Lecture

Multivariate Time Series and Spectral Representation

Description

This lecture delves into the analysis of multivariate time series, focusing on spectral representation and estimation techniques. The instructor explains the concept of p-variate time series, spectral density functions, and cross-spectral densities. The lecture covers the estimation of auto-covariance and spectral density functions, emphasizing the importance of second-order stationarity. Various spectral estimation methods, including periodogram and tapering, are discussed to improve the accuracy of spectral estimators.

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