This paper describes a framework for flexibly modeling zero-inflated data. Semiparametric regression based on penalized regression splines for zero-inflated Poisson models is introduced. Moreover, an EM-type algorithm is developed to perform maximum likelihood estimation. As an illustration, a study of animal abundance is tackled. In fact, abundance often shows excess of zeroes and is a complicated function of the explanatory variables. In particular, the relationships between avian abundance and environmental variables indicating land use are tackled.

Semiparametric zero-inflated Poisson models with application to animal abundance studies

CHIOGNA M.;
2007

Abstract

This paper describes a framework for flexibly modeling zero-inflated data. Semiparametric regression based on penalized regression splines for zero-inflated Poisson models is introduced. Moreover, an EM-type algorithm is developed to perform maximum likelihood estimation. As an illustration, a study of animal abundance is tackled. In fact, abundance often shows excess of zeroes and is a complicated function of the explanatory variables. In particular, the relationships between avian abundance and environmental variables indicating land use are tackled.
CHIOGNA M.; GAETAN C
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/646531
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