Open AccessOptimal Population Designs for Discrimination Between Two Nested Nonlinear Mixed Effects Models.
Author(s) -
Víctor Ignacio López-Ríos
Publication year - 2016
Publication title -
ciencia en desarrollo
Language(s) - English
Resource type - Journals
eISSN - 2462-7658
pISSN - 0121-7488
DOI - 10.19053/01217488.4233
Subject(s) - equivalence (formal languages) , generalization , nonlinear system , mathematics , population , covariance matrix , mathematical optimization , statistics , discrete mathematics , medicine , mathematical analysis , physics , environmental health , quantum mechanics
In this paper we consider the problem of finding optimal population designs for discrimination betweentwo nested nonlinear mixed effects models which differ in their intra-individual covariance matrix. Thecriterion proposed is a generalization of the T-optimality criterion. For this criterion an equivalence theorem is provided. The application of the criterion is illustrated with an example in pharmacokinetic.