Open AccessTest for Linearity in Non-Parametric Regression Models
Author(s) -
Khedidja Djaballah-Djeddour,
Moussa Tazerouti
Publication year - 2022
Publication title -
österreichische zeitschrift für statistik
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.