ppKernel added, which implements non-parametric
estimation of filter functions in reproducing kernel Hilbert spaces.
a few changes in the argument list, but quite a few changes in the internals).
It implements non-parametric estimation of smooth filter functions using
B-spline basis expansions.
ppLasso added. It relies on
pointProcessModel has been
removed. In future versions the formula interface for model specification
will support the use of
offset, but for the current version there is
no longer support for fixed components in the linear predictor.
pointProcessModel has been replaced
lambda. The function no longer supports general quadratic penalty
matrices but only diagonal penalization.
MultivariatePointProcess has been
introduced, which contains a list of
PointProcessModels. Each element in the list is a
model of one coordinate given one or more of the other
coordinates, and in total the list comprises a multivariate model
of point processes.
Methods such as
ppmFit have been implemented for
pointProcessModel function now interprets a
vector of variables on the left hand side of a formula as the
specification of a multivariate point process model in which case
the function returns an object of class
The implementation of the linear filters has been modified slightly concerning the treatment of the boundary.