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)
Returns an object of S3 class s2Fista
with the input arguments as fields.
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.
Beck, A., & Teboulle, M. (2009). A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM journal on imaging sciences, 2(1), 183-202. tools:::Rd_expr_doi("10.1137/080716542")
s2Params
, s2Data