DEPENDENT ERROR REGRESSION SMOOTHING - A NEW METHOD AND PC PROGRAM

被引：3

作者：

SCHIMEK, MG ^{[1
]}

SCHMARANZ, KG ^{[1
]}

机构：

[1] GRAZ UNIV,SCH MED,MED BIOMETR GRP,A-8036 GRAZ,AUSTRIA

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 1994年 / 17卷 / 04期

关键词：

NONPARAMETRIC REGRESSION; BAND-LIMITED MATRIX; C++; CUBIC SMOOTHING SPLINES; CROSS-VALIDATION; DEPENDENT ERRORS; HAT MATRIX; MEMORY MANAGEMENT; PC IMPLEMENTATION; RESIDUALS; SERIAL CORRELATION; SMOOTHING PARAMETER; TIME SERIES; TRIANGULAR MATRIX; VARIANCE ESTIMATION; AUTOREGRESSIVE; MOVING AVERAGE; MS-WINDOWS;

D O I：

10.1016/0167-9473(94)90024-8

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The problem of cubic spline smoothing of dependent data like time series and growth curves is addressed in this paper. Available statistical systems like S-PLUS (STATISTICAL SCIENCES, INC., 1991) and XploRe (XploRe SYSTEMS, 1992) do not provide appropriate algorithms. We propose a simple penalized least squares method with a number of computational advantages. It is called Dependent Error Regression Smoothing (abb. DERS) and implemented in a PC program under MS-Windows of the same name. The implementation comprises two techniques in an exploratory setting for smoothing parameter choice when the errors are serially correlated.

引用

页码：457 / 464

页数：8

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