The Nested Dirichlet Process
Author
Abstract
Suggested Citation
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Leisen, Fabrizio & Lijoi, Antonio, 2011. "Vectors of two-parameter Poisson-Dirichlet processes," Journal of Multivariate Analysis, Elsevier, vol. 102(3), pages 482-495, March.
- Lian, Heng, 2010. "Sparse Bayesian hierarchical modeling of high-dimensional clustering problems," Journal of Multivariate Analysis, Elsevier, vol. 101(7), pages 1728-1737, August.
- Bassetti, Federico & Casarin, Roberto & Leisen, Fabrizio, 2014.
"Beta-product dependent Pitman–Yor processes for Bayesian inference,"
Journal of Econometrics, Elsevier, vol. 180(1), pages 49-72.
- Federico Bassetti & Roberto Casarin & Fabrizio Leisen, 2013. "Beta-Product Dependent Pitman-Yor Processes for Bayesian Inference," Working Papers 2013:13, Department of Economics, University of Venice "Ca' Foscari".
- Jin, Xin & Maheu, John M., 2016.
"Bayesian semiparametric modeling of realized covariance matrices,"
Journal of Econometrics, Elsevier, vol. 192(1), pages 19-39.
- Jin, Xin & Maheu, John M, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," MPRA Paper 60102, University Library of Munich, Germany.
- Xin Jin & John M. Maheu, 2014. "Bayesian Semiparametric Modeling of Realized Covariance Matrices," Working Paper series 34_14, Rimini Centre for Economic Analysis.
- Jääskinen Väinö & Parkkinen Ville & Cheng Lu & Corander Jukka, 2014. "Bayesian clustering of DNA sequences using Markov chains and a stochastic partition model," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(1), pages 105-121, February.
- 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.
- Antonio Lijoi & Bernardo Nipoti, 2013. "A class of hazard rate mixtures for combining survival data from different experiments," DEM Working Papers Series 059, University of Pavia, Department of Economics and Management.
- Sudhir Voleti & Praveen K. Kopalle & Pulak Ghosh, 2015. "An Interproduct Competition Model Incorporating Branding Hierarchy and Product Similarities Using Store-Level Data," Management Science, INFORMS, vol. 61(11), pages 2720-2738, November.
- J. Griffin, 2011. "Bayesian clustering of distributions in stochastic frontier analysis," Journal of Productivity Analysis, Springer, vol. 36(3), pages 275-283, December.
- Gard, Charlotte C. & Brown, Elizabeth R., 2015. "A Bayesian hierarchical model for estimating and partitioning Bernstein polynomial density functions," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 73-83.
- Laura D'Angelo & Antonio Canale & Zhaoxia Yu & Michele Guindani, 2023. "Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data," Biometrics, The International Biometric Society, vol. 79(2), pages 1370-1382, June.
- Bassetti, Federico & Casarin, Roberto & Leisen, Fabrizio, 2011. "Beta-product Poisson-Dirichlet Processes," DES - Working Papers. Statistics and Econometrics. WS 12160, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Antonio Lijoi & Igor Prünster & Giovanni Rebaudo, 2023. "Flexible clustering via hidden hierarchical Dirichlet priors," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 50(1), pages 213-234, March.
- Ilenia Epifani & Antonio Lijoi, 2009. "Nonparametric Priors for Vectors of Survival Functions," Quaderni di Dipartimento 098, University of Pavia, Department of Economics and Quantitative Methods.
- Martínez-Ovando Juan Carlos & Walker Stephen G., 2011. "Time-series Modelling, Stationarity and Bayesian Nonparametric Methods," Working Papers 2011-08, Banco de México.
- Fabrizio Leisen & Antonio Lijoi, 2010. "Vectors of two-parameter Poisson-Dirichlet processes," Quaderni di Dipartimento 119, University of Pavia, Department of Economics and Quantitative Methods.
- Brian Hart & Michele Guindani & Stephen Malone & Mark Fiecas, 2022. "A nonparametric Bayesian model for estimating spectral densities of resting‐state EEG twin data," Biometrics, The International Biometric Society, vol. 78(1), pages 313-323, March.
- Bruno Scarpa & David B. Dunson, 2014. "Enriched Stick-Breaking Processes for Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(506), pages 647-660, June.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bes:jnlasa:v:103:i:483:y:2008:p:1131-1154. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.