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Sparse Bayesian infinite factor models

Citations

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Cited by:

  1. Joshua C. C. Chan, 2024. "BVARs and stochastic volatility," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 3, pages 43-67, Edward Elgar Publishing.
  2. Pantelis Samartsidis & Shaun R. Seaman & Silvia Montagna & André Charlett & Matthew Hickman & Daniela De Angelis, 2020. "A Bayesian multivariate factor analysis model for evaluating an intervention by using observational time series data on multiple outcomes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1437-1459, October.
  3. Dimitris Korobilis & Kenichi Shimizu, 2022. "Bayesian Approaches to Shrinkage and Sparse Estimation," Foundations and Trends(R) in Econometrics, now publishers, vol. 11(4), pages 230-354, June.
  4. Lee, Kwangmin & Lee, Jaeyong, 2023. "Post-processed posteriors for sparse covariances," Journal of Econometrics, Elsevier, vol. 236(1).
  5. Sylvia Fruhwirth-Schnatter, 2023. "Generalized Cumulative Shrinkage Process Priors with Applications to Sparse Bayesian Factor Analysis," Papers 2303.00473, arXiv.org.
  6. Chan, Joshua C.C., 2023. "Comparing stochastic volatility specifications for large Bayesian VARs," Journal of Econometrics, Elsevier, vol. 235(2), pages 1419-1446.
  7. Kastner, Gregor, 2019. "Sparse Bayesian time-varying covariance estimation in many dimensions," Journal of Econometrics, Elsevier, vol. 210(1), pages 98-115.
  8. Bai, Jushan & Ando, Tomohiro, 2013. "Multifactor asset pricing with a large number of observable risk factors and unobservable common and group-specific factors," MPRA Paper 52785, University Library of Munich, Germany, revised Dec 2013.
  9. Angelos Alexopoulos & Petros Dellaportas & Omiros Papaspiliopoulos, 2019. "Bayesian prediction of jumps in large panels of time series data," Papers 1904.05312, arXiv.org, revised Apr 2021.
  10. Jaejoon Lee & Seongil Jo & Jaeyong Lee, 2022. "Robust sparse Bayesian infinite factor models," Computational Statistics, Springer, vol. 37(5), pages 2693-2715, November.
  11. Simon Beyeler & Sylvia Kaufmann, 2021. "Reduced‐form factor augmented VAR—Exploiting sparsity to include meaningful factors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(7), pages 989-1012, November.
  12. Ling Zhou & Huazhen Lin & Xinyuan Song & Yi Li, 2014. "Selection of Latent Variables for Multiple Mixed-outcome Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1064-1082, December.
  13. Silvia Montagna & Surya T. Tokdar & Brian Neelon & David B. Dunson, 2012. "Bayesian Latent Factor Regression for Functional and Longitudinal Data," Biometrics, The International Biometric Society, vol. 68(4), pages 1064-1073, December.
  14. Zheng Lingling & Yan Xiao & Suchindran Sunil & Dressman Holly & Chute John P. & Lucas Joseph, 2014. "Biological pathway selection through Bayesian integrative modeling," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 13(4), pages 435-457, August.
  15. Andrés F. Barrientos & Alejandro Jara & Fernando A. Quintana, 2017. "Fully Nonparametric Regression for Bounded Data Using Dependent Bernstein Polynomials," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 806-825, April.
  16. Shan Feng & Wenxian Xie & Yufeng Nie, 2024. "Simultaneous Bayesian Clustering and Model Selection with Mixture of Robust Factor Analyzers," Mathematics, MDPI, vol. 12(7), pages 1-23, April.
  17. Daniele Durante & David B. Dunson & Joshua T. Vogelstein, 2017. "Nonparametric Bayes Modeling of Populations of Networks," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(520), pages 1516-1530, October.
  18. Martin Feldkircher & Luis Gruber & Florian Huber & Gregor Kastner, 2017. "Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?," Papers 1711.00564, arXiv.org, revised Mar 2024.
