Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/11187
Title: | Double hierarchical generalized linear models - Discussion | Authors: | MacKenzie, G Firth, D Rigby, RA Stasinopoulos, DM Payne, R Senn, S Browne, WJ Goldstein, H del Castillo, J Feddag, M Ha, ID Kim, D Oh, HS LAWSON, Andrew Piegorsch, WW MOLENBERGHS, Geert VERBEKE, Geert Yau, KKW Yu, KM Mamon, R Zhang, ZZ |
Issue Date: | 2006 | Publisher: | BLACKWELL PUBLISHING | Source: | JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 55(2). p. 167-185 | Abstract: | We propose a class of double hierarchical generalized linear models in which random effects can be specified for both the mean and dispersion. Heteroscedasticity between clusters can be modelled by introducing random effects in the dispersion model, as is heterogeneity between clusters in the mean model. This class will, among othr things, enable models with heavy-tailed distributions to be explored, providing robust estimation against outliers. The h-likelihood provides a unified framework for this new class of models and gives a single algorithm for fitting all members of the class. This algorithm does not require quadrature or prior probabilities. | Notes: | Univ Limerick, Limerick, Ireland. Univ Warwick, Coventry CV4 7AL, W Midlands, England. London Metropolitan Univ, London, England. Rothamsted Res, Harpenden, Herts, England. Univ Glasgow, Glasgow G12 8QQ, Lanark, Scotland. Univ Nottingham, Nottingham NG7 2RD, England. Univ Bristol, Bristol BS8 1TH, Avon, England. Univ Autonoma Barcelona, E-08193 Barcelona, Spain. Daegu Haany Univ, Gyongsan, South Korea. Hongik Univ, Seoul, South Korea. Univ S Carolina, Columbia, SC 29208 USA. Hasselt Univ, Diepenbeek, Belgium. Katholieke Univ Leuven, Louvain, Belgium. City Univ Hong Kong, Hong Kong, Hong Kong, Peoples R China. Brunel Univ, Uxbridge UB8 3PH, Middx, England. Beijing Univ Technol, Beijing, Peoples R China. | Document URI: | http://hdl.handle.net/1942/11187 | ISSN: | 0035-9254 | e-ISSN: | 1467-9876 | ISI #: | 000235696600002 | Category: | A2 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.