学术讲座

讲座预告:Janine B Illian:Realistically complex spatial models - communication and accessibility

发布者:沈彤发布时间:2024-03-19浏览次数:10

报告主题Realistically complex spatial models - communication and accessibility

报 告 人Janine B Illian(格拉斯哥大学)

报告时间202432110:00-11:00

报告地点:文波楼威尼斯9499登录入口401会议室

摘  要In this talk we will briefly discuss the capabilities of the software inlabru, but we will put a strong emphasis on exploring the need for – as well as approaches to – communicating the methodology well to potential users. We use the example of the software package inlabru and the associated broad range of statistical methodology to outline an approach to addressing the issue of juggling the right balance between treating an approach as a black box and explaining the every single mathematical detail of a modelling approach. In particular, we will discuss our recent thoughts on and attempts to finding a level of explanation that summarises what the methodology does through focusing on the role of the different model components and how they are reflected in the syntax of the package. 

报告人简介:Janine B Illian is the Chair in Statistical Sciences and Head of Statistics at Glasgow University. Her work focuses on developing realistically complex spatial and spatio-temporal modelling methodology. She is the author of “Statistical Analysis and Modelling of Spatial Point Patterns” (Wiley, 2008), which has been a standard work on point process modelling since its publication. Her research profile focuses on the development of modern, statistical methodology that is computationally feasible, relevant to and usable by end-users, especially in the context of integrated nested Laplace approximation, INLA. She has taken complex spatial modelling approaches from the theoretical literature into the real world and is encouraging statistical development by fostering strong relationships with the user community, in particular in the context of ecology. Her EPSRC funded work has led to the development of the software package inlabru that features increased flexibility of modelling approaches and observation processes combined with user-friendly implementations.