Analysing Data Summarised as Distributions - DARE Symposium 2024 скачать в хорошем качестве

Analysing Data Summarised as Distributions - DARE Symposium 2024

Keynote by Professor Scott Sisson - DARE Symposium, February 2024 Abstract: Much of the research that is generated by Universities and Research Centres is driven by PhD students. In this presentation I will showcase some of the work done by some of my recent PhD students as part of their thesis. These vignettes will focus on research in “symbolic data analysis”, which aims to perform statistical analyses for data that have been summarised into distributional form, such as random rectangles, random histograms, and other distributions. I will illustrate the ideas behind each project through both simulation studies and real-world environmental applications. Prof Scott Sisson: Scott is the Director of the UNSW Data Science Hub (uDASH) and Professor in Statistics at UNSW. uDASH is a major strategic initiative of UNSW Science, which cultivates and promotes foundational and applied research in Data Science across a range of issues and industries. The Hub provides a world-class environment, with access to state-of-the-art data visualisation and computing facilities and enables the creation, development and deployment of transformative data-driven decision-making tools that help address current and future societal challenges. As Professor of Statistics at UNSW, Scott is internationally recognised for his work in computational and Bayesian statistics, particularly for developing inferential techniques for computationally intractable models and challenging data. He has been awarded the P.A.P. Moran Medal (Australian Academy of Science), the G. N. Alexander Medal (Engineers Australia) and the J. G. Russell Award (Australian Academy of Science). Scott is a former Deputy Director of the ARC Centre of Excellence for Mathematical and Statistical Frontiers, and ARC Future Fellow. Recently he was President of the Statistical Society of Australia, and Head of Statistics at UNSW.