BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Lancaster University Faculty of Science and Technology//NONSGML v1.0//EN
BEGIN:VTIMEZONE
TZID:/Europe/London
X-LIC-LOCATION:Europe/London
BEGIN:DAYLIGHT
TZOFFSETFROM:+0000
TZOFFSETTO:+0100
TZNAME:BST
DTSTART:19700329T010000
RRULE:FREQ=YEARLY;INTERVAL=1;BYDAY=-1SU;BYMONTH=3
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0100
TZOFFSETTO:+0000
TZNAME:GMT
DTSTART:19701025T020000
RRULE:FREQ=YEARLY;INTERVAL=1;BYDAY=-1SU;BYMONTH=10
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
UID:1246
SUMMARY:Statistics Seminar: Marina Knight
DESCRIPTION:Hurst exponent estimation for long-memory processes using wavelet lifting\n\nReliable estimation of long-range dependence (LRD) parameters, such as the Hurst\nexponent, is a well studied problem in the statistical literature. However, when the observed time series presents missingness or is naturally irregularly sampled, current literature is sparse with most approaches requiring heavy modifications. \n\nIn this talk I shall present a technique for estimating the Hurst exponent of an LRD time series, that naturally deals with the time domain irregularity. The method is based on a flexible wavelet transform built by means of the lifting scheme and we demonstrate through simulation its performance.
DTSTART:20131025T140000
DTEND:20131025T150000
LOCATION:A54, Postgraduate Statistics Centre Lecture Theatre
END:VEVENT
END:VCALENDAR