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The aim of this subject is to provide students with grounding in mathematical and statistical modelling techniques that are of particular relevance to actuarial work, including methods of estimating mortality rates and assessing their adherence to data and smoothness, as well as techniques for mortality projections. Also, elementary principles of machine learning are covered, with applications to mortality modelling.
Intended learning outcomes
On completion of this subject, students should be able to:
- Apply the principles of actuarial modelling
- Demonstrate how to estimate transition intensities depending on age, exactly or using the census approximation
- Test crude estimates for consistency with a standard table or a set of graduated estimates, and illustrate the process of graduation
- Outline the approaches to forecasting mortality rates, including the Lee-Carter, age-period-cohort and p-spline regression models, and, using a computer package, apply these models to a mortality dataset
- Appraise and apply elementary principles of machine learning
- Employ prerequisite mathematical and statistical concepts in solving problems on the above topics
- High level of development: written communication; problem solving; statistical reasoning; application of theory to practice; use of computer software.
Last updated: 11 December 2019