nlminb2 function

Nonlinear programming with nonlinear constraints.

This function was contributed by Diethelm Wuertz.

nlminb2(
  start,
  objective,
  eqFun = NULL,
  leqFun = NULL,
  lower = -Inf,
  upper = Inf,
  gradient = NULL,
  hessian = NULL,
  control = list()
)

Arguments

• start: numeric vector of start values.
• objective: the function to be minimized $f(x)$.
• eqFun: functions specifying equal constraints of the form $h_i(x) = 0$. Default: NULL (no equal constraints).
• leqFun: functions specifying less equal constraints of the form $g_i(x) <= 0$. Default: NULL (no less equal constraints).
• lower: a numeric representing lower variable bounds. Repeated as needed. Default: -Inf.
• upper: a numeric representing upper variable bounds. Repeated as needed. Default: Inf.
• gradient: gradient of $f(x)$. Default: NULL (no gradiant information).
• hessian: hessian of $f(x)$. Default: NULL (no hessian provided).
• control: a list of control parameters. See nlminb() for details. The parameter "scale" is set here in contrast to nlminb() .

Returns

list()

Examples

## Equal constraint function
eval_g0_eq <- function( x, params = c(1,1,-1)) {
       return( params[1]*x^2 + params[2]*x + params[3] )
   }
eval_f0 <- function( x, ... ) {
       return( 1 )
   }

Author(s)

Diethelm Wuertz