New dynamic models simplify identification of multivariate time series patterns.
A new type of model for analyzing time series data has been developed. It is based on Factor Analysis, a method commonly used in Statistics. These models help identify patterns in data without assuming causal relationships between variables. This approach offers a simple way to understand complex multivariate time series data without making unwarranted assumptions about cause and effect.