This class is a virtual class. It implements general structures for generalized linear point process models.

`call`

:a

`"call"`

. The call that created the point process model.`Delta`

:a

`"numeric"`

. The equidistant spacings between basis function evaluations - within the support.`delta`

:a

`"numeric"`

. The interdistances between the grid (time) points in the data set.`df`

:a

`"numeric"`

. The effective degrees of freedom.`family`

:an object of class

`"Family"`

. The family object specifying the specific interpretation of the formula specification.`formula`

:a

`"formula"`

. The model formula specifying the model.`loss`

:a

`"character"`

specifying the type of loss function used for model fitting.`response`

:a

`"character"`

. The vector of response marks. Extracted from the`formula`

.`optimResult`

:a

`"list"`

containing the results from a call to`optim`

.`processData`

:a

`"MarkedPointProcess"`

- the model data.`support`

:a

`"numeric"`

. The support, [a,b], of the linear filter functions as a vector of length 2,`support = c(a,b)`

.

- computeMinusLogLikelihood
`signature(model = "PointProcessModel")`

: Computes the minus-log-likelihood function.- family
`signature(object = "PointProcess")`

: Returns the`Family`

object from the model.- formula
`signature(model = "PointProcess")`

: Returns the model formula.- formula<-
`signature(model = "PointProcess", value = "formula")`

: Sets the model formula and the response.- response
`signature(model = "PointProcess")`

: Returns the response mark(s).- processData
`signature(model = "PointProcess")`

: Returns the process data.- processData<-
`signature(model = "PointProcess", value = "ProcessData")`

: Sets the process data.

Niels Richard Hansen, Niels.R.Hansen@math.ku.dk

`pointProcessModel`

, `PointProcessModel`

, `ProcessData`

, `formula`

.

1 | ```
showClass("PointProcess")
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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