get.pi.typed.permute {IDSpatialStats} | R Documentation |
get the null distribution of the get.pi.typed function
Description
Does permutations to calculate the null distribution of get pi if there were no spatial dependence. Randomly reassigns coordinates to each observation permutations times
Usage
get.pi.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
pi values for all the distances we looked at
Author(s)
Justin Lessler and Henrik Salje
See Also
Other get.pi:
get.pi()
,
get.pi.bootstrap()
,
get.pi.ci()
,
get.pi.permute()
,
get.pi.typed()
,
get.pi.typed.bootstrap()
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"]<75)
tmp<-cbind(DengueSimR02,type=type)
typed.pi<-get.pi.typed(tmp,typeA=1,typeB=2,r=r.max,r.low=r.min)
typed.pi.type.null<-get.pi.typed.permute(tmp,typeA=1,typeB=2,r=r.max,r.low=r.min,permutations=100)
[Package IDSpatialStats version 0.4.0 Index]