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