Calculate fits of Markov Switching AR (1) model

I have created a MS-AR(1) model in EViews 9.5 (the software I'm working with) and I'm just trying to understand how some of the output is calculated.

This is really dumb and probably a simple question to answer, but I can't seem to get how the fitted values are calculated. I have tried calculating them myself and can't seem to get my calculations to match up. My model has two regimes that look like this:

y(1t) = c(1)+B1*y(t-1)

y(2t) = c(2)+B1*y(t-1)

Where y(1t) and y(2t) are the two conditional equations for regimes 1 and 2, "c" is my switching term, and y(t-1) is my AR term (lagged values of y).

I would like to calculate the fitted values for this model, but I don't know for certain how to. I have the smoothed and filtered probabilities listed in the model output. I have tried calculating the fits like this:

fity(=P(S(t)= 1)*y(1t)+P(S(t)= 2)*y(2t)

NOTE: I'm using smoothed probabilities in my calculations (which is probably part of the problem).

Please help, my calculations are really close, but don't match up with those produced in the Eviews output.