Title: INGARCH and Regression Models for Count Time Series
Authors: Weiß, Christian H. 
Language: en
Issue Date: 2018
Document Type: Article
Source: Enthalten in: Wiley StatsRef, April 2014-. - 2018, insges. 6 S.
Journal / Series / Working Paper (HSU): Wiley StatsRef 
Volume: 2018
Pages: insges. 6 S.
Abstract: 
Although the INGARCH models for count time series are said to be an integervalued counterpart to the generalized autoregressive conditional heteroskedasticity (GARCH) models, they may also be understood as an adaption of the autoregressive movingaverage (ARMA) models to the countdata case. The stochastic properties of these models as well as some extensions are discussed. In particular, the INGARCH models that are a type of linear conditional regression model, and also nonlinear regression models have been proposed for count time series.
Organization Units (connected with the publication): Quantitative Methoden der Wirtschaftswissenschaften 
URL: https://ub.hsu-hh.de/DB=1.8/XMLPRS=N/PPN?PPN=1031846794
DOI: 10.1002/9781118445112.stat08134
Appears in Collections:2018

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