Skip to main content
padlock icon - secure page this page is secure

Smooth estimation of mean and dispersion function in extended generalized additive models with application to Italian induced abortion data

Buy Article:

$61.00 + tax (Refund Policy)

We analyse data on abortion rate (AR) in Italy with a particular focus on different behaviours in different regions in Italy. The aim is to try to reveal the relationship between the AR and several covariates that describe in some way the modernity of the region and the condition of the women there. The data are mostly underdispersed and the degree of underdispersion also varies with the covariates. To analyse these data, recent techniques for flexible modelling of a mean and dispersion function in a double exponential family framework are further developed now in a generalized additive model context for dealing with the multivariate set-up. The appealing unified framework and approach even allow to semi-parametric modelling of the covariates without any additional efforts. The methodology is illustrated on ozone-level data and leads to interesting findings in the Italian abortion data.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: P-splines; dispersion function; heteroscedasticity; mean function; nonparametric estimation; overdispersion; underdispersion

Document Type: Research Article

Affiliations: Department of Mathematics, and Leuven Statistics Research Center (LStat),Katholieke Universiteit Leuven, Celestijnenlaan 200B, Box 2400B-3001Leuven (Heverlee), Belgium

Publication date: November 1, 2011

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more