# Tutorial on ABC rejection and ABC SMC for parameter estimation and model selection

## TL;DR

This tutorial explains four algorithms based on Approximate Bayesian Computation (ABC), including rejection and Sequential Monte Carlo (SMC) methods, for parameter estimation and model selection in complex models.

## Contribution

It provides a clear schematic illustration of four ABC algorithms, enhancing understanding of their implementation for parameter estimation and model selection.

## Key findings

- Clarifies the differences between rejection and SMC ABC methods.
- Provides schematic guidance for implementing ABC algorithms.
- Facilitates understanding of ABC for model selection.

## Abstract

In this tutorial we schematically illustrate four algorithms: (1) ABC rejection for parameter estimation (2) ABC SMC for parameter estimation (3) ABC rejection for model selection on the joint space (4) ABC SMC for model selection on the joint space.