Fitzpatrick Ben G
Department of Mathematics, Loyola Marymount University, Los Angeles, USA.
Cardiovasc Eng. 2008 Jun;8(2):135-43. doi: 10.1007/s10558-007-9052-6.
Comparing models with data always forces us to deal with uncertainty. This uncertainty may take many different forms and involve multiple scales of resolution in the model and in the experiment. In this paper, we discuss issues surrounding the development of deterministic dynamic models of mean behavior and the associated statistical models of the difference between model and experiment. We touch on a variety of topics, including basic exploratory data analysis, confidence bounds and model reduction hypothesis tests. Tools ranging from nonlinear regression to time series to Bayesian decision theory are presented.
将模型与数据进行比较总会迫使我们应对不确定性。这种不确定性可能呈现多种不同形式，并且涉及模型和实验中多个分辨率尺度。在本文中，我们讨论围绕平均行为确定性动态模型的开发以及模型与实验之间差异的相关统计模型的问题。我们会涉及各种主题，包括基本的探索性数据分析、置信区间和模型简化假设检验。还会介绍从非线性回归到时间序列再到贝叶斯决策理论等各种工具。
