Variable metric nonlinear function minimization, unconstrained
Description
An R implementation of a variable metric method for minimization of unconstrained nonlinear functions.
See the manual Rvmmin.Rd for details.
Usage
1 
Arguments
par 
A numeric vector of starting estimates. 
fn 
A function that returns the value of the objective at the
supplied set of parameters 
gr 
A function that returns the gradient of the objective at the
supplied set of parameters Note that a gradient function MUST be provided. See the manual for

control 
An optional list of control settings. 
... 
Further arguments to be passed to 
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 highaccuracy gradient routine.
Functions fn
must return a numeric value.
The control
argument is a list.
Successful completion.
The source code Rvmmin
for R is still a work in progress, so users should watch
the console output.
The control
argument is a list.
 maxit
A limit on the number of iterations (default 500). This is the maximum number of gradient evaluations allowed.
 maxfevals
A limit on the number of function evaluations allowed (default 3000).
 trace
Set 0 (default) for no output, >0 for trace output (larger values imply more output).
dowarn
= TRUE if we want warnings generated by optimx. Default is TRUE.
 maximize
To maximize user_function, supply a function that computes (1)*user_function. An alternative is to call Rvmmin via the package optimx.
 acctol
To adjust the acceptable point tolerance (default 0.0001) in the test f <= fmin + gradproj * steplength * acctol
As of 20111121 the following controls have been REMOVED
 usenumDeriv
There is now a choice of numerical gradient routines. See argument
gr
.
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.

message 
A description of the situation on termination of the function. 
See Also
optim
Examples
1  ####in Rvmmin.Rd ####
