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Graduation by dynamic regression methods

Published online by Cambridge University Press:  20 April 2012

R. J. Verrall
Affiliation:
The City University, London

Abstract

This paper extends the theory of graduation by parametric formulae to include dynamic estimation methods. This is an application of the Kalman filter and allows the parameters of the curve fitted to vary with age. The amount of variation is determined by the amount of smoothing required, and the method can be regarded as a combination of curve fitting and sequential smoothing, each of which has been used separately for performing graduations. In practice, a dynamic straight line can always be used for the graduation and the method has a sensible logical interpretation.

Type
Research Article
Copyright
Copyright © Institute and Faculty of Actuaries 1993

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