A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS

Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg

My solutions to the exercises in "Data Analysis Using Regression and Multilevel/Hierarchical Models" by Andrew Gelman and Jennifer Hill

(ml) - python implementation of bayesian media mix modelling with shape and carryover effect

A surface language for programming Stan models using python syntax

Basic statistical modelling examples.

A simple library to run variational inference on Stan models.

Phylogenetic inference using Stan

Source code and data for the EDM 2022 paper

spatial_attenNCM (Spatial Attention Neuro-Cognitive Modeling) used some hierarchical neuro-cognitive models to find out the spatial attention effect on perceptual decision making.

Self-study materials to give you an introduction to Bayesian inference with python

It is from Kaggle Competitions where the training dataset is very small and the testing dataset is very large and we have to avoid or reduce overfiting by looking for best possible ways to overcome the most popular problem faced in field of predictive analytics.

A python interface with Stan/PyStan Markov Chain Monte Carlo package

"Probabilistic Programming & Bayesian Methods for Hackers" book ported to Stan (python)

estimate competitive programmers' performance based on Bayesian statistical modeling

Replica Exchange Monte Carlo using PyStan2

Notebook to study Bayesian statistical modeling with pystan and "StanとRでベイズ統計モデリング"

Probabilistic modeling through Bayesian inference using PyStan with demonstrative case study experiments from Christopher Bishop's Model-based Machine Learning.