I have a proposal distribution for one parameter
theta_guess = guessleft(theta_accept(1,r-1), 0.01,0)
which is a left truncated normal (and thus non-symmetric) with inputs and output given by:
mu is the mean,
sigma is the std. deviation and
a is the lower bound. Moreover,
theta_accept(1,r-1) is last period's accepted theta because
r is the iteration counter and
theta_accept is a 1 x R vector (where R is the number of iterations to run in the M-H loop).
I want to create a correction factor for the acceptance ratio. I am not sure however how to do it. I've tried:
c=truncated_normal_a(theta_guess,theta_accept(1,r-1), 0.01,0)/... truncated_normal_a(theta_accept(1,r-1),theta_guess, 0.01,0)
which is of course one. My problem is that I have two parameters,
sigma is fixed, but
mu is not in the proposal since it depends on the last period's accepted parameter. So I have no idea what to put in
mu's place when creating my correction factor.