Hello,
I've been enjoying using the "Mixture and Hidden Markov Models in R" by Visser
& Speekenbrink to learn how to apply these analyses to my own data using
depmixS4.
I currently have a fitted 4-state mixture model with three emissions variables
and one binomial covariate (HS). I am trying to compute confidence intervals
using the following code, where fmms4s is the model:
fmms4Svov <- vcov(fmms4S)$vcov #this line runs fine
fmms4Sse <- standardError(fmms4S) #this is where I get the error
fmms4SCI <- confint(fmms4S)
This worked fine before I added the covariate, but with the covariate I receive
a warning message: In sqrt(diag(vc$vcov)) : NaNs produced.
As a result, several of my parameters have NaNs as CIs. In general, I get this
error more frequently for more complex models (even when these models converge
and show a better fit than simpler models) but I cannot find any information as
to why this happens. Getting rid of one of the emissions variables but leaving
the covariate also seems to �fix� the issue but it crops up quite often for me
in general.
Many thanks,
Heather
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