Abstract
This chapter covers the most important class of models, viz. vector generalized linear models (VGLMs). It includes the basic ideas of (parameter) link functions, constraint matrices, the xij argument, inference, computational details, (e.g., QR decomposition, Cholesky), residuals and diagnostics. Some basic details on software usage is given.
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Notes
- 1.
In being simple, the formula cannot handle terms such as . and -x2, nor interactions and nested terms, etc.
- 2.
If not, then this is known as a “varying choice set” in the discrete-choice model literature. This presently is outside the VGLM/VGAM framework.
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Yee, T.W. (2015). VGLMs. 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_3
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