We propose a class of additive generalized linear array models (GLAMs) which facilitate the classification and comparison of mortality tables. Different mortality tables are modelled in terms of their distances (gaps) from a reference table. These gaps are smooth functions of age and/or time and provide a simple graphical summary of the differences between tables. In the paper we describe the models, discuss their computational demands and their resolution with GLAM. We present the results, largely graphical, of applying our methods to various mortality tables taken from the Human Mortality Database and from the Continuous Mortality Investigation Bureau.
|Title of host publication||Proceedings of International Workshop on Statistical Modelling|
|Subtitle of host publication||July 5-9, 2010 Glasgow|
|Publication status||Published - 2010|