Penalized quadratic inference functions for single-index models with longitudinal data

JOURNAL OF MULTIVARIATE ANALYSIS

卷:100

Article

Bai, Yang¹  Fung, Wing K.¹  Zhu, Zhong Yi² 

[1] Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China

[2] Fudan Univ, Dept Stat, Shanghai 200433, Peoples R China

关键词: Longitudinal data;    P-splines;    Quadratic inference functions;    Single-index models;   

DOI  :  10.1016/j.jmva.2008.04.004

来源: Elsevier

【 摘 要 】

In this paper, we focus on single-index models for longitudinal data. We propose a procedure to estimate the single-index component and the unknown link function based on the combination of the penalized splines and quadratic inference functions. It is shown that the proposed estimation method has good asymptotic properties. We also evaluate the finite sample performance of the proposed method via Monte Carlo simulation studies. Furthermore, the proposed method is illustrated in the analysis of a real data set. (C) 2008 Elsevier Inc. All rights reserved.

【 授权许可】

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