Rvmminb: Variable metric nonlinear function minimization with bounds...
In optimx: Expanded Replacement and Extension of the 'optim' Function

Rvmminb

R Documentation

Variable metric nonlinear function minimization with bounds constraints

Description

A bounds-constarined R implementation of a variable metric method for minimization of nonlinear functions subject to bounds (box) constraints and masks (fixed parameters).

See manual Rvmmin.Rd for more details and examples.

Usage

   Rvmminb(par, fn, gr, lower, upper, bdmsk, control = list(), ...)

Arguments

`par`	A numeric vector of starting estimates.
`fn`	A function that returns the value of the objective at the supplied set of parameters `par` using auxiliary data in .... The first argument of `fn` must be `par`.
`gr`	A function that returns the gradient of the objective at the supplied set of parameters `par` using auxiliary data in .... The first argument of `fn` must be `par`. This function returns the gradient as a numeric vector. Note that a gradient function MUST be provided. See the manual for `Rvmmin`, which is the usual way `Rvmminb` is called. The user must take responsibility for errors if `Rvmminb` is called directly.
`lower`	A vector of lower bounds on the parameters.
`upper`	A vector of upper bounds on the parameters.
`bdmsk`	An indicator vector, having 1 for each parameter that is "free" or unconstrained, and 0 for any parameter that is fixed or MASKED for the duration of the optimization.
`control`	An optional list of control settings. See the manual Rvmmin.Rd for details.
`...`	Further arguments to be passed to `fn`.

Details

This routine is intended to be called from Rvmmin, which will, if necessary, supply a gradient approximation. However, some users will want to avoid the extra overhead, in which case it is important to provide an appropriate and high-accuracy gradient routine.

Note that bounds checking, if it is carried out, is done by Rvmmin.

Functions fn must return a numeric value.

Value

A list with components:

`par`	The best set of parameters found.
`value`	The value of the objective at the best set of parameters found.
`counts`	A vector of two integers giving the number of function and gradient evaluations.
`convergence`	An integer indicating the situation on termination of the function. `0` indicates that the method believes it has succeeded. Other values: `1` indicates that the iteration limit `maxit` had been reached. `20` indicates that the initial set of parameters is inadmissible, that is, that the function cannot be computed or returns an infinite, NULL, or NA value. `21` indicates that an intermediate set of parameters is inadmissible.
`message`	A description of the situation on termination of the function.
`bdmsk`	Returned index describing the status of bounds and masks at the proposed solution. Parameters for which bdmsk are 1 are unconstrained or "free", those with bdmsk 0 are masked i.e., fixed. For historical reasons, we indicate a parameter is at a lower bound using -3 or upper bound using -1.