DT-optimum designs for model discrimination and parameter estimation

被引:64
作者
Atkinson, A. C. [1 ]
机构
[1] London Sch Econ, Dept Stat, London WC2A 2AE, England
关键词
D-optimum desigm; D(I) -optimum design; equivalence theorem; nonlinear model; T-optimum design; 2 RIVAL MODELS; REGRESSION;
D O I
10.1016/j.jspi.2007.05.024
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The paper introduces DT-optimum designs that provide a specified balance between model discrimination and parameter estimation. An equivalence theorem is presented for the case of two models and extended to an arbitrary number of models and of combinations of parameters. A numerical example shows the properties of the procedure. The relationship with other design procedures for parameter estimation and model discrimination is discussed. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:56 / 64
页数:9
相关论文
共 23 条
[1]  
[Anonymous], OPTIMAL DESIGN EXPT
[2]   DESIGN OF EXPERIMENTS FOR DISCRIMINATING BETWEEN TWO RIVAL MODELS [J].
ATKINSON, AC ;
FEDOROV, VV .
BIOMETRIKA, 1975, 62 (01) :57-70
[3]  
Atkinson AnthonyC., 1992, OPTIMUM EXPT DESIGNS, DOI [10.1007/978-3-642-04898-2434, DOI 10.1007/978-3-642-04898-2434]
[4]  
Biedermann S, 2004, CONTRIB STAT, P41
[5]   An efficient design for model discrimination and parameter estimation in linear models [J].
Biswas, A ;
Chaudhuri, P .
BIOMETRIKA, 2002, 89 (03) :709-718
[6]   DESIGN OF EXPERIMENTS IN NON-LINEAR SITUATIONS [J].
BOX, GEP ;
LUCAS, HL .
BIOMETRIKA, 1959, 46 (1-2) :77-90
[7]   OPTIMUM EXPERIMENTAL-DESIGN FOR DISCRIMINATING BETWEEN 2 RIVAL MODELS IN THE PRESENCE OF PRIOR INFORMATION [J].
DELEON, ACP ;
ATKINSON, AC .
BIOMETRIKA, 1991, 78 (03) :601-608
[8]   OPTIMAL DESIGNS FOR IDENTIFYING THE DEGREE OF A POLYNOMIAL REGRESSION [J].
DETTE, H .
ANNALS OF STATISTICS, 1995, 23 (04) :1248-1266
[9]   Finite sample performance of sequential designs for model identification [J].
Dette, H ;
Kwiecien, R .
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2005, 75 (06) :477-495
[10]   A comparison of sequential and non-sequential designs for discrimination between nested regression models [J].
Dette, H ;
Kwiecien, R .
BIOMETRIKA, 2004, 91 (01) :165-176