https://github.com/axsk/gync.jl

Bayesian inference for the GynCycle model
https://github.com/axsk/gync.jl

bayesian-inference empirical-bayes mcmc paper zib

Last synced: 4 months ago
JSON representation

Bayesian inference for the GynCycle model

• Host: GitHub
• URL: https://github.com/axsk/gync.jl
• Owner: axsk
• Created: 2015-10-16T09:38:51.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2017-06-06T15:16:29.000Z (about 9 years ago)
• Last Synced: 2025-07-11T09:40:51.932Z (11 months ago)
• Topics: bayesian-inference, empirical-bayes, mcmc, paper, zib
• Language: Julia
• Homepage:
• Size: 106 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 5
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
# GynC.jl

[![Build Status](https://travis-ci.org/axsk/GynC.jl.svg?branch=master)](https://travis-ci.org/axsk/GynC.jl) [![codecov.io](https://codecov.io/github/axsk/GynC.jl/coverage.svg?branch=master)](https://codecov.io/github/axsk/GynC.jl?branch=master)

This package provides the toolchain to estimate the parameters of the GynCycle model.

Its code mainly revolves around the three main types:

- `Config` which stores the bayesian model configuration, i.e. the patient data, measurement error, priors, ... as well as the MCMC proposal density and the thinning.

- `Sampling` which is obtained by sampling from a config via `sample(::Config, iters)` containing the sampled points, the current sampler state, as well as a reference to its initial config.

- `WeightedChain` which can be constructed from multiple samplings via `WeightedChain(::Vector{Sampling})` representing the average/merged chain and is used for further prior estimation steps, for example the EM-iteration: `emiteration!(::WeightedChain)`