Slicing for Efficiency, for Autoregressive Priors?

[shira]

does it help to use cumulative_sum ? e.g. as proposed by @andre.pfeuffer here?

Random walk prior

Aware! The code about splines adds the intercept twice too. One time in calling bs and another time in a0. B has full rank checked by rankMatrix. To model the random walk just do: gamma_raw ~ normal(0, 1); gamma = cumulative_sum(gamma_raw) * tau; If you want smoothing, I’d go instead with the mgcv package and specify bs=“ts” or bs=“ad”. See: https://stats.stackexchange.com/questions/305338/adaptive-gam-smooths-in-mgcv If I’m not mistaken the variance for gamma[1] -> Infinitive. Does an…