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Article

What the collapse of the ensemble Kalman filter tells us about particle filters

, &
Article: 1283809 | Received 31 May 2016, Accepted 19 Dec 2016, Published online: 08 Mar 2017

Figures & data

Figure 1. Left: quality measure G as a function of the dimension for the various methods. Shown are the values of G for each experiment (dots) along with log-linear least-squares fits (straight lines) and one standard deviation confidence intervals (shaded regions). Right: normalized MSE as a function of the dimension for the various methods. Shown are the mean (dots) and confidence intervals (error bars) computed from 100 numerical experiments. Also shown (dashed lines) is the mean and two standard deviation confidence intervals of the ideal MSE (dashed green).

Figure 1. Left: quality measure G as a function of the dimension for the various methods. Shown are the values of G for each experiment (dots) along with log-linear least-squares fits (straight lines) and one standard deviation confidence intervals (shaded regions). Right: normalized MSE as a function of the dimension for the various methods. Shown are the mean (dots) and confidence intervals (error bars) computed from 100 numerical experiments. Also shown (dashed lines) is the mean and two standard deviation confidence intervals of the ideal MSE (dashed green).