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Inference for BART with Multinomial Outcomes. (arXiv:2101.06823v2 [stat.ME] UPDATED)
Aug. 16, 2022, 1:12 a.m. | Yizhen Xu, Joseph W. Hogan, Michael J. Daniels, Rami Kantor, Ann Mwangi
stat.ML updates on arXiv.org arxiv.org
The multinomial probit Bayesian additive regression trees (MPBART) framework
was proposed by Kindo et al. (KD), approximating the latent utilities in the
multinomial probit (MNP) model with BART (Chipman et al. 2010). Compared to
multinomial logistic models, MNP does not assume independent alternatives and
the correlation structure among alternatives can be specified through
multivariate Gaussian distributed latent utilities. We introduce two new
algorithms for fitting the MPBART and show that the theoretical mixing rates of
our proposals are equal or …
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