Non Linear Mixed Models for Predictive Modelling in Actuarial Science
Chapter 16 in Predictive Modeling Applications in Actuarial Science, Vol. 1 Predictive Modeling Techniques. (Editors E.W. Frees, R.A. Derrig, G. G. Meyers). Cambridge University Press, pages 566-601. (With peer review)
27 Pages Posted: 20 Jan 2014 Last revised: 17 May 2017
Date Written: November 24, 2013
We start with a discussion of model families for multilevel data outside the Gaussian framework. We continue with Generalized Linear Mixed Models ([GLMMs]), which enable generalized linear modeling with multilevel data. The Chapter includes highlights of estimation techniques for GLMMs, in the frequentist as well as Bayesian context. We continue with a discussion of Non Linear Mixed Models ([NLMMs]). The Chapter concludes with an extensive case study using a selection of R packages for GLMMs.
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