Causal Discovery from Temporally Aggregated Time Series.
Mingming Gong, Kun Zhang, Bernhard Schölkopf, Clark Glymour, Dacheng Tao · PubMed · 2017
is known. Assuming the time series at the causal frequency follows a vector autoregressive (VAR) model, we show that the causal structure at the causal frequency is identifiable from aggregated time series if the noise terms are independent and non-Gaussian and some other technical conditions hold. We then present an estimation method based on non-Gaussian state-space modeling and evaluate its performance on both synthetic and real data.