Bivariate models for time series of counts: a comparison study between PBINAR models and dynamic factor models
| Autor: | Manuel G. Scotto, Isabel Pereira, Magda Monteiro |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Simulation-based estimation methods 021103 operations research Series (mathematics) 0211 other engineering and technologies Context (language use) 02 engineering and technology Bivariate analysis 15. Life on land 01 natural sciences Dynamic factor models 010104 statistics & probability Work (electrical) Modeling and Simulation Dynamic factor Statistics Comparison study Bivariate count processes INAR processes 0101 mathematics Thinning operation Mathematics |
| Zdroj: | Repositório Científico de Acesso Aberto de Portugal Repositório Científico de Acesso Aberto de Portugal (RCAAP) instacron:RCAAP |
| Popis: | The aim of this work is to assess the modeling performance of two bivariate models for time series of counts, within the context of a forest fires analysis in two counties of Portugal. The first model is a periodic bivariate integer-valued autoregressive (PBINAR), easily interpreted due to the PINAR description of each component. The alternative model is a bivariate dynamic factor (BDF) that has a flexible structure, with the dynamics described through the mean value of each component that is a function of latent factors. The results reveal that BDF model exhibits a better ability to capture the dependence structure. published |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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