Lecture

Time Series: Multi-Tapering and Parametric Estimation

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In course

MATH-342: Time series

A first course in statistical time series analysis and applications. ...

Description

This lecture covers the concepts of Multi-Tapering and Parametric Estimation in Time Series analysis. Multi-Tapering involves using a set of tapers to estimate the spectral density, while Parametric Estimation focuses on fitting AR models to time series data. The instructor explains the spectral estimation process, Yule-Walker method, and the importance of AR models in approximating continuous spectra. The lecture also delves into the Whittle Likelihood method for estimating noise variance and the use of Discrete Fourier Transform in analyzing time series data.

Instructor

Sofia Charlotta Olhede

I am a professor of Statistics at EPFL. I did my PhD in Mathematics at Imperial College London, and graduated in 2003. I was an assistant professor (lecturer) at Imperial College London 2002-2006, and an associate professor (senior lecturer) 2006-2007. In 2007 I moved to University College London and became a full professor. I moved to EPFL in 2019, and in 2018 I became an Institute of Mathematical Statistics Fellow with citation “For seminal contributions to the theory and application of large and heteroge

Official source

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