Stan Models and Input Data for Posterior Uncertainty Visualization

A source of files for replicating figures from a research article on variance deltas for posterior uncertainty. It includes Stan models, corresponding input data in JSON format, and Python scripts for running the sampler and generating variance deltas. The dataset was authored by Collin Cademartori.

Use Cases

• Run the provided Stan models on the included JSON input data to generate posterior samples.
• Use the Python scripts to compute variance deltas from the model outputs for uncertainty visualization.
• Replicate the specific figures from the associated research article using the provided code and data.

Strengths

• Includes all necessary components (models, data, scripts) for full replication of the published research.
• Associated with a specific, peer-reviewed methodology for visualizing posterior uncertainty.
• Last updated in February 2026, indicating recent maintenance.

Limitations

• The dataset's size, row count, and specific file formats are unknown, making it difficult to assess scope.
• It is designed for a specific, narrow research purpose and may not be generalizable.
• Requires installation of specific software dependencies, including the variance-deltas package, to use.

Provenance

Source

Collin Cademartori's Dataverse

Collection Method

Created to accompany a specific research publication.

Freshness

2026-02-10