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Applications of a Method for the Efficient Computation of Posterior Distributions

Citations

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Cited by:

  1. Catherine ARAUJO BONJEAN & Claudio ARAUJO & Stephanie BRUNELIN, 2010. "Alert at Maradi: preventing food crisis using price signals," Working Papers 201023, CERDI.
  2. Korobilis, Dimitris & Pettenuzzo, Davide, 2020. "Machine Learning Econometrics: Bayesian algorithms and methods," MPRA Paper 100165, University Library of Munich, Germany.
  3. Cagnone, Silvia & Bartolucci, Francesco, 2013. "Adaptive quadrature for likelihood inference on dynamic latent variable models for time-series and panel data," MPRA Paper 51037, University Library of Munich, Germany.
  4. Naylor, J.C. & Tremayne, A.R. & Marriott, J.M., 2010. "Exploratory data analysis and model criticism with posterior plots," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2707-2720, November.
  5. Steele C. West & Amin W. Mugera & Ross S. Kingwell, 2024. "The impact of repayment obligations arising as a by‐product of input use on partial inefficiency: Evidence from Western Australian farm businesses," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 68(3), pages 678-700, July.
  6. Peter W. Rijn & Usama S. Ali, 2018. "A Generalized Speed–Accuracy Response Model for Dichotomous Items," Psychometrika, Springer;The Psychometric Society, vol. 83(1), pages 109-131, March.
  7. Richard Kouamé Moussa, 2019. "Heteroskedasticity in One-Way Error Component Probit Models," Econometrics, MDPI, vol. 7(3), pages 1-22, August.
  8. Lahiri, Kajal & Gao, Jian, 2002. "Bayesian analysis of nested logit model by Markov chain Monte Carlo," Journal of Econometrics, Elsevier, vol. 111(1), pages 103-133, November.
  9. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
  10. Silvia Cagnone & Paola Monari, 2013. "Latent variable models for ordinal data by using the adaptive quadrature approximation," Computational Statistics, Springer, vol. 28(2), pages 597-619, April.
  11. Burkhart, Michael C., 2019. "A Discriminative Approach to Bayesian Filtering with Applications to Human Neural Decoding," Thesis Commons 4j3fu, Center for Open Science.
  12. Angelina Hammon & Sabine Zinn, 2020. "Multiple imputation of binary multilevel missing not at random data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(3), pages 547-564, June.
  13. 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.
  14. Rossi, David & Kuusela, Olli-Pekka & Dunn, Christopher, 2022. "A microeconometric analysis of wildfire suppression decisions in the Western United States," Ecological Economics, Elsevier, vol. 200(C).
  15. 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.
  16. Efthymios Tsionas & George Halkos, 2000. "Posterior Analysis of Environmental Damage Evaluation in Europe," International Review of Applied Economics, Taylor & Francis Journals, vol. 14(3), pages 371-390.
  17. Jacek Osiewalski & Mark Steel, 1998. "Numerical Tools for the Bayesian Analysis of Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 10(1), pages 103-117, July.
  18. Silvia Cagnone & Francesco Bartolucci, 2017. "Adaptive Quadrature for Maximum Likelihood Estimation of a Class of Dynamic Latent Variable Models," Computational Economics, Springer;Society for Computational Economics, vol. 49(4), pages 599-622, April.
  19. 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.
  20. Stephen Schilling & R. Bock, 2005. "High-dimensional maximum marginal likelihood item factor analysis by adaptive quadrature," Psychometrika, Springer;The Psychometric Society, vol. 70(3), pages 533-555, September.
  21. Alaverdyan, Sevak & Zaharieva, Anna, 2022. "Immigration, social networks and occupational mismatch," Economic Modelling, Elsevier, vol. 114(C).
  22. Gael M. Martin & David T. Frazier & Christian P. Robert, 2021. "Approximating Bayes in the 21st Century," Monash Econometrics and Business Statistics Working Papers 24/21, Monash University, Department of Econometrics and Business Statistics.
  23. Edgar C. Merkle & Daniel Furr & Sophia Rabe-Hesketh, 2019. "Bayesian Comparison of Latent Variable Models: Conditional Versus Marginal Likelihoods," Psychometrika, Springer;The Psychometric Society, vol. 84(3), pages 802-829, September.
