Module Specifications.
Current Academic Year 2024 - 2025
All Module information is indicative, and this portal is an interim interface pending the full upgrade of Coursebuilder and subsequent integration to the new DCU Student Information System (DCU Key).
As such, this is a point in time view of data which will be refreshed periodically. Some fields/data may not yet be available pending the completion of the full Coursebuilder upgrade and integration project. We will post status updates as they become available. Thank you for your patience and understanding.
Date posted: September 2024
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Description MS338 aims to provide students with a grounding in survival models and their application in modelling mortality and morbidity for actuarial applications. The module covers the theory of survival models and estimation methods for mortality and morbidity rates. Mortality graduation and projection methods are introduced with practical application of the methods implemented using R. | |||||||||||||||||||||||||||||||||||||||||||
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Learning Outcomes 1. Define models of mortality and life expectancy. 2. Estimate survival models using non parametric and semi-parametric methods. 3. Estimate transition intensities for Markov mortality and morbidity models. 4. Graduate mortality data for actuarial applications. 5. Understand and implement simple mortality projection methods. | |||||||||||||||||||||||||||||||||||||||||||
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
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Indicative Content and Learning Activities
Concept of survival modellingLifetime and failure time; distributions and density functions of lifetime, survival function and the force of mortality and probabilities; laws of mortality; curtate and complete future lifetimes [CS2 – 4.1]Non-parametric estimation procedures for lifetime distributionsEstimation methodologies - Kaplan-Meier estimate; Nelson-Aalen estimate; Cox PH model. [CS2 – 4.2]Maximum likelihood estimators for and estimation of the transition intensities in models of transfers between statesDerive the Kolmogorov equations for a Markov Jump Processes / General Markov Model and solve Kolmogorov equations to obtain explicit expressions for the key probabilities associated with the process. [CS2 – 4.3, 4.4]Methods of Actuarial GraduationStatistical tests for comparison with a standard table; reasons for graduation and desirable properties; test for smoothness; the process of graduation using different method e.g., spline functions; comparison of crude and graduated estimates; allowance for duplicate policies; and comparison of crude estimates with a standard table or with graduated rates. [CS2 – 4.5]Mortality ProjectionsMortality improvement trends; simple mortality projections methods – Lee-Carter, APC and P-spline methods; implementation of projection models using R. [CS2 – 4.6] | |||||||||||||||||||||||||||||||||||||||||||
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Indicative Reading List
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Other Resources None | |||||||||||||||||||||||||||||||||||||||||||