非线性混合效应模型中个体内协方差矩阵判别和参数估计的优化设计准则

Q3 Mathematics

Revista Colombiana De Estadistica Pub Date : 2020-07-01 DOI:10.15446/rce.v43n2.81938

V. López-Ríos, M. E. Castañeda-López

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引用次数: 0

摘要

本文研究了非线性混合效应模型中个体内协方差矩阵判别和参数估计的最优种群设计问题。提出了一种综合了估计准则和判别准则的复合最优性准则。我们使用d -最优准则进行参数估计，使Fisher信息矩阵的行列式最大化。为了区分，我们提出了x -效应模型的t -最优性准则的推广。给出了这些准则的等价定理。以一个药代动力学实验为例，说明了复合标准的应用。

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An Optimal Design Criterion for Within-Individual Covariance Matrices Discrimination and Parameter Estimation in Nonlinear Mixed Effects Models

In this paper, we consider the problem of nding optimal populationdesigns for within-individual covariance matrices discrimination andparameter estimation in nonlinear mixed eects models. A compound optimality criterion is provided, which combines an estimation criterion and a discrimination criterion. We used the D-optimality criterion for parameter estimation, which maximizes the determinant of the Fisher information matrix. For discrimination, we propose a generalization of the T-optimality criterion for xed-eects models. Equivalence theorems are provided for these criteria. We illustrated the application of compound criteria with an example in a pharmacokinetic experiment.

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来源期刊

Revista Colombiana De Estadistica STATISTICS & PROBABILITY-

CiteScore

1.20

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The Colombian Journal of Statistics publishes original articles of theoretical, methodological and educational kind in any branch of Statistics. Purely theoretical papers should include illustration of the techniques presented with real data or at least simulation experiments in order to verify the usefulness of the contents presented. Informative articles of high quality methodologies or statistical techniques applied in different fields of knowledge are also considered. Only articles in English language are considered for publication. The Editorial Committee assumes that the works submitted for evaluation have not been previously published and are not being given simultaneously for publication elsewhere, and will not be without prior consent of the Committee, unless, as a result of the assessment, decides not publish in the journal. It is further assumed that when the authors deliver a document for publication in the Colombian Journal of Statistics, they know the above conditions and agree with them.