I have various runs of the same model (and sometimes with one slightly changed parameter) and I want to compare models to get the model that fits my data the best. I was told this can be seen by the lp__ value, which is printed out in the model summary. Now my (stupid) question is, which value is better?
Lets say I got those values (I know, they are really close, but nevertheless), which model would be better?
I think I do not fully understand the meaning of log posterior…
Help would be very appreciated!