| Worlds in motion: understanding international migration at the end of the millennium: understanding international migration at the end of the millennium DS Massey, J Arango, G Hugo, A Kouaouci, A Pellegrino Clarendon Press, 1999 | 5567 | 1999 |
| Random fields and geometry RJ Adler, JE Taylor Springer Science & Business Media, 2009 | 2335 | 2009 |
| Strong control, conservative point estimation and simultaneous conservative consistency of false discovery rates: a unified approach JD Storey, JE Taylor, D Siegmund Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2004 | 1711 | 2004 |
| Distributed neural representation of expected value B Knutson, J Taylor, M Kaufman, R Peterson, G Glover Journal of Neuroscience 25 (19), 4806-4812, 2005 | 1271 | 2005 |
| The solution path of the generalized lasso RJ Tibshirani Stanford University, 2011 | 1116 | 2011 |
| Exact post-selection inference, with application to the lasso JD Lee, DL Sun, Y Sun, JE Taylor | 924 | 2016 |
| A significance test for the lasso R Lockhart, J Taylor, RJ Tibshirani, R Tibshirani Annals of statistics 42 (2), 413, 2014 | 878 | 2014 |
| Strong rules for discarding predictors in lasso-type problems R Tibshirani, J Bien, J Friedman, T Hastie, N Simon, J Taylor, ... Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2012 | 781 | 2012 |
| A lasso for hierarchical interactions J Bien, J Taylor, R Tibshirani Annals of statistics 41 (3), 1111, 2013 | 629 | 2013 |
| Structural asymmetries in the human brain: a voxel-based statistical analysis of 142 MRI scans KE Watkins, T Paus, JP Lerch, A Zijdenbos, DL Collins, P Neelin, J Taylor, ... Cerebral cortex 11 (9), 868-877, 2001 | 609 | 2001 |
| Exact post-selection inference for sequential regression procedures RJ Tibshirani, J Taylor, R Lockhart, R Tibshirani Journal of the American Statistical Association 111 (514), 600-620, 2016 | 473 | 2016 |
| Degrees of freedom in lasso problems RJ Tibshirani, J Taylor | 454 | 2012 |
| Unified univariate and multivariate random field theory KJ Worsley, JE Taylor, F Tomaiuolo, J Lerch Neuroimage 23, S189-S195, 2004 | 450 | 2004 |
| Statistical learning and selective inference J Taylor, RJ Tibshirani Proceedings of the National Academy of Sciences 112 (25), 7629-7634, 2015 | 442 | 2015 |
| Optimal inference after model selection W Fithian, D Sun, J Taylor arXiv preprint arXiv:1410.2597, 2014 | 378 | 2014 |
| Genotypic predictors of human immunodeficiency virus type 1 drug resistance SY Rhee, J Taylor, G Wadhera, A Ben-Hur, DL Brutlag, RW Shafer Proceedings of the National Academy of Sciences 103 (46), 17355-17360, 2006 | 348 | 2006 |
| Deformation-based surface morphometry applied to gray matter deformation MK Chung, KJ Worsley, S Robbins, T Paus, J Taylor, JN Giedd, ... NeuroImage 18 (2), 198-213, 2003 | 338 | 2003 |
| An introduction to statistical learning: With applications in python G James, D Witten, T Hastie, R Tibshirani, J Taylor Springer Nature, 2023 | 326* | 2023 |
| A Matlab toolbox for the statistical analysis of univariate and multivariate surface and volumetric data using linear mixed effects models and random field theory KJ Worsley, J Taylor, F Carbonell, M Chung, E Duerden, B Bernhardt, ... NeuroImage organisation for human brain mapping 2009 annual meeting 47, S102, 2009 | 323 | 2009 |
| Forward stagewise regression and the monotone lasso T Hastie, J Taylor, R Tibshirani, G Walther | 301 | 2007 |
