A New Approach to Integer-Valued Time Series Modeling: The Neyman Type-A INGARCH Model*

• Autor(a) principal: Gonçalves, Esmeralda
• Data de Publicação: 2015
• Outros Autores: Mendes-Lopes, Nazaré, Silva, Filipa
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10316/44665; https://doi.org/10.1007/s10986-015-9276-x

The aim of this paper is to develop a probabilistic study of a wide class of conditionally heteroscedastic models recently introduced in the literature, the compound Poisson INGARCH processes [7]. This class includes, in particular, some well-known models like the Poisson INGARCH of Ferland, Latour, and Oraichi [4] or the negative binomial and generalized Poisson INGARCH introduced by Zhu in 2011 and 2012, respectively. Within this class, we analyze the existence and ergodicity of a strictly and weakly stationary solution. For a new particular model of that class, the Neyman type-A INGARCH model, we derive the autocorrelation function, analyze the existence of higher-order moments, and obtain an explicit form of their first four cumulants, from which we deduce the corresponding skewness and kurtosis.