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, N, exclude=TRUE, collapse=FALSE)
Arguments
- X
A marked point pattern. An object of class
"ppp"
.- R
Neighbourhood radius. Incompatible with
N
.- N
Number of neighbours of each point. Incompatible with
R
.- exclude
Logical. If
exclude=TRUE
, the neighbours of a point do not include the point itself. Ifexclude=FALSE
, a point belongs to its own neighbourhood.- collapse
Logical. If
collapse=FALSE
(the default) the results for each point are returned as separate rows of a table. Ifcollapse=TRUE
, the results are aggregated according to the type of point.
Details
This algorithm visits each point in the point pattern X
,
inspects all the neighbouring points within a radius R
of the current
point (or the N
nearest neighbours 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
.
If collapse=FALSE
(the default),
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
.
If collapse=TRUE
, this contingency table is aggregated
according to the type of point, so that the result is a contingency
table with one row and one column for each possible mark value.
The [i,j]
entry in the table gives the number of
neighbours of a point with mark 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"
).
If collapse=FALSE
, the table has one row for
each point in X
, and one column for each possible mark value.
If collapse=TRUE
, the table has one row and one column
for each possible mark value.
See Also
Examples
# NOT RUN {
head(marktable(amacrine, 0.1))
head(marktable(amacrine, 0.1, exclude=FALSE))
marktable(amacrine, N=1, collapse=TRUE)
# }