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Bayesian Generalized additive model

Bayesian Generalized Additive Models extend the frequentist GAM framework by placing prior distributions over the smooth functions and any additional model parameters. This yields full posterior distributions over each smooth effect, enabling principled uncertainty quantification, automatic smoothness selection via hyperpriors, and seamless integration with hierarchical or mixed-effects structures.

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Bayesian Generalized Additive Model

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Wood, S. N. (2017). Generalized Additive Models: An Introduction with R (2nd ed.). CRC Press. · ISBN 9781498728331
Bürkner, P.-C. (2017). brms: An R Package for Bayesian Multilevel Models Using Stan. Journal of Statistical Software, 80(1), 1–28. · DOI 10.18637/jss.v080.i01

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Taxonomic bucketBayesian Generalized Linear Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Mixed Effects Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian Multiple linear regressionmachine-suggested · Relational suggestion, not evidence.See alsoGeneralized Additive Modelmachine-suggested · Relational suggestion, not evidence.