Journal of Applied Mathematics

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

Fang-rong Yan, Jin-guan Lin, Yuan Huang, Jun-lin Liu, and Tao Lu

Full-text: Open access

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.

Article information

Source
J. Appl. Math., Volume 2012 (2012), Article ID 250909, 13 pages.

Dates
First available in Project Euclid: 5 April 2013

Permanent link to this document
https://projecteuclid.org/euclid.jam/1365174341

Digital Object Identifier
doi:10.1155/2012/250909

Mathematical Reviews number (MathSciNet)
MR3005214

Zentralblatt MATH identifier
06169870

Citation

Yan, Fang-rong; Lin, Jin-guan; Huang, Yuan; Liu, Jun-lin; Lu, Tao. Empirical Likelihood Estimation for Population Pharmacokinetic Study Based on Generalized Linear Model. J. Appl. Math. 2012 (2012), Article ID 250909, 13 pages. doi:10.1155/2012/250909. https://projecteuclid.org/euclid.jam/1365174341


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