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- W4309136952 abstract "This paper introduces Type I Tobit Bayesian Additive Regression Trees (TOBART-1). Simulation results and applications to real data sets demonstrate that TOBART-1 produces more accurate predictions than competing methods. TOBART-1 provides accurate posterior intervals for the conditional expectation and other quantities of interest. A Dirichlet Process mixture of normal distributions can flexibly model the error term for improved uncertainty quantification." @default.
- W4309136952 created "2022-11-23" @default.
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- W4309136952 date "2022-11-14" @default.
- W4309136952 modified "2023-10-17" @default.
- W4309136952 title "Type I Tobit Bayesian Additive Regression Trees for Censored Outcome Regression" @default.
- W4309136952 doi "https://doi.org/10.48550/arxiv.2211.07506" @default.
- W4309136952 hasPublicationYear "2022" @default.
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