Lung cancer incidence over 2005-2010 for 326 Local Authority Districts in England is investi- gated by ecological regression. Motivated from misspecification of a Negative Binomial additive model, a semiparametric Negative Binomial M-quantile regression model is introduced. The ad- ditive 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 capabilitiy of the semiparametric Negative Binomial M-quantile regression model to handle data with a strong spatial structure.
Semiparametric M-quantile Regression for Count data
SALVATI, NICOLA
2014-01-01
Abstract
Lung cancer incidence over 2005-2010 for 326 Local Authority Districts in England is investi- gated by ecological regression. Motivated from misspecification of a Negative Binomial additive model, a semiparametric Negative Binomial M-quantile regression model is introduced. The ad- ditive 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 capabilitiy of the semiparametric Negative Binomial M-quantile regression model to handle data with a strong spatial structure.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.