Asymptotic properties of the kernel estimate of spatial conditional mode when the regressor is functional

Sophie Dabo-Niang, Zoulikha Kaid () and Ali Laksaci ()

AStA Advances in Statistical Analysis, 2015, vol. 99, issue 2, 160 pages

Abstract: The kernel method estimator of the spatial modal regression for functional regressors is proposed. We establish, under some general mixing conditions, the $$L^p$$ L p -consistency and the asymptotic normality of the estimator. The performance of the proposed estimator is illustrated in a real data application. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Spatial process; Conditional mode estimate; Non-parametric; Functional data; 62G20; 62G08 (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:alstar:v:99:y:2015:i:2:p:131-160

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DOI: 10.1007/s10182-014-0233-5

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