# update.kppm

##### Update a Fitted Cluster Point Process Model

`update`

method for class `"kppm"`

.

##### Usage

```
# S3 method for kppm
update(object, …)
```

##### Arguments

##### Details

`object`

should be a fitted cluster point process model,
obtained from the model-fitting function `kppm`

.
The model will be updated according to the new arguments provided.

If the argument `trend`

is provided, it determines the
intensity in the updated model. It should be an R formula
(with or without a left hand side). It may include the symbols
`+`

or `-`

to specify addition or deletion of terms
in the current model formula, as shown in the Examples below.
The symbol `.`

refers to the current contents of the
formula.

The intensity in the updated model is determined by the
argument `trend`

if it is provided, or otherwise by any unnamed
argument that is a formula, or otherwise by the formula of the
original model, `formula(object)`

.

The spatial point pattern data to which the new model is fitted
is determined by the left hand side of the updated model formula,
if this is present. Otherwise it is determined by the argument
`X`

if it is provided, or otherwise by any unnamed argument
that is a point pattern or a quadrature scheme.

The model is refitted using `kppm`

.

##### Value

Another fitted cluster point process model (object of
class `"kppm"`

.

##### See Also

`kppm`

, `plot.kppm`

,
`predict.kppm`

, `simulate.kppm`

,
`methods.kppm`

,
`vcov.kppm`

##### Examples

```
# NOT RUN {
fit <- kppm(redwood ~1, "Thomas")
fitx <- update(fit, ~ . + x)
fitM <- update(fit, clusters="MatClust")
fitC <- update(fit, cells)
fitCx <- update(fit, cells ~ x)
# }
```

*Documentation reproduced from package spatstat, version 1.49-0, License: GPL (>= 2)*