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PRODID:-//Biomedical Mathematics Group - ECPv6.15.20//NONSGML v1.0//EN
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METHOD:PUBLISH
X-WR-CALNAME:Biomedical Mathematics Group
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
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BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20210101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220408T130000
DTEND;TZID=Asia/Seoul:20220408T140000
DTSTAMP:20260424T220452
CREATED:20220407T190000Z
LAST-MODIFIED:20220405T042614Z
UID:5870-1649422800-1649426400@www.ibs.re.kr
SUMMARY:RTransferEntropy — Quantifying information flow between different time series using effective transfer entropy
DESCRIPTION:We will discuss about “RTransferEntropy — Quantifying information flow between different time series using effective transfer entropy”\, Behrendt et al.\, SoftwareX\, 2019 \nAbstract: This paper shows how to quantify and test for the information flow between two time series with Shannon transfer entropy and Rényi transfer entropy using the R package RTransferEntropy. We discuss the methodology\, the bias correction applied to calculate effective transfer entropy and outline how to conduct statistical inference. Furthermore\, we describe the package in detail and demonstrate its functionality by means of several simulated processes and present an application to financial time series.
URL:https://www.ibs.re.kr/bimag/event/2022-04-08-jc/
LOCATION:B378 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
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