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

I. Gijbels, I. Prosdocimi

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)2391-2411
Number of pages21
JournalJournal of Applied Statistics
Volume38
Issue number11
DOIs
Publication statusPublished - Nov 2011

Fingerprint

Generalized Additive Models
Covariates
Underdispersion
Parametric Modeling
Ozone
Exponential Family
Abortion
Induced abortion
Generalized additive models
Vary
Methodology
Modeling
Italy

Keywords

  • Dispersion function
  • Heteroscedasticity
  • Mean function
  • Nonparametric estimation
  • Overdispersion
  • P-splines
  • Underdispersion

Cite this

Smooth estimation of mean and dispersion function in extended generalized additive models with application to italian induced abortion data. / Gijbels, I.; Prosdocimi, I.

In: Journal of Applied Statistics, Vol. 38, No. 11, 11.2011, p. 2391-2411.

Research output: Contribution to journalArticle

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