Additive mixed models with Dirichlet process mixture and P-spline priors
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DOI: 10.1007/s10182-011-0161-6
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- Jullion, Astrid & Lambert, Philippe, 2007. "Robust specification of the roughness penalty prior distribution in spatially adaptive Bayesian P-splines models," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2542-2558, February.
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Cited by:
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- Hassan Akell & Farkhondeh-Alsadat Sajadi & Iraj Kazemi, 2023. "Construction of Jointly Distributed Random Samples Drawn from the Beta Two-Parameter Process," Methodology and Computing in Applied Probability, Springer, vol. 25(3), pages 1-12, September.
- Reyhaneh Rikhtehgaran & Iraj Kazemi, 2016. "The determination of uncertainty levels in robust clustering of subjects with longitudinal observations using the Dirichlet process mixture," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(4), pages 541-562, December.
- Elisabeth Waldmann & Thomas Kneib & Yu Ryan Yu & Stefan Lang, 2012. "Bayesian semiparametric additive quantile regression," Working Papers 2012-06, Faculty of Economics and Statistics, Universität Innsbruck.
- Juan Armando Torres Munguía, 2018. "What is behind homicide gender gaps in Mexico? A spatial semiparametric approach," Ibero America Institute for Econ. Research (IAI) Discussion Papers 236, Ibero-America Institute for Economic Research.
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Keywords
Dirichlet process mixture; Mixed models; Nonparametric Bayes inference; Penalized splines;All these keywords.
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