Extreme Value Statistics
Date:
02/12/2020 - 03/12/2020
Organised by:
Royal Statistical Society
Presenter:
Dr Janet Heffernan and Dr Harry Southworth
Level:
Advanced (specialised prior knowledge)
Contact:
Description:
Course Outline
Most statistical methods are aimed at characterizing expected values, but in many settings it is the unexpected values, the extremes or outliers, that are of interest - e.g. extreme weather events, rare drug toxicities, or extreme movements in financial markets. This is an introductory course in Extreme Value Statistics, focusing mostly on univariate methods but including some multivariate modelling topics. We will cover the theory and associated statistical methods which form a cornerstone of natural hazard risk planning and engineering design safety, and which enable extrapolation to levels beyond those already observed in a dataset. We describe current best practice and step-by-step implementation of methods for calculating high quantiles and associated uncertainties. We address topical challenges arising from non-stationarity in processes. The ideas are illustrated throughout by using detailed worked examples from environmental risk assessment, financial and clinical-safety applications. All of the topics covered are accompanied by hands-on computer tutorials in R, so that participants will carry out themselves a complete set of worked examples throughout the course.
Learning Outcomes
By attending this course, attendees can hope to gain the following:
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Solid understanding of the theory and best practice to support their own independent use of Extreme Value Statistics;
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Detailed step-by-step methods for systematic Extreme Value Modelling and computation of high quantiles and extreme values;
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Practical experience of using state of the art software to carry out Extreme Value Analysis for themselves, with a complete set of worked examples and accompanying code.
Topics Covered
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Motivating examples
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Introduction to univariate Extreme Value Theory
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Modelling process maxima and threshold excesses
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Using diagnostic tools for efficient threshold selection
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Addressing non-stationarity by using covariates in EV models
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Dealing with serial dependence in data
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Extensive worked examples from environmental hazard, finance, offshore and clinical trials settings
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Modelling multivariate extreme values
Target Audience
As well as statisticians and quantitative researchers these may include but are not limited to structural design engineers, metocean scientists, offshore engineers, re/insurance natural peril defence planners, environmental consultancies, pharmaceutical companies, clinical trial safety regulators, financial risk managers.
Cost:
Ranges from £588-£816 inc. VAT
Website and registration:
Region:
Greater London
Keywords:
Statistical Theory and Methods of Inference
Related publications and presentations:
Statistical Theory and Methods of Inference