Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2021 Jun 21:dyab108. doi: 10.1093/ije/dyab108

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

© The Author(s) 2021; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.

PMC Copyright notice

A schematic of the Bayesian graphical model for computing the pooled estimates of SAR and R_h. Inference was performed via MCMC sampling using PyMC 3.4 with the built-in NUTS sampler. The sampler used eight chains with 2000 iterations each. The burn-in period is 2000. MCMC, Markov Chain Monte Carlo; NUTS, No U-Turn Sampler; PyMC, Python package for Bayesian statistical modelling.