University of Cambridge > Talks.cam > Statistics > Analysis and Forecasting of Locally Stationary Time Series

  Browse A-Z

Log in

University Account External (via Google)

🔐 Log In

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

ℹī¸ Information

Analysis and Forecasting of Locally Stationary Time Series

Download to your calendar using vCal

If you have a question about this talk, please contact .

Faced with a new time series a statistician has many questions to ask. What kind of models are appropriate? Is the sampling rate appropriate? Is the series stationary? Are nonlinear models appropriate? How can I produce good forecasts? This talk advertises a collection of tools that can provide answers or partial answers to some of these questions in situations where it is suspected that the underlying time series is not stationary. We shall summarize some of the theory underlying these new methods and also demonstrate their performance in simulated situations. Finally, we will show these tools in action on some time series recorded on the economy and from the field of wind energy.

This talk is part of the Statistics series.

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

Centre for Mathematical Sciences, Meeting Room 9 (back building, ground floor) https://zoom.us/j/96800255636 In person in the Max Perutz Lecture Theatre (CB2 0QH) and via Zoom link https://mrc-lmb-cam-ac-uk.zoom.us/j/92311841585?pwd=auhAdp8eTD8Ca0xGZpaNlZrChEcHAr.1

Other talks

Director's Briefing Christopher Cowie on the epistemology of assessing biosignature claims Scientific Steering Committee meeting Title to be confirmed Organiser's Welcome Optimal metric and approximation of free boundary minimal surfaces
 

Š 2006-2025 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity