Title: Nonparametric estimation of mean and dispersion functions in extended generalized linear models
Authors: Gijbels, Irène ×
Prosdocimi, Ilaria
Claeskens, Gerda #
Issue Date: Nov-2010
Series Title: Test vol:19 issue:3 pages:580-608
Abstract: In this paper the interest is in regression analysis for data that show possibly overdispersion or underdispersion. The starting point for modeling are generalized linear models in which we no longer admit a linear form for the mean regression function, but allow it to be any smooth function of the covariate(s). In view of analyzing overdispersed or underdispersed data, we additionally bring in an unknown dispersion function. The mean regression function and the dispersion function are then estimated using P-splines with difference type of penalty to prevent from overfitting.
We discuss two approaches: one based on an extended quasi-likelihood idea and one based on a pseudo-likelihood approach. The choices of smoothing parameters and implementation issues are discussed. The performance of the estimation method is investigated via simulations and its use is illustrated on several data, including continuous data, counts and proportions.
ISSN: 1133-0686
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Statistics Section
Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
Leuven Statistics Research Centre (LStat)
× corresponding author
# (joint) last author

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