IJPAM: Volume 87, No. 4 (2013)
INEAR ERRORS-IN-VARIABLES MODELS
WITH LONGITUDINAL DATA



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
Year: 2013
Volume: 87
Issue: 4