Nonparametric multimodal regression for circular data

Fuente: arXiv
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Main Authors: Alonso-Pena, María, Crujeiras, Rosa M.
Format: Preprint
Published: 2020
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author Alonso-Pena, María
Crujeiras, Rosa M.
author_facet Alonso-Pena, María
Crujeiras, Rosa M.
contents Multimodal regression estimation methods are introduced for regression models involving circular response and/or covariate. The regression estimators are based on the maximization of the conditional densities of the response variable over the covariate. Conditional versions of the mean shift and the circular mean shift algorithms are used to obtain the regression estimators. The asymptotic properties of the estimators are studied and the problem of bandwidth selection is discussed.
format Preprint
id arxiv_https___arxiv_org_abs_2012_09915
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Nonparametric multimodal regression for circular data
Alonso-Pena, María
Crujeiras, Rosa M.
Methodology
Multimodal regression estimation methods are introduced for regression models involving circular response and/or covariate. The regression estimators are based on the maximization of the conditional densities of the response variable over the covariate. Conditional versions of the mean shift and the circular mean shift algorithms are used to obtain the regression estimators. The asymptotic properties of the estimators are studied and the problem of bandwidth selection is discussed.
title Nonparametric multimodal regression for circular data
topic Methodology
url https://arxiv.org/abs/2012.09915