Package: changepointGA 0.1.0

changepointGA: Changepoint Detection via Modified Genetic Algorithm

The changepointGA R package implements genetic algorithms (GAs) to perform changepoint analysis in time series data. The pacakge also includes the extended island version of GAs describled in the paper of Lu, Lund and Lee (2010, <doi:10.1214/09-AOAS289>). By mimicking the principles of natural selection and evolution, GAs offer a powerful stochastic search technique for addressing combinatorial optimization problems. In changepointGA, each chromosome represents changepoint configurations, including the number and locations of changepoints, hyperparameters, and model parameters. The package uses genetic operators—selection, crossover, and mutation—to iteratively improve solutions based on fitness. Key features of changepointGA include encoding changepoint configurations in an integer format, enabling dynamic and simultaneous estimation of model hyperparameters, changepoint configurations, and associated parameters. This detail algorithm implementation can be found in the pacakge associated vignettes and the paper of Mo (2024, <doi:arXiv:2410.15571>).

Authors:Mo Li [aut, cre]