一种面向纵向数据的RE-BET算法及应用

混合效应模型是分析纵向数据的有效方法,但模型的线性结构限制了其适应现实数据的能力。提出了一种RE-BET算法及其变形的RE-BEBT算法,采用树形方法估计混合效应模型的固定效应,可以自动选择重要变量,能更好地发现和描述变量间关系;采用基于Dirichlet过程先验的贝叶斯方法估计混合效应模型的随机效应,使模型可以适用于小样本数据。以低合金钢和碳钢的海水腐蚀数据为例,通过与实验数据和其他算法的计算结果对比分析,验证了RE-BET算法可行性和有效性。

A RE-BET algorithm for longitudinal data and its application

Mixed effects model is a useful methodology for longitudinal data, but the linear structure restricts the model ability to handle the data from real world. This paper proposes a RE-BET algorithm and its deformation named RE-BEBT. The algorithm used tree-based method to estimate the fixed effects of mixed effects model so that it could select important variables automatically and could discover the relationship between variables. In order to apply model to small sample size data, a Bayesian method based on Dirichlet process prior was used to estimate the random effects of mixed effects model. We applied the RE-BET algorithm to the corrosion data of low alloy steel and carbon steel in Seawater and compared the result with other algorithms or experimental data, showing that the RE-BET algorithm is feasible and effective.