CONSISTENCY OF A CLASS OF INFORMATION CRITERIA FOR MODEL SELECTION IN NONLINEAR-REGRESSION

被引：6

作者：

HAUGHTON, D ^{[1
]}

机构：

[1] UNIV LOWELL,LOWELL,MA 01854

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 1991年 / 20卷 / 5-6期

基金：

美国国家科学基金会;

关键词：

MODEL SELECTION; INFORMATION CRITERIA; BIC; GIC; CONSISTENCY IN PROBABILITY; NONLINEAR REGRESSION;

D O I：

10.1080/03610929108830587

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：

In this paper we prove the consistency in probability of a class of generalized BIC criteria for model selection in non-linear regression, by using asymptotic results of Gallant. This extends a result obtained by Nishii for model selection in linear regression.

引用

页码：1619 / 1629

页数：11

共 29 条

[1] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].