Nonparametric estimation of a smooth trend in the presence of a periodic sequence

被引:0
作者
Matsuoka, Danilo H. [1 ]
Torrent, Hudson S. [2 ]
机构
[1] Univ Fed Rio Grande do Sul, Fac Econ, 52 Ctr, BR-90040001 Porto Alegre, Brazil
[2] Univ Fed Rio Grande do Sul, Dept Stat, Porto Alegre, Brazil
关键词
Nonparametric regression; Period estimation; Plug-in bandwidth; Local linear estimator; Asymptotics; REGRESSION ESTIMATION; KERNEL ESTIMATORS; SEA;
D O I
10.1016/j.jspi.2023.01.002
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We investigate the estimators obtained from reversing the three-step estimation pro-cedure of Vogt and Linton (2014) for a regression model including a smooth trend function, a periodic component and a stochastic error term. The asymptotic properties of the estimators are given: (a) we provide the uniform weak convergence rates of the estimators of the trend function and periodic sequence; (b) we establish the asymptotic normality for the trend function estimator; and (c) we show that the period estimator is consistent. Plug-in type bandwidths are proposed for the trend estimator. A simulation study and an application to sea level data are employed in order to complement our theoretical results. (c) 2023 Elsevier B.V. All rights reserved.
引用
收藏
页码:202 / 218
页数:17
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