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.