nftbart (Q82938)
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Nonparametric Failure Time Bayesian Additive Regression Trees
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | nftbart |
Nonparametric Failure Time Bayesian Additive Regression Trees |
Statements
28 November 2023
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Nonparametric Failure Time (NFT) Bayesian Additive Regression Trees (BART): Time-to-event Machine Learning with Heteroskedastic Bayesian Additive Regression Trees (HBART) and Low Information Omnibus (LIO) Dirichlet Process Mixtures (DPM). An NFT BART model is of the form Y = mu + f(x) + sd(x) E where functions f and sd have BART and HBART priors, respectively, while E is a nonparametric error distribution due to a DPM LIO prior hierarchy. See the following for a complete description of the model at <doi:10.1111/biom.13857>.
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expanded from: GPL (≥ 2) (English)
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