Linear Mixed Models for Predictive Modelling in Actuarial Science

We give a general discussion of linear mixed models and continue with illustrating specific actuarial applications of this type of models. Technical details on linear mixed models follow: model assumptions, specifications, estimation techniques and methods of inference. We include three worked out examples with the R lme4 package and use ggplot2 for the graphs. Full code is available from the book project's web page

MoreLess

Year of publication:	2017
Authors:	Antonio, Katrien
Other Persons:	Zhang, Yanwei (contributor)
Publisher:	[2017]: [S.l.] : SSRN
Subject:	Prognoseverfahren \| Forecasting model \| Versicherungsmathematik \| Actuarial mathematics \| Theorie \| Theory

Extent:	1 Online-Ressource (36 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	In: Chapter 8 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 266-312 Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments November 28, 2013 erstellt
Other identifiers:	10.2139/ssrn.2381505 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://ebvufind01.dmz1.zbw.eu/10012973588