Optimization algorithms implemented in R, including conjugate gradient (CG), Broyden-Fletcher-Goldfarb-Shanno (BFGS) and the limited memory BFGS (L-BFGS) methods. Most internal parameters can be set through the call interface. The solvers hold up quite well for higher-dimensional problems.
A patch release to fix an incompatibility with R-devel.
method = "TN"). Can be controlled using the
tn_init and tn_exit options.method = "SR1"), falling back to the BFGS direction if a
descent direction is not found.preconditioner, which applies to the conjugate gradient and
truncated newton methods. The only value currently available is preconditioner = "L-BFGS" which uses L-BFGS to estimate the inverse Hessian for
preconditioning. The number of updates to store for this preconditioner is
controlled by the memory parameter, just as if you were using method = "L-BFGS".fg list, supply a function hi, that takes
the par vector as input. The function can return a matrix (obviously not a
great idea for memory use), or a vector, the latter of which is assumed to be
the diagonal of the matrix.ls_max_alpha (for line_search = "More-Thuente" only): sets maximum value
of alpha that can be attained during line search.ls_max_alpha_mult (for Wolfe-type line search only): sets maximum value that
can be attained by the ratio of the initial guess for alpha for the current line
search, to the final value of alpha of the previous line search. Used to stop
line searches diverging due to very large initial guesses.ls_safe_cubic (for line_search = "More-Thuente" only): if TRUE,
use the safe-guarded cubic modification suggested by Xie and Schlick.cg_update = "prfr", the "PR-FR" (Polak-Ribiere/Fletcher-Reeves) conjugate
gradient update suggested by Gilbert and Nocedal.cg_udpate = "hs"), Conjugate Descent (cg_udpate = "cd"),
Dai-Yuan (cg_udpate = "dy") and Liu-Storey (cg_udpate = "ls").Initial release.