I am trying to use individual errors of my inputs into the Stan model. I haven’t find a way to treat them individually. The main problem here is that each entry has it own individual error.
Let’s say I have a “Y” I want to predict from an entry of values “X” of 1000 rows. Each X entry has a different error, so my question is it possible to treat them individually in the pystan model?
Hey l, yes you can treat them individually quite easily . Have a look at the measurement error section in the handbook as a general overview.
yourvalue ~ normal(x, yourerror)
Where x is a parameter indicating the mean you don’t know which you can then use in further calculations.
Ok I think I got it based on the handbook and your reply.
When you said “yourvalue” those are all my X entries right? that I will use to predict my “Y”.
Is there a reason why to peak normal, or it will vary in regards of the type of error?
Random additive error is Gaussian, but if you’ve some other error model then you should use that instead.