In this imulation study , we simulate the data and use it to compare three Penalized Least Squares Estimators:

• L1-norm penalty LASSO.
• Smoothly Clipped Absolute Deviations penalty (SCAD).
• Minimax Concave Penalty (MCP).

We perform 50 independent replications and choose tunning parrameters by cross-validation.

We answer to the question in which case SCAD and MCP mitigate bias better than LASSO, by examining the error variance.