Alternatives and similar repositories for StatisticalModeling

Users that are interested in StatisticalModeling are comparing it to the libraries listed below

• AlxndrMlk / blogs-code
  Code for blog posts.
  ☆20Updated 2 years ago
• matheusfacure / exploratory-notebooks
  Unstructured Code with interesting analysis
  ☆36Updated last year
• sktime / sktime-tutorial-pydata-global-2022
  sktime - python toolbox for time series: pipelines and transformers
  ☆25Updated 3 years ago
• luisroque / bayesian_time_series
  Machine Learning models using a Bayesian approach and often PyMC3
  ☆25Updated 5 years ago
• MLDreamer / Linkedin-posts
  ☆25Updated last month
• juanitorduz / website_projects
  Repository containing the code of the projects presented in my personal website.
  ☆46Updated this week
• eigenfoo / tests-as-linear
  Python port of "Common statistical tests are linear models" by Jonas Kristoffer Lindeløv.
  ☆97Updated last year
• lavinei / pybats
  Bayesian time series forecasting and decision analysis
  ☆120Updated 2 years ago
• RickardKarl / causal-falsify
  causal-falsify: A Python library with algorithms for falsifying unconfoundedness assumption in a composite dataset from multiple sources.
  ☆36Updated 3 weeks ago
• FlorianWilhelm / bhm-at-scale
  🪜 Bayesian Hierarchical Models at Scale
  ☆51Updated 4 years ago
• andrewtavis / causeinfer
  Machine learning based causal inference/uplift in Python
  ☆62Updated 2 weeks ago
• raz1470 / causal_ai
  This project introduces Causal AI and how it can drive business value.
  ☆54Updated last year
• AllenDowney / SurvivalAnalysisPython
  Explorations of survival analysis in Python
  ☆50Updated 2 years ago
• fonnesbeck / probabilistic_python
  PyData London 2022 Tutorial
  ☆69Updated 3 years ago
• carlomazzaferro / scikit-hts-examples
  Example usage of scikit-hts
  ☆57Updated 3 years ago
• omarfsosa / tech-talk-hierarchical-models
  ☆42Updated 3 years ago
• gdmarmerola / cfml_tools
  My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable an…
  ☆32Updated 3 years ago
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆52Updated 4 years ago
• malmgrek / gammy
  Generalized additive models in Python with a Bayesian twist
  ☆78Updated 5 months ago
• exploripy / exploripy
  Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.
  ☆51Updated 2 years ago
• vcerqueira / experiments-performance_estimation
  Comparing different performance estimation methods for time series forecasting tasks
  ☆39Updated 9 months ago
• hyosubkim / bayes-toolbox
  bayes-toolbox
  ☆93Updated 7 months ago
• soda-inria / survival-analysis-benchmark
  Exploratory repository to study predictive survival analysis models
  ☆37Updated 2 years ago
• ericmjl / causality
  In which I play with the ideas surrounding causality
  ☆54Updated 3 years ago
• oegedijk / rule_estimator
  A scikit-learn compatible estimator based on business-rules with interactive dashboard included
  ☆28Updated 4 years ago
• AngelPone / pyhts
  A python package for hierarchical forecasting, inspired by hts package in R.
  ☆29Updated 11 months ago
• canyon289 / causal_inf_bookclub
  Supporting material for the book club
  ☆15Updated 3 years ago
• guillermo-navas-palencia / cprior
  Fast Bayesian A/B and Multivariate testing.
  ☆36Updated 3 years ago
• AidanCooper / shap-clustering
  How to use SHAP values for better cluster analysis
  ☆60Updated 3 years ago
• fabsig / KTBoost
  A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and …
  ☆63Updated 4 years ago