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Bayesian clustering and product partition models

Citations

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Cited by:

  1. Navarrete, Carlos A. & Quintana, Fernando A., 2011. "Similarity analysis in Bayesian random partition models," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 97-109, January.
  2. Martinez-Vargas, Danae & Murua-Sazo, Alejandro, 2023. "Potts-Cox survival regression," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
  3. Chai, Jian & Lu, Quanying & Hu, Yi & Wang, Shouyang & Lai, Kin Keung & Liu, Hongtao, 2018. "Analysis and Bayes statistical probability inference of crude oil price change point," Technological Forecasting and Social Change, Elsevier, vol. 126(C), pages 271-283.
  4. Loschi, R.H. & Iglesias, P.L. & Arellano-Valle, R.B. & Cruz, F.R.B., 2007. "Full predictivistic modeling of stock market data: Application to change point problems," European Journal of Operational Research, Elsevier, vol. 180(1), pages 282-291, July.
  5. Alessandra Guglielmi & Francesca Ieva & Anna M. Paganoni & Fabrizio Ruggeri & Jacopo Soriano, 2014. "Semiparametric Bayesian models for clustering and classification in the presence of unbalanced in-hospital survival," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(1), pages 25-46, January.
  6. Pierpaolo De Blasi & Stefano Favaro & Antonio Lijoi & Ramsés H. Mena & Igor Prünster & Mattteo Ruggiero, 2013. "Are Gibbs-type priors the most natural generalization of the Dirichlet process?," DEM Working Papers Series 054, University of Pavia, Department of Economics and Management.
  7. Raffaele Argiento & Alessandra Guglielmi & Antonio Pievatolo, 2014. "Estimation, prediction and interpretation of NGG random effects models: an application to Kevlar fibre failure times," Statistical Papers, Springer, vol. 55(3), pages 805-826, August.
  8. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
  9. L. G. Leon-Novelo & B. Nebiyou Bekele & P. Müller & F. Quintana & K. Wathen, 2012. "Borrowing Strength with Nonexchangeable Priors over Subpopulations," Biometrics, The International Biometric Society, vol. 68(2), pages 550-558, June.
  10. Fuentes-García, Ruth & Mena, Ramsés H. & Walker, Stephen G., 2019. "Modal posterior clustering motivated by Hopfield’s network," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 92-100.
  11. Maura Mezzetti & Daniele Borzelli & Andrea d’Avella, 2022. "A Bayesian approach to model individual differences and to partition individuals: case studies in growth and learning curves," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1245-1271, December.
  12. Chen Sui-Pi & Huang Guan-Hua, 2014. "A Bayesian clustering approach for detecting gene-gene interactions in high-dimensional genotype data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(3), pages 1-23, June.
  13. Giacomo Bormetti & Maria Elena De Giuli & Danilo Delpini & Claudia Tarantola, 2008. "Bayesian Analysis of Value-at-Risk with Product Partition Models," Papers 0809.0241, arXiv.org, revised May 2009.
  14. Abel Rodr�guez & Enrique ter Horst, 2011. "Measuring expectations in options markets: an application to the S&P500 index," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1393-1405, July.
  15. Miguel-Angel Negrín-Hernández & María Martel-Escobar & Francisco-José Vázquez-Polo, 2021. "Bayesian Meta-Analysis for Binary Data and Prior Distribution on Models," IJERPH, MDPI, vol. 18(2), pages 1-18, January.
  16. Xu, Ganggang & Zhu, Huirong & Lee, J. Jack, 2020. "Borrowing strength and borrowing index for Bayesian hierarchical models," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
  17. An Cheng & Tonghui Chen & Guogang Jiang & Xinru Han, 2021. "Can Major Public Health Emergencies Affect Changes in International Oil Prices?," IJERPH, MDPI, vol. 18(24), pages 1-13, December.
  18. Im, Yunju & Tan, Aixin, 2021. "Bayesian subgroup analysis in regression using mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 162(C).
  19. Peter Müeller & Fernando A. Quintana & Garritt Page, 2018. "Nonparametric Bayesian inference in applications," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(2), pages 175-206, June.
  20. Giacomo Bormetti & Maria Elena De Giuli & Danilo Delpini & Claudia Tarantola, 2012. "Bayesian Value-at-Risk with product partition models," Quantitative Finance, Taylor & Francis Journals, vol. 12(5), pages 769-780, November.
  21. Athanasios Kottas & Milovan Krnjajić, 2009. "Bayesian Semiparametric Modelling in Quantile Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(2), pages 297-319, June.
  22. Christopher A. Bush & Juhee Lee & Steven N. MacEachern, 2010. "Minimally informative prior distributions for non‐parametric Bayesian analysis," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(2), pages 253-268, March.
  23. Lori A Dalton & Marco E Benalcázar & Edward R Dougherty, 2018. "Optimal clustering under uncertainty," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-21, October.
  24. Sylvia Frühwirth-Schnatter & Gertraud Malsiner-Walli, 2019. "From here to infinity: sparse finite versus Dirichlet process mixtures in model-based clustering," 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. 13(1), pages 33-64, March.
  25. Rosangela Loschi & Leonardo Bastos & Pilar Iglesias, 2005. "Identifying Volatility Clusters Using the PPM: A Sensitivity Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 24(4), pages 305-319, June.
  26. Sara Wade & Stephen G. Walker & Sonia Petrone, 2014. "A Predictive Study of Dirichlet Process Mixture Models for Curve Fitting," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 580-605, September.
  27. Chai Jian & Wang Shubin & Xiao Hao, 2013. "Abrupt Changes of Global Oil Price," Journal of Systems Science and Information, De Gruyter, vol. 1(1), pages 38-59, February.
  28. Loschi, R.H. & Cruz, F.R.B., 2005. "Extension to the product partition model: computing the probability of a change," Computational Statistics & Data Analysis, Elsevier, vol. 48(2), pages 255-268, February.
  29. Wang, Ketong & Porter, Michael D., 2018. "Optimal Bayesian clustering using non-negative matrix factorization," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 395-411.
  30. Yeonseung Chung & David Dunson, 2011. "The local Dirichlet process," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 63(1), pages 59-80, February.
  31. Subharup Guha & Rex Jung & David Dunson, 2022. "Predicting phenotypes from brain connection structure," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 639-668, June.
  32. Jim Q. Smith & Paul E. Anderson & Silvia Liverani, 2008. "Separation measures and the geometry of Bayes factor selection for classification," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 957-980, November.
  33. Ruth Fuentes–García & Ramsés Mena & Stephen Walker, 2010. "A Probability for Classification Based on the Dirichlet Process Mixture Model," Journal of Classification, Springer;The Classification Society, vol. 27(3), pages 389-403, November.
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