Zero-truncated compound Poisson integer-valued GARCH models for time series |
| |
Authors: | Esmeralda Gonçalves Nazaré Mendes-Lopes |
| |
Institution: | Department of Mathematics, University of Coimbra, CMUC, Coimbra, Portugal |
| |
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. |
| |
Keywords: | Compound Poisson distribution zero-truncated count time series |
|
|