Centre d'Ecologie Fonctionnelle et Evolutive, UMR 5175, 1919 Route de Mende, F34293 Montpellier Cedex 5, France.
Math Biosci. 2012 Apr;236(2):117-25. doi: 10.1016/j.mbs.2012.02.002. Epub 2012 Feb 23.
In this article, we present a method for determining whether a model is at least locally identifiable and in the case of non-identifiable models whether any of the parameters are individually at least locally identifiable. This method combines symbolic and numeric methods to create an algorithm that is extremely accurate compared to other numeric methods and computationally inexpensive. A series of generic computational steps are developed to create a method that is ideal for practitioners to use. The algorithm is compared to symbolic methods for two capture-recapture models and a compartment model.
在本文中,我们提出了一种确定模型是否至少局部可识别的方法,并且在不可识别模型的情况下,确定是否至少局部可识别任何参数。该方法结合了符号和数值方法,创建了一种与其他数值方法相比极其准确且计算成本低廉的算法。开发了一系列通用计算步骤,以创建一种非常适合从业者使用的方法。该算法与两种捕获-再捕获模型和一个房室模型的符号方法进行了比较。