Regression analysis of elliptically symmetric directional data

Zehao Yu and Xianzheng Huang

Computational Statistics & Data Analysis, 2025, vol. 208, issue C

Abstract: A comprehensive toolkit is developed for regression analysis of directional data based on a flexible class of angular Gaussian distributions. Informative testing procedures to assess rotational symmetry around the mean direction, and the dependence of model parameters on covariates are proposed. Bootstrap-based algorithms are provided to assess the significance of the proposed test statistics. Moreover, a prediction region that achieves the smallest volume in a class of ellipsoidal prediction regions of the same coverage probability is constructed. The efficacy of these inference procedures is demonstrated in simulation experiments. Finally, this new toolkit is used to analyze directional data originating from a hydrology study and a bioinformatics application.

Keywords: Angular Gaussian; Hypersphere; Isotropy; Prediction region (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:208:y:2025:i:c:s016794732500043x

DOI: 10.1016/j.csda.2025.108167

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