Spherical Principal Curves
This work addresses dimension reduction for non-Euclidean data, specifically on spheres, but is incremental as it adapts an existing Euclidean method to a spherical context.
The authors tackled the problem of dimension reduction for spherical data by proposing a new method to construct principal curves on a sphere, which avoids distortions from approximations used in prior work. Results from earthquake data and simulations show promising empirical properties.
This paper presents a new approach for dimension reduction of data observed in a sphere. Several dimension reduction techniques have recently developed for the analysis of non-Euclidean data. As a pioneer work, Hauberg (2016) attempted to implement principal curves on Riemannian manifolds. However, this approach uses approximations to deal with data on Riemannian manifolds, which causes distorted results. In this study, we propose a new approach to construct principal curves on a sphere by a projection of the data onto a continuous curve. Our approach lies in the same line of Hastie and Stuetzle (1989) that proposed principal curves for Euclidean space data. We further investigate the stationarity of the proposed principal curves that satisfy the self-consistency on a sphere. Results from real data analysis with earthquake data and simulation examples demonstrate the promising empirical properties of the proposed approach.