Hello,
I was hoping someone might be able to point me in the right direction as to where I can find information or best practice in terms of deriving the Bayesian posterior mode and mean using Stata?
I have the following pieces of information in my data set:
1. Point-wise prediction of the prior mode and a prior mean of a quiz score
2. A signal a given person observes where the signal equals their true score with probability (p) and a noisy score with probability (1-p) where the noise is perturbed to their true score and drawn from a uniform distribution of integers from (-5, 5) excluding zero.
I am wanting to produce the Bayesian prediction using the above information of a mode and a mean so I can directly include it in my model specification. Is there any clean way of doing this with Stata with some built in features or do I need to 'hard code' the predictions by writing out the entire structural model?
Thanks for any help in advance!
Nicholas
I was hoping someone might be able to point me in the right direction as to where I can find information or best practice in terms of deriving the Bayesian posterior mode and mean using Stata?
I have the following pieces of information in my data set:
1. Point-wise prediction of the prior mode and a prior mean of a quiz score
2. A signal a given person observes where the signal equals their true score with probability (p) and a noisy score with probability (1-p) where the noise is perturbed to their true score and drawn from a uniform distribution of integers from (-5, 5) excluding zero.
I am wanting to produce the Bayesian prediction using the above information of a mode and a mean so I can directly include it in my model specification. Is there any clean way of doing this with Stata with some built in features or do I need to 'hard code' the predictions by writing out the entire structural model?
Thanks for any help in advance!
Nicholas
