We consider a randomized discrete logistic equation to describe the dynamics of breast tumor volume. We propose a method, that takes advantage of the principle of maximum entropy, to assign reliable distributions to model inputs (initial condition and coefficients) and sample data, respectively. Since the distributions of coefficients depend on certain parameters, we design a computational procedure to determine the above-mentioned parameters using the information of the probabilistic distributions. The proposed method is successfully applied to model the breast tumor volume using real data. The approach seems to be flexible enough to be adapted to other stochastic models in future contributions.

我们考虑一个随机的离散逻辑方程来描述乳腺肿瘤体积的动力学。我们提出一种利用最大熵原理的方法，分别为模型输入（初始条件和系数）和样本数据分配可靠的分布。由于系数的分布取决于某些参数，因此我们设计了一种计算程序，使用概率分布的信息确定上述参数。所提出的方法已成功地用于使用实际数据对乳腺肿瘤体积进行建模。该方法似乎足够灵活，可以在将来的应用中适应其他随机模型。