Bayesian Estimation of Kendall's tau Using a Latent Normal Approach
Methodology
2018-05-25 v2
Abstract
The rank-based association between two variables can be modeled by introducing a latent normal level to ordinal data. We demonstrate how this approach yields Bayesian inference for Kendall's rank correlation coefficient, improving on a recent Bayesian solution from asymptotic properties of the test statistic.
Cite
@article{arxiv.1703.01805,
title = {Bayesian Estimation of Kendall's tau Using a Latent Normal Approach},
author = {Johnny van Doorn and Alexander Ly and Maarten Marsman and Eric-Jan Wagenmakers},
journal= {arXiv preprint arXiv:1703.01805},
year = {2018}
}
Comments
13 pages, 2 figures