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Bayesian inference of Generalized Infinite Factorization models with Structured Increasing Shrinkage prior

The repository includes R functions to perform Bayesian inference under the Structured Increasing Shrinkage model presented in the following paper: Schiavon, L., Canale, A., Dunson, D.B. (in press) Generalized infinite factorization models, Biometrika. Link to the pre-print version of the paper

File Schiavon_SISGaussian.R refers to the application of the structured increasing shrinkage prior in case of a Gaussian data matrix.

File Schiavon_SIScovariatesRegression.R refers to the application of the structured increasing shrinkage prior when we are interested in factorize a covariate matrix in a linear regression model. In particular, it refers to the paper: Schiavon, L., Canale, A. (2021) Bayesian regularized regression of football tracking data through structured factor models, in Book of Short Papers SIS 2021 (Editors: Pernal, C., Salvati, N. and Schirippa Spagnolo, F.), ISBN: 9788891927361. Link to the paper

All files include a function for the MCMC sampler and a function to estimate a meaningful posterior summary of the loadings matrix according to what discussed in Section 3.3 of Schiavon, Canale and Dunson (in press).