mathprog-NLP: Mathematical Non-Linear Programming

Description Usage Arguments Value References

Description

Mathematical Non-Linear Programming.

Usage

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rdonlp2NLP(start, objective, 
    lower=0, upper=1, linCons, funCons, control=list())   
donlp2NLP(start, objective, 
    par.lower=NULL, par.upper=NULL,
    eqA=NULL, eqA.bound=NULL,
    ineqA=NULL, ineqA.lower=NULL, ineqA.upper=NULL,
    eqFun=list(), eqFun.bound=NULL,
    ineqFun=list(), ineqFun.lower=NULL, ineqFun.upper=NULL,
    control=list())    
donlp2NLPControl(
    iterma=4000, nstep=20, fnscale=1, report=FALSE, rep.freq=1, 
    tau0=1, tau=0.1, del0=1, epsx=1e-05, delmin=0.1 * del0, 
    epsdif=1e-08, nreset.multiplier=1, difftype=3, epsfcn=1e-16, 
    taubnd=1, hessian=FALSE, te0=TRUE, te1=FALSE, te2=FALSE, 
    te3=FALSE, silent=TRUE, intakt=TRUE) 
rdonlp2

rsolnpNLP(start, objective, 
    lower=0, upper=1, linCons, funCons, control=list())   
solnpNLP(start, objective, 
    par.lower=NULL, par.upper=NULL,
    eqA=NULL, eqA.bound=NULL,
    ineqA=NULL, ineqA.lower=NULL, ineqA.upper=NULL,
    eqFun=list(), eqFun.bound=NULL,
    ineqFun=list(), ineqFun.lower=NULL, ineqFun.upper=NULL,
    control=list())    
solnpNLPControl(
    rho=1, outer.iter=400, inner.iter=800, delta=1e-07, tol=1e-08, trace=0)
      
rnlminb2NLP(start, objective, 
    lower=0, upper=1, linCons, funCons, control=list())   
nlminb2NLP(start, objective, 
    par.lower=NULL, par.upper=NULL,
    eqA=NULL, eqA.bound=NULL,
    ineqA=NULL, ineqA.lower=NULL, ineqA.upper=NULL,
    eqFun=list(), eqFun.bound=NULL,
    ineqFun=list(), ineqFun.lower=NULL, ineqFun.upper=NULL,
    control=list())    
nlminb2NLPControl(
    eval.max=500, iter.max=400, trace=0, abs.tol=1e-20, rel.tol=1e-10, 
    x.tol=1.5e-08, step.min=2.2e-14, scale=1, R=1, beta.tol=1e-20)  
rnlminb2
      
ramplNLP(start, objective, 
    lower=0, upper=1, amplCons, control=list(), ...)   
amplNLP()    
amplNLPControl(
    solver="minos", project="ampl", trace=FALSE)

Arguments

start

a numeric vector, the start values.

objective

a function object, the function to be optimized.

lower, upper

lower and upper bounds.

linCons

list of linear constraints: mat, lower, upper.

funCons

list of function constraints.

amplCons

AMPL constraints.

control

control list.

...

optional arguments to be passed.

par.lower, par.upper

...

eqA

...

eqA.bound

...

ineqA

...

ineqA.lower,ineqA.upper

...

eqFun

...

eqFun.bound

...

ineqFun

...

ineqFun.lower,ineqFun.upper

...

iterma

4000

nstep

20

fnscale

1

report

FALSE

rep.freq

1

tau0

1

tau

0.1

del0

1

epsx

1e-5

delmin

0.1 * del0

epsdif

1e-8

nreset.multiplier

1

difftype

3

epsfcn

1e-16

taubnd

1

hessian

FALSE

te0

TRUE

te1

FALSE

te2

FALSE

te3

FALSE

silent

TRUE

intakt

TRUE

rho

1

outer.iter

400

inner.iter

800

delta

1.0e-7

tol

1.0e-8

eval.max

500

iter.max

400

trace

0

abs.tol

1e-20

rel.tol

1e-10

x.tol

1.5e-08

step.min

2.2e-14

scale

1

R

1

beta.tol

1e-20

solver

solver name

project

project name

Value

a list of class solver with the following named ebtries: opt, solution, objective, status, message, solver, version.

References

Wuertz, D., Chalabi, Y., Chen W., Ellis A. (2009); Portfolio Optimization with R/Rmetrics, Rmetrics eBook, Rmetrics Association and Finance Online, Zurich.


fPortfolio documentation built on March 26, 2020, 9:17 p.m.