Systematic Identification of Two-compartment Model based on the Maximum Likelihood Method
ZHANG Yingyun
ZHANG Yufeng
WANG Yong
LI Jingjing
SHI Xinling
Abstract：A approach according to the Maximum Likelihood method was presented in this paper to identify the parameters of the Two-compartment Model.To verify the performance of this method, the estimation parameters of the Two-compartment Model ob-tained from it and their absolute errors were compared with those obtained from the methods based on recursive augmented least -squares algorithm.It could be seen that the accuracy and feasibility of the identification-parameters of the nonlinear two-compart-ment model received by Maximum Likelihood method were obviously better than those from the recursive augmented least-squares method.So those parameters with smaller deviations can be used in correlative clinical trial to improve the practicability of the nonlinear two-compartment model.
Keywords：Maximum likelihood algorithm identificationTwo-compartment modelIdentificationThe least squares methodThe absolute errorParameter identification
Publication Date：2014-01-01
Online Publishing Date：2026-09-11(First online date of this platform, not the publication date of the document)
Pages：4( 166-169 )