Tools to enable flexible and efficient hierarchical nowcasting of epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes.

Notas y contenido del curso en Modelación Bayesiana para la MCD @ ITAM

Pre-compiled CmdStan models in R packages

An in-development R package and a Bayesian hierarchical model jointly fitting multiple "local" wastewater data streams and "global" case count data to produce nowcasts and forecasts of both observations

An R package and Bayesian generative model to estimate epidemiological parameters from wastewater concentration measurements over time.

An R package providing a GUI ('shiny' app) for the R package 'brms'.

R package for the Bayesian estimation of diagnostic classification models using Stan

Example code for a possible talk at R/Medicine 2021 (submitted and under review, accepted talks not yet determined)

A Docker image to run Stan, cmdstanr, and brms for Bayesian statistical modelling. GPU support using OpenCL is available.

Slides for a possible talk at R/Medicine 2021 (submitted and under review, accepted talks not yet determined)

Presentation on targets at the New York Open Statistical Programming Meetup

Evaluating Semi-Parametric Nowcasts of COVID-19 Hospital Admissions in Germany

R package to fit EXNEX models with Stan

Gaussian processes on graphs and lattices in Stan using cmdstanr.

Learning bayesian data analysis with Statistical Rethinking

R package for bayesian methods including penalized B-splines for fitting bomb radiocarbon reference series and assessing aging bias