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Updating Schemes, Correlation Structure, Blocking and Parameterization for the Gibbs Sampler

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Cited by:

  1. Bianchi, Daniele & Tamoni, Andrea, 2016. "The dynamics of expected returns: evidence from multi-scale time series modelling," LSE Research Online Documents on Economics 118992, London School of Economics and Political Science, LSE Library.
  2. Wilkinson, Darren J & KH Yeung, Stephen, 2004. "A sparse matrix approach to Bayesian computation in large linear models," Computational Statistics & Data Analysis, Elsevier, vol. 44(3), pages 493-516, January.
  3. Roberto Casarin & Claudia Foroni & Massimiliano Marcellino & Francesco Ravazzolo, 2016. "Uncertainty Through the Lenses of A Mixed-Frequency Bayesian Panel Markov Switching Model," Working Papers 585, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  4. Moins, Théo & Arbel, Julyan & Girard, Stéphane & Dutfoy, Anne, 2023. "Reparameterization of extreme value framework for improved Bayesian workflow," Computational Statistics & Data Analysis, Elsevier, vol. 187(C).
  5. Wong, Jackie S.T. & Forster, Jonathan J. & Smith, Peter W.F., 2018. "Bayesian mortality forecasting with overdispersion," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 206-221.
  6. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2016. "Efficient Gibbs sampling for Markov switching GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 37-57.
  7. Yin, Libo & Ma, Xiyuan, 2018. "Causality between oil shocks and exchange rate: A Bayesian, graph-based VAR approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 434-453.
  8. Levine, Richard A. & Yu, Zhaoxia & Hanley, William G. & Nitao, John J., 2005. "Implementing componentwise Hastings algorithms," Computational Statistics & Data Analysis, Elsevier, vol. 48(2), pages 363-389, February.
  9. Levine, Richard A. & Casella, George, 2006. "Optimizing random scan Gibbs samplers," Journal of Multivariate Analysis, Elsevier, vol. 97(10), pages 2071-2100, November.
  10. Håvard Rue & Ingelin Steinsland & Sveinung Erland, 2004. "Approximating hidden Gaussian Markov random fields," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(4), pages 877-892, November.
  11. Jeffrey Rouder & Jordan Province & Richard Morey & Pablo Gomez & Andrew Heathcote, 2015. "The Lognormal Race: A Cognitive-Process Model of Choice and Latency with Desirable Psychometric Properties," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 491-513, June.
  12. Zhang, Xiao & Boscardin, W. John & Belin, Thomas R. & Wan, Xiaohai & He, Yulei & Zhang, Kui, 2015. "A Bayesian method for analyzing combinations of continuous, ordinal, and nominal categorical data with missing values," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 43-58.
  13. Román, Jorge Carlos & Hobert, James P. & Presnell, Brett, 2014. "On reparametrization and the Gibbs sampler," Statistics & Probability Letters, Elsevier, vol. 91(C), pages 110-116.
  14. Chun-Lung Su, 2021. "Bayesian multi-way balanced nested MANOVA models with random effects and a large number of the main factor levels," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(5), pages 663-692, July.
  15. Martin, Gael M. & Frazier, David T. & Maneesoonthorn, Worapree & Loaiza-Maya, Rubén & Huber, Florian & Koop, Gary & Maheu, John & Nibbering, Didier & Panagiotelis, Anastasios, 2024. "Bayesian forecasting in economics and finance: A modern review," International Journal of Forecasting, Elsevier, vol. 40(2), pages 811-839.
  16. Gael M. Martin & David T. Frazier & Ruben Loaiza-Maya & Florian Huber & Gary Koop & John Maheu & Didier Nibbering & Anastasios Panagiotelis, 2023. "Bayesian Forecasting in the 21st Century: A Modern Review," Monash Econometrics and Business Statistics Working Papers 1/23, Monash University, Department of Econometrics and Business Statistics.
  17. Zhou, Haiming & Huang, Xianzheng, 2022. "Bayesian beta regression for bounded responses with unknown supports," Computational Statistics & Data Analysis, Elsevier, vol. 167(C).
  18. Sanjay Chaudhuri, 2014. "Qualitative inequalities for squared partial correlations of a Gaussian random vector," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(2), pages 345-367, April.
