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Lajos Horváth works on mathematical statistics, time series and econometrics. His University of Utah profile identifies these research interests.^[ref]

His joint paper with Piotr Kokoszka and Ron Reeder studies comparisons of mean curves in a functional time series. Its Hilbert space formulation yields Gaussian limits and a test based on the distance between two estimated mean functions, retaining dependence within each sample.^[ref]

Piotr Kokoszka studies functional data analysis, time series and spatial statistical methods. His Colorado State University homepage describes inference for observations that can themselves be curves.^[ref]

With Lajos Horváth and Ron Reeder, he developed estimation and statistical hypothesis testing for mean curves under temporal dependence. Averaging many curves requires a covariance accounting for correlation between successive observations; treating the curves as independent can misstate uncertainty.^[ref]

Ron Reeder coauthored Estimation of the Mean of Functional Time Series and a Two-Sample Problem by Lajos Horváth and others with Lajos Horváth and Piotr Kokoszka. Their problem treats successive daily curves as observations of a functional time series. The paper develops a normal approximation for their mean and a comparison of two mean curves that allows dependence across days.^[ref]