Sampling schemes for generalized linear Dirichlet process random effects models
Author
Abstract
Suggested Citation
DOI: 10.1007/s10260-011-0168-x
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Minjung Kyung & Jeff Gill & George Casella, 2011. "New findings from terrorism data: Dirichlet process random‐effects models for latent groups," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 60(5), pages 701-721, November.
- Teh, Yee Whye & Jordan, Michael I. & Beal, Matthew J. & Blei, David M., 2006. "Hierarchical Dirichlet Processes," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1566-1581, December.
- Gill, Jeff & Casella, George, 2009. "Nonparametric Priors for Ordinal Bayesian Social Science Models: Specification and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 453-454.
- Chib, Siddhartha & Winkelmann, Rainer, 2001. "Markov Chain Monte Carlo Analysis of Correlated Count Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 428-435, October.
- Antonietta Mira & Luke Tierney, 2002. "Efficiency and Convergence Properties of Slice Samplers," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(1), pages 1-12, March.
- P. Damlen & J. Wakefield & S. Walker, 1999. "Gibbs sampling for Bayesian non‐conjugate and hierarchical models by using auxiliary variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(2), pages 331-344, April.
- Siddhartha Chib & Edward Greenberg & Yuxin Chen, 1998. "MCMC Methods for Fitting and Comparing Multinomial Response Models," Econometrics 9802001, University Library of Munich, Germany, revised 06 May 1998.
- Kyung, Minjung & Gill, Jeff & Casella, George, 2009. "Characterizing the variance improvement in linear Dirichlet random effects models," Statistics & Probability Letters, Elsevier, vol. 79(22), pages 2343-2350, November.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Planas Christophe & Rossi Alessandro, 2024.
"The slice sampler and centrally symmetric distributions,"
Monte Carlo Methods and Applications, De Gruyter, vol. 30(3), pages 299-313.
- Planas, Christophe & Rossi, Alessandro, 2018. "The slice sampler and centrally symmetric distributions," JRC Working Papers in Economics and Finance 2018-11, Joint Research Centre, European Commission.
- Li, Yanxin & Walker, Stephen G., 2023. "A latent slice sampling algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
- Ghosal, Rahul & Ghosh, Sujit K., 2022. "Bayesian inference for generalized linear model with linear inequality constraints," Computational Statistics & Data Analysis, Elsevier, vol. 166(C).
- Daziano, Ricardo A., 2013. "Conditional-logit Bayes estimators for consumer valuation of electric vehicle driving range," Resource and Energy Economics, Elsevier, vol. 35(3), pages 429-450.
- Chib, Siddhartha, 2004. "Markov Chain Monte Carlo Technology," Papers 2004,22, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
- Antonietta Mira & Daniel J. Sargent, 2003. "A new strategy for speeding Markov chain Monte Carlo algorithms," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 12(1), pages 49-60, February.
- Takahashi, Makoto & Watanabe, Toshiaki & Omori, Yasuhiro, 2016.
"Volatility and quantile forecasts by realized stochastic volatility models with generalized hyperbolic distribution,"
International Journal of Forecasting, Elsevier, vol. 32(2), pages 437-457.
- Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-921, CIRJE, Faculty of Economics, University of Tokyo.
- Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2015. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-975, CIRJE, Faculty of Economics, University of Tokyo.
- Makoto Takahashi & Toshiaki Watanabe & Yasuhiro Omori, 2014. "Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution," CIRJE F-Series CIRJE-F-949, CIRJE, Faculty of Economics, University of Tokyo.
- Rub'en Loaiza-Maya & Didier Nibbering, 2022. "Fast variational Bayes methods for multinomial probit models," Papers 2202.12495, arXiv.org, revised Oct 2022.
- Michelle Dietzen & Haoran Zhai & Olivia Lucas & Oriol Pich & Christopher Barrington & Wei-Ting Lu & Sophia Ward & Yanping Guo & Robert E. Hynds & Simone Zaccaria & Charles Swanton & Nicholas McGranaha, 2024. "Replication timing alterations are associated with mutation acquisition during breast and lung cancer evolution," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
- Redivo, Edoardo & Nguyen, Hien D. & Gupta, Mayetri, 2020. "Bayesian clustering of skewed and multimodal data using geometric skewed normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
- 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.
- Stephen G. Walker, 2006. "Sampling the Dirichlet Mixture Model with Slices," ICER Working Papers - Applied Mathematics Series 16-2006, ICER - International Centre for Economic Research.
- Parvin Ahmadi & Iman Gholampour & Mahmoud Tabandeh, 2018. "Cluster-based sparse topical coding for topic mining and document 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. 12(3), pages 537-558, September.
- Azam, Kazim & Pitt, Michael, 2014. "Bayesian Inference for a Semi-Parametric Copula-based Markov Chain," The Warwick Economics Research Paper Series (TWERPS) 1051, University of Warwick, Department of Economics.
- Gael M. Martin & David T. Frazier & Christian P. Robert, 2020. "Computing Bayes: Bayesian Computation from 1763 to the 21st Century," Monash Econometrics and Business Statistics Working Papers 14/20, Monash University, Department of Econometrics and Business Statistics.
- Aristidis Nikoloulopoulos & Dimitris Karlis, 2010. "Regression in a copula model for bivariate count data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(9), pages 1555-1568.
- Buzbas Erkan Ozge & Joyce Paul & Abdo Zaid, 2009. "Estimation of Selection Intensity under Overdominance by Bayesian Methods," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-24, June.
- Marcin Kacperczyk & Paul Damien & Stephen G. Walker, 2013. "A new class of Bayesian semi-parametric models with applications to option pricing," Quantitative Finance, Taylor & Francis Journals, vol. 13(6), pages 967-980, May.
- Jeffrey L. Furman & Florenta Teodoridis, 2020. "Automation, Research Technology, and Researchers’ Trajectories: Evidence from Computer Science and Electrical Engineering," Organization Science, INFORMS, vol. 31(2), pages 330-354, March.
- Xin Jin & John M. Maheu & Qiao Yang, 2019.
"Bayesian parametric and semiparametric factor models for large realized covariance matrices,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(5), pages 641-660, August.
- Jin, Xin & Maheu, John M & Yang, Qiao, 2017. "Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices," MPRA Paper 81920, University Library of Munich, Germany.
- Xin Jin & John M. Maheu & Qiao Yang, 2018. "Bayesian Parametric and Semiparametric Factor Models for Large Realized Covariance Matrices," Working Paper series 18-02, Rimini Centre for Economic Analysis.
More about this item
Keywords
Linear mixed models; Generalized linear mixed models; Hierarchical models; Gibbs sampling; Metropolis–Hastings algorithm; Slice sampling;All these keywords.
Statistics
Access and download statisticsCorrections
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:spr:stmapp:v:20:y:2011:i:3:p:259-290. 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.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.