Description Slots Methods Author(s) See Also Examples
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)
.
signature(model =
"PointProcessModel")
: Computes the minus-log-likelihood
function.
signature(object = "PointProcess")
: Returns the
Family
object from the model.
signature(model = "PointProcess")
: Returns
the model formula.
signature(model = "PointProcess",
value = "formula")
: Sets the model formula and the response.
signature(model = "PointProcess")
: Returns
the response mark(s).
signature(model = "PointProcess")
: Returns
the process data.
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")
|
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