Running iterative lasso using accuracy

1. Packing a block of code into a function
2. Changed some variable names
3. Feature selection can be done by using ERRcvglmnet, which is not
qualitatively different from cvglmnet
Running iterative Lasso using H/F

This version of iterative lasso using the difference between hit rate
and false alarm rate to perform feature selection.
This is achieved by using the new function HFcvglmnet
Plot hit rate/false rate and the difference

This is a function that plots the hit rate, false alarm rate and their
difference over 100 lambda.
Main script for running iterative lasso

Some minor changes
Function for cvglmnet using error

This function optimizes lambda using error, which is what cvglmnet can
do. We build it in order to make sure we understand the criterion for
cvglmnet.