Hi,

I am trying to fit an linear model with two random effects and an AR/ARMA effect, with normal family.

I then want to use the regression coefficiënts of the AR/ARMA effects to further sample from the posterior predictive distribution in a forecasting sense. If there is a solution for this, then that would solve the problem as well.

Using the AR() or ARMA() function does not return the wanted coefficiënts, how can I still obtain these?

The model I use is:

brm(log(vol) ~ (1 + arma(time = date_rank, p = 2, q = 1) | onoff : Market))

An example of the data:

Country date_rank date Section vol

1 Netherlands 2 2018-01-08 00:00:00 A 15735.

2 Netherlands 2 2018-01-08 00:00:00 B 755.

3 France 3 2018-01-15 00:00:00 A 93516.

4 France 3 2018-01-15 00:00:00 B 1635.

5 Netherlands 4 2018-01-22 00:00:00 A 45527.

6 Netherlands 4 2018-01-22 00:00:00 B 81913.

7 Netherlands 5 2018-01-29 00:00:00 A 43554.

8 France 5 2018-01-29 00:00:00 B 12503

9 Germany 6 2018-02-05 00:00:00 A 26751.

10Germany 6 2018-02-05 00:00:00 B 11144.

Thanks.