Seasonal Functional Autoregressive Models
Atefeh Zamani,
Hossein Haghbin,
Maryam Hashemi and
Rob Hyndman
No 16/19, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics
Abstract:
Functional autoregressive models are popular for functional time series analysis, but the standard formulation fails to address seasonal behaviour in functional time series data. To overcome this shortcoming, we introduce seasonal functional autoregressive time series models. For the model of order one, we derive sufficient stationarity conditions and limiting behavior, and provide estimation and prediction methods. Some properties of the general order P model are also presented. The merits of these models are demonstrated using simulation studies and via an application to real data.
Keywords: functional time series analysis; seasonal functional autoregressive model; central limit theorem; prediction; estimation (search for similar items in EconPapers)
JEL-codes: C14 C32 (search for similar items in EconPapers)
Pages: 26
Date: 2019
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-for and nep-ore
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