Sensible parameters for univariate and multivariate splines

被引:19
|
作者
Newson, Roger B. [1 ]
机构
[1] Univ London Imperial Coll Sci Technol & Med, Natl Heart & Lung Inst, London, England
来源
STATA JOURNAL | 2012年 / 12卷 / 03期
关键词
sg151_2; bspline; fiexcurv; frencurv; polynomial; spline; B-spline; interpolation; linear; quadratic; cubic; multivariate; factor; interaction;
D O I
10.1177/1536867X1201200310
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
The package bspline, downloadable from Statistical Software Components, now has three commands. The first, bspline, generates a basis of Schoenberg B-splines. The second, frencurv, generates a basis of reference splines whose parameters in the regression model are simply values of the spline at reference points on the X axis. The recent addition, flexcurv, is an easy-to-use version of frencurv that generates reference splines with automatically generated, sensibly spaced knots. frencurv and flexcurv now have the additional option of generating an incomplete basis of reference splines, with the reference spline for a baseline reference point omitted or set to 0. This incomplete basis can be completed by adding the standard unit vector to the design matrix and can then be used to estimate differences between values of the spline at the remaining reference points and the value of the spline at the baseline reference point. Reference splines therefore model continuous factor variables as indicator variables (or "dummies") model discrete factor variables. The method can be extended in a similar way to define factor-product bases, allowing the user to estimate factor-combination means, subset-specific effects, or even factor interactions involving multiple continuous or discrete factors.
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页码:479 / 504
页数:26
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