Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-26T00:27:45.186Z Has data issue: false hasContentIssue false

Redefining the deviance objective for generalised linear models ‐ Abstract of the London discussion

Published online by Cambridge University Press:  21 January 2013

Abstract

This abstract relates to the following paper:

LovickA.C. and LeeP.K.W.Redefining the deviance objective for generalised linear models ‐ Abstract of the London discussionBritish Actuarial Journal, doi:10.1017/S1357321712000190

Type
Sessional meetings: papers and abstracts of discussions
Copyright
Copyright © Institute and Faculty of Actuaries 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Additional References

Breiman, L., Friedman, J.H. (1994). Predicting Multivariate Responses in Multiple Linear Regression. Dept. For Statistics Stanford University, Technical Report No. 111.Google Scholar
Copas, J.B. (1987). Cross-Validation Shrinkage of Regression Parameters. Journal of the Royal Statistical Society Series B, 49(2), 175183.Google Scholar
Klinker, F. (2011). Generalized Linear Mix Models for Ratemaking: A Means of Introducing Credibility into a Generalized Linear Model Setting. Casualty Actuarial Society E-Forum, Winter, Vol. 2.Google Scholar
Tibshirani, R. (1996). Regression Shrinkage and Selection via the Lasso. Journal of the Royal Statistical Society Series B, 58(1), 267288.Google Scholar
Wood, S.N. (2003). Thin Plate regression Splines. Journal of the Royal Statistical Society Series B, 65(1), 95114.Google Scholar