Test for Linearity in Non-Parametric Regression Models | Zendy

Khedidja Djaballah-Djeddour | Zendy; Moussa Tazerouti | Zendy

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Test for Linearity in Non-Parametric Regression Models

Author(s) -

Khedidja Djaballah-Djeddour,

Moussa Tazerouti

Publication year - 2022

Publication title -

austrian journal of statistics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.342

H-Index - 9

ISSN - 1026-597X

DOI - 10.17713/ajs.v51i1.1047

Subject(s) - mathematics , linearity , nonparametric statistics , null hypothesis , statistical hypothesis testing , test statistic , statistics , parametric statistics , statistic , nonparametric regression , null distribution

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 statisticunder the null hypothesis of linearity is determined. A power study using simulation shows the new statistic to be more sensitive to non-linearity.

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