| Abstract: | ABSTRACT Computer models depending on unknown inputs are used in computer experiments in order to study the input-output relationship. Some computer models are computationally intensive and only a few computer runs can be made. A nonstationary statistical model that is used as a faster-running surrogate for computationally intensive numerical solvers of ordinary differential systems is proposed in this article. This statistical model reflects the dynamics of the system and, as a population dynamics example will show, it can be more accurate than a commonly used black box statistical model. |
