@inbook{e9c37d4bd40d4e8bbb64ccf731695f12,
title = "Flexible Seasonal Time Series Models",
abstract = "In this article, we propose a new class of flexible seasonal time series models to characterize the trend and seasonal variations. The proposed model consists of a common trend function over periods and additive individual trend (seasonal effect) functions that are specific to each season within periods. A local linear approach is developed to estimate the trend and seasonal effect functions. The consistency and asymptotic normality of the proposed estimators, together with a consistent estimator of the asymptotic variance, are obtained under the α-mixing conditions and without specifying the error distribution. The proposed methodologies are illustrated with a simulated example and two economic and financial time series, which exhibit nonlinear and nonstationary behavior.",
author = "Zongwu Cai and Rong Chen",
note = "Funding Information: The authors are grateful to the co-editor T. Fomby and the referee for their very detailed and constructive commends and suggestions, and Professors D. Findley, T. Fomby, R.H. Shumway, and R.S. Tsay as well as the audiences at the NBER/NSF Time Series Conference at Dallas 2004 for their helpful and insightful comments and suggestions. Cai's research was supported in part by the National Science Foundation grants DMS-0072400 and DMS-0404954 and funds provided by the University of North Carolina at Charlotte. Chen's research was supported in part by the National Science Foundation grants DMS-0073601, 0244541 and NIH grant R01 Gm068958. ",
year = "2006",
doi = "10.1016/S0731-9053(05)20022-1",
language = "English (US)",
isbn = "0762312734",
series = "Advances in Econometrics",
pages = "63--87",
editor = "Thomas Fomby and Dek Terrell",
booktitle = "Econometric Analysis of Financial and Economic Time Series",
}