# pppmatching

From spatstat v1.17-5
by Adrian Baddeley

##### Create a Point Matching

Creates an object of class `"pppmatching"`

representing
a matching of two planar point patterns (objects of class `"ppp"`

).

##### Usage

```
pppmatching(X, Y, am, type = NULL, cutoff = NULL, q = NULL,
mdist = NULL)
```

##### Arguments

- X,Y
- Two point patterns (objects of class
`"ppp"`

). - am
- An
`X$n`

by`Y$n`

matrix with entries $\geq 0$ that specifies which points are matched and with what weight; alternatively, an object that can be coerced to this form by`as.matrix`

. - type
- A character string giving the type of the matching.
One of
`"spa"`

,`"ace"`

or`"mat"`

, or`NULL`

for a generic or unknown matching. - cutoff, q
- Numerical values specifying the cutoff value $> 0$ for interpoint distances and
the order $q \in [1,\infty]$ of the average that is applied to them.
`NULL`

if not applicable or unknown. - mdist
- Numerical value for the distance to be associated with the matching.

##### Details

The argument `am`

is interpreted as a "generalized adjacency matrix":
if the `[i,j]`

-th entry is positive, then the `i`

-th point
of `X`

and the `j`

-th point of `Y`

are matched and the
value of the entry gives the corresponding weight of the match. For
an unweighted matching all the weights should be set to $1$.

The remaining arguments are optional and allow to save
additional information about the matching. See the help files for
`pppdist`

and `matchingdist`

for details on
the meaning of these parameters.

##### See Also

##### Examples

```
# a random unweighted complete matching
X <- runifpoint(10)
Y <- runifpoint(10)
am <- r2dtable(1, rep(1,10), rep(1,10))[[1]]
# generates a random permutation matrix
m <- pppmatching(X, Y, am)
summary(m)
m$matrix
plot(m)
# a random weighted complete matching
X <- runifpoint(7)
Y <- runifpoint(7)
am <- r2dtable(1, rep(10,7), rep(10,7))[[1]]/10
# generates a random doubly stochastic matrix
m2 <- pppmatching(X, Y, am)
summary(m2)
m2$matrix
# Note: plotting does currently not distinguish
# between different weights
plot(m2)
```

*Documentation reproduced from package spatstat, version 1.17-5, License: GPL (>= 2)*

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