Implementing a model in Stan involves several steps:
Define the Model
The first step is to define the epidemiological model you want to fit. This involves specifying the likelihood of the data given the parameters and the prior distributions for the parameters.
Write the Stan Code
Next, you write the Stan code to represent your model. The code typically includes sections for data input, parameter definitions, model specifications, and generated quantities for posterior predictive checks.
Compile the Model
Once the code is written, you compile the model using the Stan compiler. This step translates the Stan code into a form that can be executed to perform inference.
Fit the Model
After compiling the model, you fit it to your data using Markov Chain Monte Carlo (MCMC) methods. Stan provides functions to run the MCMC algorithms and obtain posterior samples.
Analyze the Results
Finally, you analyze the results using the posterior samples. This involves checking the convergence of the MCMC chains, summarizing the posterior distributions of the parameters, and conducting posterior predictive checks.
