xed-lag smoothing in state-space models
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[1] É. Mémin,et al. Weighted ensemble transform Kalman filter for image assimilation , 2013 .
[2] Ying Sun,et al. Geostatistics for Large Datasets , 2012 .
[3] G. Roberts,et al. Exact simulation of diffusions , 2005, math/0602523.
[4] A. Doucet,et al. Monte Carlo Smoothing for Nonlinear Time Series , 2004, Journal of the American Statistical Association.
[5] Geir Evensen,et al. The Ensemble Kalman Filter: theoretical formulation and practical implementation , 2003 .
[6] N. Gordon,et al. Novel approach to nonlinear/non-Gaussian Bayesian state estimation , 1993 .
[7] P. Fearnhead,et al. Particle filters for partially observed diffusions , 2007, 0710.4245.
[8] P. Fearnhead,et al. Exact and computationally efficient likelihood‐based estimation for discretely observed diffusion processes (with discussion) , 2006 .
[9] G. Evensen,et al. An ensemble Kalman smoother for nonlinear dynamics , 2000 .
[10] Jonathan R. Stroud,et al. An Ensemble Kalman Filter and Smoother for Satellite Data Assimilation , 2010 .
[11] A. Doucet,et al. Smoothing algorithms for state–space models , 2010 .
[12] P. Leeuwen,et al. Nonlinear data assimilation in geosciences: an extremely efficient particle filter , 2010 .
[13] Peter Jan,et al. Particle Filtering in Geophysical Systems , 2009 .
[14] Simon J. Godsill,et al. On sequential Monte Carlo sampling methods for Bayesian filtering , 2000, Stat. Comput..
[15] P. Bickel,et al. Obstacles to High-Dimensional Particle Filtering , 2008 .
[16] Pierre Del Moral,et al. Feynman-Kac formulae , 2004 .
[17] A. Gallant,et al. Numerical Techniques for Maximum Likelihood Estimation of Continuous-Time Diffusion Processes , 2002 .
[18] J.M.C. Clark. The simulation of pinned diffusions , 1990, 29th IEEE Conference on Decision and Control.
[19] P. Protter,et al. The Monte-Carlo method for filtering with discrete-time observations , 2001 .