Título: Modelling time series of counts with deflation or inflation of zeros
Palestrante: Prof. Dr. Marcelo Bourguignon Pereira - UFRN
Quando: 06 de outubro de 2017, sexta-feira, às 14:00h.
Onde: Sala de Seminários da Estatística – CCET- UFRN
Resumo. In this paper, we introduce a first order non-negative integer valued autoregressive process with zero-modified geometric innovations based on the binomial operator. This new model will enable one to tackle the problem of deflation or inflation of zeros inherent in the analysis of integer-valued time series data, and contains the INARG(1) model (Jazi et al., 2012a) as a particular case. The main properties of the model are derived, such as mean, variance, autocorrelation function, transition probabilities and zero probability. The methods of conditional maximum likelihood, Yule-Walker and conditional least squares are used for estimating the model parameters. A Monte Carlo experiment is conducted to evaluate the performances of these estimators in finite samples. The proposed model is fitted to time series of number of weekly sales and weekly number of syphilis cases illustrating its capabilities in challenging cases of deflated and inflated count data.