ip.optimalk(A) #this will print out optimal k

ip.invert(A,be,k,l) #this will invert your A matrix, where be is noisy be, k is the no. of iterations, and lambda is your dampening effect (best set to 1)

Authors: Kathryn N. Vasilaky and Walter Vasilaky

This project develops Inclusive Ridge (IR), a two-parameter (lambda, eta) generalization of ridge regression that modifies the geometry of spectral shrinkage to reduce the curvature of the risk function. The key theoretical result is that IR flattens the risk surface relative to ridge, lowering worst-case regret under penalty misspecification. Ridge is shown to be inadmissible within the IR family under a verifiable signal-to-noise condition.