Nonparametric estimation for a functional-circular regression model

نویسندگان

چکیده

Abstract Changes on temperature patterns, a local scale, are perceived by individuals as the most direct indicators of global warming and climate change. As specific example, for an Atlantic location, spring fall seasons should present mild transition between winter summer, summer winter, respectively. By observing daily curves along time, being each curve attached to certain calendar day, regression model these variables (temperature covariate day response) would be useful modeling their relation period. In addition, changes could assessed prediction observation comparisons in long run. Such is presented studied this work, considering nonparametric Nadaraya–Watson-type estimator functional circular response. The asymptotic bias variance estimator, well its distribution derived. Its finite sample performance evaluated simulation study proposal applied investigate real-data set concerning curves.

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ژورنال

عنوان ژورنال: Statistical papers

سال: 2023

ISSN: ['2412-110X', '0250-9822']

DOI: https://doi.org/10.1007/s00362-023-01420-5