| Bayesian computation and stochastic systems J Besag, P Green, D Higdon, K Mengersen Statistical science, 3-41, 1995 | 1598 | 1995 |
| Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling JA Vrugt, JM Hyman, BA Robinson, D Higdon, CGH Diks International journal of nonlinear sciences and numerical simulation, 2007 | 1367 | 2007 |
| Computer model calibration using high-dimensional output D Higdon, J Gattiker, B Williams, M Rightley Journal of the American Statistical Association 103 (482), 570-583, 2008 | 1206 | 2008 |
| Combining field data and computer simulations for calibration and prediction D Higdon, M Kennedy, JC Cavendish, JA Cafeo, RD Ryne SIAM Journal on Scientific Computing 26 (2), 448-466, 2004 | 872 | 2004 |
| Handbook of uncertainty quantification R Ghanem, D Higdon, H Owhadi Springer, 2017 | 713 | 2017 |
| Space and space-time modeling using process convolutions D Higdon Quantitative methods for current environmental issues, 37-56, 2002 | 679 | 2002 |
| A process-convolution approach to modelling temperatures in the North Atlantic Ocean D Higdon Environmental and Ecological Statistics 5 (2), 173-190, 1998 | 566 | 1998 |
| Non-stationary spatial modeling D Higdon, J Swall, J Kern arXiv preprint arXiv:2212.08043, 2022 | 561 | 2022 |
| The coyote universe. I. Precision determination of the nonlinear matter power spectrum K Heitmann, M White, C Wagner, S Habib, D Higdon The Astrophysical Journal 715 (1), 104, 2010 | 413 | 2010 |
| The coyote universe. II. Cosmological models and precision emulation of the nonlinear matter power spectrum K Heitmann, D Higdon, M White, S Habib, BJ Williams, E Lawrence, ... The Astrophysical Journal 705 (1), 156, 2009 | 359 | 2009 |
| The coyote universe extended: precision emulation of the matter power spectrum K Heitmann, E Lawrence, J Kwan, S Habib, D Higdon The Astrophysical Journal 780 (1), 111, 2013 | 357 | 2013 |
| Auxiliary variable methods for Markov chain Monte Carlo with applications DM Higdon Journal of the American statistical Association 93 (442), 585-595, 1998 | 318 | 1998 |
| Bayesian analysis of agricultural field experiments J Besag, D Higdon Journal of the Royal Statistical Society Series B: Statistical Methodology …, 1999 | 297 | 1999 |
| The coyote universe. III. Simulation suite and precision emulator for the nonlinear matter power spectrum E Lawrence, K Heitmann, M White, D Higdon, C Wagner, S Habib, ... The Astrophysical Journal 713 (2), 1322, 2010 | 288 | 2010 |
| Nonparametric dark energy reconstruction from supernova data T Holsclaw, U Alam, B Sanso, H Lee, K Heitmann, S Habib, D Higdon Physical Review Letters 105 (24), 241302, 2010 | 255 | 2010 |
| Primate species richness is determined by plant productivity: implications for conservation RF Kay, RH Madden, C Van Schaik, D Higdon Proceedings of the National Academy of Sciences 94 (24), 13023-13027, 1997 | 247 | 1997 |
| Using data-driven agent-based models for forecasting emerging infectious diseases S Venkatramanan, B Lewis, J Chen, D Higdon, A Vullikanti, M Marathe Epidemics 22, 43-49, 2018 | 246 | 2018 |
| Variable selection for Gaussian process models in computer experiments C Linkletter, D Bingham, N Hengartner, D Higdon, KQ Ye Technometrics 48 (4), 478-490, 2006 | 233 | 2006 |
| A Bayesian hierarchical model to predict benthic oxygen demand from organic matter loading in estuaries and coastal zones ME Borsuk, D Higdon, CA Stow, KH Reckhow Ecological modelling 143 (3), 165-181, 2001 | 212 | 2001 |
| Forecasting seasonal influenza with a state-space SIR model D Osthus, KS Hickmann, PC Caragea, D Higdon, SY Del Valle The annals of applied statistics 11 (1), 202, 2017 | 206 | 2017 |
