta.typed, get.theta

Examples

data(DengueSimR01)

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-(DengueSimR01[,"time"]<75)
tmp<-cbind(DengueSimR01,type=type)

typed.theta.R01<-get.theta.typed(tmp,typeA=1,typeB=2,r=r.max,r.low=r.min)
typed.theta.type.null<-get.theta.typed.permute(tmp, typeA=1, typeB=2, 
                                               r=r.max, r.low=r.min, permutations=100)

IDSpatialStats documentation built on Nov. 16, 2019, 1:08 a.m.