- 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.