kp.fun | R Documentation |
(Formerly ki.fun
) Computes a set of K12-functions 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 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 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)
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