{"ID":2884649,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.06150","arxiv_id":"2508.06150","title":"Nonparametric Estimation For Censored Circular Data","abstract":"We study the problem of estimating the probability density function of a circular random variable subject to censoring. To this end, we propose a fully computable quotient estimator that combines a projection estimator on linear sieves with a method-of-moments approach. We derive an upper bound for its mean integrated squared error and establish convergence rates when the underlying density lies in a Sobolev class. The practical performance of the estimator is illustrated through simulated examples.","short_abstract":"We study the problem of estimating the probability density function of a circular random variable subject to censoring. To this end, we propose a fully computable quotient estimator that combines a projection estimator on linear sieves with a method-of-moments approach. We derive an upper bound for its mean integrated...","url_abs":"https://arxiv.org/abs/2508.06150","url_pdf":"https://arxiv.org/pdf/2508.06150v1","authors":"[\"Nicolas Conanec\"]","published":"2025-08-08T09:13:45Z","proceeding":"math.ST","tasks":"[\"math.ST\"]","methods":"[]","has_code":false}