| Numerical techniques for maximum likelihood estimation of continuous-time diffusion processes GB Durham, AR Gallant Journal of Business & Economic Statistics 20 (3), 297-338, 2002 | 573 | 2002 |
| Likelihood-based specification analysis of continuous-time models of the short-term interest rate GB Durham Journal of Financial Economics 70 (3), 463-487, 2003 | 154 | 2003 |
| Monte Carlo methods for estimating, smoothing, and filtering one-and two-factor stochastic volatility models GB Durham Journal of Econometrics 133 (1), 273-305, 2006 | 114 | 2006 |
| Adaptive sequential posterior simulators for massively parallel computing environments G Durham, J Geweke Bayesian model comparison, 1-44, 2014 | 113* | 2014 |
| SV mixture models with application to S&P 500 index returns GB Durham Journal of Financial Economics 85 (3), 822-856, 2007 | 89 | 2007 |
| Risk-neutral modeling with affine and nonaffine models GB Durham Journal of Financial Econometrics 11 (4), 650-681, 2013 | 27 | 2013 |
| Beyond stochastic volatility and jumps in returns and volatility G Durham, YH Park Journal of Business & Economic Statistics 31 (1), 107-121, 2013 | 23 | 2013 |
| Improving asset price prediction when all models are false G Durham, J Geweke Journal of Financial Econometrics 12 (2), 278-306, 2013 | 22 | 2013 |
| Numerical techniques for simulated maximum likelihood estimation of stochastic differential equations GB Durham, AR Gallant Journal of Business and Economic Statistics 20 (3), 297-316, 2002 | 17 | 2002 |
| Bayesian inference for ARFIMA models G Durham, J Geweke, S Porter‐Hudak, F Sowell Journal of Time Series Analysis 40 (4), 388-410, 2019 | 15 | 2019 |
| Sequentially adaptive Bayesian learning algorithms for inference and optimization J Geweke, G Durham Journal of econometrics 210 (1), 4-25, 2019 | 15 | 2019 |
| A comment on Christoffersen, Jacobs, and Ornthanalai (2012),“Dynamic jump intensities and risk premiums: Evidence from S&P 500 returns and options” G Durham, J Geweke, P Ghosh Journal of Financial Economics 115 (1), 210-214, 2015 | 13 | 2015 |
| Bayesian inference for logistic regression models using sequential posterior simulation J Geweke, G Durham, H Xu SSRN, 2013 | 4 | 2013 |
| Sequentially Adaptive Bayesian Learning Algorithms for Inference and Optimization G Durham, J Geweke | 1 | 2015 |
| Bayesian inference for logistic regression models using sequential posterior simulation J Geweke, G Durham, H Xu Current Trends in Bayesian Methodology with Applications, 289-312, 2015 | 1 | 2015 |
| Comment: Mikhail Chernov M Chernov Journal of Business & Economic Statistics 21 (4), 485, 2003 | 1* | 2003 |
| Rényi Divergence and Monte Carlo Integration J Geweke, G Durham Advances in Info-Metrics: Information and Information Processing across …, 2020 | | 2020 |
| Statistical Methods for Stochastic Differential Equations GB Durham Journal of the American Statistical Association 109 (505), 453-454, 2014 | | 2014 |
| [Iterative and Recursive Estimation in Structural Nonadaptive Models]: Comment G Durham, J Geweke Journal of Business & Economic Statistics 21 (4), 490-492, 2003 | | 2003 |
| Comment [7](multiple letters) H Zhou, GB Durham, AR Gallant Journal of Business and Economic Statistics 20 (3), 332-335+ 338, 2002 | | 2002 |
