Usage
rdonlp2Control(iterma = 4000, nstep = 20,fnscale = 1, report = FALSE,
rep.freq = 1, tau0 = 1.0, tau = 0.1, del0 = 1.0, epsx = 1e-5,
delmin = 0.1*del0, epsdif = 1e-8, nreset.multiplier = 1,
difftype = 3,epsfcn = 1e-16,taubnd = 1.0, hessian = FALSE,
te0 = TRUE, te1 = FALSE, te2 = FALSE, te3 = FALSE, silent = FALSE,
intakt = TRUE)Arguments
iterma
maximum number of iterations.
nstep
maximum number of tries in the backtracking.
fnscale
set -1 to maximize the object function.
report
If TRUE, a list object which contains detailed
information will be passed to control.fun() in
donlp2. rep.freq
the frequency of report(positive integer). the report
will be passed to control.fun every rep.freq
iterations.
tau0
the positive amount how much any constaint other than
abound can be violated. A small tau0 diminishes the
efficiency of DONLP2, while a large tau0 may degarde the
reliability of the code.
tau
gives a weight between descent for fn and
infeasibility and is also used as a safety parameter for chosing the
penalty weigths. It can be chosen larger zero at will, but useful
values are between 0.1 and 1. The sma
del0
The positive amount by which constraints are considered
binding. If too small, the indentification of correct sets of
binding constraints may be delayed. If too large, DONLP2 will escape
to the full regularlized SQP method(quite co
epsx
successful temination is indicated if the Kuhn-Tucker
criteria are satisfied within the value.
delmin
constraints are considered as sufficiently satisfied if
absolute values of their violation are less than the value.
epsdif
relative precision in the gradients.
nreset.multiplier
maximum number of steps (nreset.multiplier times n)
until a ``restart'' of
the accumulated quasi-newton-update is tried. Value should be
integer between 1 and 4.
difftype
1,2,3. numerical differentiation algorithm. The
algorithm with difftype=2 is nearly identical to one used in
optim(). See PDF manual attached in this package.
epsfcn
relative precision of the function evaluation routine.
taubnd
The positive amount by which bounds may be violated if
numerical differention is used.
hessian
if TRUE, numeric Hessian matrix is calculated by
numerical differentiation algorithm specified in difftype.
intakt
if TRUE, informations about current iteration step in
optimization and final results are output to R console. The amount
of information depends on te0, te1, te2,
te3.
te0
if TRUE one-line-output for every step is printed.
te1
if TRUE post-mortem-dump of accumlated information is printed.
te2
if TRUE, more detailed information is ``pretty-printed''.
te3
if TRUE, the gradients and approximated Newton-Raphson
updates(in upper triangler matrix) are printed.
silent
If TRUE, donlp2() runs quietly, i.e.,
intakt=FALSE, .pro/.mes files are not created, and
te0,te1,te2,te3 are omitted.