Febrero Bande, ManuelGonzález Manteiga, WenceslaoOviedo de la Fuente, Manuel2019-04-172019-04-172017Febrero-Bande M., González-Manteiga W., de la Fuente M.O. (2017) Variable selection in Functional Additive Regression Models. In: Aneiros G., G. Bongiorno E., Cao R., Vieu P. (eds) Functional Statistics and Related Fields. Contributions to Statistics. Springer, Cham978-3-319-55845-5978-3-319-55846-2http://hdl.handle.net/10347/18649This is a post-peer-review, pre-copyedit version of an chapter published in Functional Statistics and Related Fields. The final authenticated version is available online at: https://doi.org/10.1007/978-3-319-55846-2_15This paper considers the problem of variable selection when some of the variables have a functional nature and can be mixed with other type of variables (scalar, multivariate, directional, etc). Our proposal begins with a simple null model and sequentially selects a new variable to be incorporated into the model. For the sake of simplicity, this paper only uses additive models. However, the proposed algorithm may assess the type of contribution (linear, non linear, …) of each variable. The algorithm have showed quite promising results when applied to real data setseng© Springer International Publishing AG 2017Variable SelectionDistance CorrelationFunctional CovariatesMeteorological InformationScalar Covariatesbook part10.1007/978-3-319-55846-2_15open access