This paper discusses characteristics of standard conjugate priors and their induced posteriors in Bayesian inference for von Mises-Fisher distributions, using either the canonical natural exponential family or the more commonly employed polar coordinate parameterizations. We analyze when standard conjugate priors as well as posteriors are proper, and investigate the Jeffreys prior for the von Mises-Fisher family. Finally, we characterize the proper distributions in the standard conjugate family of the (matrix-valued) von Mises-Fisher distributions on Stiefel manifolds.
Keywords: Bayesian inference; Conjugate prior; Jeffreys prior; von Mises–Fisher distribution.