Top 76 Stan open source projects

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

R package - Load, visualise and analyse daily updated data on the COVID-19 outbreak in Germany

Bayes Factors for brms Models

Apartment price trends

Beginner tutorial for using cmdstan with multithreading

library of C++ functions that support applications of Stan in Pharmacometrics

Bayesian SEIR model to estimate the effects of social-distancing on COVID-19

Full Bayesian Inference for Hidden Markov Models

hyunjimoon.github.io/sbc

Functions to simulate and estimate Mexican election results based on a random sample, the functions were used, among other methodologies, to anticipate the final results of the 2021 Mexican elections.

Process and analyze X-ray Absorption Spectroscopy data using Feff and either Larch or Ifeffit.

No description, website, or topics provided.

『基礎からわかる時系列分析』（技術評論社，2018年）のサポートサイトです。

method for modeling continuous and discrete population genetic structure

📖 现代应用统计 Modern Applied Statistics with R

Implementation of Shahryar Minhas, Peter Hoff, and Mike Ward's AMEN models for network data in stan

CmdStanR: the R interface to CmdStan

No description, website, or topics provided.

Noisy network measurement with stan

Statistical comparison of multiple algorithms

Bayesian inference from binary causal models

R-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes. Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.

A Python tool to forecast Google Analytics data using several popular time series models.

Bayesian models for data analysis

Uses Stan sampler and math library to semiparametrically fit linear and multilevel models with additive Bayesian Additive Regression Tree (BART) components.

No description, website, or topics provided.

Introduction to Data Analysis - Webbook

No description, website, or topics provided.

Fit models to data from unmarked animals using Stan. Uses a similar interface to the R package 'unmarked', while providing the advantages of Bayesian inference and allowing estimation of random effects.

Code and data for Zhang, Lengersdorff et al. (2020)

Experimenting with Stan on Spark for distributed MCMC

Hierarchical Bayesian Modeling of English Premier League

This code uses the algebra solver in Stan (https://mc-stan.org/) to find the parameters of a distribution that produce a desired tail behavior.

No description, website, or topics provided.

No description, website, or topics provided.

No description, website, or topics provided.

Dynamic estimation of group-level opinion in R

A 6 hour course on Stan with Dan Simpson, Vianey Leos-Barajas, and Andrew MacDonald

Myokit: A simple interface to cardiac cellular electrophysiology

Bayesian inference for Ruby, powered by CmdStan

Bayesian Hierarchical Hidden Markov Models applied to financial time series, a research replication project for Google Summer of Code 2017.

The Trendiness of Trends

Bayesian DFA with Stan

R package to perform Bayesian regularization using Stan.

R package to model time series accounting for noise in the temporal dimension. Specifically designed for single cell transcriptome experiments.

analysis code for "Corrected analyses show that moralizing gods precede complex societies but serious data concerns remain"

Applied Probabilistic Programming & Bayesian Machine Learning (MIT IAP 2017)

Rlgt is an R package for Bayesian Exponential Smoothing

A practical introduction to modeling in Stan

API for exploring and iterating rstan fit objects