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Bayesian Inference for Logistic Models Using Pólya--Gamma Latent Variables

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  1. Piero Mazzarisi & Paolo Barucca & Fabrizio Lillo & Daniele Tantari, 2017. "A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market," Papers 1801.00185, arXiv.org.
  2. Patricio Maturana-Russel & Renate Meyer, 2021. "Bayesian spectral density estimation using P-splines with quantile-based knot placement," Computational Statistics, Springer, vol. 36(3), pages 2055-2077, September.
  3. Buddhavarapu, Prasad & Bansal, Prateek & Prozzi, Jorge A., 2021. "A new spatial count data model with time-varying parameters," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 566-586.
  4. Cadonna, Annalisa & Kottas, Athanasios & Prado, Raquel, 2017. "Bayesian mixture modeling for spectral density estimation," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 189-195.
  5. Yunyun Wang & Tatsushi Oka & Dan Zhu, 2024. "Inflation Target at Risk: A Time-varying Parameter Distributional Regression," Papers 2403.12456, arXiv.org.
  6. 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.
  7. Prateek Bansal & Rico Krueger & Michel Bierlaire & Ricardo A. Daziano & Taha H. Rashidi, 2019. "P\'olygamma Data Augmentation to address Non-conjugacy in the Bayesian Estimation of Mixed Multinomial Logit Models," Papers 1904.07688, arXiv.org.
  8. Poon, Aubrey & Zhu, Dan, 2022. "Do Recessions Occur Concurrently Across Countries? A Multinomial Logistic Approach," Working Papers 2022:11, Örebro University, School of Business.
  9. Niko Hauzenberger & Florian Huber, 2020. "Model instability in predictive exchange rate regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 168-186, March.
  10. 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.
  11. Yeonhee Park & Suyu Liu & Peter F. Thall & Ying Yuan, 2022. "Bayesian group sequential enrichment designs based on adaptive regression of response and survival time on baseline biomarkers," Biometrics, The International Biometric Society, vol. 78(1), pages 60-71, March.
  12. 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.
  13. Ando, Tomohiro & Bai, Jushan & Li, Kunpeng, 2022. "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 230(1), pages 20-38.
  14. Toryn L. J. Schafer & Christopher K. Wikle & Jay A. VonBank & Bart M. Ballard & Mitch D. Weegman, 2020. "A Bayesian Markov Model with Pólya-Gamma Sampling for Estimating Individual Behavior Transition Probabilities from Accelerometer Classifications," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(3), pages 365-382, September.
  15. Matthew D. Koslovsky, 2023. "A Bayesian zero‐inflated Dirichlet‐multinomial regression model for multivariate compositional count data," Biometrics, The International Biometric Society, vol. 79(4), pages 3239-3251, December.
  16. Anoek Castelein & Dennis Fok & Richard Paap, 2019. "Dynamics in clickthrough and conversion probabilities of paid search advertisements," Tinbergen Institute Discussion Papers 19-056/III, Tinbergen Institute.
  17. Michael Byrd & Ross Darrow, 2021. "A note on the advantage of context in Thompson sampling," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(3), pages 316-321, June.
  18. Tamás Krisztin & Philipp Piribauer, 2021. "A Bayesian spatial autoregressive logit model with an empirical application to European regional FDI flows," Empirical Economics, Springer, vol. 61(1), pages 231-257, July.
  19. M. Marsman & K. Huth & L. J. Waldorp & I. Ntzoufras, 2022. "Objective Bayesian Edge Screening and Structure Selection for Ising Networks," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 47-82, March.
  20. Alex Diana & Eleni Matechou & Jim Griffin & Todd Arnold & Simone Tenan & Stefano Volponi, 2023. "A general modeling framework for open wildlife populations based on the Polya tree prior," Biometrics, The International Biometric Society, vol. 79(3), pages 2171-2183, September.
  21. Anindya Bhadra & Arvind Rao & Veerabhadran Baladandayuthapani, 2018. "Inferring network structure in non†normal and mixed discrete†continuous genomic data," Biometrics, The International Biometric Society, vol. 74(1), pages 185-195, March.
  22. Doris A. Oberdabernig, 2018. "Determinants of IMF lending: How different is Sub-Saharan Africa?," Economics Bulletin, AccessEcon, vol. 38(1), pages 136-145.
  23. 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.
