Wasserstein projection estimators for circular distributions
Statistics Theory
2025-10-22 v1 Statistics Theory
Abstract
For statistical models on circles, we investigate performance of estimators defined as the projections of the empirical distribution with respect to the Wasserstein distance. We develop algorithms for computing the Wasserstein projection estimators based on a formula of the Wasserstein distances on circles. Numerical results on the von Mises, wrapped Cauchy, and sine-skewed von Mises distributions show that the accuracy of the Wasserstein projection estimators is comparable to the maximum likelihood estimator. In addition, the -Wasserstein projection estimator is found to be robust against noise contamination.
Keywords
Cite
@article{arxiv.2510.18367,
title = {Wasserstein projection estimators for circular distributions},
author = {Naoki Otani and Takeru Matsuda},
journal= {arXiv preprint arXiv:2510.18367},
year = {2025}
}