rstanarm R package for Bayesian applied regression modeling
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Updated
Jun 25, 2024 - R
rstanarm R package for Bayesian applied regression modeling
🐢 bayesAB: Fast Bayesian Methods for A/B Testing
shinystan R package and ShinyStan GUI
loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)
priorsense: an R package for prior diagnostics and sensitivity
Descriptive probabilistic marker gene approach to single-cell pseudotime inference
R package providing utilities for INLA
Regression with Summary Statistics exploiting Network Topology.
Estimates the Force-of-Infection of a given pathogen from population based sero-prevalence studies
An R Package for Bayesian Nonparametric Clustering. We plan to implement several models.
Established Bayesian models and leveraged historical data to predict home and away teams’ performance. Achieved over 80% prediction accuracy of winning percentage and 53% of the goal prediction.
Predicting Absolute and Relative Abundance by Modeling Efficiency to Derive Intervals and Concentrations
Adaptive Bayesian Clinical Trial
Revisiting Whittaker-Henderson Smoothing
MultiVariate Polygenic Mixture Model
Full results to accompany Zhu and Stephens (2018).
rstanarm R package for Bayesian applied regression modeling
R package SDA4D for performing 4-dimensional sparse Bayesian tensor decomposition
Introduction to Probabilistic Programming
This is a repo for graduate computational statistics problem sets and class information/data.
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