Center for Research in Scientic Computation, North Carolina State University, Raleigh, NC 27695-8212, United States.
Math Biosci Eng. 2012 Jul;9(3):487-526. doi: 10.3934/mbe.2012.9.487.
In this paper, we investigate three particular algorithms: a stochastic simulation algorithm (SSA), and explicit and implicit tau-leaping algorithms. To compare these methods, we used them to analyze two infection models: a Vancomycin-resistant enterococcus (VRE) infection model at the population level, and a Human Immunodeficiency Virus (HIV) within host infection model. While the first has a low species count and few transitions, the second is more complex with a comparable number of species involved. The relative efficiency of each algorithm is determined based on computational time and degree of precision required. The numerical results suggest that all three algorithms have the similar computational efficiency for the simpler VRE model, and the SSA is the best choice due to its simplicity and accuracy. In addition, we have found that with the larger and more complex HIV model, implementation and modification of tau-Leaping methods are preferred.
在本文中,我们研究了三种特定的算法:随机模拟算法(SSA)、显式和隐式τ跳跃算法。为了比较这些方法,我们使用它们来分析两个感染模型:一个是人群水平的万古霉素耐药肠球菌(VRE)感染模型,另一个是人类免疫缺陷病毒(HIV)在宿主内感染模型。前者物种数量少,转换少,而后者则更复杂,涉及的物种数量相当。根据所需的计算时间和精度要求,确定每种算法的相对效率。数值结果表明,对于较简单的 VRE 模型,这三种算法具有相似的计算效率,而由于其简单性和准确性,SSA 是最佳选择。此外,我们发现,对于更大和更复杂的 HIV 模型,tau-Leaping 方法的实现和修改更为可取。