A Bayesian prior for function-on-scalar regression simultaneously selects variables, clusters correlated predictors, and smooths effects to handle multicollinearity without dropping predictors.
Ferguson distributions via p \'o lya urn schemes
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Simultaneous Variable Selection, Clustering, and Smoothing in Function on Scalar Regression
A Bayesian prior for function-on-scalar regression simultaneously selects variables, clusters correlated predictors, and smooths effects to handle multicollinearity without dropping predictors.