I think your question might be more broadly suited towards Bayesian nonparametric modeling. Chapters 21 and 23 of Bayesian Data Analysis (Gelman et al., free pdf for personal use) discuss latent Gaussian process and Dirichlet processes for density estimation. This is pretty far from my area of personal expertice but I did find an earlier thread on the forums (Bayesian nonparametric modeling - #16 by arya) discussing why Stan may or may not be your best choice.
js592
3
Related topics
| Topic | Replies | Views | Activity | |
|---|---|---|---|---|
| How Do I Do General Density Estimation with Stan | 7 | 575 | October 15, 2021 | |
| Kernel Density Estimation with STAN | 0 | 1035 | January 17, 2019 | |
| User-defined models for gaussian processes with non-gaussian likelihoods (and other generic models) | 19 | 1447 | May 9, 2018 | |
| Obtain gradient of function (e.g. multi_student_t_lpdf) within Stan? Estimating approximate density functions | 1 | 406 | January 23, 2020 | |
| Kernel density and dirichlet prior | 2 | 833 | January 4, 2020 |