Követés
Jonathan R. Stroud
Jonathan R. Stroud
Associate Professor, Georgetown University, McDonough School of Business
E-mail megerősítve itt: georgetown.edu - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
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
4482005
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
338*2009
Dynamic models for spatiotemporal data
JR Stroud, P Müller, B Sansó
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2001
3082001
Understanding the ensemble Kalman filter
M Katzfuss, JR Stroud, CK Wikle
The American Statistician 70 (4), 350-357, 2016
2842016
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
2402007
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
1862004
Practical filtering with sequential parameter learning
NG Polson, JR Stroud, P Müller
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2008
1732008
Sequential optimal portfolio performance: Market and volatility timing
MS Johannes, N Polson, JR Stroud
Available at SSRN 304976, 2002
942002
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
902010
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
852017
Ensemble Kalman methods for high-dimensional hierarchical dynamic space-time models
M Katzfuss, JR Stroud, CK Wikle
Journal of the American Statistical Association, 2020
812020
Nonlinear state-space models with state-dependent variances
JR Stroud, P Müller, NG Polson
Journal of the American Statistical Association, 2003
752003
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
722018
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
642007
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
56*2014
Sequential state and variance estimation within the ensemble Kalman filter
JR Stroud, T Bengtsson
Monthly weather review 135 (9), 3194-3208, 2007
552007
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
552001
Practical filtering for stochastic volatility models
JR Stroud, NG Polson, P Müller
State space and unobserved component models, 236-247, 2004
542004
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
482009
Bayesian inference for derivative prices
NG Polson, JR Stroud
Bayesian Statistics 7, 641-650, 2003
372003
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Cikkek 1–20