Adjustment of prediction intervals in nonlinear regression

被引：1

作者：

Goh, KL ^{[1
]}

Pooi, AH ^{[1
]}

机构：

[1] Univ Malaya, Dept Math, Kuala Lumpur 50603, Malaysia

来源：

BIOMETRICAL JOURNAL | 1997年 / 39卷 / 06期

关键词：

nonlinear model; prediction intervals; expected coverage; adjustment;

D O I：

10.1002/bimj.4710390610

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

By treating the nonlinear model as if it were linear in the parameterization theta in the neighbourhood of the least squares estimate <(theta)over cap>, two-sided nominally-q-prediction intervals can be constructed by applying the usual linear model theory. The quadratic approximation of the expected coverage of the prediction intervals is derived for a p-parameter nonlinear model. An adjustment of the nominally-q-prediction intervals is proposed. It is shown that, to the extent that quadratic approximation is adequate, the actual expected coverage of the adjusted prediction intervals is q.

引用

页码：719 / 731

页数：13