CmdStan User's Guide
Introduction
QuickStart Guide
1 CmdStan Installation
2 Example Model and Data
3 Compiling a Stan Program
4 MCMC Sampling
5 Optimization
6 Variational Inference using Pathfinder
7 Variational Inference using ADVI
8 Generating Quantities of Interest from a Fitted Model
Reference Manual
9 Command-Line Interface Overview
10 MCMC Sampling using Hamiltonian Monte Carlo
11 Maximum Likelihood Estimation
12 Pathfinder Method for Approximate Bayesian Inference
13 Variational Inference Algorithm: ADVI
14 Standalone Generate Quantities
15 Laplace sampling
16 Extracting log probabilities and gradients for diagnostics
- 16.1 Configuration
- 16.2 CSV output
17 Diagnosing HMC by Comparison of Gradients
18 Parallelization
CmdStan Tools
19 stanc: Translating Stan to C++
- 19.1 Instantiating the stanc binary
- 19.2 The Stan compiler program
20 stansummary: MCMC Output Analysis
21 diagnose: Diagnosing Biased Hamiltonian Monte Carlo Inferences
22 print (deprecated): MCMC Output Analysis
Appendices
23 Stan CSV File Format
24 JSON Format for CmdStan
25 RDump Format for CmdStan
26 Using external C++ code
- 26.1 Derivative specializations
- 26.2 Special functions: RNGs, distributions, editing target
Bibliography

CmdStan User’s Guide

This is an old version, view current version.

Reference Manual

This section provides a complete reference for all CmdStan methods:

sample
optimize
variational
generate_quantities
diagnose
help