Predictive density estimation under the Wasserstein loss
Statistics Theory
2021-09-01 v1 Statistics Theory
Abstract
We investigate predictive density estimation under the Wasserstein loss for location families and location-scale families. We show that plug-in densities form a complete class and that the Bayesian predictive density is given by the plug-in density with the posterior mean of the location and scale parameters. We provide Bayesian predictive densities that dominate the best equivariant one in normal models.
Keywords
Cite
@article{arxiv.1904.02880,
title = {Predictive density estimation under the Wasserstein loss},
author = {Takeru Matsuda and William E. Strawderman},
journal= {arXiv preprint arXiv:1904.02880},
year = {2021}
}