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Overview

This course presents General interference theory based on maximum likelihood and on Bayes methods is reviewed. Estimation, confidence set construction and hypothesis testing are discussed within decision-theoretic framework. Computationally intensive methods such as bootstrap are discussed and are compared to asymptotic approximations such as saddlepoint and empirical likelihood.Pre-requisites: 24 units of level III mathematics or a degree in a numerate discipline or permission of the Head of Department.Note: Course not offered every year - contact the School for more information.
Study Level

Postgraduate

Offering Terms

Term 1

Campus

Kensington

Delivery Mode

Fully on-site

Indicative contact hours

4

Course Outline

To access course outline, please visit:

Fees

Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)

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