Adaptive profile-empirical-likelihood inferences for generalized single-index models

Zhensheng Huang, Zhen Pang and Riquan Zhang

Computational Statistics & Data Analysis, 2013, vol. 62, issue C, 70-82

Abstract: We study generalized single-index models and propose an efficient equation for estimating the index parameter and unknown link function, deriving a quasi-likelihood-based maximum empirical likelihood estimator (QLMELE) of the index parameter. We then establish an efficient confidence region for any components of the index parameter using an adaptive empirical likelihood method. A pointwise confidence interval for the unknown link function is also established using the QLMELE. Compared with the normal approximation proposed by Cui et al. [Ann Stat. 39 (2011) 1658], our approach is more attractive not only theoretically but also empirically. Simulation studies demonstrate that the proposed method provides smaller confidence intervals than those based on the normal approximation method subject to the same coverage probabilities. Hence, the proposed empirical likelihood is preferable to the normal approximation method because of the complicated covariance estimation. An application to a real data set is also illustrated.

Keywords: Adaptive empirical likelihood; Confidence interval; Generalized single-index model; Link function; QLMELE (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167947312004409
Full text for ScienceDirect subscribers only.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:62:y:2013:i:c:p:70-82

DOI: 10.1016/j.csda.2012.12.006

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().