  24. Haoying Wang & Guohui Wu, 2022. "Modeling discrete choices with large fine-scale spatial data: opportunities and challenges," Journal of Geographical Systems, Springer, vol. 24(3), pages 325-351, July.
  25. Boere, Esther & Mosnier, Aline & Bocqueho, Geraldine & Krisztin, Tamas & Havlik, Petr, 2016. "Developing country-wide farm typologies: An analysis of Ethiopian smallholders’ income and food security," 2016 Fifth International Conference, September 23-26, 2016, Addis Ababa, Ethiopia 246924, African Association of Agricultural Economists (AAAE).
  26. Gregor Zens, 2018. "Bayesian shrinkage in mixture of experts models: Identifying robust determinants of class membership," Papers 1809.04853, arXiv.org, revised Jan 2019.
  27. Sahar Zarmehri & Ephraim M. Hanks & Lin Lin, 2021. "A Sample Covariance-Based Approach For Spatial Binary Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(2), pages 220-249, June.
  28. Koki, Constandina & Leonardos, Stefanos & Piliouras, Georgios, 2022. "Exploring the predictability of cryptocurrencies via Bayesian hidden Markov models," Research in International Business and Finance, Elsevier, vol. 59(C).
  29. 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.
  30. Lauren Hoskovec & Sheena Martenies & Tori L. Burket & Sheryl Magzamen & Ander Wilson, 2022. "Association between air pollution and COVID‐19 disease severity via Bayesian multinomial logistic regression with partially missing outcomes," Environmetrics, John Wiley & Sons, Ltd., vol. 33(7), November.
  31. Shonosuke Sugasawa & Kosuke Morikawa & Keisuke Takahata, 2022. "Bayesian semiparametric modeling of response mechanism for nonignorable missing data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 101-117, March.
  32. Wang, Xin & Roy, Vivekananda, 2018. "Analysis of the Pólya-Gamma block Gibbs sampler for Bayesian logistic linear mixed models," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 251-256.
  33. Adam Kaplan & Thomas A. Murray, 2021. "Batch Bayesian optimization design for optimizing a neurostimulator," Biometrics, The International Biometric Society, vol. 77(2), pages 661-674, June.
  34. Xia, Ye-Mao & Tang, Nian-Sheng, 2019. "Bayesian analysis for mixture of latent variable hidden Markov models with multivariate longitudinal data," Computational Statistics & Data Analysis, Elsevier, vol. 132(C), pages 190-211.
  35. Sounak Chakraborty & Tanujit Dey & Yoonbae Jun & Chae Young Lim & Anish Mukherjee & Francesca Dominici, 2022. "A Spatiotemporal Analytical Outlook of the Exposure to Air Pollution and COVID-19 Mortality in the USA," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(3), pages 419-439, September.
  36. Uddin, Md Nazir & Gaskins, Jeremy T., 2023. "Shared Bayesian variable shrinkage in multinomial logistic regression," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
  37. Onizuka, Takahiro & Iwashige, Fumiya & Hashimoto, Shintaro, 2024. "Bayesian boundary trend filtering," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
  38. Nicholas G. Polson & James G. Scott, 2016. "Mixtures, envelopes and hierarchical duality," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(4), pages 701-727, September.
  39. Didier Nibbering, 2024. "A high‐dimensional multinomial logit model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(3), pages 481-497, April.
  40. Qi Zhang & Yihui Zhang & Yemao Xia, 2024. "Bayesian Feature Extraction for Two-Part Latent Variable Model with Polytomous Manifestations," Mathematics, MDPI, vol. 12(5), pages 1-23, March.
  41. Carter Allen & Sara E. Benjamin‐Neelon & Brian Neelon, 2021. "A Bayesian multivariate mixture model for skewed longitudinal data with intermittent missing observations: An application to infant motor development," Biometrics, The International Biometric Society, vol. 77(2), pages 675-688, June.
  42. Anindya Bhadra & Jyotishka Datta & Nicholas G. Polson & Brandon T. Willard, 2020. "Global-Local Mixtures: A Unifying Framework," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 82(2), pages 426-447, August.
  43. Chase N. Joyner & Christopher S. McMahan & Joshua M. Tebbs & Christopher R. Bilder, 2020. "From mixed effects modeling to spike and slab variable selection: A Bayesian regression model for group testing data," Biometrics, The International Biometric Society, vol. 76(3), pages 913-923, September.
