Multivariate cubic spline smoothing in multiple prediction

被引：3

作者：

Khamis, H ^{[1
]}

Kepler, M

机构：

[1] Uppsala Univ, Inst Informat Vetenskap, Uppsala, Sweden

[2] Wright State Univ, Comp & Telecommun Serv, Ctr Stat Consulting, Dayton, OH 45435 USA

来源：

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE | 2002年 / 67卷 / 02期

关键词：

multiple linear regression; Cholesky factorization; orthonormalization; cubic splines; prediction;

D O I：

10.1016/S0169-2607(01)00114-6

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Given longitudinal data for several variables, including a given outcome variable, it is desired to predict the outcome for a specific individual, or more generally experimental unit, in such a way that the predicted value is both accurate and resistant (i.e. has good cross-validation). There are certain data-analytic difficulties associated with long-term multivariate longitudinal data that must be overcome in the prediction process. This paper provides a program written in the Statistical Analysis System (SAS) programming language, based generally on the Roche-Wainer-Thissen stature prediction model, that enables the researcher to overcome these difficulties. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

引用

页码：131 / 136

页数：6

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