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VGAMs

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Vector Generalized Linear and Additive Models

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Abstract

This chapter deals with the most pertinent details of the vector generalized additive model (VGAM) class. Building on the basic ideas of univariate smoothing from an earlier chapter, we develop it for vector smoothing a vector response. The two main methods (vector splines and local regression†) are described, including some inference, computational details (e.g., modified backfitting, O-splines), the vector additive model (VAM; the ‘backbone’ of VGAMs), and other topics such as using the VGAM package to fit them.

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Notes

  1. 1.

    More strictly, \(\mathcal{V}\) is defined over a field, and the operators called ‘addition’ and ‘multiplication’, and there is an element called 0.

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    Thomas W. Yee

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Yee, T.W. (2015). VGAMs. In: Vector Generalized Linear and Additive Models. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2818-7_4

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