I am using a Bayesian method to estimate a multinomial probit model through
data augmentation. All the priors are conjugate priors. Covariance matrix
follows wishart. Normalize the first element of covariance matrix to be 1. I
find that other elements of the covariance matrix are very easy to explode.
They are very sensitive to the starting value and the parameter of the priors.
Can any Da Xia tell me why those elements explode and how to deal with them?
Thank you very much.
