Hello,

I am trying to fit a simple AR 1 model, as shown below. I read over the missing values section in the Stan manual, but it is not clear to me how to fit this model if I have missing observations in my data. Would it be as straight forward as setting \tau = 0 if there is a missing observation at time i-1? Or draw another value of \tau_0 at the time point before each missing observation? In some sense, treating it again as requiring an initial value.

Y_{i} = f(\theta)_{i} + \tau_{i}

\tau_i = \rho \tau_{i-1} + \epsilon_i

\epsilon_i \sim N(0, \sigma^2)

\tau_0 \sim N(0, a)

Thank you,

Colin