kp.fun {ads}  R Documentation 
(Formerly ki.fun
) Computes a set of K12functions between all possible marks p and the other marks in
a multivariate spatial point pattern defined in a simple (rectangular or circular)
or complex sampling window (see Details).
kp.fun(p, upto, by)
p 
a 
upto 
maximum radius of the sample circles (see Details). 
by 
interval length between successive sample circles radii (see Details). 
Function kp.fun
is simply a wrapper to k12fun
, which computes K12(r) between each mark p of the pattern
and all other marks grouped together (the j points).
A list of class "fads"
with essentially the following components:
r 
a vector of regularly spaced distances ( 
labp 
a vector containing the levels i of 
gp. 
a data frame containing values of the pair density function g12(r). 
np. 
a data frame containing values of the local neighbour density function n12(r). 
kp. 
a data frame containing values of the K12(r) function. 
lp. 
a data frame containing values of the modified L12(r) function. 

Each component except 
obs 
a vector of estimated values for the observed point pattern. 
theo 
a vector of theoretical values expected under the null hypothesis of population independence (see 
There are printing and plotting methods for "fads"
objects.
plot.fads
,
spp
,
kfun
,
k12fun
,
kpqfun
.
data(BPoirier) BP < BPoirier ## Not run: multivariate spatial point pattern in a rectangle sampling window swrm < spp(BP$trees, win=BP$rect, marks=BP$species) kp.swrm < kp.fun(swrm, 25, 1) plot(kp.swrm) ## Not run: multivariate spatial point pattern in a circle with radius 50 centred on (55,45) swcm < spp(BP$trees, win=c(55,45,45), marks=BP$species) kp.swcm < kp.fun(swcm, 25, 1) plot(kp.swcm) ## Not run: multivariate spatial point pattern in a complex sampling window swrtm < spp(BP$trees, win=BP$rect, tri=BP$tri2, marks=BP$species) kp.swrtm < kp.fun(swrtm, 25, 1) plot(kp.swrtm)