Web: http://arxiv.org/abs/2007.06944

Jan. 26, 2022, 2:10 a.m. | Augusto Fasano, Daniele Durante

stat.ML updates on arXiv.org arxiv.org

Multinomial probit models are routinely-implemented representations for
learning how the class probabilities of categorical response data change with p
observed predictors. Although several frequentist methods have been developed
for estimation, inference and classification within such a class of models,
Bayesian inference is still lagging behind. This is due to the apparent absence
of a tractable class of conjugate priors, that may facilitate posterior
inference on the multinomial probit coefficients. Such an issue has motivated
increasing efforts toward the development of …

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