Visit each point in a multitype point pattern, find the neighbouring points, and compile a frequency table of the marks of these neighbour points.
marktable(X, R, N, exclude=TRUE, collapse=FALSE)
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.
A multitype point pattern.
An object of class "ppp"
, "lpp"
,
"pp3"
or "ppx"
, with marks which are a factor.
Neighbourhood radius. Incompatible with N
.
Number of neighbours of each point. Incompatible with R
.
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.
Logical. If collapse=FALSE
(the default) the results for
each point are returned as separate rows of a table.
If collapse=TRUE
, the results are aggregated according to the
type of point.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au and Rolf Turner rolfturner@posteo.net
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
.
markstat
,
applynbd
,
Kcross
,
ppp.object
,
table
head(marktable(amacrine, 0.1))
head(marktable(amacrine, 0.1, exclude=FALSE))
marktable(amacrine, N=1, collapse=TRUE)
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