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Stan is software for Bayesian estimation using the No-U-Turn sampling (NUTS) algorithm instead of the simpler Gibbs sampling (BUGS).
1
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Weighted log-probabilities in generalised gamma distribution
\Gamma(z,x) = \frac{1}{z}\left(\frac{\Gamma(z+2,x)}{z+1} - x^z e^{-x}\left(\frac{x}{z+1}+1\right)\right),
$$
which only ever needs to calculate $\Gamma$ with $z+2$, and therefore will always work in Stan … Though this involves (complete) gamma functions with negative parameters, this is usually implemented (and certainly this is the case for Stan).
Obviously, we just set $n$ to be $\lceil -z \rceil$. …
3
votes
1
answer
667
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Weighted log-probabilities in generalised gamma distribution
To make things explicit, here is the Stan code (hopefully this question is not actually stan-specific, but I think the code should be easy to understand anyway). … *weight);
}
}
Assume this functions block is included in every other stan program in this question. …
3
votes
1
answer
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Weighting observations and measurement uncertainty in bayes
I am working on using MCMC (via STAN) to estimate model parameters for a bunch of observations with measurement uncertainty. … EDIT:
I found a bug in the stan code that I had which was causing this not to work. Working code is:
data {
int<lower=0> N; //Number of obs. …