Non-centered model not fitting

Modeling
2

A few suggestions:

  • Are you sure the observation equation is right? At present the entire O3 vector is used on every loop. Perhaps you meant O3[n]?
  • Try a smaller value for the init argument (ex. 1 or .1).
  • Try student-t with df>1 or normal everywhere you currently have cauchy; cauchy tends to behave badly both numerically and in terms of what it implies as a prior.
  • If using cauchy, definitely run some prior predictive checks to ensure it implies your real expectations; you might be surprised by the consequences of the cauchy heavy-tail.
  • If using cauchy, try the reparameterization suggested by the SUG
  • Instead of doing the non-centering by hand, use the new-ish <offset=...,multiplier=...> syntax for less chance of implementation errors. (Also see here)
  • Your priors for the measurement error are such that they convey peak credibility for zero measurement error. Consider a peaked-away-from-zero prior, which can be elegantly achieved by replacing the 0-bound measurement_error parameter with an unbounded log_measurement_error parameter that is then exponentiated when it comes to its use in the likelihood ( ... , exp(measurement_error[sensor[n]]) );)
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