I'm on a Mac X1, Monterey. I've installed prophet and run into this issue when trying to fit a model. RuntimeError: Error during optimization: console log output: dyld[90668]: Library not loaded: ...

I would like to be able to suppress some output coming from fbprophet while fitting a forecasting model. This output ("Initial log joint probability...", "Optimization terminated normally:", "Conve...

I'm trying to build a survival model in JAGS that allows for time-varying covariates. I'd like it to be a parametric model — for example, assuming survival follows the Weibull distribution (but I'd...

What is the proper way to format a categorical predictor to use in STAN? I cannot seem to input a categorical predictor as a normal factor variable, so what is the quickest way to transform a norma...

I'm starting to learn Stan. Could anyone explain when and how to use syntax such as... ? target += instead of just: y ~ normal(mu, sigma) For example in Stan manual you can find the followi...

I am building a binomial regression model using 2 categorical variables. This is from an example in the book, Statistical rethinking. In the book, while using the rethinking package, we can set pri...

Is there a way to construct a matrix with simplex columns in Stan? The model I want to construct is similar to the following, where I model counts as dirichlet-multinomial: data { int g; int c; ...

I'm not able to install rstanarm on R 3.5.3 running on Ubuntu 18.04 LTS. I used the following commands: install.packages("rstanarm") and devtools::install_github("stan-dev/rstanarm", build_vign...

I'm new to both stan and brms, and having trouble extracting posterior predictive distributions. Let's say I have a simple logistic regression fit = brm(y ~ x, family="bernoulli", data=df.training...

I am doing a multiple regression in Stan. I want a trace plot of the beta vector parameter for the regressors/design matrix. When I do the following: fit = model.sampling(data=data, iter=2000, c...

Is there a possibility to extract the stan code used for the MCMC sampling in rstanarm? I would like to compare my own parametrisation of a model and prior choices to the one used in rstanarm.

I would like to get the estimated coefficients of a model using rstan in an rnotebook I have the following stan chunk: ```{stan output.var="rats"} data { int<lower=0> N; int<lower=0&gt...

The following are my r code. ```{r message=FALSE, warning=FALSE, cache=0,eval=TRUE, error=FALSE} stan_m1 <- rethinking::map2stan( alist( y ~ dbinom(n, p), logit(p) <- alpha + bP*P + bA*A ...

Say I want to model a random effect at two levels, i.e. I have two levels of nesting: individuals within a parent group and parent groups within a grandparent group. I know how to write a basic mod...

After waiting a week for three MC chains to run, the object was not saved, giving the error "Error: is.atomic(x) is not TRUE". I have run this code or variants thereof many times, so it is probably...

I hope to use MC-Stan on Spark, but it seems there is no related page searched by Google. I wonder if this approach is even possible on Spark, therefore I would appreciate if someone let me know. ...

I am very new statistical analysis world and have taken a recent interest in the BUGS/JAGS/STAN modelling language. Something which really surprises me is that I haven't seen any examples of new fu...

I am using RStan to sample from a large number of Gaussian Processes (GPs), i.e., using the function stan(). For every GP that I fit, another DLL gets loaded, as can be seen by running the R comman...

Recently stan has added the integrate_ode method. Unfortunately the only documentation I can find is the stan reference manual (p.191ff). I have a model that would require some driving signal. As I...

Stan is a new Bayesian analysis software by Gelman et al. RStan is, I am guessing, a way to call Stan from within R. Will Stan / RStan run on a supercomputer with a Linux operating system, and if...

I am using maximum-likelihood optimization in Stan, but unfortunately the optimizing() function doesn't report standard errors: > MLb4c <- optimizing(get_stanmodel(fitb4c), data = win.data, ...

I would like to run a robust logistic regression (robit) in Stan. The model is suggested in Gelman & Hill's "Data Analysis Using Regression and Multilevel Methods" (2006, pp. 124), but I'm not ...

when starting a standard example from the stan webpage like the following: schools_code <- ' data { int<lower=0> J; // number of schools real y[J]; // estimated treatment effects rea...