Stimulation with Bayesian Inference

This Tutorial Has Moved

This tutorial has been replaced by two updated pages:

Bayesian Parameter Inference with NumPyro introduces forward simulation, NUTS, SVI, parameter uncertainty, and predictions.
Bayesian Stimulation Inference: Identifiability and Prior Sensitivity develops the stimulation case study with matched observation noise, Fisher geometry, prior sensitivity, MAP estimates, and predictive checks.

Each replacement provides its own downloadable notebook and Colab link.

---
title: "Stimulation with Bayesian Inference"
format:
  html:
    toc: false
---

::: {.callout-note}
## This Tutorial Has Moved

This tutorial has been replaced by two updated pages:

- [Bayesian Parameter Inference with NumPyro](../basics/bayesian_inference.qmd)
  introduces forward simulation, NUTS, SVI, parameter uncertainty, and predictions.
- [Bayesian Stimulation Inference: Identifiability and Prior Sensitivity](Stimulation_Prior_Sensitivity.qmd)
  develops the stimulation case study with matched observation noise, Fisher
  geometry, prior sensitivity, MAP estimates, and predictive checks.

Each replacement provides its own downloadable notebook and Colab link.

:::