Bayesian variable selection has gained much empirical success recently in a variety of applications when the number K of explanatory variables $(x_{1},\ldots ,x_{K})$ is possibly much larger than the ...
High-dimensional feature screening and variable selection represent critical methodological advancements designed to address the challenges posed by datasets where the number of potential predictors ...
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