Consistent and powerful graph-based change-point test for high-dimensional data.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 28356520.
- Also identified by DOI 10.1073/pnas.1702654114 and PMC identifier 5393215.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
A change-point detection is proposed by using a Bayesian-type statistic based on the shortest Hamiltonian path, and the change-point is estimated by using ratio cut. A permutation procedure is applied to approximate the significance of Bayesian-type statistics. The change-point test is proven to be consistent, and an error probability in change-point estimation is provided. The test is very powerful against alternatives with a shift in variance and is accurate in change-point estimation, as shown in simulation studies. Its applicability in tracking cell division is illustrated.