In this study, we propose a mixture logistic regression model with a Markov structure, and consider the estimation of model parameters using maximum likelihood estimation. We also provide a forward type variable selection algorithm to choose the important explanatory variables to reduce the number of parameters in the proposed model.

翻译：本研究提出一种具有马尔可夫结构的混合逻辑回归模型，并考虑采用极大似然估计法进行模型参数估计。同时，我们提供了一种前向型变量选择算法，用于筛选重要的解释变量，以降低所提出模型的参数数量。