This is a very simple function that supplies the hyper-parameters for the Fast Iterative Soft-Threshold Algorithm (FISTA) that solves the s2net
minimization problem.
s2Fista(MAX_ITER_INNER = 5000, TOL = 1e-07, t0 = 2, step = 0.1, use_warmstart = FALSE)
Number of iterations of FISTA
The relative tolerance. The algorith stops when the objective does not improve more than TOL*
the null model's objective function evaluation, after two succesive iterations.
The initial stepsize for backtracking.
The scale factor in the stepsize to backtrack until a valid step is found.
Should we use a warm beta
to fit the model? This is useful to speed-up hyper-parameter searching methods.
Returns an object of S3 class s2Fista
with the input arguments as fields.
Beck, A., & Teboulle, M. (2009). A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM journal on imaging sciences, 2(1), 183-202. 10.1137/080716542