Model selection procedure for high‐dimensional data
Model selection procedure for high‐dimensional data
Abstract For high‐dimensional regression, the number of predictors may greatly exceed the sample size but only a small fraction of them are related to the response. Therefore, variable selection is inevitable, where consistent model selection is the primary concern. However, conventional consistent model selection criteria like Bayesian information criterion (BIC) …