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Statistics > Methodology
Title: Tests for partial correlation between repeatedly observed nonstationary nonlinear timeseries
(Submitted on 13 Jun 2021 (v1), last revised 24 Apr 2024 (this version, v2))
Abstract: 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.
Submission history
From: Kenneth Harris [view email][v1] Sun, 13 Jun 2021 21:35:10 GMT (782kb)
[v2] Wed, 24 Apr 2024 16:39:53 GMT (969kb)
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