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Title: Zero-truncated compound Poisson integer-valued GARCH models for time series
Authors: Gonçalves, Esmeralda 
Mendes-Lopes, Nazaré 
Issue Date: 2017
Publisher: Taylor & Francis
Project: info:eu-repo/grantAgreement/FCT/5876/147205/PT 
Serial title, monograph or event: Statistics
Abstract: Starting from the compound Poisson INGARCH models, we introduce in this paper a new family of integer-valued models suitable to describe count data without zeros that we name zero-truncated CP-INGARCH processes. For such class of models, a probabilistic study concerning moments existence, stationarity and ergodicity is developed. The conditional quasi-maximum likelihood method is introduced to consistently estimate the parameters of a wide zero-truncated compound Poisson subclass of models. The conditional maximum likelihood method is also used to estimate the parameters of ZTCP-INGARCH processes associated with well-specified conditional laws. A simulation study that compares some of those estimators and illustrates their finite distance behaviour as well as a real-data application conclude the paper.
Other Identifiers: 10.1080/02331888.2017.1410154
DOI: 10.1080/02331888.2017.1410154
Rights: embargoedAccess
Appears in Collections:I&D CMUC - Artigos em Revistas Internacionais

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