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#################################################################################
##
## R package rgarch by Alexios Ghalanos Copyright (C) 2008, 2009, 2010, 2011
## This file is part of the R package rgarch.
##
## The R package rgarch is free software: you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation, either version 3 of the License, or
## (at your option) any later version.
##
## The R package rgarch is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
#################################################################################
# implements nlminb, lbgs and solnp
# only solnp implements true constraint (stationarity) optimization
.garchsolver = function(solver, pars, fun, Ifn, ILB, IUB, gr, hessian, parscale,
control, LB, UB, ux=NULL, ci=NULL, mu=NULL, ...)
{
gocontrol = control
control = .getcontrol(solver, control)
retval = switch(solver,
nlminb = .nlminbsolver(pars, fun, gr, hessian, parscale, control, LB, UB, ...),
solnp = .solnpsolver(pars, fun, Ifn, ILB, IUB, control, LB, UB, ...),
gosolnp = .gosolnpsolver(pars, fun, Ifn, ILB, IUB, gocontrol, LB, UB, ...),
lbfgs = .lbfgssolver(pars, fun, gr, parscale, control, LB, UB, ...))
return(retval)
}
.nlminbsolver = function(pars, fun, gr, hessian, parscale, control, LB, UB,...){
ans = try(nlminb(start = pars, objective = fun, gradient = gr, hessian = hessian,
..., scale = 1/parscale, control = control, lower = LB, upper = UB), silent = TRUE)
if(inherits(ans, "try-error")){
sol = list()
sol$convergence = 1
sol$message = ans
sol$par = rep(NA, length(pars))
names(sol$par) = names(pars)
} else{
sol = ans
}
hess = NULL
return(list(sol = sol,hess = hess))
}
.solnpsolver = function(pars, fun, Ifn, ILB, IUB, control, LB, UB, ...){
ans = try(solnp(pars, fun = fun, eqfun = NULL, eqB = NULL, ineqfun = Ifn, ineqLB = ILB,
ineqUB = IUB, LB = LB, UB = UB, control = control, ...), silent = TRUE)
if(inherits(ans,"try-error")){
sol = list()
sol$convergence = 1
sol$message = ans
sol$par = rep(NA, length(pars))
names(sol$par) = names(pars)
cat("\nrgarch-->warning: no convergence...\n")
} else{
sol = ans
}
hess = NULL
return(list(sol = sol, hess = hess))
}
.gosolnpsolver = function(pars, fun, Ifn, ILB, IUB, gocontrol, LB, UB, ...){
control = .solnpctrl(gocontrol)
gocontrol = .gosolnpctrl(gocontrol)
n.restarts = gocontrol$n.restarts
parallel = gocontrol$parallel
parallel.control = gocontrol$parallel.control
rseed = gocontrol$rseed
n.sim = gocontrol$n.sim
op <- options()
options(warn = 0)
# use the truncated normal distribution
distr.opt = vector(mode = "list", length = length(pars))
for(i in 1:length(pars)){
distr.opt[[i]]$mean = pars[i]
distr.opt[[i]]$sd = sqrt(pars[i]^2)*2
}
# ok parallel will work with snowfall without changing the fun and Ifn to rgarch:::fun and rgarch:::Ifn
ans = try(gosolnp(pars = pars, fixed = NULL, fun = fun, eqfun = NULL,
eqB = NULL, ineqfun = Ifn, ineqLB = ILB,
ineqUB = IUB, LB = LB, UB = UB, control = control, distr = rep(2, length(LB)), distr.opt = distr.opt,
n.restarts = n.restarts, n.sim = n.sim, parallel = parallel, parallel.control = parallel.control,
rseed = rseed, ...),
silent = TRUE)
if(inherits(ans,"try-error")){
sol = list()
sol$convergence = 1
sol$message = ans
sol$par = rep(NA, length(pars))
names(sol$par) = names(pars)
} else{
sol = ans
}
hess = NULL
options(op)
return(list(sol = sol, hess = hess))
}
.lbfgssolver = function(pars, fun, gr, parscale, control, LB, UB, ...){
control$parscale = parscale
ans = try(optim(par = pars, fn = fun, gr = gr, ...,
method = "L-BFGS-B", lower = LB, upper = UB, control = control,
hessian = TRUE),silent=TRUE)
