A Nonparametric Lack-of-Fit Test of Constant Regression in the Presence of Heteroscedastic Variances

A Nonparametric Lack-of-Fit Test of Constant Regression in the Presence of Heteroscedastic Variances

We consider a <i>k</i>-nearest neighbor-based nonparametric lack-of-fit test of constant regression in presence of heteroscedastic variances. The asymptotic distribution of the test statistic is derived under the null and local alternatives for a fixed number of nearest neighbors. Advant...

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Bibliographic Details
Main Authors: Mohammed M. Gharaibeh, Mohammad Sahtout, Haiyan Wang, Suojin Wang
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Symmetry
Subjects:
lack-of-fit
hypothesis testing
k-nearest neighbor
heteroscedastic regression
Online Access:https://www.mdpi.com/2073-8994/13/7/1264

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https://www.mdpi.com/2073-8994/13/7/1264

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