IJPAM: Volume 87, No. 4 (2013)
INEAR ERRORS-IN-VARIABLES MODELS
WITH LONGITUDINAL DATA
School of Science
Lanzhou University of Technology
Lanzhou, Gansu, 730050, P.R. CHINA
Abstract. In this paper, block empirical likelihood inference for partially linear errors-in-variables models with longitudinal data are investigated. We apply the block empirical likelihood procedure to accommodate the within-group correlation of the longitudinal data. The block empirical log-likelihood ratio statistic for the parametric components, which are of primary interest, is suggested. And the nonparametric version of the Wilk's theorem is derived under mild conditions. Thus, the empirical likelihood confidence region with asymptotically correct coverage probabilities for parametric components can be constructed. Simulations are carried out to access the performance of the proposed approach.
Received: August 26, 2013
AMS Subject Classification: 62G15, 62G20
Key Words and Phrases: block empirical likelihood, partially linear model, errors-in-variables, longitudinal data
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DOI: 10.12732/ijpam.v87i4.15 How to cite this paper?
Source: International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395