if(inherits(ans, "try-error")){
sol = list()
sol$convergence = 1
sol$message = ans
sol$par = rep(NA, length(pars))
names(sol$par) = names(pars)
} else{
sol = ans
}
hess = sol$hessian
return(list(sol = sol, hess = hess))
}
# default control for solvers:
.getcontrol = function(solver, control)
{
ans = switch(solver,
nlminb = .nlminbctrl(control),
solnp = .solnpctrl(control),
gosolnp = .gosolnpctrl(control),
lbfgs = .lbfgsctrl(control))
return(ans)
}
.nlminbctrl = function(control)
{
if(is.null(control$eval.max)) control$eval.max = 2000
if(is.null(control$iter.max)) control$iter.max = 1500
if(is.null(control$abs.tol)) control$abs.tol = 1e-20
if(is.null(control$rel.tol)) control$rel.tol = 1e-10
if(is.null(control$x.tol)) control$x.tol = 1.5e-8
if(is.null(control$step.min)) control$step.min = 2.2e-14
return(control)
}
.lbfgsctrl = function(control)
{
if(is.null(control$REPORT)) control$REPORT = 10
if(is.null(control$lmm)) control$lmm = 15
if(is.null(control$pgtol)) control$pgtol = 1e-8
if(is.null(control$factr)) control$factr = 1e-8
return(control)
}
.solnpctrl = function(control){
# parameters check is now case independent
ans = list()
params = unlist(control)
if(is.null(params)) {
ans$rho = 0.5
ans$outer.iter = 50
ans$inner.iter = 1800
ans$delta = 1.0e-8
ans$tol = 1.0e-8
ans$trace = 1
} else{
npar = tolower(names(unlist(control)))
names(params) = npar
if(any(substr(npar, 1, 3) == "rho")) ans$rho = as.numeric(params["rho"]) else ans$rho = 0.5
if(any(substr(npar, 1, 5) == "outer.iter")) ans$outer.iter = as.numeric(params["outer.iter"]) else ans$outer.iter = 50
if(any(substr(npar, 1, 5) == "inner.iter")) ans$inner.iter = as.numeric(params["inner.iter"]) else ans$inner.iter = 1000
if(any(substr(npar, 1, 5) == "delta")) ans$delta = as.numeric(params["delta"]) else ans$delta = 1.0e-8
if(any(substr(npar, 1, 3) == "tol")) ans$tol = as.numeric(params["tol"]) else ans$tol = 1.0e-8
if(any(substr(npar, 1, 5) == "trace")) ans$trace = as.numeric(params["trace"]) else ans$trace = 1
}
return(ans)
}
.gosolnpctrl = function(control){
# parameters check is now case independent
ans = list()
params = unlist(control)
if(is.null(params)) {
ans$parallel = FALSE
ans$parallel.control = list(pkg = "snowfall", cores = 2)
ans$n.restarts = 1
ans$rseed
ans$n.sim = 500
} else{
npar = tolower(names(unlist(control)))
names(params) = npar
ans$parallel.control = list()
if(any(substr(npar, 1, 8) == "parallel")) ans$parallel = as.logical(params["parallel"]) else ans$parallel = FALSE
if(any(substr(npar, 1, 20) == "parallel.control.pkg")) ans$parallel.control$pkg = params["parallel.control.pkg"] else ans$parallel.control$pkg = "snowfall"
if(any(substr(npar, 1, 22) == "parallel.control.cores")) ans$parallel.control$cores = params["parallel.control.cores"] else ans$parallel.control$cores = "snowfall"
if(any(substr(npar, 1, 10) == "n.restarts")) ans$n.restarts = as.numeric(params["n.restarts"]) else ans$n.restarts = 1
if(any(substr(npar, 1, 5) == "rseed")) ans$rseed = as.numeric(params["rseed"]) else ans$rseed = NULL
if(any(substr(npar, 1, 5) == "n.sim")) ans$n.sim = as.numeric(params["n.sim"]) else ans$n.sim = 500
}
return(ans)
}
#----------------------------------------------------------------------------------
.garchconbounds = function(){
return(list(LB = eps,UB = 0.999))
}
.sgarchcon = function(pars, data, returnType, garchenv){
fixed = get("fixed", garchenv)
fixid = get("fixid", garchenv)
npar = get("npar", garchenv)
if(!is.null(fixed)){
pall = vector(mode = "numeric", length = npar)
pall[fixid] = fixed
pall[-fixid] = pars
pars = pall
}
Names = get("omodel", garchenv)$modelnames
distribution = get("dmodel", garchenv)$distribution
