get.theta.typed.permute | R Documentation |
Does permutations to calculate the null distribution of get theta if there were no spatial dependence. Randomly reassigns coordinates to each observation permutations times
get.theta.typed.permute(
posmat,
typeA = -1,
typeB = -1,
r = 1,
r.low = rep(0, length(r)),
permutations,
data.frame = TRUE
)
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) |
theta values for all the distances we looked at
Justin Lessler and Henrik Salje
Other get.theta:
get.theta()
,
get.theta.bootstrap()
,
get.theta.ci()
,
get.theta.permute()
,
get.theta.typed()
,
get.theta.typed.bootstrap()
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)
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