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Comments on: hybrid semiparametric Bayesian networks

Author

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  • Stefan Sperlich

    (University of Geneva)

Abstract

This note comments on the article of David Atienza, Pedro Larrañaga and Concha Bielza in which they first review recent contributions to Bayesian networks and then introduce a new hybrid version. It combines parametric and nonparametric density estimates for continuous variables by simultaneously allowing for discrete parents. We discuss straightforward extensions of the linear Gaussian parts and potential smoothing over the outcomes of discrete parents and conclude with some minor comments.

Suggested Citation

  • Stefan Sperlich, 2022. "Comments on: hybrid semiparametric Bayesian networks," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 335-339, June.
    • Handle: RePEc:spr:testjl:v:31:y:2022:i:2:d:10.1007_s11749-022-00817-y
    DOI: 10.1007/s11749-022-00817-y
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    References listed on IDEAS

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    1. David Atienza & Pedro Larrañaga & Concha Bielza, 2022. "Rejoinder on: Hybrid semiparametric Bayesian networks," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 344-347, June.
    2. Max Köhler & Anja Schindler & Stefan Sperlich, 2014. "A Review and Comparison of Bandwidth Selection Methods for Kernel Regression," International Statistical Review, International Statistical Institute, vol. 82(2), pages 243-274, August.
    3. David Atienza & Pedro Larrañaga & Concha Bielza, 2022. "Hybrid semiparametric Bayesian networks," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 299-327, June.
    4. Chi-Yang Chu & Daniel J. Henderson & Christopher F. Parmeter, 2015. "Plug-in Bandwidth Selection for Kernel Density Estimation with Discrete Data," Econometrics, MDPI, vol. 3(2), pages 1-16, March.
    5. Nils-Bastian Heidenreich & Anja Schindler & Stefan Sperlich, 2013. "Bandwidth selection for kernel density estimation: a review of fully automatic selectors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 403-433, October.
    6. Li, Qi & Racine, Jeff, 2003. "Nonparametric estimation of distributions with categorical and continuous data," Journal of Multivariate Analysis, Elsevier, vol. 86(2), pages 266-292, August.
    7. Stefan Sperlich, 2014. "On the choice of regularization parameters in specification testing: a critical discussion," Empirical Economics, Springer, vol. 47(2), pages 427-450, September.
    8. Chu, Chi-Yang & Henderson, Daniel J. & Parmeter, Christopher F., 2017. "On discrete Epanechnikov kernel functions," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 79-105.
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