  19. Veronika Ročková & Edward I. George, 2016. "Fast Bayesian Factor Analysis via Automatic Rotations to Sparsity," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1608-1622, October.
  20. Conti, Gabriella & Frühwirth-Schnatter, Sylvia & Heckman, James J. & Piatek, Rémi, 2014. "Bayesian exploratory factor analysis," Journal of Econometrics, Elsevier, vol. 183(1), pages 31-57.
  21. Daniele Durante & Sally Paganin & Bruno Scarpa & David B. Dunson, 2017. "Bayesian modelling of networks in complex business intelligence problems," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 555-580, April.
  22. Niko Hauzenberger & Maximilian Böck & Michael Pfarrhofer & Anna Stelzer & Gregor Zens, 2018. "Implications of Macroeconomic Volatility in the Euro Area," Department of Economics Working Papers wuwp261, Vienna University of Economics and Business, Department of Economics.
  23. Niko Hauzenberger & Florian Huber & Karin Klieber & Massimiliano Marcellino, 2022. "Bayesian Neural Networks for Macroeconomic Analysis," Papers 2211.04752, arXiv.org, revised Apr 2024.
  24. Chuan Gao & Ian C McDowell & Shiwen Zhao & Christopher D Brown & Barbara E Engelhardt, 2016. "Context Specific and Differential Gene Co-expression Networks via Bayesian Biclustering," PLOS Computational Biology, Public Library of Science, vol. 12(7), pages 1-39, July.
  25. Philip A. White & Alan E. Gelfand, 2021. "Multivariate functional data modeling with time-varying clustering," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 586-602, September.
  26. Darjus Hosszejni & Sylvia Fruhwirth-Schnatter, 2022. "Cover It Up! Bipartite Graphs Uncover Identifiability in Sparse Factor Analysis," Papers 2211.00671, arXiv.org, revised Feb 2025.
  27. Crespo Cuaresma, Jesús & Huber, Florian & Onorante, Luca, 2020. "Fragility and the effect of international uncertainty shocks," Journal of International Money and Finance, Elsevier, vol. 108(C).
  28. Kelly R. Moran & Elizabeth L. Turner & David Dunson & Amy H. Herring, 2021. "Bayesian hierarchical factor regression models to infer cause of death from verbal autopsy data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 532-557, June.
  29. Daewon Yang & Taeryon Choi & Eric Lavigne & Yeonseung Chung, 2022. "Non‐parametric Bayesian covariate‐dependent multivariate functional clustering: An application to time‐series data for multiple air pollutants," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1521-1542, November.
  30. Sung, Bongjung & Lee, Jaeyong, 2023. "Covariance structure estimation with Laplace approximation," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
  31. Matthew W. Wheeler, 2019. "Bayesian additive adaptive basis tensor product models for modeling high dimensional surfaces: an application to high‐throughput toxicity testing," Biometrics, The International Biometric Society, vol. 75(1), pages 193-201, March.
  32. S. J. Koopman & G. Mesters, 2017. "Empirical Bayes Methods for Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 99(3), pages 486-498, July.
  33. Jing Zhou & Anirban Bhattacharya & Amy H. Herring & David B. Dunson, 2015. "Bayesian Factorizations of Big Sparse Tensors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1562-1576, December.
  34. Sylvia Frühwirth-Schnatter & Darjus Hosszejni & Hedibert Freitas Lopes, 2023. "When It Counts—Econometric Identification of the Basic Factor Model Based on GLT Structures," Econometrics, MDPI, vol. 11(4), pages 1-30, November.
  35. Bonnie R. Joubert & Marianthi-Anna Kioumourtzoglou & Toccara Chamberlain & Hua Yun Chen & Chris Gennings & Mary E. Turyk & Marie Lynn Miranda & Thomas F. Webster & Katherine B. Ensor & David B. Dunson, 2022. "Powering Research through Innovative Methods for Mixtures in Epidemiology (PRIME) Program: Novel and Expanded Statistical Methods," IJERPH, MDPI, vol. 19(3), pages 1-24, January.
