Upcoming Webinar: 𝗦𝘂𝗿𝗽𝗿𝗶𝘀𝗲𝘀 𝗶𝗻 𝗧𝗶𝗺𝗲 𝗦𝗲𝗿𝗶𝗲𝘀 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀
𝗠𝗼𝗻𝗱𝗮𝘆, 𝗢𝗰𝘁 𝟮𝟲, 𝟮𝟬𝟮𝟲, 𝟲:𝟬𝟬 𝗣𝗠 𝘁𝗼 𝟳:𝟯𝟬 𝗣𝗠 𝗘𝗮𝘀𝘁𝗲𝗿𝗻
Speaker: 𝗥𝗼𝗯 𝗝 𝗛𝘆𝗻𝗱𝗺𝗮𝗻, Vice-Chancellor's Distinguished Professor of Statistics, Department of Econometrics and Business Statistics, Monash University
Register: https://events.teams.microsoft.com/event/cab77726-7373-4172-9079-7710c45db522@17f1a87e-2a25-4eaa-b9df-9d439034b080?source=copyLinkLegacyShareEventDialog
Agenda:
6:00–7:00 PM | Presentation and technical Q&A
7:00–7:30 PM | Interview and general Q&A
This event will be recorded (https://www.youtube.com/@TimeSeriesConnect)
Abstract
I will present a statistical framework for identifying anomalies in three time series settings: unusual observations within a single historical series, unusual series within a large collection, and real-time surveillance of incoming data streams. In each case, anomalies are identified using a probabilistic approach based on “surprisal values” - equal to minus the log (conditional) density of each observation - with extreme value theory used to model the tail of the surprisal distribution and avoid strong parametric assumptions. The methods will be illustrated using the {weird} package for R, with examples including French and US mortality rates, and pharmaceutical sales.
For details about upcoming webinars, please check - https://yaozheng-stat.github.io/time-series-connect/
For more information, contact: Prof. Yao Zheng at yao.zheng@uconn.edu