  44. John B. Holmes & Matthew R. Schofield & Richard J. Barker, 2022. "Pólya‐gamma data augmentation and latent variable models for multivariate binomial data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(1), pages 194-218, January.
  45. Oliver M. Crook & Colin T. R. Davies & Lisa M. Breckels & Josie A. Christopher & Laurent Gatto & Paul D. W. Kirk & Kathryn S. Lilley, 2022. "Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE," Nature Communications, Nature, vol. 13(1), pages 1-21, December.
  46. Xinyi Lu & Mevin B. Hooten & Ann M. Raiho & David K. Swanson & Carl A. Roland & Sarah E. Stehn, 2023. "Latent trajectory models for spatio‐temporal dynamics in Alaskan ecosystems," Biometrics, The International Biometric Society, vol. 79(4), pages 3664-3675, December.
  47. Bryant Davis & James P. Hobert, 2024. "Approximating the Spectral Gap of the Pólya-Gamma Gibbs Sampler," Methodology and Computing in Applied Probability, Springer, vol. 26(3), pages 1-13, September.
  48. Tianzhou Ma & Faming Liang & George C. Tseng, 2017. "Biomarker detection and categorization in ribonucleic acid sequencing meta-analysis using Bayesian hierarchical models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(4), pages 847-867, August.
  49. Louise Sealy & Karen Zwi & Gordon McDonald & Aldo Saavedra & Lisa Crawford & Hasantha Gunasekera, 2019. "Predictors of Discharge Against Medical Advice in a Tertiary Paediatric Hospital," IJERPH, MDPI, vol. 16(8), pages 1-11, April.
  50. Zhang, Siliang & Chen, Yunxiao, 2024. "A note on Ising network analysis with missing data," LSE Research Online Documents on Economics 123984, London School of Economics and Political Science, LSE Library.
  51. Patrick LeBlanc & Li Ma, 2023. "Microbiome subcommunity learning with logistic‐tree normal latent Dirichlet allocation," Biometrics, The International Biometric Society, vol. 79(3), pages 2321-2332, September.
  52. Alex Diana & Emily Beth Dennis & Eleni Matechou & Byron John Treharne Morgan, 2023. "Fast Bayesian inference for large occupancy datasets," Biometrics, The International Biometric Society, vol. 79(3), pages 2503-2515, September.
  53. Catalina A. Vallejos & Mark F. J. Steel, 2017. "Bayesian survival modelling of university outcomes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 613-631, February.
  54. Bodnar, Olha & Bodnar, Taras, 2024. "Gibbs sampler approach for objective Bayesian inference in elliptical multivariate meta-analysis random effects model," Computational Statistics & Data Analysis, Elsevier, vol. 197(C).
  55. Murray Thomas A., 2017. "Ranking ultimate teams using a Bayesian score-augmented win-loss model," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 13(2), pages 63-78, June.
  56. E. I. George & V. Ročková & P. R. Rosenbaum & V. A. Satopää & J. H. Silber, 2017. "Mortality Rate Estimation and Standardization for Public Reporting: Medicare’s Hospital Compare," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 933-947, July.
  57. Li He & Yu-Bo Wang & William C. Bridges & Zhulin He & S. Megan Che, 2023. "Bayesian Framework for Causal Inference with Principal Stratification and Clusters," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 114-140, April.
  58. Durante, Daniele & Dunson, David B., 2014. "Bayesian dynamic financial networks with time-varying predictors," Statistics & Probability Letters, Elsevier, vol. 93(C), pages 19-26.
  59. Paul A. Parker & Scott H. Holan, 2023. "A Bayesian functional data model for surveys collected under informative sampling with application to mortality estimation using NHANES," Biometrics, The International Biometric Society, vol. 79(2), pages 1397-1408, June.
  60. Reem Aljarallah & Samer A Kharroubi, 2021. "Use of Bayesian Markov Chain Monte Carlo Methods to Model Kuwait Medical Genetic Center Data: An Application to Down Syndrome and Mental Retardation," Mathematics, MDPI, vol. 9(3), pages 1-11, January.
  61. Gregor Zens, 2019. "Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership," 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(4), pages 1019-1051, December.
  62. Gloria Gonzalez-Rivera & Yun Luo, 2020. "A Truncated Mixture Transition Model for Interval-valued Time Series," Working Papers 202005, University of California at Riverside, Department of Economics.
  63. Kensuke Arai & Robert E Kass, 2017. "Inferring oscillatory modulation in neural spike trains," PLOS Computational Biology, Public Library of Science, vol. 13(10), pages 1-31, October.
