# Poisson

From spatstat v1.63-0
by Adrian Baddeley

##### Poisson Point Process Model

Creates an instance of the Poisson point process model which can then be fitted to point pattern data.

##### Usage

`Poisson()`

##### Details

The function `ppm`

, which fits point process models to
point pattern data, requires an argument `interaction`

of class `"interact"`

describing the interpoint interaction structure
of the model to be fitted.
The appropriate description of the Poisson process is
provided by the value of the function `Poisson`

.

This works for all types of Poisson processes including multitype and nonstationary Poisson processes.

##### Value

An object of class `"interact"`

describing the interpoint interaction
structure of the Poisson point process
(namely, there are no interactions).

##### See Also

##### Examples

```
# NOT RUN {
ppm(nztrees ~1, Poisson())
# fit the stationary Poisson process to 'nztrees'
# no edge correction needed
lon <- longleaf
# }
# NOT RUN {
longadult <- unmark(subset(lon, marks >= 30))
ppm(longadult ~ x, Poisson())
# fit the nonstationary Poisson process
# with intensity lambda(x,y) = exp( a + bx)
# trees marked by species
lans <- lansing
# }
# NOT RUN {
ppm(lans ~ marks, Poisson())
# fit stationary marked Poisson process
# with different intensity for each species
# }
# NOT RUN {
ppm(lansing ~ marks * polynom(x,y,3), Poisson())
# }
# NOT RUN {
# fit nonstationary marked Poisson process
# with different log-cubic trend for each species
# }
```

*Documentation reproduced from package spatstat, version 1.63-0, License: GPL (>= 2)*

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