Stan also supplies a single primitive for a Generalised Linear Model with poisson likelihood and log link function, i.e. a primitive for a poisson regression.

The random draw from the sampling distribution for ~y is coded using Stan's Poisson random number generator in the generated quantities block.

14 апр. 2015 г. · Poisson Regression in Stan · by Kazuki Yoshida · Last updated over 9 years ago.

Hi all, I'm new to stan programming. I'm trying to adapt a script written for JAG to STAN. I'd like to convert T[i] <- step(yrep[i]-y[i]) ...

For prediction, the "stan" engine can compute posterior intervals analogous to confidence and prediction intervals. In these instances, the units are the ...

6 дек. 2023 г. · In this post, I'll walk through my implementation of the GPO in Stan. The gamlss.dist package provides a full set of distributional functions for the ...

This is a description of how to fit the models in Probability and Bayesian Modeling using the Stan software and the brms package.

Example of Bayesian Poisson model in Python using Stan from Bayesian Models for Astrophysical Data, by Hilbe, de Souza and Ishida, CUP 2017.

Hi, It's been ages since I've used Stan, and I've become stuck on what should be a trivial model. Can somebody take a look and tell me what I'm missing here ...

5 мая 2019 г. · This tutorial demonstrates both approaches using a simulated dataset with counts generated from a Poisson distribution in a mixed model with a single fixed- ...