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Ed Cohen - Wavelet spectra for multivariate point processes.

Dates:26 January 2022
Times:14:00 - 15:00
What is it:Seminar
Organiser:Department of Mathematics
Who is it for:University staff, External researchers, Current University students
Speaker:Ed Cohen
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  • Department of Mathematics

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  • In category "Seminar"
  • In group "(Maths) Probability and statistics"
  • By Department of Mathematics

Ed Cohen, Senior Lecturer in Statistics at the Department of Mathematics, Imperial College London is our speaker for the Statistics seminar series.

Title: Wavelet spectra for multivariate point processes.

Abstract: Humans are harvesting vast event datasets that manifest themselves as a list of times at which particular events of interest occur. Often these are multivariate in nature, with events being of different types or arriving on multiple channels. A key question is to what extent the data-generating point processes are correlated and to track non-stationary correlation structure. Wavelets provide the flexibility to analyse stochastic processes at different scales in a time-localised manner and have had a profound impact in statistics, particularly in time series analysis. Here, we apply them to multivariate point processes as a means of detecting and analysing unknown non-stationarity, both within and across component processes. To provide statistical tractability, a temporally smoothed wavelet periodogram is developed and distributional results are extended to wavelet coherence; a time-scale measure of inter-process correlation. This statistical framework is further used to construct a test for stationarity in multivariate point-processes. The methodology is applied to neural spike train data, where it is shown to detect and characterise time-varying dependency patterns.

Speaker

Ed Cohen

Organisation: Imperial College London

  • https://www.imperial.ac.uk/people/e.cohen

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Zoom link: https://zoom.us/j/92947173491

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Olatunji Johnson

olatunji.johnson@manchester.ac.uk

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