Functional coefficient seasonal time series models with an application of Hawaii tourism data

Xialu Liu (), Zongwu Cai () and Rong Chen ()

Computational Statistics, 2015, vol. 30, issue 3, 719-744

Abstract: In this article, motivated by an analysis of the monthly number of tourists visiting Hawaii, we propose a new class of nonparametric seasonal time series models under the framework of the functional coefficient model. The coefficients change over time and consist of the trend and seasonal components to characterize seasonality. A local linear approach is developed to estimate the nonparametric trend and seasonal effect functions. The consistency of the proposed estimators is obtained without specifying the error distribution and the asymptotic normality of the proposed estimators is established under the $$\alpha $$ α -mixing conditions. A consistent estimator of the asymptotic variance is also provided. The proposed methodologies are illustrated by two simulated examples and the model is applied to characterizing the seasonality of the monthly number of tourists visiting Hawaii. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Fixed effects; Functional-coefficient models; Local linear fitting; Nonparametric smoothing; Seasonal variation (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:30:y:2015:i:3:p:719-744

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DOI: 10.1007/s00180-015-0574-x

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