Supervised learning via smoothed Polya trees
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DOI: 10.1007/s11634-018-0344-z
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- Marco Marzio & Charles C. Taylor, 2005. "On boosting kernel density methods for multivariate data: density estimation and classification," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(2), pages 163-178, November.
- Chen, Yuhui & Hanson, Timothy E., 2014. "Bayesian nonparametric k-sample tests for censored and uncensored data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 335-346.
- Bergé, Laurent & Bouveyron, Charles & Girard, Stéphane, 2012. "HDclassif: An R Package for Model-Based Clustering and Discriminant Analysis of High-Dimensional Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 46(i06).
- Mukhopadhyay, Subhadeep & Ghosh, Anil K., 2011. "Bayesian multiscale smoothing in supervised and semi-supervised kernel discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2344-2353, July.
- Hanson, Timothy E., 2006. "Inference for Mixtures of Finite Polya Tree Models," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1548-1565, December.
- Adriano Z. Zambom & Ronaldo Dias, 2013. "A Review of Kernel Density Estimation with Applications to Econometrics," International Econometric Review (IER), Econometric Research Association, vol. 5(1), pages 20-42, April.
- Cipolli III, William & Hanson, Timothy & McLain, Alexander C., 2016. "Bayesian nonparametric multiple testing," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 64-79.
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- Mahsa Samsami & Ralf Wagner, 2021. "Investment Decisions with Endogeneity: A Dirichlet Tree Analysis," JRFM, MDPI, vol. 14(7), pages 1-19, July.
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Keywords
Bayesian nonparametric; Density estimation; Classification;All these keywords.
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