Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS
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Updated
May 28, 2022 - Jupyter Notebook
Python/STAN Implementation of Multiplicative Marketing Mix Model, with deep dive into Adstock (carry-over effect), ROAS, and mROAS
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
My solutions to the exercises in "Data Analysis Using Regression and Multilevel/Hierarchical Models" by Andrew Gelman and Jennifer Hill
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
(ml) - python implementation of bayesian media mix modelling with shape and carryover effect
Basic statistical modelling examples.
A surface language for programming Stan models using python syntax
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.
Phylogenetic inference using Stan
A python interface with Stan/PyStan Markov Chain Monte Carlo package
Notebook to study Bayesian statistical modeling with pystan and "StanとRでベイズ統計モデリング"
Source code and data for the EDM 2022 paper
Replica Exchange Monte Carlo using PyStan2
A simple library to run variational inference on Stan models.
spatial_attenNCM (Spatial Attention Neuro-Cognitive Modeling) used some hierarchical neuro-cognitive models to find out the spatial attention effect on perceptual decision making.
estimate competitive programmers' performance based on Bayesian statistical modeling
Learning probabilistic modeling in python
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