Error bounds for data-driven models of dynamical systems |
| |
Authors: | Oleng' Nicholas O Gribok Andrei Reifman Jaques |
| |
Affiliation: | Bioinformatics Cell, U.S. Army Medical Research and Materiel Command, Frederick, MD 21702, USA. |
| |
Abstract: | This work provides a technique for estimating error bounds about the predictions of data-driven models of dynamical systems. The bootstrap technique is applied to predictions from a set of dynamical system models, rather than from the time-series data, to estimate the reliability (in the form of prediction intervals) for each prediction. The technique is illustrated using human core temperature data, modeled by a hybrid (autoregressive plus first principles) approach. The temperature prediction intervals obtained are in agreement with those from the Camp-Meidell inequality. Moreover, as expected, the prediction intervals increase with the prediction horizon, time-series data variability, and model inaccuracy. |
| |
Keywords: | Physiologic measurement predictions Bootstrap Error bounds Confidence interval Prediction interval Time-series data Dynamical systems |
本文献已被 ScienceDirect PubMed 等数据库收录! |
|