  24. Paul A. Jewsbury & Peter W. van Rijn, 2020. "IRT and MIRT Models for Item Parameter Estimation With Multidimensional Multistage Tests," Journal of Educational and Behavioral Statistics, , vol. 45(4), pages 383-402, August.
  25. Francis Tuerlinckx & Paul Boeck, 2005. "Two interpretations of the discrimination parameter," Psychometrika, Springer;The Psychometric Society, vol. 70(4), pages 629-650, December.
  26. Miguel Santolino & Mercedes Ayuso, 2020. "Number and severity of BI victims, assuming dependence between vehicles involved in the crash," IREA Working Papers 202018, University of Barcelona, Research Institute of Applied Economics, revised Dec 2020.
  27. Cho, S.-J. & Rabe-Hesketh, S., 2011. "Alternating imputation posterior estimation of models with crossed random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 12-25, January.
  28. Jin, Shaoze & Min, Shi & Huang, Jikun & Waibel, Hermann, 2021. "Falling price induced diversification strategies and rural inequality: Evidence of smallholder rubber farmers," World Development, Elsevier, vol. 146(C).
  29. Trushin, Eshref & Ugur, Mehmet, 2018. "Ecosystem complexity, firm learning and survival: UK evidence on intra-industry age and size diversity as exit hazards," Greenwich Papers in Political Economy 19095, University of Greenwich, Greenwich Political Economy Research Centre.
  30. Judex Hyppolite & Pravin Trivedi, 2012. "Alternative Approaches For Econometric Analysis Of Panel Count Data Using Dynamic Latent Class Models (With Application To Doctor Visits Data)," Health Economics, John Wiley & Sons, Ltd., vol. 21(S1), pages 101-128, June.
  31. Li Cai, 2010. "High-dimensional Exploratory Item Factor Analysis by A Metropolis–Hastings Robbins–Monro Algorithm," Psychometrika, Springer;The Psychometric Society, vol. 75(1), pages 33-57, March.
  32. Martin Srholec, 2016. "Persistence of Cooperation on Innovation: Econometric Evidence from Panel Micro Data," Prague Economic Papers, Prague University of Economics and Business, vol. 2016(1), pages 53-70.
  33. Pieroni, L. & d'Agostino, G., 2013. "Corruption and the effects of economic freedom," European Journal of Political Economy, Elsevier, vol. 29(C), pages 54-72.
  34. Bethany Jablonski Horton & Nolan A. Wages & Ryan D. Gentzler, 2021. "Bayesian Design for Identifying Cohort-Specific Optimal Dose Combinations Based on Multiple Endpoints: Application to a Phase I Trial in Non-Small Cell Lung Cancer," IJERPH, MDPI, vol. 18(21), pages 1-10, October.
  35. Shelby Haberman & Sandip Sinharay & Kyong Chon, 2013. "Assessing Item Fit for Unidimensional Item Response Theory Models Using Residuals from Estimated Item Response Functions," Psychometrika, Springer;The Psychometric Society, vol. 78(3), pages 417-440, July.
  36. Davidmac O. Ekeocha & Chimere O. Iheonu, 2021. "Household‐level poverty, consumption poverty thresholds, income inequality and quality of lives in sub‐Saharan Africa," African Development Review, African Development Bank, vol. 33(2), pages 234-248, June.
  37. Wu, Jianmin & Bentler, Peter M., 2012. "Application of H-likelihood to factor analysis models with binary response data," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 72-79.
  38. Jeanne Amar & Samira Demaria & Sandra Rigot, 2019. "What motivates CAC 40 companies to disclose information on climate-related financial risks?," Post-Print halshs-02407125, HAL.
  39. Ting Wang & Benjamin Graves & Yves Rosseel & Edgar C. Merkle, 2022. "Computation and application of generalized linear mixed model derivatives using lme4," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 1173-1193, September.
  40. Stroud, T. W. F. & Sykes, Alan M. & Witt, Stephen F., 1998. "Forecasting a collection of binomial proportions in the presence of covariates," International Journal of Forecasting, Elsevier, vol. 14(1), pages 5-15, March.
  41. Jianxin Pan & Robin Thompson, 2003. "Gauss-Hermite Quadrature Approximation for Estimation in Generalised Linear Mixed Models," Computational Statistics, Springer, vol. 18(1), pages 57-78, March.
  42. Li Cai, 2010. "Metropolis-Hastings Robbins-Monro Algorithm for Confirmatory Item Factor Analysis," Journal of Educational and Behavioral Statistics, , vol. 35(3), pages 307-335, June.
  43. Wu, Jianmin & Bentler, Peter M., 2013. "Limited information estimation in binary factor analysis: A review and extension," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 392-403.
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