Is it possible to use the technique below, but for autoregressive priors on parameters (as opposed to data)? Maybe not because they wouldn’t be initialized…? [image] 2.1 Autoregressive Models | Stan User’s Guide Stan user’s guide with examples and programming techniques. …

If you have temporal data, it would be better to make y_lag or whatever in the transformed data block rather than slicing every leapfrog step. For parameters … [image] shira: What is a more efficient way to code the below, which gives the warning that warning is a false positive.

Thanks, Ben! For parameters, are there ways to improve on our code snippet?

does it help to use cumulative_sum ? e.g. as proposed by @andre.pfeuffer here? [image] Random walk prior Modeling 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.…

For a random walk, that might be ok but I doubt the difference in speed will be noticeable.

Slicing for Efficiency, for Autoregressive Priors?

Modeling

shira June 13, 2019, 5:56pm 6

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

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Slicing for Efficiency, for Autoregressive Priors?

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