Journal of Applied Mathematics
Volume 2012 (2012), Article ID 250909, 13 pages
http://dx.doi.org/10.1155/2012/250909
Research Article

Empirical Likelihood Estimation for Population Pharmacokinetic Study Based on Generalized Linear Model

Fang-rong Yan,1,2,3 Jin-guan Lin,1 Yuan Huang,2,3 Jun-lin Liu,2,3 and Tao Lu2,3

1Department of Mathematics, Southeast University, Nanjing 210096, China
2Department of Mathematics, China Pharmaceutical University, Nanjing 210009, China
3State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China

Received 29 September 2012; Accepted 18 November 2012

Academic Editor: Li Weili

Copyright © 2012 Fang-rong Yan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

To obtain efficient estimation of parameters is a major objective in population pharmacokinetic study. In this paper, we propose an empirical likelihood-based method to analyze the population pharmacokinetic data based on the generalized linear model. A nonparametric version of the Wilk's theorem for the limiting distributions of the empirical likelihood ratio is derived. Simulations are conducted to demonstrate the accuracy and efficiency of empirical likelihood method. An application illustrating our methods and supporting the simulation study results is presented. The results suggest that the proposed method is feasible for population pharmacokinetic data.