Asymptotic properties of a neyman-pearson test for model discrimination, with an application to experimental design

被引：1
|
作者：
Wiens D.P. [1 ]
机构：
[1] Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB
来源：
Journal of Statistical Theory and Practice | 2009年 / 3卷 / 2期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Asymptotics; Design; Discrimination; DT-optimality; KL-optimality; Kullback-Leibler divergence; Michaelis-Menten; T-optimality;
D O I：
10.1080/15598608.2009.10411934
中图分类号：
学科分类号：
摘要：
We present and derive the asymptotic properties of a certain Neyman-Pearson test, relevant for problems concerning discrimination between two competing models. We then study an application in which this test is used to assess the efficacy of designs, the purpose of which is to aid in discriminating between two nonlinear regression models. AMS Subject Classification: Primary: 62F03; 62F05. Secondary: 62K05; 62J02. © 2009 Taylor & Francis Group, LLC. All rights reserved.
引用
收藏
页码：419 / 427
页数：8
相关论文
共 50 条
12345