  36. Leung, Dennis & Drton, Mathias, 2016. "Order-invariant prior specification in Bayesian factor analysis," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 60-66.
  37. Roberta De Vito & Ruggero Bellio & Lorenzo Trippa & Giovanni Parmigiani, 2019. "Multi‐study factor analysis," Biometrics, The International Biometric Society, vol. 75(1), pages 337-346, March.
  38. Kalli, Maria & Griffin, Jim E., 2018. "Bayesian nonparametric vector autoregressive models," Journal of Econometrics, Elsevier, vol. 203(2), pages 267-282.
  39. Korobilis, Dimitris, 2014. "Data-based priors for vector autoregressions with drifting coefficients," SIRE Discussion Papers 2014-022, Scottish Institute for Research in Economics (SIRE).
  40. Mohsen Maleki & Darren Wraith, 2019. "Mixtures of multivariate restricted skew-normal factor analyzer models in a Bayesian framework," Computational Statistics, Springer, vol. 34(3), pages 1039-1053, September.
  41. Li, Hanning & Pati, Debdeep, 2017. "Variable selection using shrinkage priors," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 107-119.
  42. Durante, Daniele, 2017. "A note on the multiplicative gamma process," Statistics & Probability Letters, Elsevier, vol. 122(C), pages 198-204.
  43. Florian Huber & Gary Koop, 2023. "Subspace shrinkage in conjugate Bayesian vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 556-576, June.
  44. Gautam Sabnis & Debdeep Pati & Anirban Bhattacharya, 2019. "Compressed Covariance Estimation with Automated Dimension Learning," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 466-481, December.
  45. Hauber, Philipp, 2022. "Real-time nowcasting with sparse factor models," EconStor Preprints 251551, ZBW - Leibniz Information Centre for Economics.
  46. Daniel R. Kowal & Antonio Canale, 2021. "Semiparametric Functional Factor Models with Bayesian Rank Selection," Papers 2108.02151, arXiv.org, revised May 2022.
  47. Marco, Nicholas & Şentürk, Damla & Jeste, Shafali & DiStefano, Charlotte C. & Dickinson, Abigail & Telesca, Donatello, 2024. "Flexible regularized estimation in high-dimensional mixed membership models," Computational Statistics & Data Analysis, Elsevier, vol. 194(C).
  48. Kaufmann, Sylvia & Schumacher, Christian, 2019. "Bayesian estimation of sparse dynamic factor models with order-independent and ex-post mode identification," Journal of Econometrics, Elsevier, vol. 210(1), pages 116-134.
  49. Samorodnitsky, Sarah & Wendt, Chris H. & Lock, Eric F., 2024. "Bayesian simultaneous factorization and prediction using multi-omic data," Computational Statistics & Data Analysis, Elsevier, vol. 197(C).
  50. Patric Dolmeta & Raffaele Argiento & Silvia Montagna, 2023. "Bayesian GARCH modeling of functional sports data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 401-423, June.
  51. Kim, Gwangsu & Choi, Taeryon, 2019. "Asymptotic properties of nonparametric estimation and quantile regression in Bayesian structural equation models," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 68-82.
  52. repec:bfi:wpaper:2014-014 is not listed on IDEAS
  53. Sylvie Tchumtchoua & Dipak Dey, 2012. "Modeling Associations Among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach," Psychometrika, Springer;The Psychometric Society, vol. 77(4), pages 670-692, October.
  54. Fangting Zhou & Kejun He & Kunbo Wang & Yanxun Xu & Yang Ni, 2023. "Functional Bayesian networks for discovering causality from multivariate functional data," Biometrics, The International Biometric Society, vol. 79(4), pages 3279-3293, December.
  55. Tao Sun, 2024. "Bundle Choice Model with Endogenous Regressors: An Application to Soda Tax," Papers 2412.05794, arXiv.org.
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