  64. Buddhavarapu, Prasad & Scott, James G. & Prozzi, Jorge A., 2016. "Modeling unobserved heterogeneity using finite mixture random parameters for spatially correlated discrete count data," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 492-510.
  65. Zhang, Chun-Xia & Xu, Shuang & Zhang, Jiang-She, 2019. "A novel variational Bayesian method for variable selection in logistic regression models," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 1-19.
  66. Måns Magnusson & Leif Jonsson & Mattias Villani, 2020. "DOLDA: a regularized supervised topic model for high-dimensional multi-class regression," Computational Statistics, Springer, vol. 35(1), pages 175-201, March.
  67. Anoek Castelein & Dennis Fok & Richard Paap, 2020. "Heterogeneous variable selection in nonlinear panel data models: A semiparametric Bayesian approach," Tinbergen Institute Discussion Papers 20-061/III, Tinbergen Institute.
  68. Jiakun Jiang & Wei Yang & Erin M. Schnellinger & Stephen E. Kimmel & Wensheng Guo, 2023. "Dynamic logistic state space prediction model for clinical decision making," Biometrics, The International Biometric Society, vol. 79(1), pages 73-85, March.
  69. Anindya Bhadra & Jyotishka Datta & Yunfan Li & Nicholas Polson, 2020. "Horseshoe Regularisation for Machine Learning in Complex and Deep Models," International Statistical Review, International Statistical Institute, vol. 88(2), pages 302-320, August.
  70. James Joseph Balamuta & Steven Andrew Culpepper, 2022. "Exploratory Restricted Latent Class Models with Monotonicity Requirements under PÒLYA–GAMMA Data Augmentation," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 903-945, September.
  71. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2019. "A Peek into the Unobservable: Hidden States and Bayesian Inference for the Bitcoin and Ether Price Series," Papers 1909.10957, arXiv.org, revised Jul 2021.
  72. Zhehan Jiang & Jonathan Templin, 2019. "Gibbs Samplers for Logistic Item Response Models via the Pólya–Gamma Distribution: A Computationally Efficient Data-Augmentation Strategy," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 358-374, June.
  73. Justin J. Van Ee & Christian A. Hagen & David C. Pavlacky Jr. & Kent A. Fricke & Matthew D. Koslovsky & Mevin B. Hooten, 2023. "Melding wildlife surveys to improve conservation inference," Biometrics, The International Biometric Society, vol. 79(4), pages 3941-3953, December.
  74. Bansal, Prateek & Krueger, Rico & Graham, Daniel J., 2021. "Fast Bayesian estimation of spatial count data models," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
  75. Carter Allen & Yuzhou Chang & Brian Neelon & Won Chang & Hang J. Kim & Zihai Li & Qin Ma & Dongjun Chung, 2023. "A Bayesian multivariate mixture model for high throughput spatial transcriptomics," Biometrics, The International Biometric Society, vol. 79(3), pages 1775-1787, September.
  76. Durante, Daniele & Canale, Antonio & Rigon, Tommaso, 2019. "A nested expectation–maximization algorithm for latent class models with covariates," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 97-103.
  77. Bakerman, Jordan & Pazdernik, Karl & Korkmaz, Gizem & Wilson, Alyson G., 2022. "Dynamic logistic regression and variable selection: Forecasting and contextualizing civil unrest," International Journal of Forecasting, Elsevier, vol. 38(2), pages 648-661.
  78. Wenjie Bi & Bing Wang & Haiying Liu, 2024. "Personalized Dynamic Pricing Based on Improved Thompson Sampling," Mathematics, MDPI, vol. 12(8), pages 1-14, April.
  79. Chu, Amanda M.Y. & Omori, Yasuhiro & So, Hing-yu & So, Mike K.P., 2023. "A Multivariate Randomized Response Model for Sensitive Binary Data," Econometrics and Statistics, Elsevier, vol. 27(C), pages 16-35.
  80. Constandina Koki & Stefanos Leonardos & Georgios Piliouras, 2020. "Exploring the Predictability of Cryptocurrencies via Bayesian Hidden Markov Models," Papers 2011.03741, arXiv.org, revised Dec 2020.
  81. Ovielt Baltodano L'opez & Roberto Casarin, 2022. "A Dynamic Stochastic Block Model for Multi-Layer Networks," Papers 2209.09354, arXiv.org.
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