Test for Linearity in Non-Parametric Regression Models

被引：0

作者：

Khedidja, Djaballah-Djeddour ^{[1
,3
]}

Moussa, Tazerouti ^{[2
,3
,4
]}

机构：

[1] USTHB, MSTD Lab, El Alia, Algeria

[2] Univ Boumerdes, Boumerdes, Algeria

[3] Univ Sci & Technol Houari Boumed, MSTD Lab Math, BP 32, El Alia 16111, Algeria

[4] Univ Mhamed Bougara Boumerdes, Dept Math, Ave Independance, Boumerdes 35000, Algeria

来源：

AUSTRIAN JOURNAL OF STATISTICS | 2022年 / 51卷 / 01期

关键词：

regression; non-linearity; Hermite coefficient; nonparametric regression; random design; GOODNESS-OF-FIT;

D O I：

10.17713/ajs.v51i1.1047

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The problem of checking the linearity of a regression relationship is addressed. The test uses nonparametric estimation techniques. The null hypothesis is that the regression function is linear; it is tested against the non-specic alternatives hypotheses. This test is based on a Hermite transform characterization of conditional expectations. A statistical test is derived, the distribution of this statistic under the null hypothesis of linearity is determined. A power study using simulation shows the new statistic to be more sensitive to non-linearity.

引用

页码：16 / 34

页数：19

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