Usage
nlminb(start, objective, gradient = NULL, hessian = NULL, …,
scale = 1, control = list(), lower = -Inf, upper = Inf)Arguments
start
numeric vector, initial values for the parameters to be optimized.
objective
Function to be minimized. Must return a scalar value. The first
argument to objective is the vector of parameters to be
optimized, whose initial values are supplied through start.
Further arguments (fixed during the course of the optimization) to
objective may be specified as well (see …).
gradient
Optional function that takes the same arguments as objective and
evaluates the gradient of objective at its first argument. Must
return a vector as long as start.
hessian
Optional function that takes the same arguments as objective and
evaluates the hessian of objective at its first argument. Must
return a square matrix of order length(start). Only the
lower triangle is used.
…
Further arguments to be supplied to objective.
scale
See PORT documentation (or leave alone).
control
A list of control parameters. See below for details.
lower, upper
vectors of lower and upper bounds, replicated to be as long as
start. If unspecified, all parameters are assumed to be
unconstrained.