Wasserstein projection estimators for circular distributions

Fuente: arXiv
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Autori principali: Otani, Naoki, Matsuda, Takeru
Natura: Preprint
Pubblicazione: 2025
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author Otani, Naoki
Matsuda, Takeru
author_facet Otani, Naoki
Matsuda, Takeru
contents 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 $L^1$-Wasserstein projection estimator is found to be robust against noise contamination.
format Preprint
id arxiv_https___arxiv_org_abs_2510_18367
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Wasserstein projection estimators for circular distributions
Otani, Naoki
Matsuda, Takeru
Statistics Theory
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 $L^1$-Wasserstein projection estimator is found to be robust against noise contamination.
title Wasserstein projection estimators for circular distributions
topic Statistics Theory
url https://arxiv.org/abs/2510.18367