ki.fun {ads}R Documentation

Multiscale second-order neigbourhood analysis of a multivariate spatial point pattern

Description

Computes a set of K12-functions between all possible marks i and the other marks in a multivariate spatial point pattern defined in a simple (rectangular or circular) or complex sampling window (see Details).

Usage

ki.fun(p, upto, by)

Arguments

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).

Details

Function ki.fun is simply a wrapper to k12fun, which computes K12(r) between each mark i of the pattern and all other marks grouped together (the j points).

Value

A list of class "fads" with essentially the following components:

r a vector of regularly spaced distances (seq(by,upto,by)).
labi a vector containing the levels i of p$marks.
gi. a data frame containing values of the pair density function g12(r).
ni. a data frame containing values of the local neighbour density function n12(r).
ki. a data frame containing values of the K12(r) function.
li. 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 k12fun).

Note

There are printing and plotting methods for "fads" objects.

Author(s)

Raphael.Pelissier@ird.fr

See Also

plot.fads, spp, kfun, k12fun, kijfun.

Examples

  data(BPoirier)
  BP<-BPoirier
  # multivariate spatial point pattern in a rectangle sampling window 
  swrm<-spp(BP$trees,win=BP$rect,marks=BP$species)
  ki.swrm<-ki.fun(swrm,25,1)
  plot(ki.swrm)
  
 # 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)
  ki.swcm<-ki.fun(swcm,25,1)
  plot(ki.swcm)
  
  # multivariate spatial point pattern in a complex sampling window
  swrtm<-spp(BP$trees,win=BP$rect,tri=BP$tri2,marks=BP$species)
  ki.swrtm<-ki.fun(swrtm,25,1)
  plot(ki.swrtm)

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