Premium
Approximate Standard Errors in Semiparametric Models
Author(s) -
Durban Maria,
Hackett Christine A.,
Currie I. D.
Publication year - 1999
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.1999.00699.x
Subject(s) - semiparametric regression , standard error , expression (computer science) , smoothing , mathematics , smoothing spline , semiparametric model , regression , computer science , mathematical optimization , statistics , parametric statistics , bilinear interpolation , programming language , spline interpolation
Summary. SUMMARY. 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.