Rates of convergence of some estimators for a semiparametric model
作者:
Jyh-Jen Horng Shiau,
Grace Wahba,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1988)
卷期:
Volume 17,
issue 4
页码: 1117-1133
ISSN:0361-0918
年代: 1988
DOI:10.1080/03610918808812716
出版商: Marcel Dekker, Inc.
关键词: Rate of convergenc;partial spline;smoothing splin;semiparametric mode;generaii~ed - cross - validation
数据来源: Taylor
摘要:
In this paper, we analyze the rates of convergence of the mean square error of a partial spline estimator and a Denby/Speckman - type estimator for the parametric component of a semiparametric model under a wide range of conditions. It is found that the Denby/Speckman - type estimator has a faster rate of convergence than the partial spline estimator for some cases. Itis shown that the optimal rate of decrease for the smoothing parameter X under the criterion of minimizing MSE for the parametric component is not necessarily the same as the optimal rate for minimization of the predictive mean square error in the function estimate. Thus data based estimates for X optimal for predictive mean square error in the function, such as GCV, maynot be optimal for mean square error in the parametric component, leaving open the question of a data based estimate for X in this context.
点击下载:
PDF (413KB)
返 回