simplex: Nelder-Mead's Simplex Method for Function Minimization.

In merkys/MixtureFitting: Fitting of Univariate Mixture Distributions to Data using Various Approaches

Nelder-Mead's Simplex Method for Function Minimization.

Description

Nelder-Mead's Simplex Method for Function Minimization.

Usage

    simplex( fn, start, ..., epsilon = 0.000001, alpha = 1,
             gamma = 2, rho = 0.5, delta = 0.5, trace = FALSE )

Arguments

fn	minimized function, has to accept the argmin vector as first parameter
start	start vector
...	other parameters passed to the minimized function
epsilon	convergence criterion
alpha	reflection coefficient
gamma	expansion coefficient
rho	contraction coefficient
delta	shrink coefficient
trace	should debug trace be printed?

Value

Vector yielding the minimum value of the minimized function

Author(s)

Andrius Merkys

References

Nelder, J. A. & Mead, R. A Simplex Method For Function Minimization. The Computer Journal, 1965, 308-313.

Users of Wikipedia. Nelder-Mead method. https://en.wikipedia.org/w/index.php?title=Nelder%E2%80%93Mead_method&oldid=1287347131

merkys/MixtureFitting documentation built on July 5, 2025, 5:43 a.m.