Gaussian processes for time series with lead-lag effects with applications to biology data.

ABSTRACT: Investigating the relationship, particularly the lead-lag effect, between time series is a common question across various disciplines, especially when uncovering biological processes. However, analyzing time series presents several challenges. Firstly, due to technical reasons, the time points at which observations are made are not at uniform intervals. Secondly, some lead-lag effects are transient, necessitating time-lag estimation based on a limited number of time points. Thirdly, external factors also impact these time series, requiring a similarity metric to assess the lead-lag relationship. To counter these issues, we introduce a model grounded in the Gaussian process, affording the flexibility to estimate lead-lag effects for irregular time series. In addition, our method outputs dis

SUBMITTER: Mu W 

PROVIDER: S-EPMC11704948 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature