Identification of Changes in Mean with Regression Trees: An Application to Market Research
提出一种基于回归树的计算高效方法，用于在未知时间点发现多个结构断点，模拟显示该方法在长序列中表现良好，并应用于1958-1963年Crest牙膏市场份额数据。
In this article we present a computationally efficient method for finding multiple structural breaks at unknown dates based on regression trees. We outline the procedure and present the results of a simulation study to assess the performance of the method and to compare it with the procedure proposed by Bai and Perron. We find the tree-based method performs well in long series which are impractical to analyze with current methods. We apply these methods plus the CUSUM test to the market share of Crest toothpaste between 1958 and 1963.