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kp.fun: Multiscale second-order neighbourhood analysis of a multivariate spatial point pattern

Description

(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).

Usage

kp.fun(p, upto, by)

Value

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

r

a vector of regularly spaced distances (seq(by,upto,by)).

labp

a vector containing the levels \(i\) of p$marks.

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 k12fun).

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 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).

See Also

plot.fads, spp, kfun, k12fun, kpqfun.