| Bayesian data analysis A Gelman, JB Carlin, HS Stern, DB Dunson, A Vehtari, DB Rubin Chapman hall/CRC Press, 2013 | 27867 | 2013 |
| Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC A Vehtari, A Gelman, J Gabry Statistics and computing 27 (5), 1413-1432, 2017 | 1439 | 2017 |
| Understanding predictive information criteria for Bayesian models A Gelman, J Hwang, A Vehtari Statistics and computing 24 (6), 997-1016, 2014 | 1053 | 2014 |
| One vs three years of adjuvant imatinib for operable gastrointestinal stromal tumor: a randomized trial H Joensuu, M Eriksson, KS Hall, JT Hartmann, D Pink, J Schütte, ... Jama 307 (12), 1265-1272, 2012 | 896 | 2012 |
| Risk of recurrence of gastrointestinal stromal tumour after surgery: an analysis of pooled population-based cohorts H Joensuu, A Vehtari, J Riihimäki, T Nishida, SE Steigen, P Brabec, ... The lancet oncology 13 (3), 265-274, 2012 | 682 | 2012 |
| Rao-Blackwellized particle filter for multiple target tracking S Särkkä, A Vehtari, J Lampinen Information Fusion 8 (1), 2-15, 2007 | 316 | 2007 |
| Bayesian approach for neural networks—review and case studies J Lampinen, A Vehtari Neural networks 14 (3), 257-274, 2001 | 298 | 2001 |
| A survey of Bayesian predictive methods for model assessment, selection and comparison A Vehtari, J Ojanen Statistics Surveys 6, 142-228, 2012 | 239 | 2012 |
| GPstuff: Bayesian modeling with Gaussian processes J Vanhatalo, J Riihimäki, J Hartikainen, P Jylänki, V Tolvanen, A Vehtari Journal of Machine Learning Research 14 (Apr), 1175-1179, 2013 | 232 | 2013 |
| loo: Efficient leave-one-out cross-validation and WAIC for Bayesian models A Vehtari, A Gelman, J Gabry R package version 2 (0), 1003, 2018 | 211 | 2018 |
| Bayesian model assessment and comparison using cross-validation predictive densities A Vehtari, J Lampinen Neural computation 14 (10), 2439-2468, 2002 | 188 | 2002 |
| Comparison of Bayesian predictive methods for model selection J Piironen, A Vehtari Statistics and Computing 27 (3), 711-735, 2017 | 168 | 2017 |
| Visualization in Bayesian workflow J Gabry, D Simpson, A Vehtari, M Betancourt, A Gelman Journal of the Royal Statistical Society Series A, 2017 | 157 | 2017 |
| Using stacking to average Bayesian predictive distributions Y Yao, A Vehtari, D Simpson, A Gelman Bayesian Analysis 13 (3), 917-1003, 2018 | 142 | 2018 |
| Gaussian processes with monotonicity information J Riihimäki, A Vehtari Proceedings of the thirteenth international conference on artificial …, 2010 | 141 | 2010 |
| R-squared for Bayesian regression models A Gelman, B Goodrich, J Gabry, A Vehtari The American Statistician 73 (3), 307-309, 2019 | 139 | 2019 |
| Discussion on the paper by Spiegelhalter, Best, Carlin and van der Linde SP Brooks, J Smith, A Vehtari, M Plummer, M Stone, CP Robert, ... Journal of the Royal Statistical Society. Series B: Statistical Methodology …, 2002 | 136 | 2002 |
| Robust Gaussian Process Regression with a Student-t Likelihood. P Jylänki, J Vanhatalo, A Vehtari Journal of Machine Learning Research 12 (11), 2011 | 134 | 2011 |
| Sparsity information and regularization in the horseshoe and other shrinkage priors J Piironen, A Vehtari Electronic Journal of Statistics 11 (2), 5018-5051, 2017 | 124 | 2017 |
| A multi-metabolite analysis of serum by 1H NMR spectroscopy: early systemic signs of Alzheimer’s disease T Tukiainen, T Tynkkynen, VP Mäkinen, P Jylänki, A Kangas, J Hokkanen, ... Biochemical and biophysical research communications 375 (3), 356-361, 2008 | 119 | 2008 |
Andrew GelmanProfessor of Statistics and Political Science, Columbia UniversityBekræftet mail på stat.columbia.edu
