Apparent bug in rmgarch

I'll try that, thanks!

On Wed, Jan 24, 2018 at 10:15 PM, alexios galanos <alexios at 4dscape.com>
wrote:

Hi Josh,

Thanks for reporting this...I'll investigate further when time permits.

In the meantime, if you let the rseed=NULL, the returned object will
include the seeds used which can then be passed back into the simulation
function to obtain reproducible results.

Here is an example:
###############################
library(rmgarch)
data(dji30retw)
Dat = dji30retw[, 1:3, drop = FALSE]
cnames = colnames(Dat)
uspec = ugarchspec(mean.model = list(armaOrder = c(2,1)), variance.model
= list(garchOrder = c(1,1), model = "eGARCH"), distribution.model = "norm")
spec1 = dccspec(uspec = multispec( replicate(3, uspec) ), dccOrder =
c(1,1), distribution = "mvnorm")
fit1 = dccfit(spec1, data = Dat, fit.control = list(eval.se=FALSE))
uspec = ugarchspec(mean.model = list(armaOrder = c(2,1)), variance.model
= list(garchOrder = c(1,1), model = "eGARCH"), distribution.model = "norm")
vspec = vector(mode = "list", length = 3)
midx = fit1 at model$midx
mpars = fit1 at model$mpars
# nasty, I know...will try to write some wrapper to perform this
automatically in future.
for(i in 1:3){
  vspec[[i]] = uspec
  setfixed(vspec[[i]])<-as.list(mpars[midx[,i]==1, i])
}
dccfix = as.list(coef(fit1, "dcc"))
spec2 = dccspec(uspec = multispec( vspec ), dccOrder = c(1,1),
distribution = "mvnorm", fixed.pars = dccfix)
# Fitted object
sim1 = dccsim(fitORspec = fit1, n.sim = 1000, n.start = 100, m.sim = 2,
startMethod = "unconditional",
              rseed = NULL)
print(sim1 at msim$rseed)

497782424 497782425 995564850

sim2 = dccsim(fitORspec = fit1, n.sim = 1000, n.start = 100, m.sim = 2,
startMethod = "unconditional",
              rseed=sim1 at msim$rseed)

all.equal(sim1 at msim$simX[[1]],sim2 at msim$simX[[1]])

TRUE

all.equal(sim1 at msim$simX[[2]],sim2 at msim$simX[[2]])

TRUE

# Specification Object
sims1 = dccsim(fitORspec = spec2, n.sim = 1000, n.start = 100, m.sim = 2,
startMethod = "unconditional",
              rseed = NULL, mexsimdata = NULL, vexsimdata = NULL, preQ =
last(rcor(fit1, type = "Q"))[,,1],
              Qbar = fit1 at mfit$Qbar)
sims2 = dccsim(fitORspec = spec2, n.sim = 1000, n.start = 100, m.sim = 2,
startMethod = "unconditional",
              rseed=sims1 at msim$rseed, preQ = last(rcor(fit1, type =
"Q"))[,,1],
              Qbar = fit1 at mfit$Qbar)

all.equal(sims1 at msim$simX[[1]],sims2 at msim$simX[[1]])

TRUE

all.equal(sims1 at msim$simX[[2]],sims2 at msim$simX[[2]])

TRUE

###############################

Regards,

Alexios


On 1/23/18 11:34 AM, Josh Segal wrote:

Hi Alexios (and others),

First, thank you for creating rmgarch, it's great.

I'm trying to generate simulations using dccsim from a spec, and find
that
when I specify a single value for rseed, the simulation results are not
reproducible (that is, each run gives different results).  I can avoid
this
issue by either using a fit instead of a spec or by specifying a vector
of
m.sim rseeds.

I did some digging in the code, and found in rdcc-main.R:
For fit, line 1224: rseed = c(rseed, (1:m.sim)*(rseed+1))
For spec, line 1493: rseed = c(rseed, as.integer(runif(m.sim, 1,
Sys.time())))

I think this explains my results.  Seems like the latter is incorrect,
and
should match the former, no?

Thanks very much,
Josh

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