Generalized Additive Models: An Introduction with R (2nd Edition)
2018; Foundation for Open Access Statistics; Volume: 86; Issue: Book Review 1 Linguagem: Inglês
10.18637/jss.v086.b01
ISSN1548-7660
Autores Tópico(s)Statistical Methods and Inference
ResumoGeneralized additive models (GAMs) are one of the main modeling tools for data analysis.GAMs can efficiently combine different types of fixed, random and smooth terms in the linear predictor of a regression model to account for different types of effects.Then this linear predictor can be conveniently linked to the mean of the observations, that are modeled using a distribution from the exponential family.As described in Wood's book, GAMs cover a wide range of statistical models used in practice, such as the general linear model, generalized linear models and mixed-effects models.This is stressed throughout the book with numerous examples.
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