Factor-Augmented Clustering Tree
Calculate Split Statistic
Correlation-Based Clustering Tree
Factor-Augmented Clustering Tree
Find Best Split Using Correlation Criterion
Find the Best Split for a Node
Generate Synthetic Group Factor Model Data
Plot a FACT Tree Object
Print a FACT Tree Object
Implements the Factor-Augmented Clustering Tree (FACT) algorithm for clustering time series data. The method constructs a classification tree where splits are determined by covariates, and the splitting criterion is based on a group factor model representation of the time series within each node. Both threshold-based and permutation-based tests are supported for splitting decisions, with an option for parallel computation. For methodological details, see Hu, Li, Luo, and Wang (2025, in preparation), Factor-Augmented Clustering Tree for Time Series.