A comparison of bandwidth selectors for moderate degree local polynomial regression

Dongying Wang () and W. John Braun ()
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Dongying Wang: Statistics, University of British Columbia
W. John Braun: Statistics, University of British Columbia

Statistical Methods & Applications, 2025, vol. 34, issue 2, No 1, 194 pages

Abstract: Abstract This paper presents a direct-plug-in bandwidth selector for local quadratic regression and local cubic regression, leveraging existing theoretical frameworks. Through extensive simulation studies, the performance of the proposed selector is evaluated using the Mean Squared Error (MSE) and Mean Absolute Error (MAE) criteria, in comparison with established methods. Additionally, empirical coverage of confidence intervals is analyzed to further assess its effectiveness. Practical applications of the methods are illustrated using wildfire rate of spread data.

Keywords: Local quadratic regression; Local cubic regression; Bandwidth selection; Cross validation; Shape information (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10260-025-00784-2

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