Nelder-Mead Solver (Derivative-Free)

Creates a solver using the Nelder-Mead simplex method via optim(). This is a derivative-free method useful when gradients are unavailable or unreliable.

Usage

nelder_mead(max_iter = 500L, tol = 1e-08)

Arguments

max_iter

Maximum number of iterations

tol

Convergence tolerance

Value

A solver function

Details

Nelder-Mead doesn't use gradient information, making it robust but potentially slower. It's useful as a fallback when gradient-based methods fail, or for problems with non-smooth likelihoods.

Examples

if (FALSE) { # \dontrun{
# Use when gradients are problematic
result <- nelder_mead()(problem, c(0, 1))

# Race against gradient methods
strategy <- gradient_ascent() %|% nelder_mead()
} # }