# Discussion of “A Gibbs Sampler for a Class of Random Convex Polytopes”

@article{Diaconis2021DiscussionO, title={Discussion of “A Gibbs Sampler for a Class of Random Convex Polytopes”}, author={Persi Diaconis and Guanyang Wang}, journal={Journal of the American Statistical Association}, year={2021}, volume={116}, pages={1193 - 1195} }

The paper offers answers to these questions by proposing a Gibbs sampler to perform statistical inference for categorical distributions using the Dempster-Shafer approach. To be precise, let x = (xi) N i=1 be the observations, each comes from one of the K categories. The model assumes that there exists a θ = (θ1, · · · , θK) in the K−simplex ∆ := {(θ1, θ2, · · · , θK) : θi ≥ 0 for every i, ∑K i=1 θi = 1} such that P(xi = k) = θk for every i, k. Moreover, it is assumed that the observations x…

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