# marktable

0th

Percentile

##### Tabulate Marks in Neighbourhood of Every Point in a Point Pattern

Visit each point in a point pattern, find the neighbouring points, and compile a frequency table of the marks of these neighbour points.

Keywords
spatial, programming
##### Usage
marktable(X, R, exclude=TRUE)
##### Arguments
X
A marked point pattern. An object of class "ppp".
R
exclude
Logical. If exclude=TRUE, the neighbours of a point do not include the point itself. If exclude=FALSE, a point belongs to its own neighbourhood.
##### Details

This algorithm visits each point in the point pattern X, inspects all the neighbouring points within a radius R of the current point, and compiles a frequency table of the marks attached to the neighbours.

The dataset X must be a multitype point pattern, that is, marks(X) must be a factor. The result is a two-dimensional contingency table with one row for each point in the pattern, and one column for each possible mark value. The [i,j] entry in the table gives the number of neighbours of point i that have mark j.

To perform more complicated calculations on the neighbours of every point, use markstat or applynbd.

##### Value

• A contingency table (object of class "table") with one row for each point in X, and one column for each possible mark value.

markstat, applynbd, Kcross, ppp.object, table

• marktable
##### Examples
data(amacrine)
head(marktable(amacrine, 0.1, exclude=FALSE))