Causal Vector Autoregression

  • Instructor: Marianna Bolla
  • Contact:
  • Prerequisites:some maturity in probability, statistics, and matrix analysis. Knowledge of stochastic processes, time series, and graphical models is not necessary, I will give the basics in the first lesson and some definitions below. Applicants having good programming skills (e.g. in Python) and ready to implement matrix decomposition algorithms, are welcome.
  • Qualifying problems: Do two of the three problems described here

Description

The task is to test a novel model connecting causality and autoregession in multivariate time series. Above completing the theoretical proofs (I have done parts of those) the research also includes technical issues: implementation an algorithm using block matrix techniques and application to simulated and real life data.

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