The Joint Applied Mathematics and Statistics Seminar continues.
Date: Thursday, February 04
Place and time: Quantum, Room M2, 12:30-14:00
Title: Some independent component analysis tools for time series data
Speaker: Markus Matilainen
Blind Source Separation models are semiparametric models, where the components of an observed p-variate vector x are assumed to be linear combinations of the components of some unobserved p-variate source vector z. In time series context, the observations are assumed to be from a p-variate time series. We focus on independent component analysis (ICA), which is a special case of Blind Source Separation. We introduce extensions of classic FOBI (Fourth Order Blind Identification) and JADE (Joint Approximate Diagonalization of Eigen-matrices) estimates and a variant of SOBI (Second Order Blind Identification) estimate for multivariate time series, with a special focus on time series with stochastic volatility. In the end we present some results from a simulation study.
All interested are warmly welcome!