BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Memento EPFL//
BEGIN:VEVENT
SUMMARY:Spectral analysis and stationarity tests for time series with miss
 ing values
DTSTART:20200619T160000
DTEND:20200619T173000
DTSTAMP:20260510T020842Z
UID:d07f2d4acb5f410aa2c407c77ebed4193f11fe2fb0047f8e01517a18
CATEGORIES:Conferences - Seminars
DESCRIPTION:Matthew Nunes\, University of Bath\nQuadratic forms are ubiqui
 tous and intensively studied in statistics\, often in time series analysis
 \, including those formed out of wavelet coefficients. Most wavelet transf
 orm methods in statistics assume regularly-spaced and complete data\, whic
 h does not always occur in real problems where observations are sometimes 
 missing\, resulting in a non-regular design. To handle this\, we use secon
 d-generation wavelets (lifting) which are explicitly designed to handle no
 n-regular situations: we introduce a new estimator of the second-generatio
 n wavelet spectrum and show that it is consistent in the case of an underl
 ying locally stationary wavelet process where the observations are subject
  to a random drop-out model. Our new estimator is then used to construct a
  new lifting-based stationarity test with significance assessed by the boo
 tstrap. The simulation study shows excellent results\, not only on time se
 ries with missing observations\, but in the complete data settings too.
LOCATION:zoom https://epfl.zoom.us/j/97961247146
STATUS:CONFIRMED
END:VEVENT
END:VCALENDAR