cmdstanr
There are 16 repositories under cmdstanr topic.
epinowcast/epinowcast
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.
CDCgov/ww-inference-model
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
agarbuno/modelacion-bayesiana
Notas y contenido del curso en Modelación Bayesiana para la MCD @ ITAM
wlandau/instantiate
Pre-compiled CmdStan models in R packages
adrian-lison/EpiSewer
An R package and Bayesian generative model to estimate epidemiological parameters from wastewater concentration measurements over time.
wjakethompson/measr
R package for the Bayesian estimation of diagnostic classification models using Stan
fweber144/shinybrms
An R package providing a GUI ('shiny' app) for the R package 'brms'.
wlandau/rmedicine2021-pipeline
Example code for a possible talk at R/Medicine 2021 (submitted and under review, accepted talks not yet determined)
JBris/stan-cmdstanr-gpu-docker
A Docker image to run Stan, cmdstanr, and brms for Bayesian statistical modelling. GPU support using OpenCL is available.
wlandau/rmedicine2021-slides
Slides for a possible talk at R/Medicine 2021 (submitted and under review, accepted talks not yet determined)
epiforecasts/eval-germany-sp-nowcasting
Evaluating Semi-Parametric Nowcasts of COVID-19 Hospital Admissions in Germany
maxdrohde/exnexstan
R package to fit EXNEX models with Stan
wlandau/nyhackr2020
Presentation on targets at the New York Open Statistical Programming Meetup
onnela-lab/gptoolsStan
This repository has been merged into https://github.com/onnela-lab/gptools/.
zsiders/BayesianBombCarbon
R package for bayesian methods including penalized B-splines for fitting bomb radiocarbon reference series and assessing aging bias
robitalec/statistical-rethinking
Learning bayesian data analysis with Statistical Rethinking