The NM-method, or Nelder-Mead method, is an optimization technique used for minimizing functions that may not be smooth or derivatives may not be easily computable. It is particularly useful for multidimensional optimization problems. The method is a direct search algorithm, which means it does not require gradient information, making it applicable for non-differentiable functions.
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