# marktable

##### 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
- Neighbourhood radius.
- 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.

##### See Also

##### Examples

```
data(amacrine)
head(marktable(amacrine, 0.1))
head(marktable(amacrine, 0.1, exclude=FALSE))
```

*Documentation reproduced from package spatstat, version 1.16-3, License: GPL (>= 2)*