Open Access Open Access  Restricted Access Subscription or Fee Access

Heteroscedasticity Testing in Nonparametric Functional Data Statistics

Mustapha Rachdi, Halima Bensmail, Noriah Al-Kandari, Idir Ouassou

Abstract



We present a consistent nonparametric test statistic for heteroscedasticity in functional data. First we construct the test by evaluating the difference between conditional and unconditional variances. Then we show the asymptotic normality of this test statistic under null hypothesis. In addition, we prove that this test is also consistent against all deviations from the homoscedasticity condition.

Keywords


Functional data analysis (FDA), Nonparametric test, Nonparametric functional data analysis (NFDA), Kernel estimate, U-statistic.

Full Text:

PDF


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.