{"success":1,"msg":"","color":"rgb(28, 35, 49)","title":"<b>Regime switching models for directional and linear observations<\/b>","description":"webinar","title2":"","start":"2021-03-12 13:00","end":"2021-03-12 14:30","responsable":"<a href=\"mailto:vladimir.rodriguez@itam.mx\">Carlos Vladimir Rodriguez-Caballero <i class=\"fa fa-envelope\"><\/i><\/a>","speaker":"Professor Andrew Harvey, University of Cambridge","id":"28","type":"webinar","timezone":"America\/Mexico_City","activity":"Zoom link:\r\nhttps:\/\/itam.zoom.us\/j\/98754360113?pwd=MU1ySDlxV2E4MDNnRTRobkJlSUlMdz09\r\n\r\nMeeting ID: 987 5436 0113\r\nAccess code: 007793\r\n","abstract":"The score-driven approach to time series modeling provides a solution to the problem of modeling circular data and it can also be used to model switching regimes with intra-regime dynamics. Furthermore,\r\nit enables a dynamic model to be fitted to a linear and a circular variable when the joint distribution is a cylinder. The viability of the new method is illustrated by estimating a model with dynamic switching\r\nand dynamic location and\/or scale in each regime to hourly data on wind direction and speed in Galicia, north-west Spain"}