| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6898059 | European Journal of Operational Research | 2013 | 10 Pages |
Abstract
⺠Error estimation is studied in Gaussian process models built from stochastic samples. ⺠The relationship between prediction error and prediction variance is quantified. ⺠With a signal-to-noise ratio less than 10, GPM loses accuracy in error estimation. ⺠The GPM prediction errors are normally distributed, despite bias in GPM prediction.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Andres F. Hernandez, Martha A. Grover,