You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Your gaussian processes 3 write-up states that the priors for the hyper parameters are half normal,
e.g.
$$\alpha \sim $ half- $\mathcal{N}(0,2)$$
and the corresponding code is parameters{ ... real<lower=0> alpha; } model{ alpha ~ normal(0,2); ... }
But according to the stan reference manual (v 2.16.0) pg. 400: "If a variable X is declared to have a lower bound $a$, it is transformed to be an unbounded random variable $Y$, where ."
$$ Y = log (X - A)$$
which in this case would just be the log, suggesting that the new random variable is log normal, not half - would you mind clearing up this discrepancy for me?
I'm using a similar parameterization in a model I'm working with and would like to know the "real" prior distribution I'm using. - Many Thanks.
The text was updated successfully, but these errors were encountered:
apeterson91
changed the title
Half Normal or Log Transform
Half Normal or Log Normal
Dec 12, 2017
Stan automatically adds the Jacobian to ensure that we are indeed specifying a half normal distribution and not a log normal distribution. Please consult the Stan manual for more information.
Your gaussian processes 3 write-up states that the priors for the hyper parameters are half normal,
e.g.$\mathcal{N}(0,2)$ $
$$\alpha \sim $ half-
and the corresponding code is
parameters{ ... real<lower=0> alpha; } model{ alpha ~ normal(0,2); ... }
But according to the stan reference manual (v 2.16.0) pg. 400: "If a variable X is declared to have a lower bound$a$ , it is transformed to be an unbounded random variable $Y$ , where ."
which in this case would just be the log, suggesting that the new random variable is log normal, not half - would you mind clearing up this discrepancy for me?
I'm using a similar parameterization in a model I'm working with and would like to know the "real" prior distribution I'm using. - Many Thanks.
The text was updated successfully, but these errors were encountered: