| A simulation approach to dynamic portfolio choice with an application to learning about return predictability MW Brandt, A Goyal, P Santa-Clara, JR Stroud The Review of Financial Studies 18 (3), 831-873, 2005 | 438 | 2005 |
| Optimal filtering of jump diffusions: Extracting latent states from asset prices MS Johannes, NG Polson, JR Stroud Review of Financial Studies 22 (7), 2759-2799, 2009 | 327* | 2009 |
| Dynamic models for spatiotemporal data JR Stroud, P Müller, B Sansó Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2001 | 295 | 2001 |
| Bayesian forecasting of an inhomogeneous Poisson process with applications to call center data J Weinberg, LD Brown, JR Stroud Journal of the American Statistical Association 102 (480), 1185-1198, 2007 | 237 | 2007 |
| Understanding the ensemble Kalman filter M Katzfuss, JR Stroud, CK Wikle The American Statistician 70 (4), 350-357, 2016 | 230 | 2016 |
| A spatiotemporal model for Mexico City ozone levels G Huerta, B Sansó, JR Stroud Journal of the Royal Statistical Society: Series C (Applied Statistics) 53 …, 2004 | 181 | 2004 |
| Practical filtering with sequential parameter learning NG Polson, JR Stroud, P Müller Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2008 | 168 | 2008 |
| Sequential optimal portfolio performance: Market and volatility timing MS Johannes, N Polson, JR Stroud Available at SSRN 304976, 2002 | 93 | 2002 |
| An ensemble Kalman filter and smoother for satellite data assimilation JR Stroud, ML Stein, BM Lesht, DJ Schwab, D Beletsky Journal of the American Statistical Association 105 (491), 978-990, 2010 | 86 | 2010 |
| Bayesian and maximum likelihood estimation for Gaussian processes on an incomplete lattice JR Stroud, ML Stein, S Lysen Journal of computational and Graphical Statistics 26 (1), 108-120, 2017 | 79 | 2017 |
| Nonlinear state-space models with state-dependent variances JR Stroud, P Müller, NG Polson Journal of the American Statistical Association, 2003 | 72 | 2003 |
| A Bayesian adaptive ensemble Kalman filter for sequential state and parameter estimation JR Stroud, M Katzfuss, CK Wikle Monthly weather review 146 (1), 373-386, 2018 | 71 | 2018 |
| Ensemble Kalman methods for high-dimensional hierarchical dynamic space-time models M Katzfuss, JR Stroud, CK Wikle Journal of the American Statistical Association, 2019 | 70 | 2019 |
| Numerical modeling of mixed sediment resuspension, transport, and deposition during the March 1998 episodic events in southern Lake Michigan C Lee, DJ Schwab, D Beletsky, J Stroud, B Lesht Journal of Geophysical Research: Oceans 112 (C2), 2007 | 64 | 2007 |
| Practical filtering for stochastic volatility models JR Stroud, NG Polson, P Müller State space and unobserved component models, 236-247, 2004 | 54 | 2004 |
| Sequential state and variance estimation within the ensemble Kalman filter JR Stroud, T Bengtsson Monthly weather review 135 (9), 3194-3208, 2007 | 52 | 2007 |
| Bayesian modeling and forecasting of 24-hour high-frequency volatility JR Stroud, MS Johannes Journal of the American Statistical Association 109 (508), 1368-1384, 2014 | 50* | 2014 |
| Optimal sampling times in population pharmacokinetic studies JR Stroud, P Muller, GL Rosner Journal of the Royal Statistical Society, Series C (Applied Statistics), 345-359, 2001 | 50 | 2001 |
| Assimilation of satellite images into a sediment transport model of Lake Michigan JR Stroud, BM Lesht, DJ Schwab, D Beletsky, ML Stein Water Resources Research 45 (2), W02419, 2009 | 48 | 2009 |
| Sequential parameter estimation in stochastic volatility models with jumps M Johannes, N Polson, J Stroud Wharton School, University of Pennsylvania, Philadelphia, PA, 2006 | 36 | 2006 |
Nick PolsonProfessor of Econometrics and Statistics, University of ChicagoVerifierad e-postadress på chicagobooth.edu
