Landaw E M, DiStefano J J
Am J Physiol. 1984 May;246(5 Pt 2):R665-77. doi: 10.1152/ajpregu.1984.246.5.R665.
Sums-of-exponentials models are widely used in biomedical research, chiefly as models of data, despite a sizable folklore criticizing their usefulness. Problems in multiexponential model fitting are addressed here, along with an exposition of how to quantify them and critically assess their quality with available statistical methods and computer programs. This class of models also is reconciled with two classes of models of systems: multicompartmental and noncompartmental models. Key issues include the importance of choosing a correct data error model, the necessity for computing model precision estimates, and the distinction between problems due to experiment design or overparameterization and purported difficulties with multiexponential models. Methods for obtaining statistical estimates of model precision, for checking goodness of fit of competing models, and for improving sampling designs are presented. Also the classic Lanczos problem is revisited, and some difficulties are resolved with a more efficient experiment design.
指数和模型在生物医学研究中被广泛使用，主要用作数据模型，尽管有大量传闻批评其效用。本文讨论了多指数模型拟合中的问题，并阐述了如何量化这些问题，以及如何使用现有的统计方法和计算机程序严格评估其质量。这类模型还与两类系统模型相协调：多房室模型和非房室模型。关键问题包括选择正确的数据误差模型的重要性、计算模型精度估计的必要性，以及区分由于实验设计或参数过多引起的问题和多指数模型所谓的困难。本文介绍了获得模型精度统计估计、检查竞争模型拟合优度以及改进抽样设计的方法。此外，还重新审视了经典的兰佐斯问题，并通过更有效的实验设计解决了一些困难。
