# markstat

0th

Percentile

##### Summarise Marks in Every Neighbourhood in a Point Pattern

Visit each point in a point pattern, find the neighbouring points, and summarise their marks

Keywords
spatial, programming
##### Usage
markstat(X, fun, N, R, ...)
##### Arguments
X
A marked point pattern. An object of class "ppp".
fun
Function to be applied to the vector of marks.
N
Integer. If this argument is present, the neighbourhood of a point of X is defined to consist of the N points of X which are closest to it. This argument is incompatible with R.
R
Nonnegative numeric value. If this argument is present, the neighbourhood of a point of X is defined to consist of all points of X which lie within a distance R of it. This argument is incompatible wi
...
extra arguments passed to the function fun. They must be given in the form name=value.
##### Details

This algorithm visits each point in the point pattern X, determines which points of X are neighbours'' of the current point, extracts the marks of these neighbouring points, applies the function fun to the marks, and collects the value or values returned by fun.

The definition of neighbours'' depends on the arguments N and R, exactly one of which must be given.

If N is given, then the neighbours of the current point are the N points of X which are closest to the current point (including the current point itself). If R is given, then the neighbourhood of the current point consists of all points of X which lie closer than a distance R from the current point.

Each point of X is visited; the neighbourhood of the current point is determined; the marks of these points are extracted as a vector v; then the function fun is called as: fun(v, ...)

where ... are the arguments passed from the call to markstat.

The results of each call to fun are collected and returned according to the usual rules for apply and its relatives. See Value above.

This function is just a convenient wrapper for a common use of the function applynbd. For more complex tasks, use applynbd. To simply tabulate the marks in every R-neighbourhood, use marktable.

##### Value

• Similar to the result of apply. if each call to fun returns a single numeric value, the result is a vector of dimension X$n, the number of points in X. If each call to fun returns a vector of the same length m, then the result is a matrix of dimensions c(m,n); note the transposition of the indices, as usual for the family of apply functions. If the calls to fun return vectors of different lengths, the result is a list of length X$n.

applynbd, marktable, ppp.object, apply

• markstat
##### Examples
data(longleaf)
<testonly>longleaf <- longleaf[seq(1, longleaf\$n, by=6)]</testonly>

# average diameter of 5 closest neighbours of each tree
md <- markstat(longleaf, mean, N=5)

# range of diameters of trees within 10 metre radius
rd <- markstat(longleaf, range, R=10)
Documentation reproduced from package spatstat, version 1.17-1, License: GPL (>= 2)

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