  19. MacEachern, Steven N. & Peruggia, Mario, 2000. "Subsampling the Gibbs sampler: variance reduction," Statistics & Probability Letters, Elsevier, vol. 47(1), pages 91-98, March.
  20. Chib, Siddhartha, 2004. "Markov Chain Monte Carlo Technology," Papers 2004,22, Humboldt University of Berlin, Center for Applied Statistics and Economics (CASE).
  21. Gael M. Martin & David T. Frazier & Christian P. Robert, 2022. "Computing Bayes: From Then `Til Now," Monash Econometrics and Business Statistics Working Papers 14/22, Monash University, Department of Econometrics and Business Statistics.
  22. Tom Wilderjans & Dirk Depril & Iven Mechelen, 2012. "Block-Relaxation Approaches for Fitting the INDCLUS Model," Journal of Classification, Springer;The Classification Society, vol. 29(3), pages 277-296, October.
  23. Ahelegbey, Daniel Felix & Giudici, Paolo, 2022. "NetVIX — A network volatility index of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
  24. Natália Caroline Costa Oliveira & Vinícius Diniz Mayrink, 2024. "Generalized mixed spatiotemporal modeling with a continuous response and random effect via factor analysis," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(3), pages 723-752, July.
  25. Strickland, Chris M. & Martin, Gael M. & Forbes, Catherine S., 2008. "Parameterisation and efficient MCMC estimation of non-Gaussian state space models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2911-2930, February.
  26. Ahelegbey, Daniel Felix & Giudici, Paolo & Hashem, Shatha Qamhieh, 2021. "Network VAR models to measure financial contagion," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
  27. Bianchi, Daniele & Billio, Monica & Casarin, Roberto & Guidolin, Massimo, 2019. "Modeling systemic risk with Markov Switching Graphical SUR models," Journal of Econometrics, Elsevier, vol. 210(1), pages 58-74.
  28. Schmidt, Paul & Mühlau, Mark & Schmid, Volker, 2017. "Fitting large-scale structured additive regression models using Krylov subspace methods," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 59-75.
  29. Hobert, James P. & Geyer, Charles J., 1998. "Geometric Ergodicity of Gibbs and Block Gibbs Samplers for a Hierarchical Random Effects Model," Journal of Multivariate Analysis, Elsevier, vol. 67(2), pages 414-430, November.
  30. Hongju Liu & Qiang Liu & Pradeep K. Chintagunta, 2017. "Promotion Spillovers: Drug Detailing in Combination Therapy," Marketing Science, INFORMS, vol. 36(3), pages 382-401, May.
  31. Jin, Zhumengmeng & Hobert, James P., 2022. "On the convergence rate of the “out-of-order” block Gibbs sampler," Statistics & Probability Letters, Elsevier, vol. 188(C).
  32. Pasanisi, Alberto & Fu, Shuai & Bousquet, Nicolas, 2012. "Estimating discrete Markov models from various incomplete data schemes," Computational Statistics & Data Analysis, Elsevier, vol. 56(9), pages 2609-2625.
  33. 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.
  34. Moores, Matthew T. & Hargrave, Catriona E. & Deegan, Timothy & Poulsen, Michael & Harden, Fiona & Mengersen, Kerrie, 2015. "An external field prior for the hidden Potts model with application to cone-beam computed tomography," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 27-41.
  35. Barone, Piero & Sebastiani, Giovanni & Stander, Julian, 2001. "General over-relaxation Markov chain Monte Carlo algorithms for Gaussian densities," Statistics & Probability Letters, Elsevier, vol. 52(2), pages 115-124, April.
  36. Marcin Mider & Paul A. Jenkins & Murray Pollock & Gareth O. Roberts, 2022. "The Computational Cost of Blocking for Sampling Discretely Observed Diffusions," Methodology and Computing in Applied Probability, Springer, vol. 24(4), pages 3007-3027, December.
  37. Gschlößl, Susanne & Czado, Claudia, 2008. "Does a Gibbs sampler approach to spatial Poisson regression models outperform a single site MH sampler?," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4184-4202, May.
  38. Sun, Xuxue & Mraied, Hesham & Cai, Wenjun & Zhang, Qiong & Liang, Guoyuan & Li, Mingyang, 2018. "Bayesian latent degradation performance modeling and quantification of corroding aluminum alloys," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 84-96.
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