%0 Journal Article
%9 Article
%W National Agricultural Library
%~ PubAg
%B Stochastic environmental research and risk assessment
%T A full ARMA model for counts with bounded support and its application to rainy-days time series
%A Gouveia, Sónia
%A Möller, Tobias A.
%A Weiß, Christian H.
%A Scotto, Manuel G.
%V 2018 v.32 no.9
%K data collection
%K models
%K statistical analysis
%K time series analysis
%K Russia
%M 6105754
%X 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.
%D 2018
%= 2018-12-01
%G
%8 2018-09
%V v. 32
%N no. 9
%P pp. 2495-2514
%R 10.1007/s00477-018-1584-3