Approximate standard errors in semiparametric models

被引:12
|
作者
Durban, M
Hackett, CA
Currie, ID [1 ]
机构
[1] Scottish Crop Res Inst, Biomath & Stat Scotland, Dundee DD2 5DA, Scotland
[2] Heriot Watt Univ, Dept Actuarial Math & Stat, Edinburgh EH14 4AS, Midlothian, Scotland
关键词
additive model; back-fitting algorithm; locally weighted regression; loess; semiparametric model; smoothing splines; standard error;
D O I
10.1111/j.0006-341X.1999.00699.x
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
We consider semiparametric models with p regressor terms and q smooth terms. We obtain an explicit expression for the estimate of the regression coefficients given by the back-fitting algorithm. The calculation of the standard errors of these estimates based on this expression is a considerable computational exercise. We present an alternative, approximate method of calculation that is less demanding. With smoothing splines, the method is exact, while with loess, it gives good estimates of standard errors. We assess the adequacy of our approximation and of another approximation with the help of two examples.
引用
收藏
页码:699 / 703
页数:5
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