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Here's a reproducible example on how you can pass starting
parameters and bounds:<br>
<p>library(rugarch)<br>
library(xts)<br>
data("dmbp")<br>
dmbp <- as.xts(dmbp, as.Date(1:nrow(dmbp)))<br>
spec <- ugarchspec(mean.model = list(armaOrder = c(0,0),
include.mean = TRUE), <br>
variance.model = list(model = "sGARCH",
garchOrder = c(1,1), external.regressors = dmbp[,2]))<br>
<br>
setstart(spec) <- list("vxreg1" = 0.5)<br>
setbounds(spec) <- list("vxreg1" = c(0, 1))<br>
<a class="moz-txt-link-abbreviated" href="mailto:spec@model$start.pars">spec@model$start.pars</a><br>
mod <- ugarchfit(spec, dmbp[,1])</p>
<p>I suspect this may also be related to a parameter scaling issue
as well. I'm working on a new implementation which should
hopefully fix<br>
this and many other issues (autodiff gradients/hessian, option for
multiplicative regressors, parameter scaling. standard error
calculation <br>
options etc), but won't have something out for at least a few
months (it will eventually be located in this repo:
github.com/tsmodels/).<br>
</p>
<p>Regards,<br>
</p>
<p></p>
<p>Alexios</p>
<p><br>
</p>
<div class="moz-cite-prefix">On 1/11/23 12:31 PM, Simon van Norden
wrote:<br>
</div>
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cite="mid:YQBPR0101MB51849AC8BD267E31ADF9B020A8FC9@YQBPR0101MB5184.CANPRD01.PROD.OUTLOOK.COM">
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<p class="MsoNormal">Having trouble with bad initial parameter
estimates in rugarch when using an external regressor.<o:p></o:p></p>
<ul style="margin-top:0cm" type="disc">
<li class="MsoListParagraph"
style="margin-left:0cm;mso-list:l0 level1 lfo1">Convergence
code is 0 and convergence is rapid, but….<o:p></o:p></li>
<li class="MsoListParagraph"
style="margin-left:0cm;mso-list:l0 level1 lfo1">Coefficient
estimate on the external regressor is always 0.00000 and
condH = NaN<o:p></o:p></li>
<li class="MsoListParagraph"
style="margin-left:0cm;mso-list:l0 level1 lfo1">Results are
robust to variable scaling and optimization algorithm (tried
them all.)<o:p></o:p></li>
</ul>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">My hunch is that I’m on a saddle point (or
similar ‘flat spot’.)<o:p></o:p></p>
<p class="MsoNormal">I’d like to try alternative initial
parameter estimates for the external regressor; can anyone
point me to an example showing how to pass this to the
optimizer?<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Would to happy to hear of other
suggestions, or provide details, a reprex, etc.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">FWIW, this may be related to the question
someone else posted back on 20-06-2022.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Thnx<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><span lang="FR-CA"><o:p> </o:p></span></p>
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