Mixed-effects random forest for clustered data 论文

2012Journal of Statistical Computation and Simulation引用 242
Bayesian Methods and Mixture ModelsStatistical Methods and InferenceStatistical Methods and Bayesian Inference

摘要

This paper presents an extension of the random forest (RF) method to the case of clustered data. The proposed ‘mixed-effects random forest’ (MERF) is implemented using a standard RF algorithm within the framework of the expectation–maximization algorithm. Simulation results show that the proposed MERF method provides substantial improvements over standard RF when the random effects are non-negligible. The use of the method is illustrated to predict the first-week box office revenues of movies.