Rvmminb: Variable metric nonlinear function minimization with bounds...
In Rvmmin: Variable Metric Nonlinear Function Minimization

Description Usage Arguments Details Value See Also Examples

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.

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

`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`.

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.

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.