Polynomial spline approach for variable selection and estimation in varying coefficient models for time series data

被引：1

作者：

Lai, Peng ^{[1
]}

Meng, Jie ^{[2
]}

Lian, Heng ^{[3
]}

机构：

[1] Nanjing Univ Informat Sci & Technol, Sch Math & Stat, Nanjing 210044, Peoples R China

[2] Macquarie Univ, Dept Mkt & Management, N Ryde, NSW 2109, Australia

[3] Nanyang Technol Univ, SPMS, Div Math Sci, Singapore 637371, Singapore

来源：

STATISTICS & PROBABILITY LETTERS | 2015年 / 96卷

基金：

中国国家自然科学基金;

关键词：

Autoregressive models; BIC; B-spline basis; SCAD penalty; NONCONCAVE PENALIZED LIKELIHOOD; REGRESSION-MODELS; ASYMPTOTIC NORMALITY; EFFICIENT ESTIMATION; ORACLE PROPERTIES; DIMENSIONALITY; SHRINKAGE; LASSO;

D O I：

10.1016/j.spl.2014.09.008

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 propose the penalized estimator with the smoothly clipped absolute deviation (SCAD) penalty for varying coefficient time series models, which in autoregressive models actually performs lag order selection. Theoretical properties are established. Some numerical examples are also presented. (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：21 / 27

页数：7

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