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- Title
Empirical likelihood for the varying-coefficient single-index model.
- Authors
Huang, Zhensheng; Zhang, Riquan
- Abstract
In this article the author investigates the application of the empirical-likelihood-based inference for the parameters of varying-coefficient single-index model (VCSIM). Unlike the usual cases, if there no bias correction the asymptotic distribution of the empirical likelihood ratio cannot achieve the standard chi-squared distribution. To this end, a bias-corrected empirical likelihood method is employed to construct the confidence regions (intervals) of regression parameters, which have two advantages, compared with those based on normal approximation, that is, (1) they do not impose prior constraints on the shape of the regions; (2) they do not require the construction of a pivotal quantity and the regions are range preserving and transformation respecting. A simulation study is undertaken to compare the empirical likelihood with the normal approximation in terms of coverage accuracies and average areas/lengths of confidence regions/intervals. A real data example is given to illustrate the proposed approach.
- Subjects
ASYMPTOTIC distribution; CHI-square distribution; ASYMPTOTIC expansions; DISTRIBUTION (Probability theory); STATISTICS
- Publication
Canadian Journal of Statistics, 2010, Vol 38, Issue 3, p434
- ISSN
0319-5724
- Publication type
Article
- DOI
10.1002/cjs.10075