


The Rpackage ppstat implements methods for point process statistics for multivariate point processes (that is, marked
point processes) on the line. The package is still under
development. Version 0.8 is available from CRAN. The development version is available from
RForge.
The package is based on another Rpackage processdata. This
package implements a data structure for
storing point process and general stochastic process data. It
includes various plotting and subsetting facilities.
The ppstat package implements a framework termed generalized linear
point process models where the model is specified in terms of a
(nonlinear) transformation of a linear combination of predictor
processes. The package supports a specification of such models via a
formula, which can be used to express a number of different
transformations and filters of the basic processes that enter into
the predictor. The data structure supports observations of one or
several independent point processes, whose intensity can be given in
terms of its own internal history as well as additional covariate
processes.
The package was originally developed for point process modeling of
genome features. However, there is nothing in the package that is
specific to genomic modeling. Indeed, that package implements models
that have been used to model such diverse things as financial trade
times and neuron spike times.
License: GPLv3
Comments and bug reports
Other programs


 To install the package from CRAN run
install.packages("ppstat") from the
command line. Make sure that dependencies get installed.
 To install the development version running the most recent
version of R (discouraged for production usage) run
install.packages("processdata", repos="http://RForge.Rproject.org")
install.packages("ppstat", repos="http://RForge.Rproject.org")
You will most likely have to install other dependencies yourself.


package?ppstat
?pointProcessModel
To use the package you will have to construct data objects of class MarkedPointProcess containing your data.
The demo examples
shows some examples. To see the results of running the demo type
demo(examples)
and to get the location of the examples.R file type
system.file("demo", "examples.R", package="processdata")
See
also ?markedPointProcess
?processdata for information
on the construction of marked point processes.
Demos demo(toyExamples) and demo(archeaVirus) from ppstat show
examples of the specification and estimation of generalized
linear models.


NOTE: These older versions are not recommended for
usage. They use a different implementation of the data structures,
and many central methods have been altered or renamed. These implementations
were used for the paper
Multivariate Hawkes process models of the occurrence of regulatory
elements and are kept here for the record.


