Note on Posterior Inference for the Bingham Distribution Mike G. Tsionas * 6th January 2017 Abstract The properties of high-dimensional Bingham distributions have been studied by Kume and Walker (2014). Fallaize and Kypraios (2016) propose Bayesian inference for the Bingham distribution and they use developments in Bayesian computation for distributions with doubly intractable normalising constants (Møller et al. 2006; Murray et al. 2006). However, they rely heavily on two Metropolis updates that they need to tune. In this paper we propose instead model selection with the marginal likelihood. Key words: Bingham distribution; Bayesian; Markov Chain Monte Carlo; marginal likelihood. * Lancaster University Management School, LA1 4YK, U.K. & Athens University of Economics and Business, Greece, m.tsionas@lancaster.ac.uk 1