Authors: Liboschik, Tobias
Fokianos, Konstantinos
Fried, Roland
Title: tscount: An R package for analysis of count time series following generalized linear models
Language (ISO): en
Abstract: The R package tscount provides likelihood-based estimation methods for analysis and modelling of count time series following generalized linear models. This is a exible class of models which can describe serial correlation in a parsimonious way. The conditional mean of the process is linked to its past values, to past observations and to potential covariate e ects. The package allows for models with the identity and with the logarithmic link function. The conditional distribution can be Poisson or Negative Binomial. An important special case of this class is the so-called INGARCH model and its log-linear extension. The package includes methods for model tting and assessment, prediction and intervention analysis. This paper summarizes the theoretical background of these methods with references to the literature for further details. It gives details on the implementation of the package and provides simulation results for models which have not been studied theoretically before. The usage of the package is demonstrated by two data examples.
Subject Headings: intervention analysis
serial correlation
regression model
R
prediction
model selection
mixed Poisson
URI: http://hdl.handle.net/2003/33904
http://dx.doi.org/10.17877/DE290R-7239
Issue Date: 2015
Appears in Collections:Sonderforschungsbereich (SFB) 823

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