names(pars) = Names
con = .persistsgarch(pars = pars, distribution = distribution)
return(con)
}
.igarchcon = function(pars, data, returnType, garchenv){
# this is an equality constraint
fixed = get("fixed", garchenv)
fixid = get("fixid", garchenv)
npar = get("npar", garchenv)
if(!is.null(fixed)){
pall = vector(mode = "numeric", length = npar)
pall[fixid] = fixed
pall[-fixid] = pars
pars = pall
}
garchOrder = get("vmodel", garchenv)$garchOrder
pos = get("omodel", garchenv)$pos.matrix
a.con = pos["alpha",1:2]
b.con = pos["beta",1:2]
alpha = pars[a.con[1]:a.con[2]]
beta = pars[b.con[1]:b.con[2]]
garchq = garchOrder[2]
if(garchq == 1){
betaz = 1-sum(alpha)
} else{
betaz = 1-sum(alpha)-sum(beta)
}
beta[garchq] = betaz
(sum(alpha) + sum(beta)) - betaz
}
.aparchcon = function(pars, data, returnType, garchenv){
fixed = get("fixed", garchenv)
fixid = get("fixid", garchenv)
npar = get("npar", garchenv)
if(!is.null(fixed)){
pall = vector(mode = "numeric", length = npar)
pall[fixid] = fixed
pall[-fixid] = pars
pars = pall
}
Names = get("omodel", garchenv)$modelnames
distribution = get("dmodel", garchenv)$distribution
names(pars) = Names
con = .persistaparch(pars = pars, distribution = distribution)
if(is.na(con)) con = 1
return(con)
}
.fgarchcon = function(pars, data, returnType, garchenv){
fixed = get("fixed", garchenv)
fixid = get("fixid", garchenv)
npar = get("npar", garchenv)
if(!is.null(fixed)){
pall = vector(mode = "numeric", length = npar)
pall[fixid] = fixed
pall[-fixid] = pars
pars = pall
}
Names = get("omodel", garchenv)$modelnames
distribution=get("dmodel", garchenv)$distribution
submodel = get("vmodel", garchenv)$submodel
names(pars) = Names
con = .persistfgarch(pars = pars, distribution = distribution, submodel = submodel)
if(is.na(con)) con = 1
return(con)
}
.gjrgarchcon = function(pars, data, returnType, garchenv){
fixed = get("fixed", garchenv)
fixid = get("fixid", garchenv)
npar = get("npar", garchenv)
if(!is.null(fixed)){
pall = vector(mode = "numeric", length = npar)
pall[fixid] = fixed
pall[-fixid] = pars
pars = pall
}
Names = get("omodel", garchenv)$modelnames
distribution = get("dmodel", garchenv)$distribution
names(pars) = Names
con = .persistgjrgarch(pars = pars, distribution = distribution)
if(is.na(con)) con = 1
return(con)
}
.egarchcon = function(pars, data, returnType, garchenv){
fixed = get("fixed", garchenv)
fixid = get("fixid", garchenv)
npar = get("npar", garchenv)
if(!is.null(fixed)){
pall = vector(mode = "numeric", length = npar)
pall[fixid] = fixed
pall[-fixid] = pars
pars = pall
}
Names = get("omodel", garchenv)$modelnames
distribution = get("dmodel", garchenv)$distribution
names(pars) = Names
con = .persistegarch(pars = pars, distribution = distribution)
if(is.na(con)) con = 1
return(con)
}
.anstgarchcon = function(pars, data, returnType, garchenv){
fixed = get("fixed", garchenv)
fixid = get("fixid", garchenv)
npar = get("npar", garchenv)
distribution = get("dmodel", garchenv)$distribution
if(!is.null(fixed)){
pall = vector(mode = "numeric", length = npar)
pall[fixid] = fixed
pall[-fixid] = pars
pars = pall
}
pos = get("omodel", garchenv)$pos.matrix
gm = dlambda = skew = shape = 0
c1 = c2 = c3 = c4 = NULL
c11 = c12 = c13 = c14 = 0
kappa = 0.5
c1 = sum(pars[pos[7,1]:pos[7,2]]) + sum(pars[pos[10,1]:pos[10,2]])
if(pos[8,3] == 1) c11 = sum(pars[pos[8,1]:pos[8,2]])
if(pos[9,3] == 1) c12 = sum(pars[pos[9,1]:pos[9,2]])
c2 = c11 + c12
if(pos[11,3] == 1) c13 = sum(pars[pos[11,1]:pos[11,2]])
if(pos[12,3] == 1) c14 = sum(pars[pos[12,1]:pos[12,2]])
c3 = c13 + c14
ans = c(c1, c2+c3)
return(ans)
}
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