Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/29228
Title: Inference for bivariate integer-valued moving average models based on binomial thinning operation
Author: Silva, Isabel
Silva, Maria Eduarda
Torres, Cristina
Keywords: Bivariate discrete distributions
Bivariate models
Generalized method of moments
Moving average
Time series of counts
Issue Date: 2020
Publisher: Taylor & Francis
Abstract: 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.
Peer review: yes
URI: http://hdl.handle.net/10773/29228
DOI: 10.1080/02664763.2020.1747411
ISSN: 0266-4763
Publisher Version: https://www.tandfonline.com/doi/full/10.1080/02664763.2020.1747411
Appears in Collections:CIDMA - Artigos
PSG - Artigos

Files in This Item:
File Description SizeFormat 
JAS2020_IMS_MES_CT_Repositorio.pdf459.86 kBAdobe PDFembargoedAccess


FacebookTwitterLinkedIn
Formato BibTex MendeleyEndnote Degois 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.