Revisiting Marginal Regression

Understand

The lasso has become an important practical tool for high dimensional regression as well as the object of intense theoretical investigation.

• But despite the availability of efficient algorithms, the lasso remains computationally demanding in regression problems where the number of variables vastly exceeds the number of data points.
• A much older method, marginal regression, largely displaced by the lasso, offers a promising alternative in this case.
• Computation for marginal regression is practical even when the dimension is very high.