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fPortfolio (version 3011.81)

mathprog-NLP: Mathematical Non-Linear Programming

Description

Mathematical Non-Linear Programming.

Usage

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)
rsolnp
      
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.