Please use this identifier to cite or link to this item: http://hdl.handle.net/10773/24476
Title: A full ARMA model for counts with bounded support and its application to rainy-days time series
Author: Gouveia, Sónia
Möller, Tobias A.
Weiß, Christian H.
Scotto, Manuel G.
Keywords: Binomial variation
Count time series
ARMA structure
Rainy-days time series
Issue Date: Sep-2018
Publisher: Springer
Abstract: Motivated by a large dataset containing time series of weekly number of rainy days collected over two thousand locations across Europe and Russia for the period 2000–2010, we propose a new class of ARMA-like model for time series of bounded counts, which can also handle extra-binomial variation. We abbreviate this model as bvARMA, as it is based upon a novel operation referred to as binomial variation. After having discussed important stochastic properties and proposed a model-fitting approach relying on maximum likelihood estimation, we apply the bvARMA model family to the rainy-days time series. Results show that both bvAR and bvMA models are adequate and exhibit a similar performance. Furthermore, bvARMA results outperform those obtained by fitting ordinary discrete ARMA (NDARMA) models of the same order.
Peer review: yes
URI: http://hdl.handle.net/10773/24476
DOI: 10.1007/s00477-018-1584-3
ISSN: 1436-3240
Publisher Version: https://link.springer.com/article/10.1007/s00477-018-1584-3
Appears in Collections:CIDMA - Artigos
IEETA - Artigos

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