Spike-and-slab regression

ID: spike-and-slab-regression

Spike-and-slab regression is a statistical technique used in Bayesian regression analysis that aims to perform variable selection while simultaneously estimating regression coefficients. It is particularly useful when dealing with high-dimensional data where the number of predictors may exceed the number of observations, leading to issues such as overfitting. ### Key Concepts: 1. **Spike-and-Slab Priors**: The technique employs a specific type of prior distribution known as a spike-and-slab prior.

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