Function reference • nloptr

All functions
`auglag()`	Augmented Lagrangian Algorithm
`bobyqa()`	Bound Optimization by Quadratic Approximation
`ccsaq()`	Conservative Convex Separable Approximation with Affine Approximation plus Quadratic Penalty
`check.derivatives()`	Check analytic gradients of a function using finite difference approximations
`cobyla()`	Constrained Optimization by Linear Approximations
`crs2lm()`	Controlled Random Search
`direct()` `directL()`	DIviding RECTangles Algorithm for Global Optimization
`is.nloptr()`	R interface to NLopt
`isres()`	Improved Stochastic Ranking Evolution Strategy
`lbfgs()`	Low-storage BFGS
`mlsl()`	Multi-level Single-linkage
`mma()`	Method of Moving Asymptotes
`neldermead()`	Nelder-Mead Simplex
`newuoa()`	New Unconstrained Optimization with quadratic Approximation
`nl.grad()`	Numerical Gradients and Jacobians
`nl.opts()`	Setting NL Options
`nloptr-package`	R interface to NLopt
`nloptr()`	R interface to NLopt
`nloptr.get.default.options()`	Return a data.frame with all the options that can be supplied to nloptr.
`nloptr.print.options()`	Print description of nloptr options
`print(<nloptr>)`	Print results after running nloptr
`sbplx()`	Subplex Algorithm
`slsqp()`	Sequential Quadratic Programming (SQP)
`stogo()`	Stochastic Global Optimization
`tnewton()`	Preconditioned Truncated Newton
`varmetric()`	Shifted Limited-memory Variable-metric

Reference