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    Discussion of: "Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects"


    Prado, Estevão B. and O'Neill, Eoghan and Hernandez, Belinda and Parnell, Andrew and de Andrade Moral, Rafael (2020) Discussion of: "Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects". Bayesian Analysis, 15 (3). pp. 1029-1031. ISSN 1931-6690

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    Abstract

    Contributed discussion included in P. Richard Hahn. Jared S. Murray. Carlos M. Carvalho. "Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects (with Discussion)." Bayesian Anal. 15 (3) 965 - 1056, September 2020. https://doi.org/10.1214/19-BA1195

    Item Type: Article
    Keywords: Bayesian; Causal inference; heterogeneous treatment effects; machine learning; predictor-dependent priors; regression trees; regularization; shrinkage;
    Academic Unit: Faculty of Science and Engineering > Mathematics and Statistics
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 15552
    Identification Number: https://doi.org/10.1214/19-BA1195
    Depositing User: Rafael de Andrade Moral
    Date Deposited: 22 Feb 2022 15:09
    Journal or Publication Title: Bayesian Analysis
    Publisher: International Society for Bayesian Analysis (ISBA)
    Refereed: Yes
    URI:
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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