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Let's us this to start chatting about stan section
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**Describe the bug**
I am using a staged installation in an R package I am developing (using the machinery of `instantiate`). When I use `cmdstanr::cmdstan_model` without the additional argument `com…
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It might be useful to have a model transformation `marginalize_discrete` that marginalizes out discrete parameters and control flow when possible to turn a model with latent discrete parameters into o…
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Hi,
I would like to use R290 refrigerant in the simulation of a refrigeration circuit, but it is not available in the library. Can I connect some external library that contains its properties? Is th…
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Hamiltonian Monte Carlo (HMC) is a widely used, gradient based, MCMC algorithm, that is the backbone of Stan's inference. I plan to implement it for monad-bayes. Todos (checkboxes indicate things done…
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This is a feature request to allow the dispersion parameter to be observation-specific, as, for example, in models like the following:
```r
library(brms)
set.seed(4734)
data_het
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At the moment the package supports using `loo` to produce estimates of the leave one out information criterion. This is not appropriate for most nowcasting tasks where the aim is to nowcast future dat…
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Use the readme as an example.
- [ ] @syclik: decide where this document should go
- [ ] @bgoodri write the requirements in a clear language that can be understood by contributors and reviewers for wha…
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As far as I understand, the tfp backend represents a model as a class inheriting from `tfd.Distribution`, which then exposes a `log_prob` function for the sampler to use (and parameter shapes and bije…
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#### Summary:
make: *** [/datb/home/wanglab27/bin/r_base/R-4.1.0/etc/Makeconf:177: stan_fit.o] Error 1
ERROR: compilation failed for package ‘rstan’
#### Description:
** libs
g++ -std=gnu++14 -…