Inference for bivariate integer-valued moving average models based on binomial thinning operation

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Isabel Silva (Author) FEUP; Maria Eduarda Silva (Author) FEP; Torres, C (Author) Other

Journal

Title: Journal of Applied Statistics

Vol. 47

Pages: 2546-2564

ISSN: 0266-4763

Publisher: Taylor & Francis

Indexing

ISI Web of Knowledge - 6 Citations

Scopus - 6 Citations

Other information

Authenticus ID: P-00R-Y08

DOI: 10.1080/02664763.2020.1747411

Abstract (EN): Time series of (small) counts are common in practice and appear in a wide variety of fields. In the last three decades, several models that explicitly account for the discreteness of the data have been proposed in the literature. However, for multivariate time series of counts several difficulties arise and the literature is not so detailed. This work considers Bivariate INteger-valued Moving Average, BINMA, models based on the binomial thinning operation. The main probabilistic and statistical properties of BINMA models are studied. Two parametric cases are analysed, one with the cross-correlation generated through a Bivariate Poisson innovation process and another with a Bivariate Negative Binomial innovation process. Moreover, parameter estimation is carried out by the Generalized Method of Moments. The performance of the model is illustrated with synthetic data as well as with real datasets.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 19