Stochastic volatility is super unstable & Round error result in negative variance

Hi dude, I tested the whole model on the test data. The stochastic volatility level is super unstable. You can check out the pdfs of all the figures. 

I think that we still need to replicate Carlos' code and try to match the result. It is worth to see whether the result there is that unstable or not.

Btw, I fixed the problem of working directory. If you click BABproject.Rproj, it will automatically set the working directory for you. 

2. When I try to use the real data, it always pops up an error saying that the probability is NA. I did some debug stuff. For example, I added stopifnot(sum(is.na(theta)) == 0) to 1MCMC.R. The stop condition means that theta(which is beta outside the function ffbsu) has NA. Because theta is drawn from a normal distribution, the only explanation is the variance is negative. I checked all the negative variance. They are super small like 1e_14. I think it is the round error that causes all this. I am still trying to figure it.

Best,
Long