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neldermead

The neldermead package provides several direct search optimization algorithms based on the simplex method. The provided algorithms are direct search algorithms, i.e. algorithms which do not use the derivative of the cost function. They are based on the update of a simplex. The following algorithms are available: the fixed shape simplex method of Spendley, Hext and Himsworth (unconstrained optimization with a fixed shape simplex), the variable shape simplex method of Nelder and Mead (unconstrained optimization with a variable shape simplex made), and Box's complex method (constrained optimization with a variable shape simplex).

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Version

Install

install.packages('neldermead')

Monthly Downloads

407

Version

1.0-13

License

CeCILL-2

Maintainer

Sebastien Bihorel

Last Published

January 26th, 2026

Functions in neldermead (1.0-13)

fminsearch.outputfun

fminsearch Output Function Call
fminbnd.outputfun

fminbnd Output Function Call
fminsearch.function

fminsearch Cost Function Call
costf.transposex

Cost Function Call
fminbnd.function

fminbnd Cost Function Call
neldermead

Neldermead objects
neldermead.destroy

Erase a neldermead object.
optimset

Configures and returns an optimization data structure.
Secondary search functions

Secondary functions for neldermead.search
neldermead.algo

Nelder-Mead Algorithm
neldermead.set

Neldermead Object Configuration
optimget

Queries an optimization option list
neldermead.restart

Restart neldermead search.
neldermead.function

Call Cost Function.
neldermead.get

Get the value for the given element
neldermead.search

Starts the optimization
optimset.method

Default set of optimization options
neldermead-package

R port of the Scilab neldermead module
fmin.gridsearch

Grid evaluation of an unconstrained cost function
fminbnd

Computation of the constrained minimimum of given function with the Nelder-Mead algorithm.
fminsearch

Computation of the unconstrained minimum of given function with the Nelder-Mead algorithm.