PARAMETER AND STRUCTURAL IDENTIFIABILITY CONCEPTS AND AMBIGUITIES - A CRITICAL-REVIEW AND ANALYSIS
PARAMETER AND STRUCTURAL IDENTIFIABILITY CONCEPTS AND AMBIGUITIES - A CRITICAL-REVIEW AND ANALYSIS
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DOI：
10.1152/ajpregu.1980.239.1.r7
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发表时间：
1980-01-01
影响因子：
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通讯作者：
DISTEFANO, JJ
中科院分区：
文献类型：
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作者：
COBELLI, C;DISTEFANO, JJ
可识别性的概念解决了这样的问题：是否有可能从在模型所代表的动态系统上进行的明确定义的刺激响应实验中收集的数据，获得数学模型中感兴趣的未知参数的唯一解决方案。对建模和数据缩减问题的这一关键方面进行了审查、分析和统一，重点是在生物学中的应用。详细研究了几种生理系统模型。它们说明了在进行参数估计实验之前进行可识别性分析的重要性、代数困难、可能的陷阱和可能遇到的不明显的歧义（即使对于简单模型）以及该概念在实验设计中的实用性。对可识别性测试方法进行了审查和比较，重点是适用性和局限性。给定模型用于预测通常无法直接测量（例如组织浓度）的感兴趣的系统变量（而不是参数）的时间进程（定量模型的常见用途）的有用性取决于模型的可识别性属性，以一种不容易但必须评估的方式：以这种方式进行的状态变量预测可能本质上是模糊的。
The notion of identifiability addresses the question of whether it is possible to obtain unique solutions for unknown parameters of interest in a mathematical model, from data collected in well-defined stimulus-response experiments performed on a dynamic system represented by the model. This critical aspect of the modeling and data reduction problem is reviewed, analyzed and unified, with emphasis on applications in biology. Several physiological system models are examined in detail. They illustrate the importance of identifiability analysis prior to performing a parameter estimation experiment, the algebraic difficulties, possible pitfalls and nonapparent ambiguities that may be enountered (even for simple models) and the utility of the concept in experiment design. Methods for testing for identifiability are reviewed and compared, with emphasis on applicability and limitations. The usefulness of a given model for predicting the time course of system variable (not parameters) of interest normally inaccessible to direct measurement (e.g., tissue concentrations), a common use for quantitative models, depends on the identifiability properties of the model, in a manner not easy but essential to assess: state variable predictions made in this manner can be inherently ambiguous.