First time user of these forums. I’m currently working on developing three different models using multiple approaches and tools. The data sets are small enough (between 34 and 40 records of data) that most models I run, the solutions converge quickly.
All of my models are using multiple regression. I’m developing models / solutions using 1) brms 2) pystan 3) pymc3 4) rstan and 5) Constrained Non-Linear Optimization in Excel (GRG Method).
In a comparison today, I used the same priors in (strong informative) brms and pymc3. The results showed that brms solution did not change at all my priors (both the coefficient and its’ std. deviation, except for intercept that went negative) whereas the pymc3 solution showed greater movement (-22% to +32% range).
Since both are based on NUTS and use AD I expected the solutions to be some what similar, but the lack of change from the given priors in brms was a significant surprise to me.
I can share the necessary data and scripts, if you let me know what you need to see.
- Operating System: Windows 10 -X64
- brms Version: 2.4.0 (RStudio 1.1456 & R 3.5.1 via Anaconda 3)
- pymc3 3.6 on Anaconda 3 using Python 3.6.7
P.S: for any one out there struggling to get RTools working with R and RStudio I can share my configuration if interested (if you do not have admin rights to change Windows System Environment (not user variables) there is no greater hell than that)