Factor-Augmented Clustering Tree
Description
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.