Hello,

I am trying to model a time series (life expectancy **wy** by year from 1900 to 2010) and **GDP**. I just started very simple

`lm(wy ~ igdp_log)`

Here an example of the results from a toy model.

Of course, this model has serial correlation. I can do filtering by using:

`lm(I(wy - r1*lag_wy) ~ I(igdp_log - r1*lag_igdp_log)`

Where r1 is the 1st serial correlation coefficient (0.846). The gdp coefficient goes from 1.30 to 0.71.

I am trying to replicate these results using brms. When I specify the `autocor`

term I use:

`autocor = cor_arr(~ 1, r=1)`

The gdp coefficient I get is 0.15. Is there a way to replicate the coefficient of 0.70 using brms?

Thanks in advance!

- Operating System: Capitan OSX
- brms Version: 2.2.0