kijfun {ads} | R Documentation |
Computes a set of K- and K12-functions for all possible pairs of marks (i,j) in a multivariate spatial point pattern defined in a simple (rectangular or circular) or complex sampling window (see Details).
kijfun(p, upto, by)
p |
a "spp" object defining a multivariate spatial point pattern in a given sampling window (see spp ). |
upto |
maximum radius of the sample circles (see Details). |
by |
interval length between successive sample circles radii (see Details). |
Function kijfun
is simply a wrapper to kfun
and k12fun
, which computes either K(r)
for points of mark i when i=j or K12(r) between the marks i and j otherwise.
A list of class "fads"
with essentially the following components:
r |
a vector of regularly spaced distances (seq(by,upto,by) ). |
labij |
a vector containing the (i,j) paired levels of p$marks . |
gij |
a data frame containing values of the pair density functions g(r) and g12(r). |
nij |
a data frame containing values of the local neighbour density functions n(r) and n12(r). |
kij |
a data frame containing values of the K(r) and K12(r) functions. |
lij |
a data frame containing values of the modified L(r) and L12(r) functions. |
|
Each component except r is a data frame with the following variables: |
obs |
a vector of estimated values for the observed point pattern. |
theo |
a vector of theoretical values expected under the null hypotheses of spatial randomness (see kfun ) and
population independence (see kijfun ). |
There are printing and plotting methods for "fads"
objects.
plot.fads
,
spp
,
kfun
,
k12fun
,
ki.fun
.
data(BPoirier) BP<-BPoirier # multivariate spatial point pattern in a rectangle sampling window swrm<-spp(BP$trees,win=BP$rect,marks=BP$species) kijswrm<-kijfun(swrm,25,1) plot(kijswrm) # multivariate spatial point pattern in a circle with radius 50 centred on (55,45) swcm<-spp(BP$trees,win=c(55,45,45),marks=BP$species) kijswcm<-kijfun(swcm,25,1) plot(kijswcm) # multivariate spatial point pattern in a complex sampling window swrtm<-spp(BP$trees,win=BP$rect,tri=BP$tri2,marks=BP$species) kijswrtm<-kijfun(swrtm,25,1) plot(kijswrtm)