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 |
upto |
maximum radius of the sample circles (see Details). |
by |
interval length between successive sample circles radii (see Details). |
marks |
by default |
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 P?Pelissier & Goreaud 2001.
A list of class c("vads","k12val")
with essentially the following components:
r |
a vector of regularly spaced distances ( |
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.
P?Pelissier, 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 ## Not run: spatial point pattern in a rectangle sampling window of size [0,110] x [0,90] swrm <- spp(BP$trees, win=BP$rect, marks=BP$species) k12vswrm <- k12val(swrm, 25, 1, marks=c("beech","oak")) summary(k12vswrm) plot(k12vswrm) ## Not run: spatial point pattern in a circle with radius 50 centred on (55,45) swc <- spp(BP$trees, win=c(55,45,45), marks=BP$species) k12vswc <- k12val(swc, 25, 1, marks=c("beech","oak")) summary(k12vswc) plot(k12vswc) ## Not run: spatial point pattern in a complex sampling window swrt <- spp(BP$trees, win=BP$rect, tri=BP$tri2, marks=BP$species) k12vswrt <- k12val(swrt, 25, 1, marks=c("beech","oak")) summary(k12vswrt) plot(k12vswrt)