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

<Para ID="Par1">The kernel method estimator of the spatial modal regression for functional regressors is proposed. We establish, under some general mixing conditions, the <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$L^p$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <msup> <mi>L</mi> <mi>p</mi> </msup> </math> </EquationSource> </InlineEquation>-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