| k12val {ads} | R Documentation |
Computes local second-order neighbour density estimates for a bivariate spatial point pattern, i.e. the number of neighbours of type 2 per unit area within sample circles of regularly increasing radii r, centred at each type 1 point of the pattern (see Details).
k12val(p, upto, by, marks)
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). |
marks |
by default c(1,2), otherwise a vector of two numbers or character strings identifying the types (the p$marks levels)
of points of type 1 and 2, respectively. |
Function K12val returns individual values of K12(r) and associated functions (see k12fun)
estimated at each type 1 point of the pattern. For a given distance r, these values can be mapped within the sampling window, as in
Getis & Franklin 1987 or Pélissier & Goreaud 2001.
A list of class c("vads","k12val") with essentially the following components:
r |
a vector of regularly spaced distances (seq(by,upto,by)). |
xy |
a data frame with 2 components giving (x,y) coordinates of type 1 points of the pattern. |
g12val |
a matrix of size (length(xy),length(r)) giving individual values of the bivariate pair density function g12(r). |
n12val |
a matrix of size (length(xy),length(r)) giving individual values of the bivariate neighbour density function n12(r). |
k12val |
a matrix of size (length(xy),length(r)) giving individual values of the intertype function K12(r). |
l12val |
a matrix of size (length(xy),length(r)) giving individual values the modified intertype function L12(r). |
There are printing, summary and plotting methods for "vads" objects.
Getis, A. and Franklin, J. 1987. Second-order neighborhood analysis of mapped point patterns. Ecology, 68:473-477.
Pélissier, R. and Goreaud, F. 2001. A practical approach to the study of spatial structure in simple cases of heterogeneous vegetation. Journal of Vegetation Science, 12:99-108.
plot.vads,
k12fun,
dval,
kval.
data(BPoirier)
BP<-BPoirier
# spatial point pattern in a rectangle sampling window of size [0,110] x [0,90]
swrm<-spp(BP$trees,win=BP$rect,marks=BP$species)
k12vswrm<-k12val(swrm,25,1,marks=c("beech","oak"))
summary(k12vswrm)
plot(k12vswrm)
# spatial point pattern in a circle with radius 50 centred on (55,45)
swc<-spp(BP$trees,win=c(55,45,45),marks=BP$species)
k12vswc<-k12val(swc,25,1,marks=c("beech","oak"))
summary(k12vswc)
plot(k12vswc)
# spatial point pattern in a complex sampling window
swrt<-spp(BP$trees,win=BP$rect,tri=BP$tri2,marks=BP$species)
k12vswrt<-k12val(swrt,25,1,marks=c("beech","oak"))
summary(k12vswrt)
plot(k12vswrt)