Hi - I'm currently trying to work with a markov chain transition matrix
developed using the markovchain package (it's a 42x42 matrix model). I've
got the matrix up and running smoothly with no problems.
However, I'm trying to run some sensitivity analyses and distribution
analyses on the model, and I'm having some trouble. I thought that using
latin hypercube sampling (package 'lhs') and/or partial rank correlation
coefficients (package 'sensitivity', PRCC) would be a good route to go, but
I'm having trouble implementing them with the markov chain I already have
programmed.
Does anyone have any experience running these kinds of analyses and have
any advice? Specifically how to implement them on a markov model?
Thanks in advance for any help.
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