Semiparametric M-quantile regression for count data.
Lung cancer incidence over 2005-2010 for 326 Local Authority Districts in England is investigated by ecological regression. Motivated from mis-specification of a Negative Binomial additive model, a semiparametric Negative Binomial M-quantile regression model is introduced. The additive part relates to those univariate or bivariate smoothing components, which are included in the model to capture nonlinearities in the predictor or to account for spatial dependence. All such components are estimated using penalized splines. The results show the capability of the semiparametric Negative Binomial M-quantile regression model to handle data with a strong spatial structure.
Dipartimento di Statistica, Informatica, Applicazioni, Università di Firenze, Firenze, Italy dreassi@disia.unifi.it.
Emanuela
E
Dreassi
Dipartimento di Scienze Politiche, Università di Perugia, Perugia, Italy.
M Giovanna
MG
Ranalli
Dipartimento di Economia e Management, Università di Pisa, Pisa, Italy.
Nicola
N
Salvati
D004739:England / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D008175:Lung Neoplasms / Q000453:epidemiology*; D012044:Regression Analysis
Disease mapping; Negative Binomial; ecological regression; geoadditive models; penalized splines; robust method