2021/06/13 by Kenneth D. Harris, Harris, Kenneth D., Yuan, Alex E.
Engineering · #Advanced Control Systems Optimization #Applications (stat.AP) #Control Systems and Identification #FOS: Biological sciences #FOS: Computer and information sciences #Fault Detection and Control Systems #Methodology (stat.ME) #Neurons and Cognition (q-bio.NC)
paper · pdf · doi:10.48550/arxiv.2106.07096
openalex publication_date 2021/06/13 · openalex created_date 2021/06/22 · openalex updated_date 2026/07/28
We describe two families of statistical tests to detect partial correlation in vectorial timeseries. The tests measure whether an observed timeseries Y can be predicted from a second series X, even after accounting for a third series Z which may correlate with X. They do not make any assumptions on the nature of these timeseries, such as stationarity or linearity, but they do require that multiple statistically independent recordings of the 3 series are available. Intuitively, the tests work by asking if the series Y recorded on one experiment can be better predicted from X recorded on the same experiment than on a different experiment, after accounting for the prediction from Z recorded on both experiments.