The use of generalized additive models in statistical data analysis suffers from the restriction to few explanatory variables and the problems of selection of smoothing parameters. Generalized ...

Generalized additive models have been popular among statisticians and data analysts in multivariate nonparametric regression with non-Gaussian responses including binary and count data. In this paper, ...

Partially linear additive models provide an attractive middle ground between the simplicity of generalized linear model and the flexibility of generalized additive model, and are important models ...

Based on a statistical approach known as generalized additive modeling, they were able to map annual wildfire probabilities throughout California from 1970 to 2016 by incorporating data on local ...

The population pharmacokinetic model was built in sequential manner, starting with a covariate-free model and progressing to a covariate model with the aid of generalized additive modeling. RESULTS: A ...

We carried out the development of the predictive model via a Generalized Additive Modeling (GAM) approach, able to incorporate emissions-transport, demographics, weather, and scheduling (day of week) ...

A study in National Science Review reports systematic observations of diazotroph abundance, community structure, and N2 ...